commit 85ec0e75011e08c6abaaac214b53133f5c652ceb Author: Roman Necas Date: Tue Apr 14 19:28:46 2026 +0200 Initial import of project archive (1BIT-3BIT) diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..94fcdd9 --- /dev/null +++ b/.gitignore @@ -0,0 +1,9 @@ +# Large binary — kept only locally / in OneDrive +2BIT/winter-semester/ITU/03_xnecasr00_video.mp4 + +# OS / editor noise +Thumbs.db +desktop.ini +.DS_Store +*.tmp +*~ diff --git a/1BIT/summer-semester/IJC-1/Makefile b/1BIT/summer-semester/IJC-1/Makefile new file mode 100644 index 0000000..9164086 --- /dev/null +++ b/1BIT/summer-semester/IJC-1/Makefile @@ -0,0 +1,52 @@ +# Makefile +# Řešení IJC-DU1, 22.3.2024 +# Autor: Roman Nečas, FIT + +# Compiler and Flags +CC=gcc +CFLAGS += -g -std=c11 -pedantic -Wall -Wextra -fsanitize=address -O2 +LDFLAGS += -fsanitize=address + +# Executables +EXECUTABLES = primes primes-i no-comment + +# Default Target +.PHONY: all +all: $(EXECUTABLES) + +# Rules for Targets +primes: primes.o error.o eratosthenes.o + $(CC) $(CFLAGS) $(LDFLAGS) $^ -o $@ + +primes-i: primes-i.o error.o eratosthenes-i.o bitset.o + $(CC) $(CFLAGS) $(LDFLAGS) -DUSE_INLINE $^ -o $@ + +no-comment: no-comment.o error.o + $(CC) $(CFLAGS) $(LDFLAGS) $^ -o $@ + +# Rules for Object Files +primes.o: primes.c primes.h bitset.h +primes-i.o: primes.c + $(CC) $(CFLAGS) -DUSE_INLINE -c $^ -o $@ + +eratosthenes.o: eratosthenes.c primes.h bitset.h +eratosthenes-i.o: eratosthenes.c primes.h + $(CC) $(CFLAGS) -DUSE_INLINE -c $< -o $@ + +bitset.o: bitset.c bitset.h + $(CC) $(CFLAGS) -DUSE_INLINE -c $< -o $@ + +error.o: error.c error.h +no-comment.o: no-comment.c error.h + +# Clean +.PHONY: clean +clean: + rm $(EXECUTABLES) *.o + +# Run +.PHONY: run +run: primes primes-i + ulimit -s 81920 && ./primes + ulimit -s 81920 && ./primes-i + diff --git a/1BIT/summer-semester/IJC-1/bitset.c b/1BIT/summer-semester/IJC-1/bitset.c new file mode 100644 index 0000000..7f0f39d --- /dev/null +++ b/1BIT/summer-semester/IJC-1/bitset.c @@ -0,0 +1,17 @@ +// bitset.c +// Řešení IJC-DU1, příklad a), 22.3.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 13.2.1 +// +#include "bitset.h" + +/* Sets the specified bit in the array to the value given by the expression */ +extern void bitset_setbit(bitset_t name, bitset_index_t index, bool expr); + +extern void bitset_fill(bitset_t name, bool bool_expr); + +/* Gets the value of the specified bit, returns 0 or 1 */ +extern char bitset_getbit(bitset_t name, bitset_index_t index); + +/* Returns the declared size of the array stored at index 0 */ +extern unsigned long bitset_size(bitset_t name); diff --git a/1BIT/summer-semester/IJC-1/bitset.h b/1BIT/summer-semester/IJC-1/bitset.h new file mode 100644 index 0000000..e27573f --- /dev/null +++ b/1BIT/summer-semester/IJC-1/bitset.h @@ -0,0 +1,106 @@ +// bitset.h +// Řešení IJC-DU1, příklad a), 22.3.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 13.2.1 + +#ifndef BITSET_H + #define BITSET_H + + #include + #include + #include + #include + #include "error.h" + #include + + #define WORD_BITS (sizeof(unsigned long) * CHAR_BIT) // Number of bits in an unsigned long + #define WORD_BYTES sizeof(unsigned long) // Number of bytes in an unsigned long + #define HEADER_WORD 1 // First element is reserved for size + + /* Index type for the bit set. */ + typedef unsigned long bitset_index_t; + + /* Bit set type (for passing as a parameter by reference). */ + typedef unsigned long *bitset_t; + + /* MACROS that are used always */ + + /* defines and initializes the variable name */ + #define bitset_create(name, size) \ + static_assert(size > 0 && size < ULONG_MAX, "ERROR: bitset_create: Invalid array size."); \ + bitset_index_t name[(size)/WORD_BITS + HEADER_WORD + (((size) % WORD_BITS) ? 1 : 0)] = {size} + + #define bitset_alloc(name, size) \ + static_assert(size > 0 && size < ULONG_MAX, "ERROR: bitset_create: Invalid array size."); \ + bitset_t name = calloc((size)/WORD_BITS + HEADER_WORD + (((size) % WORD_BITS) ? 1 : 0), sizeof(bitset_index_t)); \ + if (name == NULL) error_exit("bitset_alloc: Memory allocation error"); \ + name[0] = size + + /* Frees the memory of a dynamically allocated array. */ + #define bitset_free(name) free(name) + + #ifdef USE_INLINE + /* INLINE FUNCTIONS */ + /* Returns the declared size of the array stored at index 0 */ + inline bitset_index_t bitset_size(bitset_t name) + { + return name[0]; + } + + /* Sets all bits in the array to 0 (false) or 1 (true) */ + inline void bitset_fill(bitset_t name, bool bool_expr) + { + unsigned long i; + for (i = HEADER_WORD; i < ((bitset_size(name) / WORD_BITS) + HEADER_WORD + (((bitset_size(name)) % WORD_BITS) ? 1 : 0)); i++) + { + name[i] = (bool_expr) ? ~0UL : 0UL; + } + } + + /* Sets the specified bit in the array to the value given by the expression */ + inline void bitset_setbit(bitset_t name, bitset_index_t index, bool bool_expr) + { + if (index >= bitset_size(name)) + error_exit("bitset_setbit: Index %lu out of range 0..%lu", (unsigned long)index, (unsigned long)bitset_size(name)); + name[(index/WORD_BITS) + HEADER_WORD] = (bool_expr) ? (name[(index/WORD_BITS) + HEADER_WORD] | (1UL << (index & (WORD_BITS - 1)))) + : (name[(index/WORD_BITS) + HEADER_WORD] & ~(1UL << (index & (WORD_BITS - 1)))); + } + + /* Gets the value of the specified bit, returns 0 or 1 */ + inline char bitset_getbit(bitset_t name, bitset_index_t index) + { + if (index >= bitset_size(name)) + error_exit("bitset_getbit: Index %lu out of range 0..%lu", (unsigned long)index, (unsigned long)bitset_size(name)); + return name[(index/WORD_BITS + HEADER_WORD)] >> (index & (WORD_BITS - 1)) & 1UL; + } + #else + /* MACROS */ + /* Sets all bits in the array to 0 (false) or 1 (true) */ + #define bitset_fill(name, bool_expr) do \ + { \ + unsigned long i; \ + for (i = HEADER_WORD; i < ((bitset_size(name) / WORD_BITS) + HEADER_WORD + (((bitset_size(name)) % WORD_BITS) ? 1 : 0)); i++) \ + { \ + name[i] = (bool_expr) ? ~0UL : 0UL; \ + } \ + } while (0) + + /* Sets the specified bit in the array to the value given by the expression */ + #define bitset_setbit(name, index, bool_expr) do \ + { \ + if ((index) >= bitset_size(name)) error_exit("bitset_setbit: Index %lu out of range 0..%lu", \ + (unsigned long)index, (unsigned long)bitset_size(name)); \ + name[((index)/WORD_BITS) + HEADER_WORD] = (bool_expr) ? (name[((index)/WORD_BITS) + HEADER_WORD] | (1UL << ((index) & (WORD_BITS - 1)))) \ + : (name[((index)/WORD_BITS) + HEADER_WORD] & ~(1UL << ((index) & (WORD_BITS - 1)))); \ + } while (0) + + /* Gets the value of the specified bit, returns 0 or 1 */ + #define bitset_getbit(name, index) \ + (((index) >= bitset_size(name)) ? (error_exit("bitset_getbit: Index %lu out of range 0..%lu", (unsigned long)index, (unsigned long)bitset_size(name)), 0) \ + : ((name[((index)/WORD_BITS + HEADER_WORD)] >> ((index) & (WORD_BITS - 1))) & 1UL)) + + /* Returns the declared size of the array stored at index 0 */ + #define bitset_size(name) name[0] + + #endif +#endif diff --git a/1BIT/summer-semester/IJC-1/eratosthenes.c b/1BIT/summer-semester/IJC-1/eratosthenes.c new file mode 100644 index 0000000..d6fcfae --- /dev/null +++ b/1BIT/summer-semester/IJC-1/eratosthenes.c @@ -0,0 +1,21 @@ +// bitset.h +// Řešení IJC-DU1, příklad a), 22.3.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 13.2.1 + +#include "primes.h" +void Eratosthenes(bitset_t pole) { + + bitset_index_t size = bitset_size(pole); + bitset_fill(pole, true); // Assume all numbers are prime initially + bitset_setbit(pole, 0, false); // 0 is not prime + bitset_setbit(pole, 1, false); // 1 is not prime + + for (bitset_index_t i = 2; i * i < size; i++) { + if (bitset_getbit(pole, i)) { + for (bitset_index_t j = i * i; j < size; j += i) { + bitset_setbit(pole, j, false); // Mark multiples of i as not prime + } + } + } +} diff --git a/1BIT/summer-semester/IJC-1/error.c b/1BIT/summer-semester/IJC-1/error.c new file mode 100644 index 0000000..b265089 --- /dev/null +++ b/1BIT/summer-semester/IJC-1/error.c @@ -0,0 +1,28 @@ +// error.c +// Řešení IJC-DU1, příklad a), 22.3.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 13.2.1 + +#include "error.h" +#include +#include +#include + +void warning(const char *fmt, ...) +{ + va_list args; + va_start(args, fmt); + fprintf(stderr, "Warning: "); + vfprintf(stderr, fmt, args); + va_end(args); +} + +void error_exit(const char *fmt, ...) +{ + va_list args; + va_start(args, fmt); + fprintf(stderr, "Error: "); + vfprintf(stderr, fmt, args); + va_end(args); + exit(1); +} diff --git a/1BIT/summer-semester/IJC-1/error.h b/1BIT/summer-semester/IJC-1/error.h new file mode 100644 index 0000000..566159c --- /dev/null +++ b/1BIT/summer-semester/IJC-1/error.h @@ -0,0 +1,12 @@ +// error.h +// Řešení IJC-DU1, příklad a), 22.3.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 13.2.1 + +#ifndef ERROR_H + #define ERROR_H + + void warning(const char *fmt, ...); + void error_exit(const char *fmt, ...); + +#endif diff --git a/1BIT/summer-semester/IJC-1/no-comment.c b/1BIT/summer-semester/IJC-1/no-comment.c new file mode 100644 index 0000000..6925f59 --- /dev/null +++ b/1BIT/summer-semester/IJC-1/no-comment.c @@ -0,0 +1,163 @@ +// no-comment.c +// Řešení IJC-DU1, příklad b), 22.3.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 13.2.1 + + +#include +#include "error.h" + +int main(int argc, char *argv[]) +{ + FILE *fp; + int state = 0; + int c; + int lastChar = 0; // To keep track of the last character to handle line continuation in comments + + if (argc > 2) + { + error_exit("Too many arguments"); + } + + if(argc == 2) + { + fp = fopen(argv[1], "r"); + if (!fp) { + error_exit("Cannot open file: %s", argv[1]); + } + } + else + { + fp = stdin; + } + + while ((c = fgetc(fp)) != EOF) + { + switch (state) + { + case 0: // Normal code + if (c == '/') + { + state = 1; // Possible comment start + } + else if (c == '"') + { + putchar(c); + state = 4; // String literal start + } + else if (c == '\'') // Handle single quotes + { + putchar(c); + state = 7; // Character literal start + } + else + { + putchar(c); + } + break; + + case 1: // After first '/' + if (c == '*') + { + state = 2; // Multi-line comment start + } + else if (c == '/') + { + // Transition to single-line comment state but do not output '/' + state = 6; // Single-line comment start + } + else + { + putchar('/'); // Not a comment, print '/' and current char + putchar(c); + state = 0; + } + break; + + case 2: // Inside multi-line comment + if (c == '*') + { + state = 3; // Possible end of comment + } + break; + + case 3: // Possible end of multi-line comment + if (c == '/') + { + state = 0; // End of comment + } + else if (c != '*') + { + state = 2; // Still inside comment + } + break; + + case 4: // Inside string literal + if (c == '\\') + { + putchar(c); + c = fgetc(fp); // Read next character + putchar(c); // Print escaped character + // Do not change state, stay in string literal + } + else if (c == '"') + { + putchar(c); // End of string literal + state = 0; + } + else + { + putchar(c); // Part of string literal + } + break; + + case 5: // After escape character in string literal + putchar(c); // Print escaped character + state = 4; + break; + + case 6: // Inside single-line comment + if (c == '\n') + { + if (lastChar != '\\') // If not a continuation + { + putchar(c); // Ensure newline is outputted to maintain original structure + state = 0; // End of single-line comment + } + // If it was a continuation, simply ignore and continue in state 6 + } + break; + + case 7: // Inside character literal + putchar(c); + if (c == '\\') + { + state = 8; // Escape sequence within character literal + } + else if (c == '\'') + { + state = 0; // End of character literal + } + break; + + case 8: // After escape character in character literal + putchar(c); // Print escaped character + state = 7; // Return to character literal state + break; + } + lastChar = c; // Update lastChar at the end of the loop + } + + if (ferror(fp)) + { + error_exit("Read error\n"); + } + + if (state != 0) + { + error_exit("Unterminated comment or string\n"); + } + + fclose(fp); + return 0; +} diff --git a/1BIT/summer-semester/IJC-1/primes.c b/1BIT/summer-semester/IJC-1/primes.c new file mode 100644 index 0000000..4061895 --- /dev/null +++ b/1BIT/summer-semester/IJC-1/primes.c @@ -0,0 +1,36 @@ +// primes.c +// Řešení IJC-DU1, příklad a), 22.3.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 13.2.1 + +#include "primes.h" +#include +#include + +#define N 666000000 + +int main() { + clock_t start = clock(); + bitset_create(name, N); + Eratosthenes(name); + + // Saves last 10 primes + bitset_index_t primes[10] = {0, }; + int count = 0; + for (bitset_index_t i = bitset_size(name)-1; count < 10 && i > 0; i--) + { + if (bitset_getbit(name, i)) + { + primes[9 - count++] = i; + } + } + //Writes last 10 primes + for (unsigned int i = 0; i < 10; i++) + { + printf("%lu\n", primes[i]); + } + + fprintf(stderr, "Time=%.3g\n", (double)(clock() - start) / CLOCKS_PER_SEC); + return 0; + +} diff --git a/1BIT/summer-semester/IJC-1/primes.h b/1BIT/summer-semester/IJC-1/primes.h new file mode 100644 index 0000000..6a65e73 --- /dev/null +++ b/1BIT/summer-semester/IJC-1/primes.h @@ -0,0 +1,13 @@ +// primes.h +// Řešení IJC-DU1, příklad a), 22.3.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 13.2.1 + +#ifndef PRIMES_H +#define PRIMES_H + +#include "bitset.h" + +void Eratosthenes(bitset_t name); + +#endif diff --git a/1BIT/summer-semester/IJC-1/xnecasr00.zip b/1BIT/summer-semester/IJC-1/xnecasr00.zip new file mode 100644 index 0000000..4cf1624 Binary files /dev/null and b/1BIT/summer-semester/IJC-1/xnecasr00.zip differ diff --git a/1BIT/summer-semester/IJC-2/Makefile b/1BIT/summer-semester/IJC-2/Makefile new file mode 100644 index 0000000..09fd328 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/Makefile @@ -0,0 +1,56 @@ +#Makefile +#Řešení IJC-DU2, 22.4.2024 +#Autor: Roman Nečas, FIT + +# Nastavenie kompilátora a príznakov +CC=gcc +CFLAGS=-std=c11 -pedantic -Wall -Wextra -g +PIC_CFLAGS=$(CFLAGS) -fPIC + +# Zdrojove subory kniznice +HTAB_SRCS=htab_init.c htab_size.c htab_bucket_count.c htab_find.c htab_lookup_add.c htab_erase.c htab_for_each.c htab_clear.c htab_free.c htab_statistics.c htab_hash_function.c + +#Ciele +all: tail wordcount wordcount-dynamic libhtab.a libhtab.so + +# Pravidla pre programy +tail: tail.o + $(CC) $(CFLAGS) $< -o $@ + +wordcount: wordcount.o io.o libhtab.a + $(CC) $(CFLAGS) $^ -o $@ + +wordcount-dynamic: wordcount.o io.o libhtab.so + $(CC) $(CFLAGS) $^ -o $@ + +# Zavislosti pre objektove subory +%.o: %.c htab.h htab_struct.h + $(CC) $(PIC_CFLAGS) -c $< + +io.o: io.c + $(CC) $(CFLAGS) -c $< + +# Pravidla pre staticku a dynamicku kniznicu +libhtab.a: $(HTAB_SRCS:.c=.o) + ar rcs $@ $^ + +libhtab.so: $(HTAB_SRCS:.c=.o) + $(CC) $(CFLAGS) -shared -o $@ $^ + +# Pravidla pre spustenie programov +run: run-tail run-wordcount run-wordcount-dynamic + +run-wordcount: wordcount + ./wordcount < wordcount.c + +run-wordcount-dynamic: wordcount-dynamic + LD_LIBRARY_PATH="." ./wordcount-dynamic < wordcount.c + +run-tail: tail + ./tail < wordcount.c + +# Cistenie +clean: + rm -f *.o *.a *.so tail wordcount wordcount-dynamic + +.PHONY: all clean run run-wordcount run-wordcount-dynamic run-tail \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab.h b/1BIT/summer-semester/IJC-2/htab.h new file mode 100644 index 0000000..154e580 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab.h @@ -0,0 +1,49 @@ +// htab.h -- rozhraní knihovny htab (řešení IJC-DU2) +// Licence: žádná (Public domain) + +// následující řádky zabrání násobnému vložení: +#ifndef HTAB_H__ +#define HTAB_H__ + +#include // size_t +#include // bool + +// Tabulka: +struct htab; // neúplná deklarace struktury - uživatel nevidí obsah +typedef struct htab htab_t; // typedef podle zadání + +// Typy: +typedef const char * htab_key_t; // typ klíče +typedef int htab_value_t; // typ hodnoty + +// Dvojice dat v tabulce: +typedef struct htab_pair { + htab_key_t key; // klíč + htab_value_t value; // asociovaná hodnota +} htab_pair_t; // typedef podle zadání + +// Rozptylovací (hash) funkce (stejná pro všechny tabulky v programu) +// Pokud si v programu definujete stejnou funkci, použije se ta vaše. +size_t htab_hash_function(htab_key_t str); + +// Funkce pro práci s tabulkou: +htab_t *htab_init(const size_t n); // konstruktor tabulky +size_t htab_size(const htab_t * t); // počet záznamů v tabulce +size_t htab_bucket_count(const htab_t * t); // velikost pole + +htab_pair_t * htab_find(const htab_t * t, htab_key_t key); // hledání +htab_pair_t * htab_lookup_add(htab_t * t, htab_key_t key); + +bool htab_erase(htab_t * t, htab_key_t key); // ruší zadaný záznam + +// for_each: projde všechny záznamy a zavolá na ně funkci f +// Pozor: f nesmí měnit klíč .key ani přidávat/rušit položky +void htab_for_each(const htab_t * t, void (*f)(htab_pair_t *data)); + +void htab_clear(htab_t * t); // ruší všechny záznamy +void htab_free(htab_t * t); // destruktor tabulky + +// výpočet a tisk statistik délky seznamů (min,max,avg) do stderr: +void htab_statistics(const htab_t * t); + +#endif // HTAB_H__ \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_bucket_count.c b/1BIT/summer-semester/IJC-2/htab_bucket_count.c new file mode 100644 index 0000000..41cf6d2 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_bucket_count.c @@ -0,0 +1,11 @@ +// htab_bucket_count.c +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include "htab.h" +#include "htab_struct.h" + +size_t htab_bucket_count(const htab_t *t) { + return t->arr_size; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_clear.c b/1BIT/summer-semester/IJC-2/htab_clear.c new file mode 100644 index 0000000..5a0f3ad --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_clear.c @@ -0,0 +1,22 @@ +// htab_clear.c +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include +#include "htab.h" +#include "htab_struct.h" + +void htab_clear(htab_t *t) { + for (size_t i = 0; i < t->arr_size; i++) { + struct htab_item *item = t->arr_ptr[i]; + while (item != NULL) { + struct htab_item *next = item->next; + free((void *)item->pair.key); + free(item); + item = next; + } + t->arr_ptr[i] = NULL; + } + t->size = 0; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_erase.c b/1BIT/summer-semester/IJC-2/htab_erase.c new file mode 100644 index 0000000..5451c59 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_erase.c @@ -0,0 +1,30 @@ +// htab_erase.c +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include +#include +#include "htab.h" +#include "htab_struct.h" + +bool htab_erase(htab_t *t, htab_key_t key) { + size_t idx = htab_hash_function(key) % t->arr_size; + struct htab_item *item = t->arr_ptr[idx]; + struct htab_item *prev = NULL; + while (item != NULL) { + if (strcmp(item->pair.key, key) == 0) { + if (prev == NULL) + t->arr_ptr[idx] = item->next; + else + prev->next = item->next; + free((void *)item->pair.key); + free(item); + t->size--; + return true; + } + prev = item; + item = item->next; + } + return false; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_find.c b/1BIT/summer-semester/IJC-2/htab_find.c new file mode 100644 index 0000000..ae52b95 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_find.c @@ -0,0 +1,19 @@ +// htab_find.c +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include +#include "htab.h" +#include "htab_struct.h" + +htab_pair_t *htab_find(const htab_t *t, htab_key_t key) { + size_t idx = htab_hash_function(key) % t->arr_size; + struct htab_item *item = t->arr_ptr[idx]; + while (item != NULL) { + if (strcmp(item->pair.key, key) == 0) + return &item->pair; + item = item->next; + } + return NULL; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_for_each.c b/1BIT/summer-semester/IJC-2/htab_for_each.c new file mode 100644 index 0000000..3a13b07 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_for_each.c @@ -0,0 +1,17 @@ +// htab_for_each.c +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include "htab.h" +#include "htab_struct.h" + +void htab_for_each(const htab_t *t, void (*f)(htab_pair_t *data)) { + for (size_t i = 0; i < t->arr_size; i++) { + struct htab_item *item = t->arr_ptr[i]; + while (item != NULL) { + f(&item->pair); + item = item->next; + } + } +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_free.c b/1BIT/summer-semester/IJC-2/htab_free.c new file mode 100644 index 0000000..c9f93d0 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_free.c @@ -0,0 +1,13 @@ +// htab_free.c +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include "htab.h" +#include "htab_struct.h" +#include + +void htab_free(htab_t *t) { + htab_clear(t); + free(t); +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_hash_function.c b/1BIT/summer-semester/IJC-2/htab_hash_function.c new file mode 100644 index 0000000..f36fedf --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_hash_function.c @@ -0,0 +1,14 @@ +// htab_hash_function.c +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include "htab.h" + +size_t htab_hash_function(htab_key_t str) { + int h = 0; + const unsigned char *p; + for (p = (const unsigned char *)str; *p != '\0'; p++) + h = 65599 * h + *p; + return h; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_init.c b/1BIT/summer-semester/IJC-2/htab_init.c new file mode 100644 index 0000000..6aecccd --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_init.c @@ -0,0 +1,20 @@ +// htab_init +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include +#include "htab.h" +#include "htab_struct.h" + +htab_t *htab_init(const size_t n) { + htab_t *t = malloc(sizeof(htab_t) + n * sizeof(struct htab_item *)); + if (t == NULL) + return NULL; + t->size = 0; + t->arr_size = n; + t->arr_ptr = (struct htab_item **)((char *)t + sizeof(htab_t)); + for (size_t i = 0; i < n; i++) + t->arr_ptr[i] = NULL; + return t; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_lookup_add.c b/1BIT/summer-semester/IJC-2/htab_lookup_add.c new file mode 100644 index 0000000..54a5b3d --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_lookup_add.c @@ -0,0 +1,44 @@ +// htab_lookup_add +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include +#include +#include "htab.h" +#include "htab_struct.h" + +htab_pair_t *htab_lookup_add(htab_t *t, htab_key_t key) { + size_t idx = htab_hash_function(key) % t->arr_size; + struct htab_item *item = t->arr_ptr[idx]; + struct htab_item *prev = NULL; + while (item != NULL) { + if (strcmp(item->pair.key, key) == 0) + return &item->pair; + prev = item; + item = item->next; + } + + // kluc nebol najdeny, musime pridat novy zaznam + char *new_key = malloc(strlen(key) + 1); + if (new_key == NULL) + return NULL; + strcpy(new_key, key); + + struct htab_item *new_item = malloc(sizeof(struct htab_item)); + if (new_item == NULL) { + free(new_key); + return NULL; + } + new_item->pair.key = new_key; + new_item->pair.value = 0; + new_item->next = NULL; + + if (prev == NULL) + t->arr_ptr[idx] = new_item; + else + prev->next = new_item; + + t->size++; + return &new_item->pair; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_size.c b/1BIT/summer-semester/IJC-2/htab_size.c new file mode 100644 index 0000000..280602e --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_size.c @@ -0,0 +1,11 @@ +// htab_size +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include "htab.h" +#include "htab_struct.h" + +size_t htab_size(const htab_t *t) { + return t->size; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_statistics.c b/1BIT/summer-semester/IJC-2/htab_statistics.c new file mode 100644 index 0000000..ae7a006 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_statistics.c @@ -0,0 +1,25 @@ +// htab_statistics +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include +#include "htab.h" +#include "htab_struct.h" + +void htab_statistics(const htab_t *t) { + size_t max_len = 0, sum_len = 0; + for (size_t i = 0; i < t->arr_size; i++) { + size_t len = 0; + struct htab_item *item = t->arr_ptr[i]; + while (item != NULL) { + len++; + item = item->next; + } + if (len > max_len) + max_len = len; + sum_len += len; + } + double avg_len = (double)sum_len / t->arr_size; + fprintf(stderr, "Statistiky delky seznamu: min=0, max=%zu, avg=%.2f\n", max_len, avg_len); +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/htab_struct.h b/1BIT/summer-semester/IJC-2/htab_struct.h new file mode 100644 index 0000000..53d3075 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/htab_struct.h @@ -0,0 +1,23 @@ +// htab_struct.h +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#ifndef HTAB_STRUCT_H +#define HTAB_STRUCT_H + +#include "htab.h" + +// Definicia privatnej struktury +struct htab_item{ + htab_pair_t pair; + struct htab_item *next; +}; + +struct htab{ + size_t size; + size_t arr_size; + struct htab_item **arr_ptr; +}; + +#endif // HTAB_STRUCT_H \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/io.c b/1BIT/summer-semester/IJC-2/io.c new file mode 100644 index 0000000..74bea0f --- /dev/null +++ b/1BIT/summer-semester/IJC-2/io.c @@ -0,0 +1,23 @@ +// io.c +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include +#include +#include "io.h" + +int read_word(char *s, int max, FILE *f) { + int c, len = 0; + while ((c = fgetc(f)) != EOF && isspace(c)) + ; // ignoruj uvodne biele znaky + if (c == EOF) + return EOF; + s[len++] = c; + while ((c = fgetc(f)) != EOF && !isspace(c)) { + if (len < max) + s[len++] = c; + } + s[len] = '\0'; + return len; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/io.h b/1BIT/summer-semester/IJC-2/io.h new file mode 100644 index 0000000..6d81099 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/io.h @@ -0,0 +1,13 @@ +// io.h +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#ifndef IO_H +#define IO_H + +#include + +int read_word(char *s, int max, FILE *f); + +#endif \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/tail.c b/1BIT/summer-semester/IJC-2/tail.c new file mode 100644 index 0000000..2a5a6f0 --- /dev/null +++ b/1BIT/summer-semester/IJC-2/tail.c @@ -0,0 +1,196 @@ +// tail.c +// Řešení IJC-DU2, příklad a), 15.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include +#include +#include +#include +#include + +#define MAX_LINE_LENGTH 2048 // Maximalna dlzka riadku je 2047 + '\n' + +typedef struct { + char **buffer; // pole ukazatelov na riadky + int size; // velkost bufferu + int start; // Index prveho riadku + int count; // pocet riadkov v bufferi +} CircularBuffer; + +// vytvori kruhovy buffer s kapacitou n +CircularBuffer *cbuf_create(int n) { + CircularBuffer *cb = (CircularBuffer *)malloc(sizeof(CircularBuffer)); + if (cb == NULL) { + fprintf(stderr, "Error: Failed to allocate memory for circular buffer.\n"); + exit(EXIT_FAILURE); + } + cb->buffer = (char **)malloc(n * sizeof(char *)); + if (cb->buffer == NULL) { + fprintf(stderr, "Error: Failed to allocate memory for line buffer.\n"); + exit(EXIT_FAILURE); + } + for (int i = 0; i < n; i++) { + cb->buffer[i] = (char *)malloc((MAX_LINE_LENGTH+1) * sizeof(char)); + if (cb->buffer[i] == NULL) { + fprintf(stderr, "Error: Failed to allocate memory for line.\n"); + exit(EXIT_FAILURE); + } + } + cb->size = n; + cb->start = 0; + cb->count = 0; + return cb; +} + +// vloz riadok do bufferu +void cbuf_put(CircularBuffer *cb, char *line) { + line[MAX_LINE_LENGTH] = '\0'; + line[MAX_LINE_LENGTH-1] = '\n'; + strncpy(cb->buffer[(cb->start + cb->count) % cb->size], line, MAX_LINE_LENGTH); + cb->buffer[(cb->start + cb->count) % cb->size][MAX_LINE_LENGTH] = '\0'; + if (cb->count < cb->size) { + cb->count++; + } else { + cb->start = (cb->start + 1) % cb->size; + } +} + +// nacitaj riadok z bufferu +char *cbuf_get(CircularBuffer *cb, int index) { + if (index < 0 || index >= cb->count) { + fprintf(stderr, "Error: Line index out of buffer range.\n"); + exit(EXIT_FAILURE); + } + return cb->buffer[(cb->start + index) % cb->size]; +} + +// vyscisti pamat +void cbuf_free(CircularBuffer *cb) { + for (int i = 0; i < cb->size; i++) { + free(cb->buffer[i]); + } + free(cb->buffer); + free(cb); +} + +bool isNumber(char *str) { + for(int i = 0; str[i] != '\0'; i++) { + if(!isdigit(str[i])) { + return false; + } + } + return true; +} +int main(int argc, char *argv[]) { + int n = 10; // defaultny pocet riadkov + FILE *file = stdin; + + // Parsing argumentov + if (argc == 3 && strcmp(argv[1], "-n") == 0) { // 3 argumenty nacitja z stdin + if(isNumber(argv[2]) == false) + { + fprintf(stderr, "Error: Invalid number of lines.\n"); + return 1; + } + n = atoi(argv[2]); + if (n < 0) { + fprintf(stderr, "Error: Invalid number of lines.\n"); + return EXIT_FAILURE; + } + else if (n == 0) + { + return 0; + } + } + else if(argc == 4 && strcmp(argv[1], "-n") == 0) { // 4 argumenty, subor je posledny + if(isNumber(argv[2]) == false) + { + fprintf(stderr, "Error: Invalid number of lines.\n"); + return 1; + } + n = atoi(argv[2]); + if (n < 0) { + fprintf(stderr, "Error: Invalid number of lines.\n"); + return EXIT_FAILURE; + } + else if (n == 0) + { + return 0; + } + file = fopen(argv[3], "r"); + if (file == NULL) { + fprintf(stderr, "Error: Unable to open file '%s'.\n", argv[3]); + return EXIT_FAILURE; + } + } + else if(argc == 4 && strcmp(argv[2], "-n") == 0) { // 4 argumenty, subor je 2 + if(isNumber(argv[3]) == false) + { + fprintf(stderr, "Error: Invalid number of lines.\n"); + return 1; + } + + n = atoi(argv[3]); + if (n < 0) { + fprintf(stderr, "Error: Invalid number of lines.\n"); + return EXIT_FAILURE; + } + else if (n == 0) + { + return 0; + } + file = fopen(argv[1], "r"); + if (file == NULL) { + fprintf(stderr, "Error: Unable to open file '%s'.\n", argv[1]); + return EXIT_FAILURE; + } + } + + else if (argc == 2) { // 2 argument, subor je druhy + file = fopen(argv[1], "r"); + if (file == NULL) { + fprintf(stderr, "Error: Unable to open file '%s'.\n", argv[1]); + return EXIT_FAILURE; + } + } else if(argc != 1) { + fprintf(stderr, "Usage: %s [-n number] [file]\n", argv[0]); + return EXIT_FAILURE; + } + + // Inicializacia kruhoveho bufferu + CircularBuffer *cb = cbuf_create(n); + + // nacitame riadky + char line[MAX_LINE_LENGTH]; + int islonger = 0; + while (fgets(line, sizeof(line), file) != NULL) { + int len = strlen(line); + if (len == (MAX_LINE_LENGTH-1) && line[MAX_LINE_LENGTH -1] != '\n') { + islonger = 1; + // zahodime zvysok riadku + int c; + while ((c = fgetc(file)) != '\n'&& c!= EOF); + } + cbuf_put(cb, line); + } + if (islonger == 1) + { + fprintf(stderr, "Too long line, above limit will be truncated\n"); + } + + // vypiseme poslledne riadky + int start_index = cb->count >= n ? cb->count - n : 0; + for (int i = start_index; i < cb->count; i++) { + printf("%s", cbuf_get(cb, i)); + } + + // vycisti pamet + cbuf_free(cb); + if (file != stdin) { + fclose(file); + } + + return EXIT_SUCCESS; +} + diff --git a/1BIT/summer-semester/IJC-2/wordcount.c b/1BIT/summer-semester/IJC-2/wordcount.c new file mode 100644 index 0000000..532806a --- /dev/null +++ b/1BIT/summer-semester/IJC-2/wordcount.c @@ -0,0 +1,49 @@ +// wordcount.c +// Řešení IJC-DU2, příklad b), 22.4.2024 +// Autor: Roman Nečas, FIT +// Přeloženo: gcc 11.4.0 + +#include +#include "htab.h" +#include "io.h" +#include "htab_struct.h" + +#define MAX_WORD_LEN 255 +#define HTAB_SIZE 130003 //program som testoval napriklad na prikaze seq 100000 200000|shuf, teda 100 0000 slov, velkost by mala byt 1.3 + //nasobok a zaroven prvocislo, teda najblizsie cislo je 130003 + +static void print_pair(htab_pair_t *pair) { + printf("%s\t%d\n", pair->key, pair->value); +} +int main() { + htab_t *t = htab_init(HTAB_SIZE); + if (t == NULL) { + fprintf(stderr, "Chyba: Nedostatok pamati pre tabulku\n"); + return 1; + } + + char word[MAX_WORD_LEN]; + int ret; + while ((ret = read_word(word, sizeof(word), stdin)) != EOF) { + if (ret == MAX_WORD_LEN) { + fprintf(stderr, "Varovanie: Niektore slova boli skratene na 255 znakov.\n"); + } + htab_pair_t *pair = htab_lookup_add(t, word); + if (pair == NULL) { + fprintf(stderr, "Chyba: Nedostatok pamati pre novy zaznam\n"); + htab_free(t); + return 1; + } + pair->value++; + } + + htab_for_each(t, print_pair); + +#ifdef STATISTICS + htab_statistics(t); +#endif + + + htab_free(t); + return 0; +} \ No newline at end of file diff --git a/1BIT/summer-semester/IJC-2/xnecasr00.zip b/1BIT/summer-semester/IJC-2/xnecasr00.zip new file mode 100644 index 0000000..c7319db Binary files /dev/null and b/1BIT/summer-semester/IJC-2/xnecasr00.zip differ diff --git a/1BIT/summer-semester/INC/xnecasr00.zip b/1BIT/summer-semester/INC/xnecasr00.zip new file mode 100644 index 0000000..b5a9c81 Binary files /dev/null and b/1BIT/summer-semester/INC/xnecasr00.zip differ diff --git a/1BIT/summer-semester/IOS-1/hodnoceni.tgz b/1BIT/summer-semester/IOS-1/hodnoceni.tgz new file mode 100644 index 0000000..b715352 Binary files /dev/null and b/1BIT/summer-semester/IOS-1/hodnoceni.tgz differ diff --git a/1BIT/summer-semester/IOS-1/xtf b/1BIT/summer-semester/IOS-1/xtf new file mode 100644 index 0000000..6421162 --- /dev/null +++ b/1BIT/summer-semester/IOS-1/xtf @@ -0,0 +1,154 @@ +#!/bin/sh +#xnecasr00 Roman Nečas +#9.3.2024 + +export POSIXLY_CORRECT=yes + +# Function to display help message +print_help() { + echo "Usage: xtf [-h|--help] [FILTER] [COMMAND] USER LOG [LOG2 ...]" + echo "" + echo "Options:" + echo "" + echo " COMMAND can be one of these:" + echo " list - displays records for the given user." + echo " list-currency - displays sorted list of currencies." + echo " status - displays account status for the given user." + echo " profit - calculates profit for the given user." + echo "" + echo " FILTER can be a combination of:" + echo " -a DATETIME - after: considers records after this date and time (exclusive)." + echo " -b DATETIME - before: considers records before this date and time (exclusive)." + echo " -c CURRENCY - considers records matching the given currency." + echo "" + echo " -h or --help displays this help message." +} + +# Function to display error message and exit with code 1 +print_error() { + echo "Error: $1" >&2 + exit 1 +} + +# Function to validate date +validate_date() { + date -d "$1" >/dev/null 2>&1 || print_error "Invalid date: $1" +} + +USER="" +LOGS="" +COMMAND="" +AFTER_DATE="" +BEFORE_DATE="" +CURRENCY_FILTER="" + +# Process arguments +while [ "$#" -gt 0 ]; do + case $1 in + -h|--help) + print_help + exit 0 + ;; + list|list-currency|status|profit) + if [ -z "$COMMAND" ]; then + COMMAND=$1 + else + print_error "Multiple commands provided" + fi + ;; + -a) + validate_date "$2" + AFTER_DATE=$2 + shift + ;; + -b) + validate_date "$2" + if [ -z "$BEFORE_DATE" ]; then + BEFORE_DATE=$2 + else + print_error "Multiple 'before' dates provided. Please provide only one 'before' date." + fi + shift + ;; + -c) + CURRENCY_FILTER=$2 + shift + ;; + *) + if [ -z "$USER" ]; then + USER=$1 + else + # Use a special character to separate log files + LOGS="$LOGS|$1" + fi + ;; + esac + shift +done + +# Set default command (list) if none specified +if [ -z "$COMMAND" ]; then + COMMAND="list" +fi + +# Check if user is specified +if [ -z "$USER" ]; then + print_error "No user specified." +fi + +# Change IFS to handle log files with spaces +OLD_IFS="$IFS" +IFS="|" + +# Process logs +for LOG in $LOGS +do + case "$LOG" in + *.gz) + zcat "$LOG" || print_error "Failed to read log: $LOG" + ;; + *) + cat "$LOG" || print_error "Failed to read log: $LOG" + ;; + esac +done + +# Restore IFS +IFS="$OLD_IFS" + +# Filter records +awk -v user="$USER" -v after="$AFTER_DATE" -v before="$BEFORE_DATE" -v currency_filter="$CURRENCY_FILTER" ' + BEGIN { + FS=";" + } + { + if ($1 == "" || $2 !~ /^[0-9]{4}-[0-9]{2}-[0-9]{2} [0-9]{2}:[0-9]{2}:[0-9]{2}$/ || $3 !~ /^[A-Z]{3}$/ || + $4 !~ /^-?[0-9]+\.[0-9]{4}$/) { + print "Error: Invalid record format: " $0 > "/dev/stderr" + exit 1 + } + } + $1 == user && ($2 > after || after == "") && ($2 < before || before == "") && ($3 ~ currency_filter || currency_filter == "") { + print + } +' | +# Process command +case "$COMMAND" in + list) + cat + ;; + list-currency) + awk -F ";" '{print $3}' | sort -u + ;; + status) + awk -F ";" '{ currency[$3] += $4 } END { for (cur in currency) { printf "%s : %.4f\n", cur, currency[cur] } }' | sort + ;; + profit) + if [ -z "$XTF_PROFIT" ]; then + XTF_PROFIT=20 + fi + awk -v profit="$XTF_PROFIT" -F ";" '{ currency[$3] += $4 } END { for (cur in currency) { if (currency[cur] > 0) currency[cur] = + currency[cur] * (1 + profit / 100); printf "%s : %.4f\n", cur, currency[cur] } }' | sort + ;; +esac + diff --git a/1BIT/summer-semester/IOS-2/Makefile b/1BIT/summer-semester/IOS-2/Makefile new file mode 100644 index 0000000..13d10f3 --- /dev/null +++ b/1BIT/summer-semester/IOS-2/Makefile @@ -0,0 +1,17 @@ +# Makefile pro proj2 + +CC = gcc +CFLAGS = -std=gnu99 -Wall -Wextra -Werror -pedantic -pthread +LDLIBS = -lrt -pthread +SOURCES = proj2.c +EXECUTABLE = proj2 + +all: $(EXECUTABLE) + +$(EXECUTABLE): $(SOURCES) + $(CC) $(CFLAGS) $(SOURCES) -o $@ $(LDLIBS) + +clean: + rm -f $(EXECUTABLE) + +.PHONY: all clean diff --git a/1BIT/summer-semester/IOS-2/proj2.c b/1BIT/summer-semester/IOS-2/proj2.c new file mode 100644 index 0000000..4dc58ba --- /dev/null +++ b/1BIT/summer-semester/IOS-2/proj2.c @@ -0,0 +1,309 @@ +//Autor: Roman Necas + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +// Macros for memory mapping +#define MMAP(ptr) {(ptr) = mmap(NULL, sizeof(*(ptr)), PROT_READ | PROT_WRITE, MAP_SHARED | MAP_ANONYMOUS, -1, 0);} +#define UNMAP(ptr) {munmap((ptr), sizeof(*(ptr)));} + +// Shared memory variables + +int *order = NULL; // Order of execution for print statements +int *bus_stop; // Array to store bus stop IDs for each skier + +// Semaphores +sem_t *sem_mutex = NULL; // Mutex semaphore for critical sections +sem_t *sem_boarded = NULL; // Semaphore for skiers boarding the bus +sem_t *sem_order = NULL; // Semaphore for print order +sem_t *sem_ubus = NULL; // Semaphore for skiers unboarding the bus +sem_t *sem_unboard = NULL; // Semaphore for skiers unboarding the bus +sem_t **sem_busstops = NULL; // Array of semaphores for each bus stop + +FILE *output; // File pointer for output + +// Function prototypes +void bus_loop(int Z, int K, int TB, int L); +void skier_loop(int idL, int idZ, int TL); + +int main(int argc, char* argv[]) { + // Check for correct number of arguments + if (argc != 6) { + fprintf(stderr, "Usage: %s L Z K TL TB\n", argv[0]); + return 1; + } + + // Parse command-line arguments + int L = atoi(argv[1]); // Number of skiers + int Z = atoi(argv[2]); // Number of bus stops + int K = atoi(argv[3]); // Maximum skiers on the bus + int TL = atoi(argv[4]); // Maximum time for a skier to reach the bus stop + int TB = atoi(argv[5]); // Maximum time for the bus to travel between stops + + // Validate argument values + if (L < 0 || L >= 20000 || Z <= 0 || Z > 10 || K < 10 || K > 100 || TL < 0 || TL > 10000 || TB < 0 || TB > 1000) { + fprintf(stderr, "Invalid arguments\n"); + return 1; + } + output = fopen("proj2.out", "w"); + + // Memory mapping for shared variables + + MMAP(order); + bus_stop = mmap(NULL, sizeof(*bus_stop) * L, PROT_READ | PROT_WRITE, + MAP_SHARED | MAP_ANONYMOUS, -1, 0); + for (int i = 0; i < L; i++) { + bus_stop[i] = 0; // Initialize bus stop array + } + + *order = 1; // Initialize order + + // Create semaphores + if (( sem_mutex = sem_open("/xnecasr00_sem_mutex", O_CREAT | O_EXCL, 0666, 1)) == SEM_FAILED) { + fprintf(stderr, "Error: Opening sem_mutex failed.\n"); + return 1; + } + if ((sem_boarded = sem_open("/xnecasr00_sem_boarded", O_CREAT | O_EXCL, 0666, 0)) == SEM_FAILED) { + fprintf(stderr, "Error: Opening sem_boarded failed.\n"); + return 1; + } + if ((sem_order = sem_open("/xnecasr00_sem_order", O_CREAT | O_EXCL, 0666, 1)) == SEM_FAILED) { + fprintf(stderr, "Error: Opening sem_order failed.\n"); + return 1; + } + if ((sem_ubus = sem_open("/xnecasr00_sem_ubus", O_CREAT | O_EXCL, 0666, 0)) == SEM_FAILED) { + fprintf(stderr, "Error: Opening sem_ubus failed.\n"); + return 1; + } + if ((sem_unboard = sem_open("/xnecasr00_sem_unboard", O_CREAT | O_EXCL, 0666, 0)) == SEM_FAILED) { + fprintf(stderr, "Error: Opening sem_unboard failed.\n"); + return 1; + } + + // Create semaphores for each bus stop + MMAP(sem_busstops); + for (int i = 0; i < Z; i++) { + char sem_name[35]; + snprintf(sem_name, sizeof(sem_name), "/xnecasr00_sem_busstop_%d", i + 1); + if ((sem_busstops[i] = sem_open(sem_name, O_CREAT | O_EXCL, 0666, 0)) == SEM_FAILED) { + fprintf(stderr, "Error: Opening semaphore %s failed.\n", sem_name); + return 1; + } + } + + // Fork for bus process + pid_t bus_pid = fork(); + if (bus_pid == -1) { + perror("fork"); + return 1; + } else if (bus_pid == 0) { + bus_loop(Z, K, TB, L); + exit(0); + } + + // Fork for skier processes + for (int i = 1; i <= L; i++) { + pid_t skier_pid = fork(); + if (skier_pid == -1) { + perror("fork"); + return 1; + } else if (skier_pid == 0) { + srand(time(0) * getpid()); + int idZ = rand() % Z + 1; // Randomly assign bus stop ID + skier_loop(i, idZ, TL); + exit(0); + } + } + + // Wait for all child processes to finish + for (int i = 0; i <= L; i++) { + wait(NULL); + } + + // Clean up shared memory and semaphores + + UNMAP(order); + munmap(bus_stop, sizeof(*bus_stop)*L); + sem_close(sem_mutex); + sem_unlink("/xnecasr00_sem_mutex"); + sem_close(sem_boarded); + sem_unlink("/xnecasr00_sem_boarded"); + sem_close(sem_order); + sem_unlink("/xnecasr00_sem_order"); + sem_close(sem_ubus); + sem_unlink("/xnecasr00_sem_ubus"); + sem_close(sem_unboard); + sem_unlink("/xnecasr00_sem_unboard"); + + // Close and unlink semaphores for each bus stop + for (int i = 0; i < Z; i++) { + char sem_name[35]; + snprintf(sem_name, sizeof(sem_name), "/xnecasr00_sem_busstop_%d", i + 1); + sem_close(sem_busstops[i]); + sem_unlink(sem_name); + } + + fclose(output); + + return 0; +} + +void bus_loop(int Z, int K, int TB, int L) { + srand(time(0) * getpid()); + + // Print bus started + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: BUS: started\n", *order); + *order += 1; + sem_post(sem_order); + + int boarded = 0; // Number of skiers on the bus + int idZ = 1; // Current bus stop ID + int skiing = 0; + while (1) { + // Sleep for a random time before arriving at the next stop + usleep(rand() % (TB + 1)); + + // Print bus arrival at the current stop + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: BUS: arrived to %d\n",*order, idZ); + *order += 1; + sem_post(sem_order); + + // Board skiers waiting at the current stop + sem_wait(sem_mutex); + int waiting_at_stop = 0; + for (int i = 0; i < L; i++) { + if ((bus_stop[i] == idZ) && waiting_at_stop < K) { + bus_stop[i] = 0; // Reset bus stop ID for skiers who boarded + waiting_at_stop++; + sem_post(sem_busstops[idZ - 1]); // Signal skiers at the current stop to board + sem_wait(sem_boarded); // Wait for skiers to board + } + } + + boarded += waiting_at_stop; // Increment the number of skiers on the bus + sem_post(sem_mutex); + + // Print bus leaving the current stop + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: BUS: leaving %d\n",*order, idZ); + *order += 1; + sem_post(sem_order); + + // If the bus has reached the final stop + if (idZ == Z) { + usleep(rand() % (TB + 1)); // Sleep for a random time before arriving at the final stop + + // Print bus arrival at the final stop + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: BUS: arrived to final\n", *order); + *order += 1; + sem_post(sem_order); + + // Unboard skiers at the final stop + for (int i = 0; i < boarded; i++) { + sem_post(sem_ubus); // Signal skiers to unboard + sem_wait(sem_unboard); // Wait for skiers to unboard + skiing++; + } + + // Print bus leaving the final stop + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: BUS: leaving final\n", *order); + *order += 1; + sem_post(sem_order); + + idZ = 1; // Reset bus stop ID to the first stop + boarded = 0; // Reset the number of skiers on the bus + + sem_wait(sem_mutex); + // Check if there are any remaining skiers at the bus stops + int remaining = 0; + for (int i = 0; i < L; i++) { + if (bus_stop[i] != 0) { + remaining++; + } + } + sem_post(sem_mutex); + + // If there are no remaining skiers, print finish and exit the loop + if (remaining == 0 && skiing == L) { + + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: BUS: finish\n", *order); + *order += 1; + sem_post(sem_order); + break; + } + } else { + idZ++; // Move to the next bus stop + } + } +} + +void skier_loop(int idL, int idZ, int TL) { + srand(time(0) * getpid()); + + // Print skier started + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: L %d: started\n",*order, idL); + *order += 1; + sem_post(sem_order); + + // Sleep for a random time before arriving at the bus stop + usleep(rand() % (TL + 1)); + + // Print skier arrival at the bus stop + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: L %d: arrived to %d\n",*order, idL, idZ); + *order += 1; + sem_post(sem_order); + + // Store the skier's bus stop ID and increment the waiting count + sem_wait(sem_mutex); + bus_stop[idL - 1] = idZ; + + sem_post(sem_mutex); + + // Wait for the bus to arrive at the skier's bus stop + sem_wait(sem_busstops[idZ - 1]); + + // Print skier boarding the bus + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: L %d: boarding\n",*order, idL); + *order += 1; + sem_post(sem_order); + sem_post(sem_boarded); // Signal that the skier has boarded + + // Wait for the bus to reach the final stop + sem_wait(sem_ubus); + + // Print skier going to ski + sem_wait(sem_order); + setbuf(output, NULL); + fprintf(output, "%d: L %d: going to ski\n",*order, idL); + *order += 1; + sem_post(sem_order); + sem_post(sem_unboard); // Signal that the skier has unboarded + +} diff --git a/1BIT/summer-semester/IOS-2/proj2.zip b/1BIT/summer-semester/IOS-2/proj2.zip new file mode 100644 index 0000000..7fdfcb4 Binary files /dev/null and b/1BIT/summer-semester/IOS-2/proj2.zip differ diff --git a/1BIT/summer-semester/IZLO-1/.idea/.gitignore b/1BIT/summer-semester/IZLO-1/.idea/.gitignore new file mode 100644 index 0000000..13566b8 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/.idea/.gitignore @@ -0,0 +1,8 @@ +# Default ignored files +/shelf/ +/workspace.xml +# Editor-based HTTP Client requests +/httpRequests/ +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml diff --git a/1BIT/summer-semester/IZLO-1/.idea/.name b/1BIT/summer-semester/IZLO-1/.idea/.name new file mode 100644 index 0000000..9cbecbb --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/.idea/.name @@ -0,0 +1 @@ +izlo_projekt1 \ No newline at end of file diff --git a/1BIT/summer-semester/IZLO-1/.idea/izlo-projekt1.iml b/1BIT/summer-semester/IZLO-1/.idea/izlo-projekt1.iml new file mode 100644 index 0000000..f08604b --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/.idea/izlo-projekt1.iml @@ -0,0 +1,2 @@ + + \ No newline at end of file diff --git a/1BIT/summer-semester/IZLO-1/.idea/misc.xml b/1BIT/summer-semester/IZLO-1/.idea/misc.xml new file mode 100644 index 0000000..79b3c94 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/.idea/misc.xml @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/1BIT/summer-semester/IZLO-1/.idea/modules.xml b/1BIT/summer-semester/IZLO-1/.idea/modules.xml new file mode 100644 index 0000000..01d4661 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git 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defined(_MSC_BUILD) +# define COMPILER_VERSION_TWEAK DEC(_MSC_BUILD) +# endif + +#elif defined(_ADI_COMPILER) +# define COMPILER_ID "ADSP" +#if defined(__VERSIONNUM__) + /* __VERSIONNUM__ = 0xVVRRPPTT */ +# define COMPILER_VERSION_MAJOR DEC(__VERSIONNUM__ >> 24 & 0xFF) +# define COMPILER_VERSION_MINOR DEC(__VERSIONNUM__ >> 16 & 0xFF) +# define COMPILER_VERSION_PATCH DEC(__VERSIONNUM__ >> 8 & 0xFF) +# define COMPILER_VERSION_TWEAK DEC(__VERSIONNUM__ & 0xFF) +#endif + +#elif defined(__IAR_SYSTEMS_ICC__) || defined(__IAR_SYSTEMS_ICC) +# define COMPILER_ID "IAR" +# if defined(__VER__) && defined(__ICCARM__) +# define COMPILER_VERSION_MAJOR DEC((__VER__) / 1000000) +# define COMPILER_VERSION_MINOR DEC(((__VER__) / 1000) % 1000) +# define COMPILER_VERSION_PATCH DEC((__VER__) % 1000) +# define COMPILER_VERSION_INTERNAL DEC(__IAR_SYSTEMS_ICC__) +# elif defined(__VER__) && (defined(__ICCAVR__) || defined(__ICCRX__) || defined(__ICCRH850__) || defined(__ICCRL78__) || defined(__ICC430__) || defined(__ICCRISCV__) || defined(__ICCV850__) || defined(__ICC8051__) || defined(__ICCSTM8__)) +# define COMPILER_VERSION_MAJOR DEC((__VER__) / 100) +# define COMPILER_VERSION_MINOR DEC((__VER__) - (((__VER__) / 100)*100)) +# define COMPILER_VERSION_PATCH DEC(__SUBVERSION__) +# define COMPILER_VERSION_INTERNAL DEC(__IAR_SYSTEMS_ICC__) +# endif + +#elif defined(__SDCC_VERSION_MAJOR) || defined(SDCC) +# define COMPILER_ID "SDCC" +# if defined(__SDCC_VERSION_MAJOR) +# define COMPILER_VERSION_MAJOR DEC(__SDCC_VERSION_MAJOR) +# define COMPILER_VERSION_MINOR DEC(__SDCC_VERSION_MINOR) +# define COMPILER_VERSION_PATCH DEC(__SDCC_VERSION_PATCH) +# else + /* SDCC = VRP */ +# define COMPILER_VERSION_MAJOR DEC(SDCC/100) +# define COMPILER_VERSION_MINOR DEC(SDCC/10 % 10) +# define COMPILER_VERSION_PATCH DEC(SDCC % 10) +# endif + + +/* These compilers are either not known or too old to define an + identification macro. Try to identify the platform and guess that + it is the native compiler. */ +#elif defined(__hpux) || defined(__hpua) +# define COMPILER_ID "HP" + +#else /* unknown compiler */ +# define COMPILER_ID "" +#endif + +/* Construct the string literal in pieces to prevent the source from + getting matched. Store it in a pointer rather than an array + because some compilers will just produce instructions to fill the + array rather than assigning a pointer to a static array. */ +char const* info_compiler = "INFO" ":" "compiler[" COMPILER_ID "]"; +#ifdef SIMULATE_ID +char const* info_simulate = "INFO" ":" "simulate[" SIMULATE_ID "]"; +#endif + +#ifdef __QNXNTO__ +char const* qnxnto = "INFO" ":" "qnxnto[]"; +#endif + +#if defined(__CRAYXT_COMPUTE_LINUX_TARGET) +char const *info_cray = "INFO" ":" "compiler_wrapper[CrayPrgEnv]"; +#endif + +#define STRINGIFY_HELPER(X) #X +#define STRINGIFY(X) STRINGIFY_HELPER(X) + +/* Identify known platforms by name. */ +#if defined(__linux) || defined(__linux__) || defined(linux) +# define PLATFORM_ID "Linux" + +#elif defined(__MSYS__) +# define PLATFORM_ID "MSYS" + +#elif defined(__CYGWIN__) +# define PLATFORM_ID "Cygwin" + +#elif defined(__MINGW32__) +# define PLATFORM_ID "MinGW" + +#elif defined(__APPLE__) +# define PLATFORM_ID "Darwin" + +#elif defined(_WIN32) || defined(__WIN32__) || defined(WIN32) +# define PLATFORM_ID "Windows" + +#elif defined(__FreeBSD__) || defined(__FreeBSD) +# define PLATFORM_ID "FreeBSD" + +#elif defined(__NetBSD__) || defined(__NetBSD) +# define PLATFORM_ID "NetBSD" + +#elif defined(__OpenBSD__) || defined(__OPENBSD) +# define PLATFORM_ID "OpenBSD" + +#elif defined(__sun) || defined(sun) +# define PLATFORM_ID "SunOS" + +#elif defined(_AIX) || defined(__AIX) || defined(__AIX__) || defined(__aix) || defined(__aix__) +# define PLATFORM_ID "AIX" + +#elif defined(__hpux) || defined(__hpux__) +# define PLATFORM_ID "HP-UX" + +#elif defined(__HAIKU__) +# define PLATFORM_ID "Haiku" + +#elif defined(__BeOS) || defined(__BEOS__) || defined(_BEOS) +# define PLATFORM_ID "BeOS" + +#elif defined(__QNX__) || defined(__QNXNTO__) +# define PLATFORM_ID "QNX" + +#elif defined(__tru64) || defined(_tru64) || defined(__TRU64__) +# define PLATFORM_ID "Tru64" + +#elif defined(__riscos) || defined(__riscos__) +# define PLATFORM_ID "RISCos" + +#elif defined(__sinix) || defined(__sinix__) || defined(__SINIX__) +# define PLATFORM_ID "SINIX" + +#elif defined(__UNIX_SV__) +# define PLATFORM_ID "UNIX_SV" + +#elif defined(__bsdos__) +# define PLATFORM_ID "BSDOS" + +#elif defined(_MPRAS) || defined(MPRAS) +# define PLATFORM_ID "MP-RAS" + +#elif defined(__osf) || defined(__osf__) +# define PLATFORM_ID "OSF1" + +#elif defined(_SCO_SV) || defined(SCO_SV) || defined(sco_sv) +# define PLATFORM_ID "SCO_SV" + +#elif defined(__ultrix) || defined(__ultrix__) || defined(_ULTRIX) +# define PLATFORM_ID "ULTRIX" + +#elif defined(__XENIX__) || defined(_XENIX) || defined(XENIX) +# define PLATFORM_ID "Xenix" + +#elif defined(__WATCOMC__) +# if defined(__LINUX__) +# define PLATFORM_ID "Linux" + +# elif defined(__DOS__) +# define PLATFORM_ID "DOS" + +# elif defined(__OS2__) +# define PLATFORM_ID "OS2" + +# elif defined(__WINDOWS__) +# define PLATFORM_ID "Windows3x" + +# elif defined(__VXWORKS__) +# define PLATFORM_ID "VxWorks" + +# else /* unknown platform */ +# define PLATFORM_ID +# endif + +#elif defined(__INTEGRITY) +# if defined(INT_178B) +# define PLATFORM_ID "Integrity178" + +# else /* regular Integrity */ +# define PLATFORM_ID "Integrity" +# endif + +# elif defined(_ADI_COMPILER) +# define PLATFORM_ID "ADSP" + +#else /* unknown platform */ +# define PLATFORM_ID + +#endif + +/* For windows compilers MSVC and Intel we can determine + the architecture of the compiler being used. This is because + the compilers do not have flags that can change the architecture, + but rather depend on which compiler is being used +*/ +#if defined(_WIN32) && defined(_MSC_VER) +# if defined(_M_IA64) +# define ARCHITECTURE_ID "IA64" + +# elif defined(_M_ARM64EC) +# define ARCHITECTURE_ID "ARM64EC" + +# elif defined(_M_X64) || defined(_M_AMD64) +# define ARCHITECTURE_ID "x64" + +# elif defined(_M_IX86) +# define ARCHITECTURE_ID "X86" + +# elif defined(_M_ARM64) +# define ARCHITECTURE_ID "ARM64" + +# elif defined(_M_ARM) +# if _M_ARM == 4 +# define ARCHITECTURE_ID "ARMV4I" +# elif _M_ARM == 5 +# define ARCHITECTURE_ID "ARMV5I" +# else +# define ARCHITECTURE_ID "ARMV" STRINGIFY(_M_ARM) +# endif + +# elif defined(_M_MIPS) +# define ARCHITECTURE_ID "MIPS" + +# elif defined(_M_SH) +# define ARCHITECTURE_ID "SHx" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +#elif defined(__WATCOMC__) +# if defined(_M_I86) +# define ARCHITECTURE_ID "I86" + +# elif defined(_M_IX86) +# define ARCHITECTURE_ID "X86" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +#elif defined(__IAR_SYSTEMS_ICC__) || defined(__IAR_SYSTEMS_ICC) +# if defined(__ICCARM__) +# define ARCHITECTURE_ID "ARM" + +# elif defined(__ICCRX__) +# define ARCHITECTURE_ID "RX" + +# elif defined(__ICCRH850__) +# define ARCHITECTURE_ID "RH850" + +# elif defined(__ICCRL78__) +# define ARCHITECTURE_ID "RL78" + +# elif defined(__ICCRISCV__) +# define ARCHITECTURE_ID "RISCV" + +# elif defined(__ICCAVR__) +# define ARCHITECTURE_ID "AVR" + +# elif defined(__ICC430__) +# define ARCHITECTURE_ID "MSP430" + +# elif defined(__ICCV850__) +# define ARCHITECTURE_ID "V850" + +# elif defined(__ICC8051__) +# define ARCHITECTURE_ID "8051" + +# elif defined(__ICCSTM8__) +# define ARCHITECTURE_ID "STM8" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +#elif defined(__ghs__) +# if defined(__PPC64__) +# define ARCHITECTURE_ID "PPC64" + +# elif defined(__ppc__) +# define ARCHITECTURE_ID "PPC" + +# elif defined(__ARM__) +# define ARCHITECTURE_ID "ARM" + +# elif defined(__x86_64__) +# define ARCHITECTURE_ID "x64" + +# elif defined(__i386__) +# define ARCHITECTURE_ID "X86" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +#elif defined(__TI_COMPILER_VERSION__) +# if defined(__TI_ARM__) +# define ARCHITECTURE_ID "ARM" + +# elif defined(__MSP430__) +# define ARCHITECTURE_ID "MSP430" + +# elif defined(__TMS320C28XX__) +# define ARCHITECTURE_ID "TMS320C28x" + +# elif defined(__TMS320C6X__) || defined(_TMS320C6X) +# define ARCHITECTURE_ID "TMS320C6x" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +# elif defined(__ADSPSHARC__) +# define ARCHITECTURE_ID "SHARC" + +# elif defined(__ADSPBLACKFIN__) +# define ARCHITECTURE_ID "Blackfin" + +#elif defined(__TASKING__) + +# if defined(__CTC__) || defined(__CPTC__) +# define ARCHITECTURE_ID "TriCore" + +# elif defined(__CMCS__) +# define ARCHITECTURE_ID "MCS" + +# elif defined(__CARM__) +# define ARCHITECTURE_ID "ARM" + +# elif defined(__CARC__) +# define ARCHITECTURE_ID "ARC" + +# elif defined(__C51__) +# define ARCHITECTURE_ID "8051" + +# elif defined(__CPCP__) +# define ARCHITECTURE_ID "PCP" + +# else +# define ARCHITECTURE_ID "" +# endif + +#else +# define ARCHITECTURE_ID +#endif + +/* Convert integer to decimal digit literals. */ +#define DEC(n) \ + ('0' + (((n) / 10000000)%10)), \ + ('0' + (((n) / 1000000)%10)), \ + ('0' + (((n) / 100000)%10)), \ + ('0' + (((n) / 10000)%10)), \ + ('0' + (((n) / 1000)%10)), \ + ('0' + (((n) / 100)%10)), \ + ('0' + (((n) / 10)%10)), \ + ('0' + ((n) % 10)) + +/* Convert integer to hex digit literals. */ +#define HEX(n) \ + ('0' + ((n)>>28 & 0xF)), \ + ('0' + ((n)>>24 & 0xF)), \ + ('0' + ((n)>>20 & 0xF)), \ + ('0' + ((n)>>16 & 0xF)), \ + ('0' + ((n)>>12 & 0xF)), \ + ('0' + ((n)>>8 & 0xF)), \ + ('0' + ((n)>>4 & 0xF)), \ + ('0' + ((n) & 0xF)) + +/* Construct a string literal encoding the version number. */ +#ifdef COMPILER_VERSION +char const* info_version = "INFO" ":" "compiler_version[" COMPILER_VERSION "]"; + +/* Construct a string literal encoding the version number components. */ +#elif defined(COMPILER_VERSION_MAJOR) +char const info_version[] = { + 'I', 'N', 'F', 'O', ':', + 'c','o','m','p','i','l','e','r','_','v','e','r','s','i','o','n','[', + COMPILER_VERSION_MAJOR, +# ifdef COMPILER_VERSION_MINOR + '.', COMPILER_VERSION_MINOR, +# ifdef COMPILER_VERSION_PATCH + '.', COMPILER_VERSION_PATCH, +# ifdef COMPILER_VERSION_TWEAK + '.', COMPILER_VERSION_TWEAK, +# endif +# endif +# endif + ']','\0'}; +#endif + +/* Construct a string literal encoding the internal version number. */ +#ifdef COMPILER_VERSION_INTERNAL +char const info_version_internal[] = { + 'I', 'N', 'F', 'O', ':', + 'c','o','m','p','i','l','e','r','_','v','e','r','s','i','o','n','_', + 'i','n','t','e','r','n','a','l','[', + COMPILER_VERSION_INTERNAL,']','\0'}; +#elif defined(COMPILER_VERSION_INTERNAL_STR) +char const* info_version_internal = "INFO" ":" "compiler_version_internal[" COMPILER_VERSION_INTERNAL_STR "]"; +#endif + +/* Construct a string literal encoding the version number components. */ +#ifdef SIMULATE_VERSION_MAJOR +char const info_simulate_version[] = { + 'I', 'N', 'F', 'O', ':', + 's','i','m','u','l','a','t','e','_','v','e','r','s','i','o','n','[', + SIMULATE_VERSION_MAJOR, +# ifdef SIMULATE_VERSION_MINOR + '.', SIMULATE_VERSION_MINOR, +# ifdef SIMULATE_VERSION_PATCH + '.', SIMULATE_VERSION_PATCH, +# ifdef SIMULATE_VERSION_TWEAK + '.', SIMULATE_VERSION_TWEAK, +# endif +# endif +# endif + ']','\0'}; +#endif + +/* Construct the string literal in pieces to prevent the source from + getting matched. Store it in a pointer rather than an array + because some compilers will just produce instructions to fill the + array rather than assigning a pointer to a static array. */ +char const* info_platform = "INFO" ":" "platform[" PLATFORM_ID "]"; +char const* info_arch = "INFO" ":" "arch[" ARCHITECTURE_ID "]"; + + + +#if !defined(__STDC__) && !defined(__clang__) +# if defined(_MSC_VER) || defined(__ibmxl__) || defined(__IBMC__) +# define C_VERSION "90" +# else +# define C_VERSION +# endif +#elif __STDC_VERSION__ > 201710L +# define C_VERSION "23" +#elif __STDC_VERSION__ >= 201710L +# define C_VERSION "17" +#elif __STDC_VERSION__ >= 201000L +# define C_VERSION "11" +#elif __STDC_VERSION__ >= 199901L +# define C_VERSION "99" +#else +# define C_VERSION "90" +#endif +const char* info_language_standard_default = + "INFO" ":" "standard_default[" C_VERSION "]"; + +const char* info_language_extensions_default = "INFO" ":" "extensions_default[" +#if (defined(__clang__) || defined(__GNUC__) || defined(__xlC__) || \ + defined(__TI_COMPILER_VERSION__)) && \ + !defined(__STRICT_ANSI__) + "ON" +#else + "OFF" +#endif +"]"; + +/*--------------------------------------------------------------------------*/ + +#ifdef ID_VOID_MAIN +void main() {} +#else +# if defined(__CLASSIC_C__) +int main(argc, argv) int argc; char *argv[]; +# else +int main(int argc, char* argv[]) +# endif +{ + int require = 0; + require += info_compiler[argc]; + require += info_platform[argc]; + require += info_arch[argc]; +#ifdef COMPILER_VERSION_MAJOR + require += info_version[argc]; +#endif +#ifdef COMPILER_VERSION_INTERNAL + require += info_version_internal[argc]; +#endif +#ifdef SIMULATE_ID + require += info_simulate[argc]; +#endif +#ifdef SIMULATE_VERSION_MAJOR + require += info_simulate_version[argc]; +#endif +#if defined(__CRAYXT_COMPUTE_LINUX_TARGET) + require += info_cray[argc]; +#endif + require += info_language_standard_default[argc]; + require += info_language_extensions_default[argc]; + (void)argv; 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CMakeFiles/3.26.4/CMakeSystem.cmake: phony + + +############################################# +# Clean all the built files. + +build clean: CLEAN + + +############################################# +# Print all primary targets available. + +build help: HELP + + +############################################# +# Make the all target the default. + +default all diff --git a/1BIT/summer-semester/IZLO-1/cmake-build-debug/cmake_install.cmake b/1BIT/summer-semester/IZLO-1/cmake-build-debug/cmake_install.cmake new file mode 100644 index 0000000..e3884c6 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/cmake-build-debug/cmake_install.cmake @@ -0,0 +1,49 @@ +# Install script for directory: C:/Users/roman/OneDrive/Počítač/izlo-projekt1 + +# Set the install prefix +if(NOT DEFINED CMAKE_INSTALL_PREFIX) + set(CMAKE_INSTALL_PREFIX "C:/Program Files (x86)/izlo_projekt1") +endif() +string(REGEX REPLACE "/$" "" CMAKE_INSTALL_PREFIX "${CMAKE_INSTALL_PREFIX}") + +# Set the install configuration name. +if(NOT DEFINED CMAKE_INSTALL_CONFIG_NAME) + if(BUILD_TYPE) + string(REGEX REPLACE "^[^A-Za-z0-9_]+" "" + CMAKE_INSTALL_CONFIG_NAME "${BUILD_TYPE}") + else() + set(CMAKE_INSTALL_CONFIG_NAME "Debug") + endif() + message(STATUS "Install configuration: \"${CMAKE_INSTALL_CONFIG_NAME}\"") +endif() + +# Set the component getting installed. +if(NOT CMAKE_INSTALL_COMPONENT) + if(COMPONENT) + message(STATUS "Install component: \"${COMPONENT}\"") + set(CMAKE_INSTALL_COMPONENT "${COMPONENT}") + else() + set(CMAKE_INSTALL_COMPONENT) + endif() +endif() + +# Is this installation the result of a crosscompile? +if(NOT DEFINED CMAKE_CROSSCOMPILING) + set(CMAKE_CROSSCOMPILING "FALSE") +endif() + +# Set default install directory permissions. +if(NOT DEFINED CMAKE_OBJDUMP) + set(CMAKE_OBJDUMP "C:/Program Files/JetBrains/CLion 2023.2.2/bin/mingw/bin/objdump.exe") +endif() + +if(CMAKE_INSTALL_COMPONENT) + set(CMAKE_INSTALL_MANIFEST "install_manifest_${CMAKE_INSTALL_COMPONENT}.txt") +else() + set(CMAKE_INSTALL_MANIFEST "install_manifest.txt") +endif() + +string(REPLACE ";" "\n" CMAKE_INSTALL_MANIFEST_CONTENT + "${CMAKE_INSTALL_MANIFEST_FILES}") +file(WRITE "C:/Users/roman/OneDrive/Počítač/izlo-projekt1/cmake-build-debug/${CMAKE_INSTALL_MANIFEST}" + "${CMAKE_INSTALL_MANIFEST_CONTENT}") diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/Makefile b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/Makefile new file mode 100644 index 0000000..ad26f26 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/Makefile @@ -0,0 +1,23 @@ +CC=gcc +CFLAGS=--std=c99 -Wall + +TARGET=main + +HEADERS := cnf.h +OBJECTS := main.o add_conditions.o + + +default: $(TARGET) + +%.o: %.c $(HEADERS) + $(CC) $(CFLAGS) -c $< -o $@ + +$(TARGET): $(OBJECTS) + $(CC) $(OBJECTS) -Wall -o $@ + +clean: + -rm -f $(OBJECTS) + -rm -f $(TARGET) + +test: default + @python3 ../tests/run_tests.py diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/add_conditions.c b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/add_conditions.c new file mode 100644 index 0000000..589af29 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/add_conditions.c @@ -0,0 +1,105 @@ +#include +#include "cnf.h" + +// +// LOGIN: +// + +// Tato funkce by mela do formule pridat klauzule predstavujici podminku 1) +// Křižovatky jsou reprezentovany cisly 0, 1, ..., num_of_crossroads-1 +// Cislo num_of_streets predstavuje pocet ulic a proto i pocet kroku cesty +// Pole streets ma velikost num_of_streets a obsahuje vsechny existujuci ulice +// - pro 0 <= i < num_of_streets predstavuje streets[i] jednu existujici +// ulici od krizovatky streets[i].crossroad_from ke krizovatce streets[i].crossroad_to +void at_least_one_valid_street_for_each_step(CNF* formula, unsigned num_of_crossroads, unsigned num_of_streets, const Street* streets) { + assert(formula != NULL); + assert(num_of_crossroads > 0); + assert(num_of_streets > 0); + assert(streets != NULL); + + for (unsigned i = 0; i < num_of_streets; ++i) { + Clause* cl = create_new_clause(formula); + for (unsigned j = 0; j < num_of_streets; ++j) { + add_literal_to_clause(cl, true, i, streets[j].crossroad_from, streets[j].crossroad_to); + } + } +} + +// Tato funkce by mela do formule pridat klauzule predstavujici podminku 2) +// Křižovatky jsou reprezentovany cisly 0, 1, ..., num_of_crossroads-1 +// Cislo num_of_streets predstavuje pocet ulic a proto i pocet kroku cesty +void at_most_one_street_for_each_step(CNF* formula, unsigned num_of_crossroads, unsigned num_of_streets) { + assert(formula != NULL); + assert(num_of_crossroads > 0); + assert(num_of_streets > 0); + + for (unsigned i = 0; i < num_of_streets; ++i) { + for (unsigned z = 0; z < num_of_crossroads; ++z) { + for (unsigned k = 0; k < num_of_crossroads; ++k) { + for (unsigned z2 = 0; z2 < num_of_crossroads; ++z2) { + for (unsigned k2 = 0; k2 < num_of_crossroads; ++k2) { + if ((z2 != z) || (k != k2)) { + Clause* cl = create_new_clause(formula); + add_literal_to_clause(cl, false, i, z, k); + add_literal_to_clause(cl, false, i, z2, k2); + } + } + } + + } + } + } +} +// Tato funkce by mela do formule pridat klauzule predstavujici podminku 3) +// Křižovatky jsou reprezentovany cisly 0, 1, ..., num_of_crossroads-1 +// Cislo num_of_streets predstavuje pocet ulic a proto i pocet kroku cesty + void streets_connected(CNF *formula, unsigned num_of_crossroads, unsigned num_of_streets) { + assert(formula != NULL); + assert(num_of_crossroads > 0); + assert(num_of_streets > 0); + + + for (unsigned i = 0; i < num_of_streets-1; ++i) { + for (unsigned z = 0; z < num_of_crossroads; ++z) { + for (unsigned k = 0; k < num_of_crossroads; ++k) { + for (unsigned z2 =0; z2 < num_of_crossroads; ++z2) { + for (unsigned k2 = 0; k2 < num_of_crossroads; ++k2) { + if (z2 != k) { + Clause* cl = create_new_clause(formula); + add_literal_to_clause(cl, false, i, z, k); + add_literal_to_clause(cl, false, i+1, z2, k2); + } + } + } + + } + } + } + + } + +// Tato funkce by mela do formule pridat klauzule predstavujici podminku 4) +// Křižovatky jsou reprezentovany cisly 0, 1, ..., num_of_crossroads-1 +// Cislo num_of_streets predstavuje pocet ulic a proto i pocet kroku cesty + void streets_do_not_repeat(CNF *formula, unsigned num_of_crossroads, unsigned num_of_streets) { + assert(formula != NULL); + assert(num_of_crossroads > 0); + assert(num_of_streets > 0); + + for (unsigned i = 0; i < num_of_streets; ++i) { + // pro kazdy krok i + for (unsigned j = 0; j < num_of_streets; ++j) { + if (i != j) { + // pro kazdy jiny krok j + for (unsigned z = 0; z < num_of_crossroads; ++z) { + for (unsigned k = 0; k < num_of_crossroads; ++k) { + // pro kazdu dvojici krizovatek (z, k) + Clause *cl = create_new_clause(formula); + add_literal_to_clause(cl, false, i, z, k); + add_literal_to_clause(cl, false, j, z, k); + } + } + } + } + } + } \ No newline at end of file diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/add_conditions.o b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/add_conditions.o new file mode 100644 index 0000000..3b07a86 Binary files /dev/null and b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/add_conditions.o differ diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/cnf.h b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/cnf.h new file mode 100644 index 0000000..81d1382 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/cnf.h @@ -0,0 +1,29 @@ +#ifndef __CNF_H +#define __CNF_H + +#include +#include + +typedef struct Literal Literal; + +typedef struct Clause Clause; + +typedef struct CNF CNF; + +// Struktura reprezentujici ulici z křižovatky crossroad_from do křižovatky crossroad_to +typedef struct { + unsigned crossroad_from; + unsigned crossroad_to; +} Street; + +// Vytvoreni nove klauzule v danej formuli +Clause* create_new_clause(CNF *formula); +// Prida (pripadne negovanou) promennou do klauzule reprezentujici, že v kroku step je zvolena ulice z křižovatky crossroad_from do křižovatky crossroad_to +void add_literal_to_clause(Clause *clause, bool is_positive, unsigned step, unsigned crossroad_from, unsigned crossroad_to); + +void at_least_one_valid_street_for_each_step(CNF* formula, unsigned num_of_crossroads, unsigned num_of_streets, const Street* streets); +void at_most_one_street_for_each_step(CNF* formula, unsigned num_of_crossroads, unsigned num_of_streets); +void streets_connected(CNF* formula, unsigned num_of_crossroads, unsigned num_of_streets); +void streets_do_not_repeat(CNF* formula, unsigned num_of_crossroads, unsigned num_of_streets); + +#endif \ No newline at end of file diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/main b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/main new file mode 100644 index 0000000..75085cc Binary files /dev/null and b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/main differ diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/main.c b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/main.c new file mode 100644 index 0000000..cc73af7 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/main.c @@ -0,0 +1,195 @@ +#include +#include + +#include "cnf.h" + +struct Literal { + int var; + struct Literal *next_literal; +}; + +struct Clause { + Literal* first_literal; + Literal* last_literal; + + struct Clause* next_clause; + + unsigned num_of_crossroads; +}; + +struct CNF { + Clause* first_clause; + Clause* last_clause; + + unsigned num_of_clauses; + unsigned num_of_crossroads; + unsigned num_of_streets; +}; + +void add_clause_to_formula(Clause *clause, CNF *formula) { + assert(clause != NULL); + assert(formula != NULL); + + if (formula->last_clause == NULL) { + assert(formula->first_clause == NULL); + formula->first_clause = clause; + } else { + formula->last_clause->next_clause = clause; + } + formula->last_clause = clause; + clause->num_of_crossroads = formula->num_of_crossroads; + + ++formula->num_of_clauses; +} + +Clause* create_new_clause(CNF* formula) { + Clause *new_clause = malloc(sizeof(Clause)); + new_clause->first_literal = NULL; + new_clause->last_literal = NULL; + new_clause->next_clause = NULL; + add_clause_to_formula(new_clause, formula); + return new_clause; +} + +void add_literal_to_clause(Clause *clause, bool is_positive, unsigned step, unsigned crossroad_from, unsigned crossroad_to) { + assert(clause != NULL); + + Literal *new_literal = malloc(sizeof(Literal)); + + unsigned num_of_crossroads = clause->num_of_crossroads; + int lit_num = step*num_of_crossroads*num_of_crossroads + crossroad_from*num_of_crossroads + crossroad_to + 1; + + if (!is_positive) { + lit_num = -lit_num; + } + new_literal->var = lit_num; + new_literal->next_literal = NULL; + + if (clause->last_literal == NULL) { + assert(clause->first_literal == NULL); + clause->first_literal = new_literal; + } else { + clause->last_literal->next_literal = new_literal; + } + clause->last_literal = new_literal; +} + + +unsigned get_num_of_variables(CNF* formula) { + assert(formula != NULL); + return formula->num_of_crossroads * formula->num_of_crossroads * formula->num_of_streets; +} + +unsigned get_num_of_clauses(CNF* formula) { + assert(formula != NULL); + return formula->num_of_clauses; +} + +void clear_clause(Clause* cl) { + assert(cl != NULL); + while(cl->first_literal != NULL) { + Literal *cur_lit = cl->first_literal; + cl->first_literal = cl->first_literal->next_literal; + free(cur_lit); + } + cl->last_literal = NULL; +} + +void clear_cnf(CNF* formula) { + assert(formula != NULL); + while(formula->first_clause != NULL) { + Clause *this_cl = formula->first_clause; + formula->first_clause = formula->first_clause->next_clause; + clear_clause(this_cl); + free(this_cl); + } + formula->last_clause = NULL; + formula->num_of_clauses = 0; +} + +void error(char* error_msg) { + fprintf(stderr, "%s\n", error_msg); + exit(-1); +} + +void print_formula(CNF* formula) { + assert(formula != NULL); + + printf("p cnf %u %u\n", get_num_of_variables(formula), get_num_of_clauses(formula)); + Clause *next_cl = formula->first_clause; + while (next_cl != 0) { + Literal *next_lit = next_cl->first_literal; + while (next_lit != 0) { + printf("%d ", next_lit->var); + next_lit = next_lit->next_literal; + } + next_cl = next_cl->next_clause; + printf("0\n"); + } +} + +int main (int argc, char** argv) { + if (argc != 2) { + error("Program ocekava presne jeden argument: soubor obsahujici seznam ulic"); + } + + FILE *input_file = fopen(argv[1], "r"); + if (input_file == NULL) { + error("Vstupni soubor nelze otevrit"); + } + + printf("c Vstupni soubor:\n"); + + unsigned num_of_crossroads, num_of_streets; + if (fscanf(input_file, "%u %u", &num_of_crossroads, &num_of_streets) != 2) { + fclose(input_file); + error("Hlavicka souboru by mela obsahovat dve cisla: pocet krizovatek a pocet ulic v souboru"); + } + printf("c %u %u\n", num_of_crossroads, num_of_streets); + if (num_of_crossroads == 0 || num_of_streets == 0) { + fclose(input_file); + error("Je treba stanovit kladny pocet krizovatek a pocet ulic"); + } + + Street* streets = malloc(num_of_streets * sizeof(Street)); + + for (unsigned i = 0; i < num_of_streets; ++i) { + Street e; + if (fscanf(input_file, "%u %u", &e.crossroad_from, &e.crossroad_to) != 2) { + free(streets); + fclose(input_file); + error("Ulice je dana dvema cisly - krizovatkou, ze ktere vychazi a do ktere vede"); + } + printf("c %u %u\n", e.crossroad_from, e.crossroad_to); + if (e.crossroad_from >= num_of_crossroads || e.crossroad_to >= num_of_crossroads) { + free(streets); + fclose(input_file); + error("Krizovatka pro nejakou ulici ma vyssi hodnotu nez maximalni povolena hodnota"); + } + streets[i] = e; + } + fclose(input_file); + + printf("c\nc Mapovani promennych na krok a ulici:\n"); + for (unsigned var = 1; var <= num_of_crossroads * num_of_crossroads * num_of_streets; ++var) { + unsigned step = (var-1) / (num_of_crossroads * num_of_crossroads); + unsigned rest = (var-1) % (num_of_crossroads * num_of_crossroads); + printf("c %u - v kroku %u se pouzije ulice od krizovatky %u ke krizovatce %u\n", var, step, rest / num_of_crossroads, rest % num_of_crossroads); + } + + printf("c\nc\n"); + + CNF f = { .first_clause = NULL, .last_clause = NULL, .num_of_clauses = 0, .num_of_crossroads = num_of_crossroads, .num_of_streets = num_of_streets }; + at_least_one_valid_street_for_each_step(&f, num_of_crossroads, num_of_streets, streets); + free(streets); + at_most_one_street_for_each_step(&f, num_of_crossroads, num_of_streets); + streets_connected(&f, num_of_crossroads, num_of_streets); + streets_do_not_repeat(&f, num_of_crossroads, num_of_streets); + + printf("c Formula:\n"); + print_formula(&f); + + clear_cnf(&f); + + return 0; +} diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/main.o b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/main.o new file mode 100644 index 0000000..3536dd3 Binary files /dev/null and b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/main.o differ diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/run.sh b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/run.sh new file mode 100644 index 0000000..2c1c139 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/code/run.sh @@ -0,0 +1,3 @@ +#!/bin/sh + +python3 ../tests/run.py $1 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/__pycache__/model.cpython-310.pyc b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/__pycache__/model.cpython-310.pyc new file mode 100644 index 0000000..70f43c3 Binary files /dev/null and b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/__pycache__/model.cpython-310.pyc differ diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/model.py b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/model.py new file mode 100644 index 0000000..47ebe80 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/model.py @@ -0,0 +1,160 @@ +from collections import Counter + +STATUS_SAT = "SAT" +STATUS_UNSAT = "UNSAT" + + +class ModelError(Exception): + pass + +class Edge: + def __init__(self, src, dst): + self.src = src + self.dst = dst + + def __eq__(self, other): + return self.src == other.src and self.dst == other.dst + + def __hash__(self): + return hash((self.src, self.dst)) + + def __repr__(self): + return f"{self.src} -> {self.dst}" + +class Input: + def __init__(self, num_of_nodes, edges): + self.num_of_nodes = num_of_nodes + self.edges = edges + + @staticmethod + def load(path): + with open(path) as f: + lines = f.read().split("\n") + header = lines[0].split(" ") + num_of_nodes = int(header[0]) + + edges = [] + for line in lines[1:]: + if line not in ["", "\n"]: + edge = line.split(" ") + src = int(edge[0]) + dst = int(edge[1]) + edges.append(Edge(src, dst)) + + return Input(num_of_nodes, edges) + + @property + def num_of_edges(self): + return len(self.edges) + + def compute_var_index(self, step, src, dst): + return step * (self.num_of_nodes ** 2) + src * self.num_of_nodes + dst + 1 + + +class Model: + def __init__(self, status, literals, input): + self.status = status + self.literals = literals + self.input = input + + def is_sat(self): + return self.status == STATUS_SAT + + @staticmethod + def load(path, input): + """ + The output of the minisat always has the form: + STATUS + [MODEL 0] + """ + with open(path, "r") as f: + lines = f.read().split("\n") + status = lines[0] + + if status == STATUS_UNSAT: + return Model(status, None, input) + else: + model = lines[1].split(" ")[0:-1] # Discard '0' + + if model == [""]: + return Model(status, [], input) + + model = list(map(lambda x: int(x), model)) + return Model(status, model, input) + + def __getitem__(self, key): + var = self.input.compute_var_index(*key) + + if var in self.literals: + return True + elif -var in self.literals: + return False + else: + return True # variable is undefined + + def edges_in_step(self, step): + # Return all edges taken in the given step + acc = [] + for src in range(self.input.num_of_nodes): + for dst in range(self.input.num_of_nodes): + if self[step, src, dst]: + acc.append(Edge(src, dst)) + return acc + + def all_edges(self): + # Return all edges taken + acc = [] + for step in range(self.input.num_of_edges): + acc += self.edges_in_step(step) + return acc + + def print(self): + print("Status:", self.status) + + if self.status == STATUS_UNSAT: + return + + print("Model:") + for step in range(self.input.num_of_edges): + edges = ", ".join([str(e) for e in self.edges_in_step(step)]) + print(f" krok {step}: {edges}") + + def check_one_valid_edge_in_step(self): + for step in range(self.input.num_of_edges): + edges = self.edges_in_step(step) + if len(edges) == 0: + raise ModelError(f"Nesprávný model: žádná ulice v kroku {step}") + if len(edges) > 1: + raise ModelError(f"Nesprávný model: více ulic v kroku {step}") + for edge in edges: + if edge not in self.input.edges: + raise ModelError(f"Nesprávný model: neexistující ulice {edge} v kroku {step}") + + def check_path(self): + edges = self.all_edges() + duplicates = [str(edge) for (edge, count) in Counter(edges).items() if count > 1] + if len(duplicates) > 0: + duplicates = ", ".join(duplicates) + raise ModelError(f"Nesprávný model: některé ulice byly navštíveny vícekrát: {duplicates}.") + + # This should not happen + if len(edges) != len(self.input.edges): + raise ModelError(f"Nesprávný model: některá z ulic nebyla navštívena.") + + def check_connectivity(self): + for step in range(self.input.num_of_edges - 1): + edges = self.edges_in_step(step) + edges_next = self.edges_in_step(step+1) + + assert(len(edges) == 1) + assert(len(edges_next) == 1) + current_e = edges[0] + next_e = edges_next[0] + + if current_e.dst != next_e.src: + raise ModelError(f"Nesprávný model: ulice {next_e} v kroku {step+1} nenavazuje na ulici {current_e} z kroku {step}.") + + def check(self): + self.check_one_valid_edge_in_step() + self.check_path() + self.check_connectivity() diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/run.py b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/run.py new file mode 100644 index 0000000..63e5167 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/run.py @@ -0,0 +1,33 @@ +import sys + +from model import ModelError +from run_tests import execute, smoke_test, print_ok, print_err, SolverError, GeneratorError + + +if __name__ == "__main__": + if len(sys.argv) != 2: + print("Usage: ./run.sh input") + exit(1) + + smoke_test() + + try: + result = execute(sys.argv[1]) + except GeneratorError as e: + print_err("Chyba generátoru:") + print(e) + exit(1) + except SolverError as e: + print_err("Chyba SAT solveru:") + print(e) + exit(1) + + result.print() + + if result.is_sat(): + try: + result.check() + print_ok("Nalezený model je korektní") + except ModelError as e: + print_err(f"\n{e}") + exit(1) diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/run_tests.py b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/run_tests.py new file mode 100644 index 0000000..95ee58b --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/run_tests.py @@ -0,0 +1,103 @@ +import os + +from tempfile import NamedTemporaryFile as TmpFile +from subprocess import run, PIPE, TimeoutExpired + +from model import Model, Input, STATUS_SAT, STATUS_UNSAT, ModelError + +TRANSLATOR = "../code/main" +SOLVER = "minisat" + +RC_SAT = 10 +RC_UNSAT = 20 + + +class colors: + red = "\033[91m" + green = "\033[92m" + white = "\033[m" + + +def print_ok(text): + print(f"{colors.green}{text}{colors.white}") + + +def print_err(text): + print(f"{colors.red}{text}{colors.white}") + + +class GeneratorError(Exception): + pass + + +class SolverError(Exception): + pass + + +def smoke_test(): + # Verify that MiniSat solver is available + try: + run([SOLVER, "--help"], stdout=PIPE, stderr=PIPE) + except Exception: + print("Minisat není nainstalovaný nebo není k dispozici v cestě") + exit(1) + + +def execute(path): + with TmpFile(mode="w+") as dimacs_out, TmpFile(mode="w+") as model_out: + try: + translator = run([TRANSLATOR, path], stdout=dimacs_out, stderr=PIPE) + except Exception: + raise GeneratorError("Chyba při spuštění generátoru formule") + + if translator.returncode != 0: + raise GeneratorError(translator.stderr.decode().strip()) + + try: + solver = run( + [SOLVER, dimacs_out.name, model_out.name], stdout=PIPE, stderr=PIPE + ) + except Exception: + raise SolverError("Chyba při spuštění SAT solveru") + + if not solver.returncode in [RC_SAT, RC_UNSAT]: + raise SolverError(solver.stderr.decode().strip()) + + input = Input.load(path) + model = Model.load(model_out.name, input) + return model + + +def run_test_case(path, expected_status): + try: + result = execute(path) + except GeneratorError: + print_err(f"{path}: Chyba generátoru") + return + except SolverError: + print_err(f"{path}: Chyba SAT solveru") + return + + if expected_status != result.status: + print_err( + f"{path}: Chybný výsledek ({result.status}, očekávaný {expected_status})" + ) + else: + try: + if result.is_sat(): + result.check() + print_ok(f"{path}: OK") + except ModelError as e: + print_err(f"{path}: {e}") + + +def run_test_suite(path, expected_status): + for test_case in sorted(os.listdir(path)): + if test_case.endswith(".in"): + run_test_case(os.path.join(path, test_case), expected_status) + + +if __name__ == "__main__": + smoke_test() + run_test_suite("../tests/sat", STATUS_SAT) + run_test_suite("../tests/unsat", STATUS_UNSAT) diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/complex.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/complex.in new file mode 100644 index 0000000..d3cb16a --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/complex.in @@ -0,0 +1,11 @@ +6 9 + +0 1 +0 3 +1 2 +1 4 +1 5 +2 0 +3 1 +4 4 +4 1 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/loop.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/loop.in new file mode 100644 index 0000000..3c7fb7f --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/loop.in @@ -0,0 +1,10 @@ +5 8 + +0 1 +1 2 +2 3 +3 4 +4 3 +3 2 +2 1 +1 0 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/multiple_paths.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/multiple_paths.in new file mode 100644 index 0000000..098327e --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/multiple_paths.in @@ -0,0 +1,12 @@ +5 10 + +0 1 +1 2 +2 1 +3 4 +4 3 +1 0 +3 1 +1 3 +0 2 +2 0 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/one_edge.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/one_edge.in new file mode 100644 index 0000000..082f77a --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/one_edge.in @@ -0,0 +1,3 @@ +2 1 + +0 1 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/path_with_self_loops.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/path_with_self_loops.in new file mode 100644 index 0000000..053b815 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/path_with_self_loops.in @@ -0,0 +1,11 @@ +5 9 + +0 1 +1 2 +2 3 +3 4 +0 0 +1 1 +2 2 +3 3 +4 4 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/self_loop.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/self_loop.in new file mode 100644 index 0000000..d7b5304 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/self_loop.in @@ -0,0 +1,3 @@ +1 1 + +0 0 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/simple_path.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/simple_path.in new file mode 100644 index 0000000..fa5acab --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/sat/simple_path.in @@ -0,0 +1,6 @@ +5 4 + +0 1 +1 2 +2 3 +3 4 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/diamond.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/diamond.in new file mode 100644 index 0000000..60268c6 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/diamond.in @@ -0,0 +1,6 @@ +4 4 + +0 1 +0 2 +1 3 +2 3 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/loop_in_middle.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/loop_in_middle.in new file mode 100644 index 0000000..517efc5 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/loop_in_middle.in @@ -0,0 +1,6 @@ +4 4 + +0 1 +1 2 +2 1 +2 3 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/many_random.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/many_random.in new file mode 100644 index 0000000..9891927 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/many_random.in @@ -0,0 +1,10 @@ +5 8 + +0 1 +1 4 +3 4 +2 3 +1 2 +3 1 +0 4 +3 2 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/same_dir.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/same_dir.in new file mode 100644 index 0000000..74b2ed1 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/same_dir.in @@ -0,0 +1,4 @@ +3 2 + +0 1 +2 1 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/simple_path_disconnected.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/simple_path_disconnected.in new file mode 100644 index 0000000..fa85f8e --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/simple_path_disconnected.in @@ -0,0 +1,5 @@ +5 3 + +0 1 +1 2 +3 4 diff --git a/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/two_disconnected.in b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/two_disconnected.in new file mode 100644 index 0000000..3182e76 --- /dev/null +++ b/1BIT/summer-semester/IZLO-1/izlo-projekt1/tests/unsat/two_disconnected.in @@ -0,0 +1,13 @@ +9 11 + +0 1 +1 2 +2 3 +3 4 +4 3 +3 2 +5 6 +6 7 +7 8 +8 7 +7 6 diff --git a/1BIT/summer-semester/IZLO-2/projekt2.smt2 b/1BIT/summer-semester/IZLO-2/projekt2.smt2 new file mode 100644 index 0000000..ff4f41a --- /dev/null +++ b/1BIT/summer-semester/IZLO-2/projekt2.smt2 @@ -0,0 +1,109 @@ +(set-logic NIA) + +(set-option :produce-models true) +(set-option :incremental true) + +; Deklarace promennych pro vstupy +; =============================== + +; Parametry +(declare-fun A () Int) +(declare-fun B () Int) +(declare-fun C () Int) +(declare-fun D () Int) +(declare-fun E () Int) + +;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; +;;;;;;;; START OF SOLUTION ;;;;;;;;;; +;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; + +; Declare the variables +(declare-fun x () Int) +(declare-fun y () Int) +(declare-fun z () Int) + + +; Constraints for D and E +(assert (and (> D 0) (> E 0))) + +; Compute the variables +(assert (= x (* A B 2))) +(assert (ite (< x E) (= y (+ x (* 5 B))) (= y (- x C)))) +(assert (ite (< (+ y 2) D) (= z (- (* x A) (* y B))) (= z (+ (* x B) (* y A))))) + +; Function f returns true +(assert (< z (+ E D))) + +; D + E is the smallest possible +(assert (forall ((d Int) (e Int) (X Int) (Y Int) (Z Int)) + (=> (and (> d 0) (> e 0) + (= X (* A B 2)) + (ite (< X e) (= Y (+ X (* 5 B))) (= Y (- X C))) + (ite (< (+ Y 2) d) (= Z (- (* X A) (* Y B))) (= Z (+ (* X B) (* Y A)))) + (< Z (+ e d))) + (<= (+ D E) (+ d e)) +))) + + +;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; +;;;;;;;;; END OF SOLUTION ;;;;;;;;;;; +;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; + +; Testovaci vstupy +; ================ + +(echo "Test 1 - vstup A=1, B=1, C=3") +(echo "a) Ocekavany vystup je sat a D+E se rovna 2") +(check-sat-assuming ( + (= A 1) (= B 1) (= C 3) +)) +(get-value (D E (+ D E))) +(echo "b) Neexistuje jine reseni nez 2, ocekavany vystup je unsat") +(check-sat-assuming ( + (= A 1) (= B 1) (= C 3) (distinct (+ D E) 2) +)) + + +(echo "Test 2 - vstup A=5, B=2, C=5") +(echo "a) Ocekavany vystup je sat a D+E se rovna 54") +(check-sat-assuming ( + (= A 5) (= B 2) (= C 5) +)) +(get-value (D E (+ D E))) +(echo "b) Neexistuje jine reseni nez 54, ocekavany vystup je unsat") +(check-sat-assuming ( + (= A 5) (= B 2) (= C 5) (distinct (+ D E) 54) +)) + +(echo "Test 3 - vstup A=100, B=15, C=1") +(echo "a) Ocekavany vystup je sat a D+E se rovna 253876") +(check-sat-assuming ( + (= A 100) (= B 15) (= C 1) +)) +(get-value (D E (+ D E))) +(echo "b) Neexistuje jine reseni nez 253876, ocekavany vystup je unsat") +(check-sat-assuming ( + (= A 100) (= B 15) (= C 1) (distinct (+ D E) 253876) +)) + +(echo "Test 4 - vstup A=5, B=5, C=3") +(echo "a) Ocekavany vystup je sat a D+E se rovna 51") +(check-sat-assuming ( + (= A 5) (= B 5) (= C 3) +)) +(get-value (D E (+ D E))) +(echo "b) Neexistuje jine reseni nez 51, ocekavany vystup je unsat") +(check-sat-assuming ( + (= A 5) (= B 5) (= C 3) (distinct (+ D E) 51) +)) + +(echo "Test 5 - vstup A=2, B=1, C=2") +(echo "a) Ocekavany vystup je sat a D+E se rovna 7") +(check-sat-assuming ( + (= A 2) (= B 1) (= C 2) +)) +(get-value (D E (+ D E))) +(echo "b) Neexistuje jine reseni nez 7, ocekavany vystup je unsat") +(check-sat-assuming ( + (= A 2) (= B 1) (= C 2) (distinct (+ D E) 7) +)) diff --git a/1BIT/winter-semester/1. Projekt Keyfilter/adresy.txt b/1BIT/winter-semester/1. Projekt Keyfilter/adresy.txt new file mode 100644 index 0000000..b6b1c14 --- /dev/null +++ b/1BIT/winter-semester/1. Projekt Keyfilter/adresy.txt @@ -0,0 +1,6 @@ +Brno +Bratislava +Praha +Bruntal +Brno hl. + diff --git a/1BIT/winter-semester/1. Projekt Keyfilter/keyfilter b/1BIT/winter-semester/1. Projekt Keyfilter/keyfilter new file mode 100644 index 0000000..c844bcc Binary files /dev/null and b/1BIT/winter-semester/1. Projekt Keyfilter/keyfilter differ diff --git a/1BIT/winter-semester/1. Projekt Keyfilter/keyfilter.c b/1BIT/winter-semester/1. Projekt Keyfilter/keyfilter.c new file mode 100644 index 0000000..061bc8a --- /dev/null +++ b/1BIT/winter-semester/1. Projekt Keyfilter/keyfilter.c @@ -0,0 +1,124 @@ +#include +#include +#include +#include +#include + +#define MAX_ADRESS_LENGTH 103 // 0->99 + \n + \0 + check for wrong input +#define ASCII_LENGTH 129 // 0->127 + \0 + +int findPrefix(char *prefix, char *found, char *enabled) //funkcia, ktora prudovo prejde po riadku zoznam miest a robi s nimi 3 + //hlavne operacie, zapisuje pocet zhod prefixu s adresou, zapisuje + //poslednu zhodnu adresu s prefixom do premennej found a zapisuje + //povolene klavesy +{ + + char adress [MAX_ADRESS_LENGTH]; + bool preocc = false; // prefix occurence, vyskyt prefixu v jednej adrese + int prenum = 0; //prefix number(pocet vsetkych zhod prefixu s adresami) + while(fgets(adress, sizeof(adress), stdin) != NULL) //cyklus, ktory prechadza riadok po riadku adresy, konci na konci suboru + { + if(strlen(adress) == MAX_ADRESS_LENGTH - 1) + { + fprintf(stderr, "Wrong input(too long adress)\n"); + exit(1); + } + + for(size_t i = 0; i < strlen(prefix); i++) + { + if(toupper(prefix[i]) == toupper(adress[i])) + preocc = true; // ak sa kazdy znak v prefixe zhoduje so znakmi adresy, do vyskytu prefixu dame hodnotu true + + else + { + preocc = false; //ak sa aspon jedno pismeno nezhoduje + break; + } + + } + if(preocc == true) // ak sa vsetky pismena v prefixe zhodovali + { + prenum++; + strcpy(found, adress); + int enable = toupper(adress[strlen(prefix)]); // do enable zapiseme poradie v ascii nasledujuceho znaku v adrese po + // zhodnom prefixe + enabled[enable] = 1; // do pola povolenych znakov zaznacime povoleny znak na pozicii enable + preocc = false; + } + else if(strlen(prefix) == 0) // specialny pripad, ak je program spusteny bez 2. argumentu(prazdny retazec) + { + int enable = toupper(adress[0]);// povolime vsetky zaciatocne pismena adries + enabled[enable] = 1; + prenum = 42; // nemozeme dat hodntou 1, pretoze najst zhodu nemozeme + // nemozeme dat ani 0, pretoze ak bol zadany spravny vstup,musime vypisat aspon jednu povolenu klavesu + } + + } + + return prenum; + +} +void printFound(char *found) +{ + printf ("FOUND: "); + for(size_t i = 0; i < strlen(found); i++) + { + printf ("%c", toupper(found[i])); + } +} +void printNotFound() +{ + printf ("NOT FOUND\n"); +} + +void printEnabled(char *enabled) +{ + printf("ENABLE: "); + for (int i = 0; i < ASCII_LENGTH - 1; i++) + { + if (enabled[i]) printf("%c", i); // prechadzame ascii tabulku a vypisujeme znaky, ktore sme si do nej zaznacili ako povolene + } + printf ("\n"); +} + +int main(int argc, char** argv){ + char prefix [MAX_ADRESS_LENGTH];//max prefix == max adress + + if (argc == 1) + { + strcpy(prefix, "\0"); //zaciatocny stav(prefix) berieme ako prazdny retazec + } + else if (argc == 2) + { + strcpy(prefix, argv[1]); + if(strlen(prefix) > MAX_ADRESS_LENGTH - 3) + { + fprintf(stderr, "Wrong argument\n"); + return 1; + } + } + else + { + fprintf(stderr,"Wrong argument\n"); + return 1; + } + + char found[MAX_ADRESS_LENGTH]; // najdene mesto + char enabled[ASCII_LENGTH] = {0}; // pole povolenych znakov, znaci, ci za znak z ascii tabulky nachadza v povolenych znakoch + int prenum = findPrefix(prefix, found, enabled); + + if(prenum == 1) + { + printFound(found); // ak je pocet zhodnych prefixov len jeden, vypiseme najdenu adresu + } + else if (prenum == 0) // ziadna zhoda + { + printNotFound(); + } + else + { + printEnabled(enabled); + } + + return 0; +} diff --git a/1BIT/winter-semester/1. Projekt Keyfilter/makefile b/1BIT/winter-semester/1. Projekt Keyfilter/makefile new file mode 100644 index 0000000..dc40758 --- /dev/null +++ b/1BIT/winter-semester/1. Projekt Keyfilter/makefile @@ -0,0 +1,4 @@ +CFLAGS=-std=c11 -Wall -Wextra -Werror + +keyfilter: keyfilter.c + gcc $(CFLAGS) keyfilter.c -o keyfilter diff --git a/1BIT/winter-semester/2. Projekt Maze/.idea/.gitignore b/1BIT/winter-semester/2. Projekt Maze/.idea/.gitignore new file mode 100644 index 0000000..13566b8 --- /dev/null +++ b/1BIT/winter-semester/2. Projekt Maze/.idea/.gitignore @@ -0,0 +1,8 @@ +# Default ignored files +/shelf/ +/workspace.xml +# Editor-based HTTP Client requests +/httpRequests/ +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml diff --git a/1BIT/winter-semester/2. Projekt Maze/.idea/2. Projekt Maze.iml b/1BIT/winter-semester/2. Projekt Maze/.idea/2. Projekt Maze.iml new file mode 100644 index 0000000..bc2cd87 --- /dev/null +++ b/1BIT/winter-semester/2. Projekt Maze/.idea/2. Projekt Maze.iml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/1BIT/winter-semester/2. Projekt Maze/.idea/modules.xml b/1BIT/winter-semester/2. Projekt Maze/.idea/modules.xml new file mode 100644 index 0000000..0962ea8 --- /dev/null +++ b/1BIT/winter-semester/2. Projekt Maze/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/1BIT/winter-semester/2. Projekt Maze/makefile b/1BIT/winter-semester/2. Projekt Maze/makefile new file mode 100644 index 0000000..8cb877e --- /dev/null +++ b/1BIT/winter-semester/2. Projekt Maze/makefile @@ -0,0 +1,4 @@ +CFLAGS=-std=c11 -Wall -Wextra -Werror + +maze: maze.c + gcc $(CFLAGS) maze.c -o maze diff --git a/1BIT/winter-semester/2. Projekt Maze/maze b/1BIT/winter-semester/2. Projekt Maze/maze new file mode 100644 index 0000000..3c7bca5 Binary files /dev/null and b/1BIT/winter-semester/2. Projekt Maze/maze differ diff --git a/1BIT/winter-semester/2. Projekt Maze/maze.c b/1BIT/winter-semester/2. Projekt Maze/maze.c new file mode 100644 index 0000000..126cae2 --- /dev/null +++ b/1BIT/winter-semester/2. Projekt Maze/maze.c @@ -0,0 +1,447 @@ +#include +#include +#include +#include + +typedef struct { + int rows; + int cols; + unsigned char *cells; +} Map; + +#define RIGHT_HAND 0 +#define LEFT_HAND 1 + +#define LEFT_BORDER 0 +#define RIGHT_BORDER 1 +#define TOP_BORDER 2 + +bool isborder(Map *map, int r, int c, int border); +int start_border(Map *map, int r, int c, int leftright); +Map* init_map(int rows, int cols); +void load_map(Map* map, const char* filename); +void free_map(Map* map); +bool validate_map(Map* map); +void find_path(Map* map, int r, int c, int leftright, int sborder); +int load_mapsize(int* mrow, int* mcol, const char* filename); + +bool isborder(Map *map, int r, int c, int border) // kontroluje, ci na konkretnej bunke sa nachadza konkretna stena +{ + unsigned char cell = map->cells[r * map->cols + c]; + return (cell & (1 << border)) != 0; // ak sa stena bunky zhoduje s typom kontrolovanej steny, vrati true, inak false +} + +int start_border(Map *map, int r, int c, int leftright) //zistenie zaciatocnej steny podla zadania + // a kontrola, ci zaciatocna bunka moze byt + // vstupna bunka bludiska +{ + if (leftright == RIGHT_HAND) + { + if (c == 0 && r % 2 == 0 && !isborder(map, r, c, LEFT_BORDER)) return RIGHT_BORDER; // r je v nasej matici o 1 mensie, teda parny, obdobne dalsi if + else if (c == 0 && r % 2 == 1 && !isborder(map, r, c, LEFT_BORDER)) return TOP_BORDER; + else if (c == map->cols - 1 && ((r+c)%2==0) && !isborder(map, r, c, RIGHT_BORDER)) return TOP_BORDER; + else if (c == map->cols - 1 && ((r+c)%2==1) && !isborder(map, r, c, RIGHT_BORDER)) return LEFT_BORDER; + else if (r == 0 && !isborder(map, r, c, TOP_BORDER)) return LEFT_BORDER; + else if (r == map->rows - 1 && !isborder(map, r, c, TOP_BORDER)) return RIGHT_BORDER; + else return -1; + } else if (leftright == LEFT_HAND) + { + if (c == 0 && r % 2 == 0 && !isborder(map, r, c, LEFT_BORDER) ) return TOP_BORDER; + else if (c == 0 && r % 2 == 1 && !isborder(map, r, c, LEFT_BORDER)) return RIGHT_BORDER; + else if (c == map->cols - 1 && ((r+c)%2==0) && !isborder(map, r, c, RIGHT_BORDER)) return LEFT_BORDER; + else if (c == map->cols - 1 && ((r+c)%2==1) && !isborder(map, r, c, RIGHT_BORDER)) return TOP_BORDER; + else if (r == 0 && !isborder(map, r, c, TOP_BORDER)) return RIGHT_BORDER; + else if (r == map->rows - 1 && !isborder(map, r, c, TOP_BORDER)) return LEFT_BORDER; + else return -1; + } + return -1; +} + +Map* init_map(int rows, int cols) { //inicializacia mapy + Map* map = malloc(sizeof(Map)); // alokujeme najprv miesto pre strukturu map + map->rows = rows; + map->cols = cols; + map->cells = malloc(rows * cols * sizeof(unsigned char)); // alokujeme miesto pre dany pocet buniek(rows * cols) + return map; +} + +void load_map(Map* map, const char* filename) { //nacitanie mapy zo suboru + FILE *file = fopen(filename, "r"); + if (file == NULL) { + fprintf(stderr,"File opening failed\n"); + return; + } + fscanf(file, "%d %d", &(map->rows), &(map->cols)); + for (int i = 0; i < map->rows; i++) { + for (int j = 0; j < map->cols; j++) { + fscanf(file, "%hhu", &(map->cells[i * map->cols + j])); + } + } + fclose(file); +} + +void free_map(Map* map) { //uvolnenie mapy + free(map->cells); + free(map); +} + +bool validate_map(Map* map) { //overenie spravnosti bludiska, kontrolujeme, ci je policko definovane validnym cislo(<=7) + for (int i = 0; i < map->rows; i++) { + for (int j = 0; j < map->cols; j++) { + unsigned char cell = map->cells[i * map->cols + j]; + if (cell > 7) { + return false; + } + if (i > 0 && ((cell & (1 << TOP_BORDER)) != (map->cells[(i-1) * map->cols + j] & (1 << TOP_BORDER))) && ((j + i) % 2 == 0)) { + return false; + } + if (j > 0 && ((cell & (1 << LEFT_BORDER)) != ((map->cells[i * map->cols + (j-1)] & (1 << RIGHT_BORDER))>>RIGHT_BORDER))) { // pravu stenu popisuje druhy najnizsi bit + //a teda ho musime posunut na najnizsi, aby + //sa mohol porovnat s lavou stenou, ktora je + //na najnizsom bite + return false; + } + } + } + return true; +} + +void find_path(Map* map, int r, int c, int leftright, int sborder) { //hladanie cesty bludiskom + int x = r, y = c; + int current_border = sborder;// aktualna stena + int next_border; // nasledujuca stena + + while ((x >= 0) && (x <= (map->rows - 1)) && (y >= 0) && (y <= map->cols - 1)) + { //kym nevyjdeme mimo bludiska + //v if vetvach hladame dalsiu stenu, na ktorej ma byt polozena ruka + printf("%d,%d\n", x + 1, y + 1); + if (leftright == RIGHT_HAND) { //podla pravidla pravej ruky + if (current_border == TOP_BORDER && ((x + y) % 2 == 1)) { + if (!isborder(map, x, y, TOP_BORDER)) { + next_border = LEFT_BORDER;x++; + } else if (!isborder(map, x, y, RIGHT_BORDER)) { + next_border = RIGHT_BORDER;y++; + } else { + next_border = TOP_BORDER;y--; + }} + else if (current_border == TOP_BORDER && ((x + y) % 2 == 0)) { + if (!isborder(map, x, y, TOP_BORDER)) { + next_border = RIGHT_BORDER;x--; + } else if (!isborder(map, x, y, LEFT_BORDER)) { + next_border = LEFT_BORDER;y--; + } else { + next_border = TOP_BORDER;y++; + } + } else if (current_border == RIGHT_BORDER && ((x + y) % 2 == 1)) { + if (!isborder(map, x, y, RIGHT_BORDER)) { + next_border = RIGHT_BORDER; y++; + } else if (!isborder(map, x, y, LEFT_BORDER)) { + next_border = TOP_BORDER;y--; + } else { + next_border = LEFT_BORDER;x++; + }} + else if (current_border == RIGHT_BORDER && ((x + y) % 2 == 0)) { + if (!isborder(map, x, y, RIGHT_BORDER)) { + next_border = TOP_BORDER;y++; + } else if (!isborder(map, x, y, TOP_BORDER)) { + next_border = RIGHT_BORDER;x--; + } else { + next_border = LEFT_BORDER;y--; + } + + } else if (current_border == LEFT_BORDER && ((x + y) % 2 == 1)) { + if (!isborder(map, x, y, LEFT_BORDER)) { + next_border = TOP_BORDER;y--; + } else if (!isborder(map, x, y, TOP_BORDER)) { + next_border = LEFT_BORDER;x++; + } else { + next_border = RIGHT_BORDER;y++; + } + } + else if (current_border == LEFT_BORDER && ((x + y) % 2 == 0)) { + if (!isborder(map, x, y, LEFT_BORDER)) { + next_border = LEFT_BORDER;y--; + } else if (!isborder(map, x, y, RIGHT_BORDER)) { + next_border = TOP_BORDER;y++; + } else { + next_border = RIGHT_BORDER;x--; + } + } + } + else if (leftright == LEFT_HAND) { //podla pravidla lavej ruky + if (current_border == TOP_BORDER && ((x + y) % 2 == 0)) { + if (!isborder(map, x, y, TOP_BORDER)) { + next_border = LEFT_BORDER;x--; + } else if (!isborder(map, x, y, RIGHT_BORDER)) { + next_border = RIGHT_BORDER;y++; + } else { + next_border = TOP_BORDER;y--; + }} + else if (current_border == TOP_BORDER && ((x + y) % 2 == 1)) { + if (!isborder(map, x, y, TOP_BORDER)) { + next_border = RIGHT_BORDER;x++; + } else if (!isborder(map, x, y, LEFT_BORDER)) { + next_border = LEFT_BORDER;y--; + } else { + next_border = TOP_BORDER;y++; + } + } else if (current_border == RIGHT_BORDER && ((x + y) % 2 == 0)) { + if (!isborder(map, x, y, RIGHT_BORDER)) { + next_border = RIGHT_BORDER; y++; + } else if (!isborder(map, x, y, LEFT_BORDER)) { + next_border = TOP_BORDER;y--; + } else { + next_border = LEFT_BORDER;x--; + }} + else if (current_border == RIGHT_BORDER && ((x + y) % 2 == 1)) { + if (!isborder(map, x, y, RIGHT_BORDER)) { + next_border = TOP_BORDER;y++; + } else if (!isborder(map, x, y, TOP_BORDER)) { + next_border = RIGHT_BORDER;x++; + } else { + next_border = LEFT_BORDER;y--; + } + + } else if (current_border == LEFT_BORDER && ((x + y) % 2 == 0)) { + if (!isborder(map, x, y, LEFT_BORDER)) { + next_border = TOP_BORDER;y--; + } else if (!isborder(map, x, y, TOP_BORDER)) { + next_border = LEFT_BORDER;x--; + } else { + next_border = RIGHT_BORDER;y++; + } + } + else if (current_border == LEFT_BORDER && ((x + y) % 2 == 1)) { + if (!isborder(map, x, y, LEFT_BORDER)) { + next_border = LEFT_BORDER;y--; + } else if (!isborder(map, x, y, RIGHT_BORDER)) { + next_border = TOP_BORDER;y++; + } else { + next_border = RIGHT_BORDER;x++; + } + } + + } + current_border = next_border; + + } +} +int load_mapsize(int* mrow, int* mcol, const char* filename) // nacita velkost mapy zo suboru +{ + FILE* file = fopen(filename, "r"); + if (file == NULL) + { + fprintf(stderr,"Failed to open file\n"); + return 1; + } + fscanf(file, "%d %d", mrow, mcol); + if(*mrow <= 0 || *mcol <= 0) //velkost mapy musi byt kladna, nulova je tiez chybna + { + return 2; + } + fclose(file); + return 0; +} + + +int main(int argc, char *argv[]) { + if (argc < 2) + { + fprintf(stderr,"Missing arguments\n"); + return 1; + } + + if (strcmp(argv[1], "--help") == 0) + { + printf(" Start program with these arguments:\n" + "\n" + "./maze --help\n" + "shows this guide\n" + "or\n" + "./maze --test soubor.txt\n" + "checks the validity of maze given in a file in second argument\n" + "nebo\n" + "./maze --rpath R C soubor.txt\n" + "finds path from input R-row,C-column in the maze to exit with right-hand rule,\n" + "nebo\n" + "./maze --lpath R C soubor.txt\n" + "finds path from input R-row,C-column in the maze to exit with left-hand rule,\n"); + } + else if (strcmp(argv[1], "--test") == 0) + { + if (argc < 3) + { + fprintf(stderr,"missing name of file\n"); + return 1; + } + // nacitanie velkosti mapy + int* mrows; + int* mcols; + mrows = malloc(sizeof(int)); + mcols = malloc(sizeof(int)); + + int err = load_mapsize(mrows,mcols, argv[2]); + if(err == 1) + { + free(mrows); + free(mcols); + return 1; + } + else if(err == 2) + { + printf("Invalid\n"); + free(mrows); + free(mcols); + return 0; + } + //koniec nacitania velkosti mapy + + Map* map = init_map(*mrows, *mcols); + free(mrows); + free(mcols); + load_map(map, argv[2]); + bool valid = validate_map(map); + if (valid) + { + printf("Valid\n"); + } + else + { + printf("Invalid\n"); + } + free_map(map); + + } + else if (strcmp(argv[1], "--rpath") == 0) + { + if (argc < 4) { + fprintf(stderr,"Missing arguments\n"); + return 1; + } + int r = atoi(argv[2]); + int c = atoi(argv[3]); + + //nacitannie velkosti mapy + int* mrows; + int* mcols; + mrows = malloc(sizeof(int)); + mcols = malloc(sizeof(int)); + + int err = load_mapsize(mrows,mcols, argv[4]); + if(err == 1) + { + free(mrows); + free(mcols); + return 1; + } + else if(err == 2) + { + printf("Invalid\n"); + free(mrows); + free(mcols); + return 0; + } + //koniec nacitania veloksti mapy + + Map* map = init_map(*mrows, *mcols); + free(mrows); + free(mcols); + + load_map(map, argv[4]); + if (r < 1 || r > map->rows || c < 1 || c > map->cols) + { + fprintf(stderr,"Wrong input coordinates\n"); + free_map(map); + return 1; + } + + bool valid = validate_map(map); + if (!valid) + { + printf("Invalid\n"); + free_map(map); + return 1; + } + int sborder = start_border(map, r-1, c-1, RIGHT_HAND); + if (sborder == -1) + { + fprintf(stderr, "Invalid start border\n"); + free_map(map); + return 1; + } + else + { + find_path(map, r - 1, c - 1, RIGHT_HAND, sborder); + } + + free_map(map); + + } + else if (strcmp(argv[1], "--lpath") == 0) + { + + if (argc < 4) + { + fprintf(stderr,"Missing arguments\n"); + return 1; + } + int r =atoi(argv[2]); + int c =atoi(argv[3]); + + //nacitanie velksoti mapy + int* mrows; + int* mcols; + mrows = malloc(sizeof(int)); + mcols = malloc(sizeof(int)); + + int err = load_mapsize(mrows,mcols, argv[4]); + if(err == 1) + { + free(mrows); + free(mcols); + return 1; + } + else if(err == 2) + { + printf("Invalid\n"); + free(mrows); + free(mcols); + return 0; + } + //koniec nacitania velkosti mapy + + Map* map = init_map(*mrows, *mcols); + free(mrows); + free(mcols); + + load_map(map, argv[4]); + if (r < 1 || r > map->rows || c < 1 || c > map->cols) + { + fprintf(stderr,"Wrong input coordinates\n"); + free_map(map); + return 1; + } + + bool valid = validate_map(map); + if (!valid) + { + printf("Invalid\n"); + free_map(map); + return 1; + } + + int sborder = start_border(map, r-1, c-1, LEFT_HAND); + if (sborder == -1) + { + fprintf(stderr, "Invalid start border\n"); + free_map(map); + return 1; + } + else + { + find_path(map, r - 1, c - 1, LEFT_HAND, sborder); + } + free_map(map); + } + return 0; +} diff --git a/1BIT/winter-semester/2. Projekt Maze/soubor.txt b/1BIT/winter-semester/2. Projekt Maze/soubor.txt new file mode 100644 index 0000000..8da2e54 --- /dev/null +++ b/1BIT/winter-semester/2. Projekt Maze/soubor.txt @@ -0,0 +1,7 @@ +6 7 +1 4 4 2 5 0 6 +1 4 4 0 4 0 2 +1 0 4 0 4 6 1 +1 2 7 1 0 4 2 +3 1 4 2 3 1 2 +4 2 5 0 4 2 5 \ No newline at end of file diff --git a/1BIT/winter-semester/Projekt IEL/Zdrojove kody/falstad1(1).txt b/1BIT/winter-semester/Projekt IEL/Zdrojove kody/falstad1(1).txt new file mode 100644 index 0000000..24d5402 --- /dev/null +++ b/1BIT/winter-semester/Projekt IEL/Zdrojove kody/falstad1(1).txt @@ -0,0 +1,17 @@ +$ 1 0.000005 10.20027730826997 50 5 43 5e-11 +v 144 336 144 160 0 0 40 100 0 0 0.5 +v 144 400 144 336 0 0 40 80 0 0 0.5 +w 144 160 208 160 0 +r 208 160 336 160 0 450 +w 208 160 208 224 0 +r 208 224 336 224 0 810 +r 336 160 336 224 0 190 +r 336 224 448 224 0 220 +w 336 160 448 160 0 +r 448 160 448 224 0 220 +w 448 160 496 160 0 +r 496 160 496 224 0 720 +w 448 224 496 224 0 +w 448 224 448 384 0 +r 448 384 320 384 0 180 +r 320 384 144 400 0 260 diff --git a/1BIT/winter-semester/Projekt IEL/Zdrojove kody/ielsolver.m b/1BIT/winter-semester/Projekt IEL/Zdrojove kody/ielsolver.m new file mode 100644 index 0000000..adbc49c --- /dev/null +++ b/1BIT/winter-semester/Projekt IEL/Zdrojove kody/ielsolver.m @@ -0,0 +1,448 @@ +z1 = "C"; +z2 = "H"; +z3 = "H"; +z4 = "C"; + + + +% ZADANIE 1 +fprintf("priklad 1 [%s]\n",z1); + + +if strcmp(z1, 'A') + U1 = 80; + U2 = 120; + R1 = 350; + R2 = 650; + R3 = 410; + R4 = 130; + R5 = 360; + R6 = 750; + R7 = 310; + R8 = 190; +elseif strcmp(z1, 'B') + U1 = 95; + U2 = 115; + R1 = 650; + R2 = 730; + R3 = 340; + R4 = 330; + R5 = 410; + R6 = 830; + R7 = 340; + R8 = 220; +elseif strcmp(z1, 'C') + U1 = 100; + U2 = 80; + R1 = 450; + R2 = 810; + R3 = 190; + R4 = 220; + R5 = 220; + R6 = 720; + R7 = 260; + R8 = 180; +elseif strcmp(z1, 'D') + U1 = 105; + U2 = 85; + R1 = 420; + R2 = 980; + R3 = 330; + R4 = 280; + R5 = 310; + R6 = 710; + R7 = 240; + R8 = 200; +elseif strcmp(z1, 'E') + U1 = 115; + U2 = 55; + R1 = 485; + R2 = 660; + R3 = 100; + R4 = 340; + R5 = 575; + R6 = 815; + R7 = 255; + R8 = 225; +elseif strcmp(z1, 'F') + U1 = 125; + U2 = 65; + R1 = 510; + R2 = 500; + R3 = 550; + R4 = 250; + R5 = 300; + R6 = 800; + R7 = 330; + R8 = 250; +elseif strcmp(z1, 'G') + U1 = 130; + U2 = 60; + R1 = 380; + R2 = 420; + R3 = 330; + R4 = 440; + R5 = 450; + R6 = 650; + R7 = 410; + R8 = 275; +elseif strcmp(z1, 'H') + U1 = 135; + U2 = 80; + R1 = 680; + R2 = 600; + R3 = 260; + R4 = 310; + R5 = 575; + R6 = 870; + R7 = 355; + R8 = 265; +else + error('Invalid variation specified.'); +end + +R78 = R7 + R8; +R56 = (R5*R6)/(R5+R6); +fprintf('R56 = %.8f, R78 = %.8f\n\n', R56, R78); + +RA = (R1*R2)/(R1+R2+R3); +RB = (R1*R3)/(R1+R2+R3); +RC = (R2*R3)/(R1+R2+R3); +fprintf('RA = %.8f, RC = %.8f\n\n', RA, RC); +RB56 = RB + R56; +RC4 = RC + R4; +fprintf('RB56 = %.8f\n', RB56); +fprintf('RC4 = %.8f\n', RC4); + + +RBC456 = (RB56*RC4)/(RB56+RC4); +fprintf('RCB56C4 = %.8f\n', RBC456); + +R = RA + RBC456 + R78; +fprintf('R = %.8f\n',R); + +I = (U1+U2)/R; +fprintf('I = %.8f\n',I); + +URA = I * RA; +URBC456 = I * RBC456; +fprintf('URBC... = %.8f\n', URBC456); +IRB56 = URBC456/RB56; +fprintf('IRB56 = %.8f\n', IRB56); + +IRC4 = URBC456/RC4; +fprintf('IRC4 = %.8f\n', IRC4); +URC = IRC4 * RC; +fprintf('URA = %.8f\n', URA); + +UR2 = URA + URC; + +IR2 = UR2/R2; + +fprintf('UR2 = %.8fV, IR2 = %.8fA\n\n', UR2, IR2); + + + +% ZADANIE 2 +fprintf("priklad 2 [%s]\n",z2); + +if strcmp(z2, 'A') + U = 50; + R1 = 100; + R2 = 525; + R3 = 620; + R4 = 210; + R5 = 530; + R6 = 50; +elseif strcmp(z2, 'B') + U = 100; + R1 = 50; + R2 = 310; + R3 = 610; + R4 = 220; + R5 = 570; + R6 = 100; +elseif strcmp(z2, 'C') + U = 200; + R1 = 70; + R2 = 220; + R3 = 630; + R4 = 240; + R5 = 450; + R6 = 200; +elseif strcmp(z2, 'D') + U = 150; + R1 = 200; + R2 = 200; + R3 = 660; + R4 = 200; + R5 = 550; + R6 = 150; +elseif strcmp(z2, 'E') + U = 250; + R1 = 150; + R2 = 335; + R3 = 625; + R4 = 245; + R5 = 600; + R6 = 300; +elseif strcmp(z2, 'F') + U = 130; + R1 = 180; + R2 = 350; + R3 = 600; + R4 = 195; + R5 = 650; + R6 = 80; +elseif strcmp(z2, 'G') + U = 180; + R1 = 250; + R2 = 315; + R3 = 615; + R4 = 180; + R5 = 460; + R6 = 120; +elseif strcmp(z2, 'H') + U = 220; + R1 = 190; + R2 = 360; + R3 = 580; + R4 = 205; + R5 = 560; + R6 = 250; +else + error('Invalid variation specified.'); +end + +Rekv = R1 + ((R2 + R3) * (R4 + R5))/(R2 + R3 + R4 + R5); +fprintf("Rekv=%.8f\n", Rekv); +I = U/Rekv; +fprintf("I=%.8f\n", I); + +UR45 = U - I * R1; +IR45 = UR45/(R4 + R5); +fprintf("IR45=%.8f\n", IR45); + +Ui = IR45 * R5; + +Ri = (((((R3+R2)*R1)/(R1+R2+R3))+R4)*R5)/(((((R3+R2)*R1)/(R1+R2+R3))+R4)+R5); + +IR6 = Ui/(Ri + R6); +UR6 = R6 * IR6; + +fprintf('Ui = %.8fV, Ri=%.8fΩ, UR6 = %.8fV, IR6 = %.8fA\n\n',Ui,Ri, UR6, IR6); + +% zadanie 3 +fprintf("priklad 3 [%s]\n",z3); + +if strcmp(z3, 'A') + U = 120; + I1 = 0.9; + I2 = 0.7; + R1 = 53; + R2 = 49; + R3 = 65; + R4 = 39; + R5 = 32; +elseif strcmp(z3, 'B') + U = 150; + I1 = 0.7; + I2 = 0.8; + R1 = 49; + R2 = 45; + R3 = 61; + R4 = 34; + R5 = 34; +elseif strcmp(z3, 'C') + U = 110; + I1 = 0.85; + I2 = 0.75; + R1 = 44; + R2 = 31; + R3 = 56; + R4 = 20; + R5 = 30; +elseif strcmp(z3, 'D') + U = 115; + I1 = 0.6; + I2 = 0.9; + R1 = 50; + R2 = 38; + R3 = 48; + R4 = 37; + R5 = 28; +elseif strcmp(z3, 'E') + U = 135; + I1 = 0.55; + I2 = 0.65; + R1 = 52; + R2 = 42; + R3 = 52; + R4 = 42; + R5 = 21; +elseif strcmp(z3, 'F') + U = 145; + I1 = 0.75; + I2 = 0.85; + R1 = 48; + R2 = 44; + R3 = 53; + R4 = 36; + R5 = 25; +elseif strcmp(z3, 'G') + U = 160; + I1 = 0.65; + I2 = 0.45; + R1 = 46; + R2 = 41; + R3 = 53; + R4 = 33; + R5 = 29; +elseif strcmp(z3, 'H') + U = 130; + I1 = 0.95; + I2 = 0.50; + R1 = 47; + R2 = 39; + R3 = 58; + R4 = 28; + R5 = 25; +else + error('Invalid variation specified.'); +end + + +A = [(1/R1)+(1/R2) -(1/R2) 0;-(1/R2) (1/R2)+(1/R3) -(1/R3);(-1/R2) 1/R2 (1/R4)+(1/R5)]; +disp(A) +I = [I1;I2;(U/R5)]; +fprintf("I3=%.8fA\n", (U/R5)); +U = inv(A) * I; +Ua = U(1); +Ub = U(2); +Uc = U(3); +UR4 = Uc; +IR4 = UR4/R4; +fprintf("Ua=%.8fV\n", Ua); +fprintf("Ub=%.8fV\n", Ub); +fprintf("Uc=%.8fV\n", Uc); + + +fprintf('UR4 = %.8fV, IR4 = %.8fA\n\n', UR4, IR4); + + +% pr4 +fprintf("priklad 4 [%s]\n",z4); + +if strcmp(z4, 'A') + u1 = 3; + u2 = 5; + R1 = 12; + R2 = 14; + L1 = 120 * 10^(-3); + L2 = 100 * 10^(-3); + C1 = 200 * 10^(-6); + C2 = 105 * 10^(-6); + f = 70; +elseif strcmp(z4, 'B') + u1 = 2; + u2 = 4; + R1 = 11; + R2 = 15; + L1 = 100 * 10^(-3); + L2 = 85 * 10^(-3); + C1 = 220 * 10^(-6); + C2 = 95 * 10^(-6); + f = 80; +elseif strcmp(z4, 'C') + u1 = 3; + u2 = 4; + R1 = 10; + R2 = 13; + L1 = 220 * 10^(-3); + L2 = 70 * 10^(-3); + C1 = 230 * 10^(-6); + C2 = 85 * 10^(-6); + f = 75; +elseif strcmp(z4, 'D') + u1 = 4; + u2 = 5; + R1 = 13; + R2 = 15; + L1 = 180 * 10^(-3); + L2 = 90 * 10^(-3); + C1 = 210 * 10^(-6); + C2 = 75 * 10^(-6); + f = 85; +elseif strcmp(z4, 'E') + u1 = 5; + u2 = 3; + R1 = 14; + R2 = 13; + L1 = 130 * 10^(-3); + L2 = 60 * 10^(-3); + C1 = 100 * 10^(-6); + C2 = 65 * 10^(-6); + f = 90; +elseif strcmp(z4, 'F') + u1 = 2; + u2 = 3; + R1 = 12; + R2 = 10; + L1 = 170 * 10^(-3); + L2 = 80 * 10^(-3); + C1 = 150 * 10^(-6); + C2 = 90 * 10^(-6); + f = 65; +elseif strcmp(z4, 'G') + u1 = 5; + u2 = 5; + R1 = 13; + R2 = 12; + L1 = 140 * 10^(-3); + L2 = 60 * 10^(-3); + C1 = 160 * 10^(-6); + C2 = 80 * 10^(-6); + f = 60; +elseif strcmp(z4, 'H') + u1 = 5; + u2 = 6; + R1 = 10; + R2 = 10; + L1 = 160 * 10^(-3); + L2 = 75 * 10^(-3); + C1 = 155 * 10^(-6); + C2 = 70 * 10^(-6); + f = 95; +else + error('Invalid variation specified.'); +end + + +w = 2*pi*f; +ZL1 = 1j*w*L1; +ZL2 = 1j*w*L2; +ZC1 = -(1j/(w*C1)); +ZC2 = -(1j/(w*C2)); +fprintf("wL1=%.8f\n", w*L1);fprintf("wL1=%.8f\n", w*L2); +A = [R2+R1+ZC1+ZL1 -ZC1-R1 -R2;-R1-ZC1 ZC1+R1+ZL2 -ZL2;R2 ZL2 -ZL2-R2-ZC2]; + +U = [0;u1;u2]; + +P = inv(A) * U; % prudy +Ia = P(1); +Ib = P(2); +Ic = P(3); +fprintf("%.8f + j%.8f \n",real(Ia), imag(Ia) ); +fprintf("%.8f + j%.8f \n",real(Ib), imag(Ib) ); +fprintf("%.8f + j%.8f \n",real(Ic), imag(Ic) ); +fprintf("%.8f + j%.8f \n",real(Ib-Ic), imag(Ib-Ic) ); + +ul2 = ZL2 *(Ib-Ic); +UL2 = abs(ul2); +fprintf("%.8f \n", imag(ul2)*imag(ul2) ); +fprintf("%.8f \n", real(ul2)*real(ul2) ); + +theta = rad2deg(atan(imag(ul2)/real(ul2))) + "°"; +fprintf("%.8f \n", atan(imag(ul2)/real(ul2)) ); + +fprintf("ul2 = %.8f + j%.8fV, UL2 = %.8fV, theta = %s\n\n",real(ul2),imag(ul2),UL2,theta); \ No newline at end of file diff --git a/1BIT/winter-semester/Projekt IEL/obrazky povodne/Pr12023.eps b/1BIT/winter-semester/Projekt IEL/obrazky povodne/Pr12023.eps new file mode 100644 index 0000000..4e47a4f --- /dev/null +++ b/1BIT/winter-semester/Projekt IEL/obrazky povodne/Pr12023.eps @@ -0,0 +1,791 @@ +%!PS-Adobe-2.0 EPSF-2.0 +%%Title: C:\Users\roman\OneDrive\Počítač\Pr1_2023.dia +%%Creator: Dia v0.97.2 +%%CreationDate: Thu Dec 07 17:36:22 2023 +%%For: roman +%%Orientation: Portrait +%%Magnification: 1.0000 +%%BoundingBox: 0 0 634 273 +%%BeginSetup +%%EndSetup +%%EndComments +%%BeginProlog +[ /.notdef /.notdef /.notdef /.notdef /.notdef /.notdef /.notdef /.notdef /.notdef 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b/2BIT/summer-semester/IDS/xnecasr00_xpribik00.sql new file mode 100644 index 0000000..4634803 --- /dev/null +++ b/2BIT/summer-semester/IDS/xnecasr00_xpribik00.sql @@ -0,0 +1,480 @@ +-- IDS - project 3rd part +-- Roman Nečas - xnecasr00 +-- Kristián Pribila - xpribik00 +-- 9.4.2025 + +-- Drop existing tables (if they exist) +DROP TABLE Recenzia CASCADE CONSTRAINTS; +DROP TABLE Vypozicka CASCADE CONSTRAINTS; +DROP TABLE Rezervacia CASCADE CONSTRAINTS; +DROP TABLE Exemplar CASCADE CONSTRAINTS; +DROP TABLE Kniha CASCADE CONSTRAINTS; +DROP TABLE Casopis CASCADE CONSTRAINTS; +DROP TABLE Titul CASCADE CONSTRAINTS; +DROP TABLE Citatel CASCADE CONSTRAINTS; +DROP TABLE Zamestnanec CASCADE CONSTRAINTS; +DROP TABLE Pouzivatel CASCADE CONSTRAINTS; + +-- Drop sequences (if they exist) +DROP SEQUENCE pouzivatel_seq; +DROP SEQUENCE titul_seq; +DROP SEQUENCE exemplar_seq; +DROP SEQUENCE rezervacia_seq; +DROP SEQUENCE vypozicka_seq; +DROP SEQUENCE recenzia_seq; + +-- Create sequences for primary keys +CREATE SEQUENCE pouzivatel_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE titul_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE exemplar_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE rezervacia_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE vypozicka_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE recenzia_seq START WITH 1 INCREMENT BY 1; + + +-- Create tables +-- Implementation of generalization/specialization: +-- We are using the approach where parent tables (Pouzivatel and Titul) contain common attributes, +-- and child tables (Citatel, Zamestnanec, Kniha, Casopis) contain specific attributes. +-- Child tables have primary keys that are also foreign keys referencing parent tables. +-- This allows us to maintain the integrity of the inheritance relationship while +-- having specific attributes for each specialization. + +-- Parent table for Users +CREATE TABLE Pouzivatel ( + ID_pouzivatela NUMBER PRIMARY KEY, + Meno VARCHAR2(50) NOT NULL, + Priezvisko VARCHAR2(50) NOT NULL, + Email VARCHAR2(100) NOT NULL UNIQUE, + Telefon VARCHAR2(20), + Adresa VARCHAR2(200), + Datum_registracie DATE DEFAULT SYSDATE NOT NULL +); + +-- Child table for Readers +CREATE TABLE Citatel ( + ID_pouzivatela NUMBER PRIMARY KEY, + Cislo_preukazu VARCHAR2(20) NOT NULL UNIQUE, + Platnost_do DATE NOT NULL, + Status VARCHAR2(20) DEFAULT 'Aktívny' CHECK (Status IN ('Aktívny', 'Neaktívny', 'Pozastavený')), + Pocet_vypoziciek NUMBER DEFAULT 0, + CONSTRAINT fk_citatel_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela) + ON DELETE CASCADE +); + +-- Child table for Employees +CREATE TABLE Zamestnanec ( + ID_pouzivatela NUMBER PRIMARY KEY, + Osobne_cislo VARCHAR2(20) NOT NULL UNIQUE, + Datum_nastupu DATE NOT NULL, + Oddelenie VARCHAR2(50) NOT NULL, + Titul VARCHAR2(20), + CONSTRAINT fk_zamestnanec_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela) + ON DELETE CASCADE +); + +-- Parent table for Titles +CREATE TABLE Titul ( + ID_titulu NUMBER PRIMARY KEY, + Nazov VARCHAR2(200) NOT NULL, + Vydavatelstvo VARCHAR2(100), + Rok_vydania NUMBER(4), + Popis VARCHAR2(4000), + Kategoria VARCHAR2(50), + Pocet_exemplarov NUMBER DEFAULT 0 +); + +-- Child table for Books with ISBN validation +CREATE TABLE Kniha ( + ID_titulu NUMBER PRIMARY KEY, + ISBN VARCHAR2(13) NOT NULL UNIQUE, + Autor VARCHAR2(200) NOT NULL, + Pocet_stran NUMBER, + Zaner VARCHAR2(50), + CONSTRAINT fk_kniha_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) + ON DELETE CASCADE, + -- ISBN must be exactly 13 digits + CONSTRAINT chk_isbn CHECK (REGEXP_LIKE(ISBN, '^[0-9]{13}$')) +); + +-- Child table for Magazines with ISSN validation +CREATE TABLE Casopis ( + ID_titulu NUMBER PRIMARY KEY, + ISSN VARCHAR2(9) NOT NULL UNIQUE, + Rocnik NUMBER, + Cislo NUMBER, + Periodicita VARCHAR2(50), + CONSTRAINT fk_casopis_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) + ON DELETE CASCADE, + -- ISSN must be in format XXXX-XXXX where X is a digit + CONSTRAINT chk_issn CHECK (REGEXP_LIKE(ISSN, '^[0-9]{4}-[0-9]{4}$')) +); + +-- Table for Copies +CREATE TABLE Exemplar ( + ID_exemplaru NUMBER PRIMARY KEY, + ID_titulu NUMBER NOT NULL, + Datum_nadobudnutia DATE, + Umiestnenie VARCHAR2(100), + Signatura VARCHAR2(50), + Status VARCHAR2(20) DEFAULT 'Dostupný' CHECK (Status IN ('Dostupný', 'Vypožičaný', 'Rezervovaný', 'Vyradený', 'Poškodený')), + CONSTRAINT fk_exemplar_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) + ON DELETE CASCADE +); + +-- Table for Reservations +CREATE TABLE Rezervacia ( + ID_rezervacie NUMBER PRIMARY KEY, + ID_pouzivatela NUMBER NOT NULL, + ID_titulu NUMBER NOT NULL, + Datum_rezervacie DATE DEFAULT SYSDATE NOT NULL, + Datum_expiracie DATE, + Stav VARCHAR2(20) DEFAULT 'Aktívna' CHECK (Stav IN ('Aktívna', 'Vybavená', 'Zrušená')), + CONSTRAINT fk_rezervacia_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela), + CONSTRAINT fk_rezervacia_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) +); + +-- Table for Loans +CREATE TABLE Vypozicka ( + ID_vypozicky NUMBER PRIMARY KEY, + ID_pouzivatela NUMBER NOT NULL, + ID_exemplaru NUMBER NOT NULL, + Datum_vypozicania DATE DEFAULT SYSDATE NOT NULL, + Planovany_datum_vratenia DATE NOT NULL, + Skutocny_datum_vratenia DATE, + Stav VARCHAR2(20) DEFAULT 'Aktívna' CHECK (Stav IN ('Aktívna', 'Vrátená', 'Oneskorená')), + CONSTRAINT fk_vypozicka_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela), + CONSTRAINT fk_vypozicka_exemplar FOREIGN KEY (ID_exemplaru) REFERENCES Exemplar(ID_exemplaru) +); + +-- Table for Reviews +CREATE TABLE Recenzia ( + ID_recenzie NUMBER PRIMARY KEY, + ID_pouzivatela NUMBER NOT NULL, + ID_titulu NUMBER NOT NULL, + Hodnotenie NUMBER(1) CHECK (Hodnotenie BETWEEN 1 AND 5), + Sprava VARCHAR2(2000), + Datum DATE DEFAULT SYSDATE NOT NULL, + CONSTRAINT fk_recenzia_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela), + CONSTRAINT fk_recenzia_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) +); + +-- Create triggers for auto-incrementing primary keys from sequences +CREATE OR REPLACE TRIGGER pouzivatel_bir +BEFORE INSERT ON Pouzivatel +FOR EACH ROW +BEGIN + IF :NEW.ID_pouzivatela IS NULL THEN + SELECT pouzivatel_seq.NEXTVAL + INTO :NEW.ID_pouzivatela + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER titul_bir +BEFORE INSERT ON Titul +FOR EACH ROW +BEGIN + IF :NEW.ID_titulu IS NULL THEN + SELECT titul_seq.NEXTVAL + INTO :NEW.ID_titulu + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER exemplar_bir +BEFORE INSERT ON Exemplar +FOR EACH ROW +BEGIN + IF :NEW.ID_exemplaru IS NULL THEN + SELECT exemplar_seq.NEXTVAL + INTO :NEW.ID_exemplaru + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER rezervacia_bir +BEFORE INSERT ON Rezervacia +FOR EACH ROW +BEGIN + IF :NEW.ID_rezervacie IS NULL THEN + SELECT rezervacia_seq.NEXTVAL + INTO :NEW.ID_rezervacie + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER vypozicka_bir +BEFORE INSERT ON Vypozicka +FOR EACH ROW +BEGIN + IF :NEW.ID_vypozicky IS NULL THEN + SELECT vypozicka_seq.NEXTVAL + INTO :NEW.ID_vypozicky + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER recenzia_bir +BEFORE INSERT ON Recenzia +FOR EACH ROW +BEGIN + IF :NEW.ID_recenzie IS NULL THEN + SELECT recenzia_seq.NEXTVAL + INTO :NEW.ID_recenzie + FROM dual; + END IF; +END; +/ + +-- Insert sample data +-- Insert Users +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Ján', 'Novák', 'jan.novak@example.com', '+421901234567', 'Bratislavská 123, Bratislava', TO_DATE('2022-01-15', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Anna', 'Králová', 'anna.kralova@example.com', '+421902345678', 'Košická 456, Košice', TO_DATE('2022-02-20', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Peter', 'Malý', 'peter.maly@example.com', '+421903456789', 'Hlavná 789, Žilina', TO_DATE('2022-03-10', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Eva', 'Veľká', 'eva.velka@example.com', '+421904567890', 'Námestie SNP 10, Banská Bystrica', TO_DATE('2022-04-05', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Milan', 'Kovář', 'milan.kovar@example.com', '+421905678901', 'Moyzesova 321, Nitra', TO_DATE('2022-05-12', 'YYYY-MM-DD')); + +-- Insert Readers +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (1, 'CIT-001', TO_DATE('2025-01-15', 'YYYY-MM-DD'), 'Aktívny', 0); + +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (2, 'CIT-002', TO_DATE('2025-02-20', 'YYYY-MM-DD'), 'Aktívny', 0); + +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (3, 'CIT-003', TO_DATE('2025-03-10', 'YYYY-MM-DD'), 'Pozastavený', 0); + +-- Insert Employees +INSERT INTO Zamestnanec (ID_pouzivatela, Osobne_cislo, Datum_nastupu, Oddelenie, Titul) +VALUES (4, 'ZAM-001', TO_DATE('2020-04-05', 'YYYY-MM-DD'), 'Katalogizácia', 'Mgr.'); + +INSERT INTO Zamestnanec (ID_pouzivatela, Osobne_cislo, Datum_nastupu, Oddelenie, Titul) +VALUES (5, 'ZAM-002', TO_DATE('2021-05-12', 'YYYY-MM-DD'), 'Výpožičky', 'Ing.'); + +-- Insert Titles +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Pán Prsteňov: Spoločenstvo prsteňa', 'Slovart', 2001, 'Prvá časť fantasy trilógie od J.R.R. Tolkiena', 'Fantasy', 200); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Harry Potter a Kameň mudrcov', 'Ikar', 2000, 'Prvá kniha zo série o mladom čarodejníkovi', 'Fantasy', 80); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('National Geographic', 'National Geographic Society', 2023, 'Populárno-náučný časopis', 'Veda', 25); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Forbes', 'Forbes Media', 2023, 'Ekonomický časopis', 'Biznis', 100); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('1984', 'Slovart', 2015, 'Dystopický román od George Orwella', 'Sci-fi', 50); + +-- Insert Books +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (1, '9788055603261', 'J.R.R. Tolkien', 432, 'Fantasy'); + +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (2, '9788055159423', 'J.K. Rowling', 320, 'Fantasy'); + +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (5, '9788055138887', 'George Orwell', 288, 'Sci-fi'); + +-- Insert Magazines +INSERT INTO Casopis (ID_titulu, ISSN, Rocnik, Cislo, Periodicita) +VALUES (3, '0027-9358', 2023, 3, 'Mesačník'); + +INSERT INTO Casopis (ID_titulu, ISSN, Rocnik, Cislo, Periodicita) +VALUES (4, '0015-6914', 2023, 4, 'Mesačník'); + +-- Insert Copies +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (1, TO_DATE('2022-01-10', 'YYYY-MM-DD'), 'Regál A, Polica 1', 'F-TOL-001', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (1, TO_DATE('2022-01-10', 'YYYY-MM-DD'), 'Regál A, Polica 1', 'F-TOL-002', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (2, TO_DATE('2022-02-15', 'YYYY-MM-DD'), 'Regál A, Polica 2', 'F-ROW-001', 'Vypožičaný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (3, TO_DATE('2023-03-01', 'YYYY-MM-DD'), 'Regál B, Polica 1', 'C-NAT-001', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (4, TO_DATE('2023-04-05', 'YYYY-MM-DD'), 'Regál B, Polica 2', 'C-FOR-001', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (5, TO_DATE('2022-06-10', 'YYYY-MM-DD'), 'Regál C, Polica 1', 'S-ORW-001', 'Vypožičaný'); + +-- Insert Reservations +INSERT INTO Rezervacia (ID_pouzivatela, ID_titulu, Datum_rezervacie, Datum_expiracie, Stav) +VALUES (1, 2, TO_DATE('2023-04-10', 'YYYY-MM-DD'), TO_DATE('2023-04-17', 'YYYY-MM-DD'), 'Aktívna'); + +INSERT INTO Rezervacia (ID_pouzivatela, ID_titulu, Datum_rezervacie, Datum_expiracie, Stav) +VALUES (2, 5, TO_DATE('2023-04-12', 'YYYY-MM-DD'), TO_DATE('2023-04-19', 'YYYY-MM-DD'), 'Vybavená'); + +-- Insert Loans +INSERT INTO Vypozicka (ID_pouzivatela, ID_exemplaru, Datum_vypozicania, Planovany_datum_vratenia, Skutocny_datum_vratenia, Stav) +VALUES (1, 3, TO_DATE('2023-04-10', 'YYYY-MM-DD'), TO_DATE('2023-05-10', 'YYYY-MM-DD'), NULL, 'Aktívna'); + +INSERT INTO Vypozicka (ID_pouzivatela, ID_exemplaru, Datum_vypozicania, Planovany_datum_vratenia, Skutocny_datum_vratenia, Stav) +VALUES (2, 6, TO_DATE('2023-04-12', 'YYYY-MM-DD'), TO_DATE('2023-05-12', 'YYYY-MM-DD'), TO_DATE('2023-04-30', 'YYYY-MM-DD'), 'Vrátená'); + +-- Insert Reviews +INSERT INTO Recenzia (ID_pouzivatela, ID_titulu, Hodnotenie, Sprava, Datum) +VALUES (1, 1, 5, 'Vynikajúca kniha, jedno z najlepších fantasy diel všetkých čias.', TO_DATE('2023-03-15', 'YYYY-MM-DD')); + +INSERT INTO Recenzia (ID_pouzivatela, ID_titulu, Hodnotenie, Sprava, Datum) +VALUES (2, 2, 4, 'Skvelá kniha pre mladých čitateľov, fascinujúci magický svet.', TO_DATE('2023-03-20', 'YYYY-MM-DD')); + +INSERT INTO Recenzia (ID_pouzivatela, ID_titulu, Hodnotenie, Sprava, Datum) +VALUES (3, 5, 5, 'Nadčasový dystopický román, stále aktuálny aj dnes.', TO_DATE('2023-03-25', 'YYYY-MM-DD')); + + + +-- 3rd part of the project +-- Extra Data for better filtering +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Lucia', 'Horváthová', 'lucia.horvathova@example.com', '+421906789012', 'Dlhá 5, Trnava', TO_DATE('2022-06-01', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Martin', 'Šimek', 'martin.simek@example.com', '+421907890123', 'Jarná 22, Prešov', TO_DATE('2022-07-10', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Barbora', 'Petrová', 'barbora.petrova@example.com', '+421908901234', 'Letná 7, Poprad', TO_DATE('2022-08-18', 'YYYY-MM-DD')); + +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (6, 'CIT-004', TO_DATE('2025-06-01', 'YYYY-MM-DD'), 'Aktívny', 1); + +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (7, 'CIT-005', TO_DATE('2025-07-10', 'YYYY-MM-DD'), 'Pozastavený', 0); + +INSERT INTO Zamestnanec (ID_pouzivatela, Osobne_cislo, Datum_nastupu, Oddelenie, Titul) +VALUES (8, 'ZAM-003', TO_DATE('2021-08-18', 'YYYY-MM-DD'), 'Oddelenie vývoja databáz', 'PhDr.'); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Bratstvo čiernej dýky', 'Ikar', 2012, 'Moderný mestský fantasy román s upírskou tematikou', 'Fantasy', 30); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Sapiens: Stručná história ľudstva', 'Tatran', 2018, 'Fascinujúci pohľad na vývoj ľudskej civilizácie', 'História',120); + +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (6, '9788055163223', 'J.R. Ward', 400, 'Fantasy'); + +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (7, '9788022209223', 'Yuval Noah Harari', 448, 'História'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (6, TO_DATE('2022-09-01', 'YYYY-MM-DD'), 'Regál D, Polica 1', 'F-WAR-001', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (7, TO_DATE('2022-10-01', 'YYYY-MM-DD'), 'Regál E, Polica 3', 'H-HAR-001', 'Vypožičaný'); + +INSERT INTO Rezervacia (ID_pouzivatela, ID_titulu, Datum_rezervacie, Datum_expiracie, Stav) +VALUES (6, 6, TO_DATE('2023-06-05', 'YYYY-MM-DD'), TO_DATE('2023-06-12', 'YYYY-MM-DD'), 'Aktívna'); + + +INSERT INTO Vypozicka (ID_pouzivatela, ID_exemplaru, Datum_vypozicania, Planovany_datum_vratenia, Skutocny_datum_vratenia, Stav) +VALUES (6, 7, TO_DATE('2023-06-06', 'YYYY-MM-DD'), TO_DATE('2023-07-06', 'YYYY-MM-DD'), NULL, 'Aktívna'); + +INSERT INTO Recenzia (ID_pouzivatela, ID_titulu, Hodnotenie, Sprava, Datum) +VALUES (6, 7, 5, 'Skvelo napísané a veľmi poučné. Harari píše pútavo.', TO_DATE('2023-06-10', 'YYYY-MM-DD')); + + +--Selects +-- Show information about employees +SELECT p.meno || ' ' || p.priezvisko AS zamestnanec, p.ID_pouzivatela ,p.Telefon, p.Email, p.Adresa +FROM Zamestnanec z +JOIN Pouzivatel p ON z.ID_pouzivatela = p.ID_pouzivatela; + +-- Show information about reservations +SELECT p.meno || ' ' || p.priezvisko AS citatel, r.ID_titulu, r.Datum_expiracie, r.Datum_rezervacie, r.Stav +FROM Rezervacia r +JOIN Pouzivatel p ON p.ID_pouzivatela = r.ID_pouzivatela; + +-- Show reviews +SELECT p.meno || ' ' || p.priezvisko AS recenzent, t.Nazov, r.Hodnotenie, r.Sprava +FROM Recenzia r +JOIN Titul t ON r.ID_titulu = t.ID_titulu +JOIN Pouzivatel p ON r.ID_pouzivatela = p.ID_pouzivatela ; + +-- Show available titles and their count +SELECT + t.Nazov, + COUNT(e.ID_exemplaru) AS Pocet_dostupnych +FROM Titul t +JOIN Exemplar e ON t.ID_titulu = e.ID_titulu +WHERE e.Status = 'Dostupný' +GROUP BY t.Nazov; + +-- Show active borrowings +SELECT + p.Meno || ' ' || p.Priezvisko AS Citatel, + t.Nazov AS Kniha, + v.Datum_vypozicania, + v.Planovany_datum_vratenia +FROM Vypozicka v +JOIN Pouzivatel p ON v.ID_pouzivatela = p.ID_pouzivatela +JOIN Exemplar e ON v.ID_exemplaru = e.ID_exemplaru +JOIN Titul t ON e.ID_titulu = t.ID_titulu +WHERE v.Stav = 'Aktívna'; + +-- Show all names with their role +SELECT + p.ID_pouzivatela, + p.Meno, + p.Priezvisko, + CASE + WHEN EXISTS (SELECT 1 FROM Citatel c WHERE c.ID_pouzivatela = p.ID_pouzivatela) THEN 'Citatel' + WHEN EXISTS (SELECT 1 FROM Zamestnanec z WHERE z.ID_pouzivatela = p.ID_pouzivatela) THEN 'Zamestnanec' + ELSE 'Neznámy' + END AS Typ_pouzivatela +FROM Pouzivatel p; + +-- Show which books wasnt returned +SELECT p.Meno || ' ' || p.Priezvisko AS citatel +FROM Pouzivatel p +WHERE EXISTS ( + SELECT 1 + FROM Vypozicka v + WHERE v.ID_pouzivatela = p.ID_pouzivatela + AND v.Skutocny_datum_vratenia IS NULL +); + +-- Show titles based on genre +SELECT + Nazov, + Kategoria, + Pocet_exemplarov +FROM Titul +WHERE Kategoria = 'Fantasy'; + +-- Show how many borrows and reservations reader made. +SELECT p.Meno || ' ' || p.Priezvisko AS Citatel, c.ID_pouzivatela, v.Stav, COUNT(DISTINCT v.ID_vypozicky) AS pocet_vypoziciek, COUNT(DISTINCT r.ID_rezervacie) AS pocet_rezervaci +FROM Citatel c +JOIN Vypozicka v ON c.ID_pouzivatela = v.ID_pouzivatela +JOIN Pouzivatel p ON c.ID_pouzivatela = p.ID_pouzivatela +JOIN Rezervacia r ON p.ID_pouzivatela = r.ID_pouzivatela +GROUP BY p.Meno, p.Priezvisko, c.ID_pouzivatela, v.Stav; + +-- Show only reviewed titles +SELECT nazov +FROM Titul +WHERE id_titulu IN ( + SELECT id_titulu + FROM Recenzia +); + +COMMIT; diff --git a/2BIT/summer-semester/IDS/xnecasr00_xpribik00.zip b/2BIT/summer-semester/IDS/xnecasr00_xpribik00.zip new file mode 100644 index 0000000..9ab563e Binary files /dev/null and b/2BIT/summer-semester/IDS/xnecasr00_xpribik00.zip differ diff --git a/2BIT/summer-semester/IDS/xnecasr00_xpribik00/database.sql b/2BIT/summer-semester/IDS/xnecasr00_xpribik00/database.sql new file mode 100644 index 0000000..edee7da --- /dev/null +++ b/2BIT/summer-semester/IDS/xnecasr00_xpribik00/database.sql @@ -0,0 +1,959 @@ +-- IDS - project 4th part +-- Roman Nečas - xnecasr00 +-- Kristián Pribila - xpribik00 +-- 03.05.2025 + +-- Drop existing tables (if they exist) +DROP TABLE Recenzia CASCADE CONSTRAINTS; +DROP TABLE Vypozicka CASCADE CONSTRAINTS; +DROP TABLE Rezervacia CASCADE CONSTRAINTS; +DROP TABLE Exemplar CASCADE CONSTRAINTS; +DROP TABLE Kniha CASCADE CONSTRAINTS; +DROP TABLE Casopis CASCADE CONSTRAINTS; +DROP TABLE Titul CASCADE CONSTRAINTS; +DROP TABLE Citatel CASCADE CONSTRAINTS; +DROP TABLE Zamestnanec CASCADE CONSTRAINTS; +DROP TABLE Pouzivatel CASCADE CONSTRAINTS; + +-- Drop sequences (if they exist) +DROP SEQUENCE pouzivatel_seq; +DROP SEQUENCE titul_seq; +DROP SEQUENCE exemplar_seq; +DROP SEQUENCE rezervacia_seq; +DROP SEQUENCE vypozicka_seq; +DROP SEQUENCE recenzia_seq; + +-- Drop procedures (if they exist) +BEGIN + EXECUTE IMMEDIATE 'DROP PROCEDURE spracuj_rezervaciu'; +EXCEPTION + WHEN OTHERS THEN NULL; +END; +/ + +BEGIN + EXECUTE IMMEDIATE 'DROP PROCEDURE generuj_report_oneskorene'; +EXCEPTION + WHEN OTHERS THEN NULL; +END; +/ + +BEGIN + EXECUTE IMMEDIATE 'DROP PROCEDURE aktualizuj_oneskorene_vypozicky'; +EXCEPTION + WHEN OTHERS THEN NULL; +END; +/ + +-- Create sequences for primary keys +CREATE SEQUENCE pouzivatel_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE titul_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE exemplar_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE rezervacia_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE vypozicka_seq START WITH 1 INCREMENT BY 1; +CREATE SEQUENCE recenzia_seq START WITH 1 INCREMENT BY 1; + + +-- Create tables +-- Implementation of generalization/specialization: +-- We are using the approach where parent tables (Pouzivatel and Titul) contain common attributes, +-- and child tables (Citatel, Zamestnanec, Kniha, Casopis) contain specific attributes. +-- Child tables have primary keys that are also foreign keys referencing parent tables. +-- This allows us to maintain the integrity of the inheritance relationship while +-- having specific attributes for each specialization. + +-- Parent table for Users +CREATE TABLE Pouzivatel ( + ID_pouzivatela NUMBER PRIMARY KEY, + Meno VARCHAR2(50) NOT NULL, + Priezvisko VARCHAR2(50) NOT NULL, + Email VARCHAR2(100) NOT NULL UNIQUE, + Telefon VARCHAR2(20), + Adresa VARCHAR2(200), + Datum_registracie DATE DEFAULT SYSDATE NOT NULL +); + +-- Child table for Readers +CREATE TABLE Citatel ( + ID_pouzivatela NUMBER PRIMARY KEY, + Cislo_preukazu VARCHAR2(20) NOT NULL UNIQUE, + Platnost_do DATE NOT NULL, + Status VARCHAR2(20) DEFAULT 'Aktívny' CHECK (Status IN ('Aktívny', 'Neaktívny', 'Pozastavený')), + Pocet_vypoziciek NUMBER DEFAULT 0, + CONSTRAINT fk_citatel_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela) + ON DELETE CASCADE +); + +-- Child table for Employees +CREATE TABLE Zamestnanec ( + ID_pouzivatela NUMBER PRIMARY KEY, + Osobne_cislo VARCHAR2(20) NOT NULL UNIQUE, + Datum_nastupu DATE NOT NULL, + Oddelenie VARCHAR2(50) NOT NULL, + Titul VARCHAR2(20), + CONSTRAINT fk_zamestnanec_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela) + ON DELETE CASCADE +); + +-- Parent table for Titles +CREATE TABLE Titul ( + ID_titulu NUMBER PRIMARY KEY, + Nazov VARCHAR2(200) NOT NULL, + Vydavatelstvo VARCHAR2(100), + Rok_vydania NUMBER(4), + Popis VARCHAR2(4000), + Kategoria VARCHAR2(50), + Pocet_exemplarov NUMBER DEFAULT 0 +); + +-- Child table for Books with ISBN validation +CREATE TABLE Kniha ( + ID_titulu NUMBER PRIMARY KEY, + ISBN VARCHAR2(13) NOT NULL UNIQUE, + Autor VARCHAR2(200) NOT NULL, + Pocet_stran NUMBER, + Zaner VARCHAR2(50), + CONSTRAINT fk_kniha_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) + ON DELETE CASCADE, + -- ISBN must be exactly 13 digits + CONSTRAINT chk_isbn CHECK (REGEXP_LIKE(ISBN, '^[0-9]{13}$')) +); + +-- Child table for Magazines with ISSN validation +CREATE TABLE Casopis ( + ID_titulu NUMBER PRIMARY KEY, + ISSN VARCHAR2(9) NOT NULL UNIQUE, + Rocnik NUMBER, + Cislo NUMBER, + Periodicita VARCHAR2(50), + CONSTRAINT fk_casopis_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) + ON DELETE CASCADE, + -- ISSN must be in format XXXX-XXXX where X is a digit + CONSTRAINT chk_issn CHECK (REGEXP_LIKE(ISSN, '^[0-9]{4}-[0-9]{4}$')) +); + +-- Table for Copies +CREATE TABLE Exemplar ( + ID_exemplaru NUMBER PRIMARY KEY, + ID_titulu NUMBER NOT NULL, + Datum_nadobudnutia DATE, + Umiestnenie VARCHAR2(100), + Signatura VARCHAR2(50), + Status VARCHAR2(20) DEFAULT 'Dostupný' CHECK (Status IN ('Dostupný', 'Vypožičaný', 'Rezervovaný', 'Vyradený', 'Poškodený')), + CONSTRAINT fk_exemplar_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) + ON DELETE CASCADE +); + +-- Table for Reservations +CREATE TABLE Rezervacia ( + ID_rezervacie NUMBER PRIMARY KEY, + ID_pouzivatela NUMBER NOT NULL, + ID_titulu NUMBER NOT NULL, + Datum_rezervacie DATE DEFAULT SYSDATE NOT NULL, + Datum_expiracie DATE, + Stav VARCHAR2(20) DEFAULT 'Aktívna' CHECK (Stav IN ('Aktívna', 'Vybavená', 'Zrušená')), + CONSTRAINT fk_rezervacia_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela), + CONSTRAINT fk_rezervacia_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) +); + +-- Table for Loans +CREATE TABLE Vypozicka ( + ID_vypozicky NUMBER PRIMARY KEY, + ID_pouzivatela NUMBER NOT NULL, + ID_exemplaru NUMBER NOT NULL, + Datum_vypozicania DATE DEFAULT SYSDATE NOT NULL, + Planovany_datum_vratenia DATE NOT NULL, + Skutocny_datum_vratenia DATE, + Stav VARCHAR2(20) DEFAULT 'Aktívna' CHECK (Stav IN ('Aktívna', 'Vrátená', 'Oneskorená')), + CONSTRAINT fk_vypozicka_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela), + CONSTRAINT fk_vypozicka_exemplar FOREIGN KEY (ID_exemplaru) REFERENCES Exemplar(ID_exemplaru) +); + +-- Table for Reviews +CREATE TABLE Recenzia ( + ID_recenzie NUMBER PRIMARY KEY, + ID_pouzivatela NUMBER NOT NULL, + ID_titulu NUMBER NOT NULL, + Hodnotenie NUMBER(1) CHECK (Hodnotenie BETWEEN 1 AND 5), + Sprava VARCHAR2(2000), + Datum DATE DEFAULT SYSDATE NOT NULL, + CONSTRAINT fk_recenzia_pouzivatel FOREIGN KEY (ID_pouzivatela) REFERENCES Pouzivatel(ID_pouzivatela), + CONSTRAINT fk_recenzia_titul FOREIGN KEY (ID_titulu) REFERENCES Titul(ID_titulu) +); + +-- Create triggers for auto-incrementing primary keys from sequences +CREATE OR REPLACE TRIGGER pouzivatel_bir +BEFORE INSERT ON Pouzivatel +FOR EACH ROW +BEGIN + IF :NEW.ID_pouzivatela IS NULL THEN + SELECT pouzivatel_seq.NEXTVAL + INTO :NEW.ID_pouzivatela + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER titul_bir +BEFORE INSERT ON Titul +FOR EACH ROW +BEGIN + IF :NEW.ID_titulu IS NULL THEN + SELECT titul_seq.NEXTVAL + INTO :NEW.ID_titulu + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER exemplar_bir +BEFORE INSERT ON Exemplar +FOR EACH ROW +BEGIN + IF :NEW.ID_exemplaru IS NULL THEN + SELECT exemplar_seq.NEXTVAL + INTO :NEW.ID_exemplaru + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER rezervacia_bir +BEFORE INSERT ON Rezervacia +FOR EACH ROW +BEGIN + IF :NEW.ID_rezervacie IS NULL THEN + SELECT rezervacia_seq.NEXTVAL + INTO :NEW.ID_rezervacie + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER vypozicka_bir +BEFORE INSERT ON Vypozicka +FOR EACH ROW +BEGIN + IF :NEW.ID_vypozicky IS NULL THEN + SELECT vypozicka_seq.NEXTVAL + INTO :NEW.ID_vypozicky + FROM dual; + END IF; +END; +/ + +CREATE OR REPLACE TRIGGER recenzia_bir +BEFORE INSERT ON Recenzia +FOR EACH ROW +BEGIN + IF :NEW.ID_recenzie IS NULL THEN + SELECT recenzia_seq.NEXTVAL + INTO :NEW.ID_recenzie + FROM dual; + END IF; +END; +/ + +-- Insert sample data +-- Insert Users +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Ján', 'Novák', 'jan.novak@example.com', '+421901234567', 'Bratislavská 123, Bratislava', TO_DATE('2022-01-15', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Anna', 'Králová', 'anna.kralova@example.com', '+421902345678', 'Košická 456, Košice', TO_DATE('2022-02-20', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Peter', 'Malý', 'peter.maly@example.com', '+421903456789', 'Hlavná 789, Žilina', TO_DATE('2022-03-10', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Eva', 'Veľká', 'eva.velka@example.com', '+421904567890', 'Námestie SNP 10, Banská Bystrica', TO_DATE('2022-04-05', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Milan', 'Kovář', 'milan.kovar@example.com', '+421905678901', 'Moyzesova 321, Nitra', TO_DATE('2022-05-12', 'YYYY-MM-DD')); + +-- Insert Readers +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (1, 'CIT-001', TO_DATE('2025-01-15', 'YYYY-MM-DD'), 'Aktívny', 0); + +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (2, 'CIT-002', TO_DATE('2025-02-20', 'YYYY-MM-DD'), 'Aktívny', 0); + +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (3, 'CIT-003', TO_DATE('2025-03-10', 'YYYY-MM-DD'), 'Pozastavený', 0); + +-- Insert Employees +INSERT INTO Zamestnanec (ID_pouzivatela, Osobne_cislo, Datum_nastupu, Oddelenie, Titul) +VALUES (4, 'ZAM-001', TO_DATE('2020-04-05', 'YYYY-MM-DD'), 'Katalogizácia', 'Mgr.'); + +INSERT INTO Zamestnanec (ID_pouzivatela, Osobne_cislo, Datum_nastupu, Oddelenie, Titul) +VALUES (5, 'ZAM-002', TO_DATE('2021-05-12', 'YYYY-MM-DD'), 'Výpožičky', 'Ing.'); + +-- Insert Titles +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Pán Prsteňov: Spoločenstvo prsteňa', 'Slovart', 2001, 'Prvá časť fantasy trilógie od J.R.R. Tolkiena', 'Fantasy', 2); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Harry Potter a Kameň mudrcov', 'Ikar', 2000, 'Prvá kniha zo série o mladom čarodejníkovi', 'Fantasy', 1); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('National Geographic', 'National Geographic Society', 2023, 'Populárno-náučný časopis', 'Veda', 1); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Forbes', 'Forbes Media', 2023, 'Ekonomický časopis', 'Biznis', 1); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('1984', 'Slovart', 2015, 'Dystopický román od George Orwella', 'Sci-fi', 1); + +-- Insert Books +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (1, '9788055603261', 'J.R.R. Tolkien', 432, 'Fantasy'); + +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (2, '9788055159423', 'J.K. Rowling', 320, 'Fantasy'); + +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (5, '9788055138887', 'George Orwell', 288, 'Sci-fi'); + +-- Insert Magazines +INSERT INTO Casopis (ID_titulu, ISSN, Rocnik, Cislo, Periodicita) +VALUES (3, '0027-9358', 2023, 3, 'Mesačník'); + +INSERT INTO Casopis (ID_titulu, ISSN, Rocnik, Cislo, Periodicita) +VALUES (4, '0015-6914', 2023, 4, 'Mesačník'); + +-- Insert Copies +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (1, TO_DATE('2022-01-10', 'YYYY-MM-DD'), 'Regál A, Polica 1', 'F-TOL-001', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (1, TO_DATE('2022-01-10', 'YYYY-MM-DD'), 'Regál A, Polica 1', 'F-TOL-002', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (2, TO_DATE('2022-02-15', 'YYYY-MM-DD'), 'Regál A, Polica 2', 'F-ROW-001', 'Vypožičaný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (3, TO_DATE('2023-03-01', 'YYYY-MM-DD'), 'Regál B, Polica 1', 'C-NAT-001', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (4, TO_DATE('2023-04-05', 'YYYY-MM-DD'), 'Regál B, Polica 2', 'C-FOR-001', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (5, TO_DATE('2022-06-10', 'YYYY-MM-DD'), 'Regál C, Polica 1', 'S-ORW-001', 'Vypožičaný'); + +-- Insert Reservations +INSERT INTO Rezervacia (ID_pouzivatela, ID_titulu, Datum_rezervacie, Datum_expiracie, Stav) +VALUES (1, 2, TO_DATE('2023-04-10', 'YYYY-MM-DD'), TO_DATE('2023-04-17', 'YYYY-MM-DD'), 'Aktívna'); + +INSERT INTO Rezervacia (ID_pouzivatela, ID_titulu, Datum_rezervacie, Datum_expiracie, Stav) +VALUES (2, 5, TO_DATE('2023-04-12', 'YYYY-MM-DD'), TO_DATE('2023-04-19', 'YYYY-MM-DD'), 'Vybavená'); + +-- Insert Loans +INSERT INTO Vypozicka (ID_pouzivatela, ID_exemplaru, Datum_vypozicania, Planovany_datum_vratenia, Skutocny_datum_vratenia, Stav) +VALUES (1, 3, TO_DATE('2023-04-10', 'YYYY-MM-DD'), TO_DATE('2023-05-10', 'YYYY-MM-DD'), NULL, 'Aktívna'); + +INSERT INTO Vypozicka (ID_pouzivatela, ID_exemplaru, Datum_vypozicania, Planovany_datum_vratenia, Skutocny_datum_vratenia, Stav) +VALUES (2, 6, TO_DATE('2023-04-12', 'YYYY-MM-DD'), TO_DATE('2023-05-12', 'YYYY-MM-DD'), TO_DATE('2023-04-30', 'YYYY-MM-DD'), 'Vrátená'); + +-- Insert Reviews +INSERT INTO Recenzia (ID_pouzivatela, ID_titulu, Hodnotenie, Sprava, Datum) +VALUES (1, 1, 5, 'Vynikajúca kniha, jedno z najlepších fantasy diel všetkých čias.', TO_DATE('2023-03-15', 'YYYY-MM-DD')); + +INSERT INTO Recenzia (ID_pouzivatela, ID_titulu, Hodnotenie, Sprava, Datum) +VALUES (2, 2, 4, 'Skvelá kniha pre mladých čitateľov, fascinujúci magický svet.', TO_DATE('2023-03-20', 'YYYY-MM-DD')); + +INSERT INTO Recenzia (ID_pouzivatela, ID_titulu, Hodnotenie, Sprava, Datum) +VALUES (3, 5, 5, 'Nadčasový dystopický román, stále aktuálny aj dnes.', TO_DATE('2023-03-25', 'YYYY-MM-DD')); + +-- Extra data for better testing +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Lucia', 'Horváthová', 'lucia.horvathova@example.com', '+421906789012', 'Dlhá 5, Trnava', TO_DATE('2022-06-01', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Martin', 'Šimek', 'martin.simek@example.com', '+421907890123', 'Jarná 22, Prešov', TO_DATE('2022-07-10', 'YYYY-MM-DD')); + +INSERT INTO Pouzivatel (Meno, Priezvisko, Email, Telefon, Adresa, Datum_registracie) +VALUES ('Barbora', 'Petrová', 'barbora.petrova@example.com', '+421908901234', 'Letná 7, Poprad', TO_DATE('2022-08-18', 'YYYY-MM-DD')); + +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (6, 'CIT-004', TO_DATE('2025-06-01', 'YYYY-MM-DD'), 'Aktívny', 1); + +INSERT INTO Citatel (ID_pouzivatela, Cislo_preukazu, Platnost_do, Status, Pocet_vypoziciek) +VALUES (7, 'CIT-005', TO_DATE('2025-07-10', 'YYYY-MM-DD'), 'Pozastavený', 0); + +INSERT INTO Zamestnanec (ID_pouzivatela, Osobne_cislo, Datum_nastupu, Oddelenie, Titul) +VALUES (8, 'ZAM-003', TO_DATE('2021-08-18', 'YYYY-MM-DD'), 'Oddelenie vývoja databáz', 'PhDr.'); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Bratstvo čiernej dýky', 'Ikar', 2012, 'Moderný mestský fantasy román s upírskou tematikou', 'Fantasy', 1); + +INSERT INTO Titul (Nazov, Vydavatelstvo, Rok_vydania, Popis, Kategoria, Pocet_exemplarov) +VALUES ('Sapiens: Stručná história ľudstva', 'Tatran', 2018, 'Fascinujúci pohľad na vývoj ľudskej civilizácie', 'História', 1); + +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (6, '9788055163223', 'J.R. Ward', 400, 'Fantasy'); + +INSERT INTO Kniha (ID_titulu, ISBN, Autor, Pocet_stran, Zaner) +VALUES (7, '9788022209223', 'Yuval Noah Harari', 448, 'História'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (6, TO_DATE('2022-09-01', 'YYYY-MM-DD'), 'Regál D, Polica 1', 'F-WAR-001', 'Dostupný'); + +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (7, TO_DATE('2022-10-01', 'YYYY-MM-DD'), 'Regál E, Polica 3', 'H-HAR-001', 'Vypožičaný'); + +INSERT INTO Rezervacia (ID_pouzivatela, ID_titulu, Datum_rezervacie, Datum_expiracie, Stav) +VALUES (6, 6, TO_DATE('2023-06-05', 'YYYY-MM-DD'), TO_DATE('2023-06-12', 'YYYY-MM-DD'), 'Aktívna'); + +INSERT INTO Vypozicka (ID_pouzivatela, ID_exemplaru, Datum_vypozicania, Planovany_datum_vratenia, Skutocny_datum_vratenia, Stav) +VALUES (6, 8, TO_DATE('2023-06-06', 'YYYY-MM-DD'), TO_DATE('2023-07-06', 'YYYY-MM-DD'), NULL, 'Aktívna'); + +INSERT INTO Recenzia (ID_pouzivatela, ID_titulu, Hodnotenie, Sprava, Datum) +VALUES (6, 7, 5, 'Skvelo napísané a veľmi poučné. Harari píše pútavo.', TO_DATE('2023-06-10', 'YYYY-MM-DD')); + +--Selects +-- Show information about employees +SELECT p.meno || ' ' || p.priezvisko AS zamestnanec, p.ID_pouzivatela ,p.Telefon, p.Email, p.Adresa +FROM Zamestnanec z +JOIN Pouzivatel p ON z.ID_pouzivatela = p.ID_pouzivatela; + +-- Show information about reservations +SELECT p.meno || ' ' || p.priezvisko AS citatel, r.ID_titulu, r.Datum_expiracie, r.Datum_rezervacie, r.Stav +FROM Rezervacia r +JOIN Pouzivatel p ON p.ID_pouzivatela = r.ID_pouzivatela; + +-- Show reviews +SELECT p.meno || ' ' || p.priezvisko AS recenzent, t.Nazov, r.Hodnotenie, r.Sprava +FROM Recenzia r +JOIN Titul t ON r.ID_titulu = t.ID_titulu +JOIN Pouzivatel p ON r.ID_pouzivatela = p.ID_pouzivatela ; + +-- Show available titles and their count +SELECT + t.Nazov, + COUNT(e.ID_exemplaru) AS Pocet_dostupnych +FROM Titul t +JOIN Exemplar e ON t.ID_titulu = e.ID_titulu +WHERE e.Status = 'Dostupný' +GROUP BY t.Nazov; + +-- Show active borrowings +SELECT + p.Meno || ' ' || p.Priezvisko AS Citatel, + t.Nazov AS Kniha, + v.Datum_vypozicania, + v.Planovany_datum_vratenia +FROM Vypozicka v +JOIN Pouzivatel p ON v.ID_pouzivatela = p.ID_pouzivatela +JOIN Exemplar e ON v.ID_exemplaru = e.ID_exemplaru +JOIN Titul t ON e.ID_titulu = t.ID_titulu +WHERE v.Stav = 'Aktívna'; + +-- Show all names with their role +SELECT + p.ID_pouzivatela, + p.Meno, + p.Priezvisko, + CASE + WHEN EXISTS (SELECT 1 FROM Citatel c WHERE c.ID_pouzivatela = p.ID_pouzivatela) THEN 'Citatel' + WHEN EXISTS (SELECT 1 FROM Zamestnanec z WHERE z.ID_pouzivatela = p.ID_pouzivatela) THEN 'Zamestnanec' + ELSE 'Neznámy' + END AS Typ_pouzivatela +FROM Pouzivatel p; + +-- Show which books wasnt returned +SELECT p.Meno || ' ' || p.Priezvisko AS citatel +FROM Pouzivatel p +WHERE EXISTS ( + SELECT 1 + FROM Vypozicka v + WHERE v.ID_pouzivatela = p.ID_pouzivatela + AND v.Skutocny_datum_vratenia IS NULL +); + +-- Show titles based on genre +SELECT + Nazov, + Kategoria, + Pocet_exemplarov +FROM Titul +WHERE Kategoria = 'Fantasy'; + +-- Show how many borrows and reservations reader made. +SELECT p.Meno || ' ' || p.Priezvisko AS Citatel, c.ID_pouzivatela, v.Stav, COUNT(DISTINCT v.ID_vypozicky) AS pocet_vypoziciek, COUNT(DISTINCT r.ID_rezervacie) AS pocet_rezervaci +FROM Citatel c +JOIN Vypozicka v ON c.ID_pouzivatela = v.ID_pouzivatela +JOIN Pouzivatel p ON c.ID_pouzivatela = p.ID_pouzivatela +JOIN Rezervacia r ON p.ID_pouzivatela = r.ID_pouzivatela +GROUP BY p.Meno, p.Priezvisko, c.ID_pouzivatela, v.Stav; + +-- Show only reviewed titles +SELECT nazov +FROM Titul +WHERE id_titulu IN ( + SELECT id_titulu + FROM Recenzia +); + +COMMIT; + +-- PART 4 +-- *** 1. DATABASE TRIGGERS *** + +-- Trigger 1: Update loan count +CREATE OR REPLACE TRIGGER trigger_pocet_vypoziciek +AFTER INSERT ON Vypozicka +FOR EACH ROW +BEGIN + UPDATE Citatel + SET Pocet_vypoziciek = Pocet_vypoziciek + 1 + WHERE ID_pouzivatela = :NEW.ID_pouzivatela; +END; +/ + +-- Trigger 2: Check if max limit for loans wasnt reached +CREATE OR REPLACE TRIGGER trigger_maximalny_pocet_vypoziciek +BEFORE INSERT ON Vypozicka +FOR EACH ROW +DECLARE + v_pocet NUMBER; +BEGIN + SELECT Pocet_vypoziciek INTO v_pocet + FROM Citatel + WHERE ID_pouzivatela = :NEW.ID_pouzivatela + AND Status = 'Aktívny'; + + IF v_pocet >= 4 THEN + RAISE_APPLICATION_ERROR(-20001, 'Citatel uz ma 4 aktivnych vypoziciek.'); + END IF; +END; +/ + +-- Trigger 3: Update exemplar count in Titul table when a new exemplar is added or removed +CREATE OR REPLACE TRIGGER trigger_pocet_exemplarov +AFTER INSERT OR DELETE OR UPDATE OF ID_titulu ON Exemplar +FOR EACH ROW +BEGIN + -- When a new copy is added + IF INSERTING THEN + UPDATE Titul + SET Pocet_exemplarov = Pocet_exemplarov + 1 + WHERE ID_titulu = :NEW.ID_titulu; + -- When a copy is deleted + ELSIF DELETING THEN + UPDATE Titul + SET Pocet_exemplarov = Pocet_exemplarov - 1 + WHERE ID_titulu = :OLD.ID_titulu; + -- When a copy's title is changed + ELSIF UPDATING THEN + -- Decrement count for old title + UPDATE Titul + SET Pocet_exemplarov = Pocet_exemplarov - 1 + WHERE ID_titulu = :OLD.ID_titulu; + + -- Increment count for new title + UPDATE Titul + SET Pocet_exemplarov = Pocet_exemplarov + 1 + WHERE ID_titulu = :NEW.ID_titulu; + END IF; +END; +/ + +-- Trigger 4: Update loan status to "Oneskorená" when return date passes +CREATE OR REPLACE TRIGGER trigger_aktualizuj_stav_vypozicky +BEFORE UPDATE OR INSERT ON Vypozicka +FOR EACH ROW +BEGIN + -- If loan is active and planned return date has passed + IF (:NEW.Stav = 'Aktívna' AND :NEW.Planovany_datum_vratenia < SYSDATE) THEN + :NEW.Stav := 'Oneskorená'; + END IF; +END; +/ + +-- Procedure to manually check and update overdue loans +CREATE OR REPLACE PROCEDURE aktualizuj_oneskorene_vypozicky +AS + v_count NUMBER; +BEGIN + UPDATE Vypozicka + SET Stav = 'Oneskorená' + WHERE Stav = 'Aktívna' + AND Planovany_datum_vratenia < SYSDATE; + + v_count := SQL%ROWCOUNT; + + COMMIT; + DBMS_OUTPUT.PUT_LINE('Aktualizácia oneskorených výpožičiek dokončená. Počet aktualizovaných záznamov: ' || v_count); +EXCEPTION + WHEN OTHERS THEN + ROLLBACK; + DBMS_OUTPUT.PUT_LINE('Chyba pri aktualizácii oneskorených výpožičiek: ' || SQLERRM); +END; +/ + +-- *** 2. STORED PROCEDURES *** + +-- Procedure 1: Process a reservation +CREATE OR REPLACE PROCEDURE spracuj_rezervaciu ( + p_id_rezervacie IN NUMBER, + p_days_to_return IN NUMBER DEFAULT 30 +) +AS + v_rezervacia Rezervacia%ROWTYPE; + v_exemplar_id NUMBER; + v_user_id NUMBER; + v_title_id NUMBER; + v_today DATE := SYSDATE; + + -- Custom exceptions + e_rezervacia_not_found EXCEPTION; + e_rezervacia_not_active EXCEPTION; + e_no_copy_available EXCEPTION; + +BEGIN + -- Get reservation details + BEGIN + SELECT * INTO v_rezervacia + FROM Rezervacia + WHERE ID_rezervacie = p_id_rezervacie; + EXCEPTION + WHEN NO_DATA_FOUND THEN + RAISE e_rezervacia_not_found; + END; + + -- Check if reservation is active + IF v_rezervacia.Stav != 'Aktívna' THEN + RAISE e_rezervacia_not_active; + END IF; + + v_user_id := v_rezervacia.ID_pouzivatela; + v_title_id := v_rezervacia.ID_titulu; + + -- Find available copy + BEGIN + SELECT ID_exemplaru INTO v_exemplar_id + FROM Exemplar + WHERE ID_titulu = v_title_id + AND Status = 'Dostupný' + AND ROWNUM = 1; + EXCEPTION + WHEN NO_DATA_FOUND THEN + RAISE e_no_copy_available; + END; + + -- Start transaction + SAVEPOINT start_transaction; + + BEGIN + -- Create loan + INSERT INTO Vypozicka ( + ID_pouzivatela, + ID_exemplaru, + Datum_vypozicania, + Planovany_datum_vratenia, + Stav + ) VALUES ( + v_user_id, + v_exemplar_id, + v_today, + v_today + p_days_to_return, + 'Aktívna' + ); + + -- Update copy status + UPDATE Exemplar + SET Status = 'Vypožičaný' + WHERE ID_exemplaru = v_exemplar_id; + + -- Update reservation status + UPDATE Rezervacia + SET Stav = 'Vybavená' + WHERE ID_rezervacie = p_id_rezervacie; + + COMMIT; + DBMS_OUTPUT.PUT_LINE('Rezervácia úspešne spracovaná. Vytvorená výpožička pre používateľa ID: ' || v_user_id); + + EXCEPTION + WHEN OTHERS THEN + ROLLBACK TO start_transaction; + DBMS_OUTPUT.PUT_LINE('Chyba pri spracovaní rezervácie: ' || SQLERRM); + RAISE; + END; + +EXCEPTION + WHEN e_rezervacia_not_found THEN + DBMS_OUTPUT.PUT_LINE('Rezervácia s ID ' || p_id_rezervacie || ' nebola nájdená.'); + WHEN e_rezervacia_not_active THEN + DBMS_OUTPUT.PUT_LINE('Rezervácia s ID ' || p_id_rezervacie || ' nie je aktívna.'); + WHEN e_no_copy_available THEN + DBMS_OUTPUT.PUT_LINE('Pre titul s ID ' || v_title_id || ' nie je dostupný žiadny exemplár.'); + WHEN OTHERS THEN + DBMS_OUTPUT.PUT_LINE('Neočakávaná chyba: ' || SQLERRM); +END; +/ + +-- Procedure 2: Generate overdue loans report with cursor +CREATE OR REPLACE PROCEDURE generuj_report_oneskorene ( + p_datum IN DATE DEFAULT SYSDATE +) +AS + -- Cursor declaration for overdue loans + CURSOR c_oneskorene IS + SELECT + v.ID_vypozicky, + v.Datum_vypozicania, + v.Planovany_datum_vratenia, + p.ID_pouzivatela, + p.Meno, + p.Priezvisko, + t.ID_titulu, + t.Nazov, + ROUND(p_datum - v.Planovany_datum_vratenia) AS dni_po_termine + FROM Vypozicka v + JOIN Pouzivatel p ON v.ID_pouzivatela = p.ID_pouzivatela + JOIN Exemplar e ON v.ID_exemplaru = e.ID_exemplaru + JOIN Titul t ON e.ID_titulu = t.ID_titulu + WHERE v.Stav IN ('Aktívna', 'Oneskorená') + AND v.Planovany_datum_vratenia < p_datum + ORDER BY dni_po_termine DESC; + + -- Variables + v_record c_oneskorene%ROWTYPE; + v_count NUMBER := 0; + +BEGIN + DBMS_OUTPUT.PUT_LINE('=== REPORT ONESKORENÝCH VÝPOŽIČIEK K DÁTUMU ' || TO_CHAR(p_datum, 'DD.MM.YYYY') || ' ==='); + DBMS_OUTPUT.PUT_LINE('--------------------------------------------------------------------------------'); + DBMS_OUTPUT.PUT_LINE('ID | POUŽÍVATEĽ | TITUL | DÁTUM VRÁTENIA | DNI PO TERMÍNE'); + DBMS_OUTPUT.PUT_LINE('--------------------------------------------------------------------------------'); + + -- Process cursor data + OPEN c_oneskorene; + LOOP + FETCH c_oneskorene INTO v_record; + EXIT WHEN c_oneskorene%NOTFOUND; + + v_count := v_count + 1; + DBMS_OUTPUT.PUT_LINE( + RPAD(v_record.ID_vypozicky, 3) || ' | ' || + RPAD(v_record.Meno || ' ' || v_record.Priezvisko, 19) || ' | ' || + RPAD(v_record.Nazov, 28) || ' | ' || + RPAD(TO_CHAR(v_record.Planovany_datum_vratenia, 'DD.MM.YYYY'), 14) || ' | ' || + LPAD(v_record.dni_po_termine, 13) + ); + END LOOP; + CLOSE c_oneskorene; + + IF v_count = 0 THEN + DBMS_OUTPUT.PUT_LINE('Žiadne oneskorené výpožičky.'); + ELSE + DBMS_OUTPUT.PUT_LINE('--------------------------------------------------------------------------------'); + DBMS_OUTPUT.PUT_LINE('CELKOM ONESKORENÝCH VÝPOŽIČIEK: ' || v_count); + END IF; + +EXCEPTION + WHEN OTHERS THEN + IF c_oneskorene%ISOPEN THEN + CLOSE c_oneskorene; + END IF; + DBMS_OUTPUT.PUT_LINE('Chyba pri generovaní reportu: ' || SQLERRM); +END; +/ + +-- *** 3. INDEXES AND EXPLAIN PLAN *** + +-- Complex query for loan statistics that will benefit from indexing +EXPLAIN PLAN FOR +SELECT + p.ID_pouzivatela, + p.Meno || ' ' || p.Priezvisko AS Pouzivatel, + COUNT(v.ID_vypozicky) AS Pocet_vypoziciek, + ROUND(AVG(NVL(v.Skutocny_datum_vratenia, SYSDATE) - v.Datum_vypozicania)) AS Priemerna_dlzka_vypozicky, + COUNT(CASE WHEN v.Stav = 'Aktívna' THEN 1 END) AS Aktivne_vypozicky, + COUNT(CASE WHEN v.Stav = 'Oneskorená' THEN 1 END) AS Oneskorene_vypozicky +FROM Pouzivatel p +JOIN Vypozicka v ON p.ID_pouzivatela = v.ID_pouzivatela +JOIN Exemplar e ON v.ID_exemplaru = e.ID_exemplaru +WHERE v.Datum_vypozicania > ADD_MONTHS(SYSDATE, -12) +GROUP BY p.ID_pouzivatela, p.Meno, p.Priezvisko +HAVING COUNT(v.ID_vypozicky) > 0; + +-- Display the execution plan before creating the index +SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY); + +-- Create indexes to optimize the query +CREATE INDEX idx_vypozicka_pouzivatela ON Vypozicka(ID_pouzivatela); +CREATE INDEX idx_vypozicka_datum ON Vypozicka(Datum_vypozicania); +CREATE INDEX idx_vypozicka_stav ON Vypozicka(Stav); + +-- Run EXPLAIN PLAN again to see the improvement +EXPLAIN PLAN FOR +SELECT + p.ID_pouzivatela, + p.Meno || ' ' || p.Priezvisko AS Pouzivatel, + COUNT(v.ID_vypozicky) AS Pocet_vypoziciek, + ROUND(AVG(NVL(v.Skutocny_datum_vratenia, SYSDATE) - v.Datum_vypozicania)) AS Priemerna_dlzka_vypozicky, + COUNT(CASE WHEN v.Stav = 'Aktívna' THEN 1 END) AS Aktivne_vypozicky, + COUNT(CASE WHEN v.Stav = 'Oneskorená' THEN 1 END) AS Oneskorene_vypozicky +FROM Pouzivatel p +JOIN Vypozicka v ON p.ID_pouzivatela = v.ID_pouzivatela +JOIN Exemplar e ON v.ID_exemplaru = e.ID_exemplaru +WHERE v.Datum_vypozicania > ADD_MONTHS(SYSDATE, -12) +GROUP BY p.ID_pouzivatela, p.Meno, p.Priezvisko +HAVING COUNT(v.ID_vypozicky) > 0; + +-- Display the execution plan after creating the index +SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY); + +-- *** 4. ACCESS RIGHTS *** + +GRANT SELECT ON Pouzivatel TO xpribik00; +GRANT SELECT ON Citatel TO xpribik00; +GRANT SELECT ON Zamestnanec TO xpribik00; +GRANT SELECT ON Titul TO xpribik00; +GRANT SELECT ON Kniha TO xpribik00; +GRANT SELECT ON Casopis TO xpribik00; +GRANT SELECT ON Exemplar TO xpribik00; +GRANT SELECT, INSERT, UPDATE ON Rezervacia TO xpribik00; +GRANT SELECT, INSERT, UPDATE ON Vypozicka TO xpribik00; +GRANT SELECT, INSERT, UPDATE ON Recenzia TO xpribik00; + +-- Grant execute privileges on procedures +GRANT EXECUTE ON spracuj_rezervaciu TO xpribik00; +GRANT EXECUTE ON generuj_report_oneskorene TO xpribik00; +GRANT EXECUTE ON aktualizuj_oneskorene_vypozicky TO xpribik00; + +-- *** 6. COMPLEX QUERY WITH WITH CLAUSE AND CASE *** + +-- Complex query using WITH clause and CASE operator to categorize readers +WITH + -- Subquery 1: Calculate loan statistics for users + user_stats AS ( + SELECT + p.ID_pouzivatela, + p.Meno || ' ' || p.Priezvisko AS Pouzivatel, + COUNT(v.ID_vypozicky) AS Pocet_vypoziciek, + COUNT(CASE WHEN v.Stav = 'Oneskorená' THEN 1 END) AS Pocet_oneskoreni, + ROUND(AVG(NVL(v.Skutocny_datum_vratenia, SYSDATE) - v.Datum_vypozicania)) AS Priemerne_dni + FROM Pouzivatel p + LEFT JOIN Vypozicka v ON p.ID_pouzivatela = v.ID_pouzivatela + JOIN Citatel c ON p.ID_pouzivatela = c.ID_pouzivatela + GROUP BY p.ID_pouzivatela, p.Meno, p.Priezvisko + ), + -- Subquery 2: Calculate preferred genres for users + user_genres AS ( + SELECT + v.ID_pouzivatela, + t.Kategoria, + COUNT(*) AS Pocet_vypoziciek_kategorie, + RANK() OVER (PARTITION BY v.ID_pouzivatela ORDER BY COUNT(*) DESC) AS Poradia + FROM Vypozicka v + JOIN Exemplar e ON v.ID_exemplaru = e.ID_exemplaru + JOIN Titul t ON e.ID_titulu = t.ID_titulu + GROUP BY v.ID_pouzivatela, t.Kategoria + ) +-- Main query combining the CTE results with categorization using CASE +SELECT + us.Pouzivatel, + us.Pocet_vypoziciek, + CASE + WHEN us.Pocet_vypoziciek = 0 THEN 'Neaktívny čitateľ' + WHEN us.Pocet_vypoziciek BETWEEN 1 AND 3 THEN 'Príležitostný čitateľ' + WHEN us.Pocet_vypoziciek BETWEEN 4 AND 10 THEN 'Aktívny čitateľ' + ELSE 'Náruživý čitateľ' + END AS Kategoria_citatela, + CASE + WHEN us.Pocet_oneskoreni = 0 THEN 'Vzorný' + WHEN us.Pocet_oneskoreni = 1 THEN 'Občas mešká' + WHEN us.Pocet_oneskoreni BETWEEN 2 AND 3 THEN 'Často mešká' + ELSE 'Chronicky mešká' + END AS Spolahlivost, + us.Priemerne_dni AS Priemerna_doba_vypozicky, + ug.Kategoria AS Preferovana_kategoria +FROM user_stats us +LEFT JOIN user_genres ug ON us.ID_pouzivatela = ug.ID_pouzivatela AND ug.Poradia = 1 +ORDER BY us.Pocet_vypoziciek DESC, us.Pouzivatel; + +-- *** 7. DEMONSTRATION OF FUNCTIONALITY *** + +-- Demonstration of Trigger 1: Update loan count for reader (trigger_pocet_vypoziciek) +-- First, check the current loan count for a reader +SELECT c.ID_pouzivatela, p.Meno, p.Priezvisko, c.Pocet_vypoziciek FROM Citatel c JOIN Pouzivatel p ON c.ID_pouzivatela = p.ID_pouzivatela WHERE c.ID_pouzivatela = 1; + +-- Insert a new loan for the reader +INSERT INTO Vypozicka (ID_pouzivatela, ID_exemplaru, Datum_vypozicania, Planovany_datum_vratenia, Stav) +VALUES (1, 5, SYSDATE, SYSDATE + 30, 'Aktívna'); + +-- Check if the loan count was automatically updated by the trigger +SELECT c.ID_pouzivatela, p.Meno, p.Priezvisko, c.Pocet_vypoziciek FROM Citatel c JOIN Pouzivatel p ON c.ID_pouzivatela = p.ID_pouzivatela WHERE c.ID_pouzivatela = 1; + +-- Demonstration of Trigger 2: Check maximum loan limit (trigger_maximalny_pocet_vypoziciek) +-- For demonstration purposes, we update the count directly +UPDATE Citatel SET Pocet_vypoziciek = 4 WHERE ID_pouzivatela = 2; +BEGIN + DBMS_OUTPUT.PUT_LINE('Pokus o vytvorenie piatej výpožičky pre čitateľa s ID 3:'); + + INSERT INTO Vypozicka (ID_pouzivatela, ID_exemplaru, Datum_vypozicania, Planovany_datum_vratenia, Stav) + VALUES (2, 4, SYSDATE, SYSDATE + 30, 'Aktívna'); + +EXCEPTION + WHEN OTHERS THEN + DBMS_OUTPUT.PUT_LINE('Chyba: ' || SQLERRM); +END; +/ + +-- Demonstration of Trigger 3: Update copy count +SELECT t.ID_titulu, t.Nazov, t.Pocet_exemplarov FROM Titul t WHERE t.ID_titulu = 1; + +-- Insert a new copy +INSERT INTO Exemplar (ID_titulu, Datum_nadobudnutia, Umiestnenie, Signatura, Status) +VALUES (1, SYSDATE, 'Regál A, Polica 1', 'F-TOL-003', 'Dostupný'); + +-- Check if the count was updated +SELECT t.ID_titulu, t.Nazov, t.Pocet_exemplarov FROM Titul t WHERE t.ID_titulu = 1; + +-- Demonstration of Trigger 4: Update loan status to "Oneskorená" +INSERT INTO Vypozicka (ID_pouzivatela, ID_exemplaru, Datum_vypozicania, Planovany_datum_vratenia, Stav) +VALUES (1, 1, SYSDATE, SYSDATE - 5, 'Aktívna'); -- Intentionally setting a past date + +-- Check if the loan status was updated automatically to 'Oneskorená' +SELECT ID_vypozicky, Stav FROM Vypozicka WHERE ID_exemplaru = 1 AND ID_pouzivatela = 1; + +-- Run the procedure to update any other overdue loans +BEGIN + aktualizuj_oneskorene_vypozicky; +END; +/ + +-- Demonstration of Procedure 1: Process a reservation +-- First, create a new reservation +INSERT INTO Rezervacia (ID_pouzivatela, ID_titulu, Datum_rezervacie, Datum_expiracie, Stav) +VALUES (1, 3, SYSDATE, SYSDATE + 7, 'Aktívna'); + +-- Get the ID of the inserted reservation and process it +DECLARE + v_id NUMBER; +BEGIN + SELECT MAX(ID_rezervacie) INTO v_id FROM Rezervacia WHERE ID_pouzivatela = 1 AND ID_titulu = 3; + -- Process the reservation + spracuj_rezervaciu(v_id); +END; +/ + +-- Demonstration of Procedure 2: Generate overdue loans report +BEGIN + generuj_report_oneskorene(SYSDATE); +END; +/ + +-- Demonstration of Materialized View +SELECT * FROM xpribik00.mv_aktivita_citatelov WHERE ID_pouzivatela = 1; + +-- Make changes that affect the view +UPDATE Vypozicka SET Stav = 'Vrátená', Skutocny_datum_vratenia = SYSDATE WHERE ID_vypozicky = + (SELECT MIN(ID_vypozicky) FROM Vypozicka WHERE ID_pouzivatela = 1 AND Stav = 'Aktívna'); + +-- View now shows updated data (after it's refreshed by xpribik00) +SELECT * FROM xpribik00.mv_aktivita_citatelov WHERE ID_pouzivatela = 1; + +COMMIT; \ No newline at end of file diff --git a/2BIT/summer-semester/IDS/xnecasr00_xpribik00/mv.sql b/2BIT/summer-semester/IDS/xnecasr00_xpribik00/mv.sql new file mode 100644 index 0000000..9e0ad50 --- /dev/null +++ b/2BIT/summer-semester/IDS/xnecasr00_xpribik00/mv.sql @@ -0,0 +1,24 @@ +CREATE MATERIALIZED VIEW mv_aktivita_citatelov +AS +SELECT + p.ID_pouzivatela, + p.Meno, + p.Priezvisko, + c.Cislo_preukazu, + c.Status AS Status_citatela, + COUNT(v.ID_vypozicky) AS Celkovy_pocet_vypoziciek, + COUNT(CASE WHEN v.Stav IN ('Aktívna','Oneskorená') THEN 1 END) AS Aktivne_vypozicky, + COUNT(CASE WHEN v.Stav = 'Vrátená' THEN 1 END) AS Ukoncene_vypozicky, + COUNT(CASE WHEN v.Stav = 'Oneskorená' THEN 1 END) AS Oneskorene_vypozicky, + ROUND(AVG(NVL(v.Skutocny_datum_vratenia, SYSDATE) - v.Datum_vypozicania)) AS Priemerna_dlzka_vypozicky, + MAX(v.Datum_vypozicania) AS Posledna_vypozicka +FROM xnecasr00.Pouzivatel p +JOIN xnecasr00.Citatel c ON c.ID_pouzivatela = p.ID_pouzivatela +LEFT JOIN xnecasr00.Vypozicka v ON v.ID_pouzivatela = p.ID_pouzivatela +GROUP BY p.ID_pouzivatela, p.Meno, p.Priezvisko, c.Cislo_preukazu, c.Status; + +GRANT SELECT ON mv_aktivita_citatelov TO xnecasr00; + +BEGIN + DBMS_MVIEW.REFRESH('mv_aktivita_citatelov'); +END; \ No newline at end of file diff --git a/2BIT/summer-semester/IPK1/xnecasr00.zip b/2BIT/summer-semester/IPK1/xnecasr00.zip new file mode 100644 index 0000000..478e9f3 Binary files /dev/null and b/2BIT/summer-semester/IPK1/xnecasr00.zip differ diff --git a/2BIT/summer-semester/IPK2/xnecasr00.zip b/2BIT/summer-semester/IPK2/xnecasr00.zip new file mode 100644 index 0000000..4efcef6 Binary files /dev/null and b/2BIT/summer-semester/IPK2/xnecasr00.zip differ diff --git a/2BIT/summer-semester/IPP1/parse.py b/2BIT/summer-semester/IPP1/parse.py new file mode 100644 index 0000000..4e96d0f --- /dev/null +++ b/2BIT/summer-semester/IPP1/parse.py @@ -0,0 +1,716 @@ +#!/usr/bin/env python3.11 +# author: Roman Necas (xnecasr00) +# date: 26.2.2025 +""" +parse.py - A compact parser and static analyzer for SOL25. + +This script reads SOL25 source code from standard input and performs the following: + • Lexical analysis using Lark (version 1.2.2) + • Syntactic parsing according to the SOL25 grammar to produce a parse tree + • Transformation of the parse tree into an Abstract Syntax Tree (AST) + • Static semantic analysis (e.g., checking for reserved identifiers, undefined classes/variables, + arity mismatches, duplicate definitions, etc.) + • Generation of an XML representation of the AST for further processing + +Exit codes: + 10 - Wrong or extra command-line parameters + 11 - Error opening input + 21 - Lexical error (e.g., illegal escape sequences, newline in string literal) + 22 - Syntactic error or misuse of reserved identifiers + 31 - Missing Main class or parameterless run method + 32 - Use of undefined variable/class/method + 33 - Arity mismatch in method block literal + 34 - Assignment to a formal parameter + 35 - Duplicate formal parameters or class redefinition + 99 - Internal error +""" + +import sys +import re +import xml.etree.ElementTree as ET +import xml.dom.minidom +from lark import Lark, Transformer, UnexpectedToken, UnexpectedCharacters + +# --- Helper: Error Handling --- +def error_exit(code, msg=""): + """ + Print an error message (if provided) to stderr and exit with the specified error code. + Ensures that the message is printed before exiting. + """ + if msg: + sys.stderr.write(msg + "\n") + # Force stderr to flush to ensure the message is displayed + sys.stderr.flush() + + sys.exit(code) + +# --- AST Node Definitions --- +# Each class below represents a node in the AST. + +class Program: + def __init__(self, classes, description=None): + # List of class definitions and an optional description (e.g., from a comment in the source). + self.classes = classes + self.description = description + +class ClassDef: + def __init__(self, name, parent, methods): + # name: Name of the class (string) + # parent: Name of the parent class (string) + # methods: List of method definitions in this class + self.name = name + self.parent = parent + self.methods = methods + +class MethodDef: + def __init__(self, selector, block): + # selector: The method's selector (string) + # block: The block (body) of the method + self.selector = selector + self.block = block + # Calculate expected parameter count based on the selector + self.expected_params = selector.count(':') + + +class Block: + def __init__(self, parameters, assignments): + # parameters: List of parameter names (strings) + # assignments: List of assignment statements (each an Assignment instance) + self.parameters = parameters + self.assignments = assignments + +class Assignment: + def __init__(self, var, expr): + # var: Variable name being assigned to (string) + # expr: Expression that is assigned (an instance of an Expr subclass) + self.var = var + self.expr = expr + +# --- Expression Hierarchy --- +# Base class for all expressions. +class Expr: + pass + +class LiteralExpr(Expr): + def __init__(self, lit_class, value): + # lit_class: The type of literal (e.g., "Integer", "String", "Nil", etc.) + # value: The literal value as a string + self.lit_class = lit_class + self.value = value + +class VarExpr(Expr): + def __init__(self, name): + # name: Variable name (string) + self.name = name + +class BlockExpr(Expr): + def __init__(self, block): + # block: A Block instance representing the block literal + self.block = block + +class MessageSendExpr(Expr): + def __init__(self, receiver, sends): + # receiver: Expression representing the message receiver + # sends: List of tuples (selector, argument) for the message sends + self.receiver = receiver + self.sends = sends + # Attributes for flattened compound sends (if applicable) + self.compound = False + self.compound_selector = "" + self.compound_args = None + +# --- Lark Grammar for SOL25 --- +SOL25_GRAMMAR = r""" + ?start: program + program: (class_def)* + class_def: "class" CLASS_ID ":" CLASS_ID "{" (method_def)* "}" + method_def: selector block_literal + selector: IDENT | send_selector + send_selector: SEND_SELECTOR+ + block_literal: "[" block_params? "|" statement_list "]" + block_params: BLOCK_PARAM+ + statement_list: (assignment_statement)* + assignment_statement: IDENT ":=" expression "." + ?expression: primary (send_part)* + ?primary: literal | IDENT -> var_expr + | CLASS_ID -> class_literal + | block_literal -> block_expr + | "(" expression ")" + send_part: SEND_SELECTOR expression | IDENT + literal: INT -> int_literal + | STRING -> string_literal + CLASS_ID: /[A-Z][A-Za-z0-9]*/ + IDENT: /[a-z_][A-Za-z0-9_]*/ + SEND_SELECTOR: /[a-z_][A-Za-z0-9_]*:/ + INT: /[+-]?[0-9]+/ + STRING: /'(?:[^\r'\\\n]|\\(?!n)(?:'|\\)|\\n|\n)*'/ + COMMENT: /"((?:[^"\\]|\\.)*)"/ + %import common.WS + %ignore WS + %ignore COMMENT + BLOCK_PARAM: /:[a-z_][A-Za-z0-9_]*/ +""" + +# --- Transformer: Converting Parse Tree to AST --- +class SOL25Transformer(Transformer): + def start(self, children): + # Start symbol: return the Program node. + return children[0] + + def program(self, children): + # Create a Program instance with the list of classes. + return Program(children) + + def class_def(self, children): + # The first token is the class name, the second is the parent class, + # and the remaining tokens represent method definitions. + return ClassDef(str(children[0]), str(children[1]), children[2:]) + + def method_def(self, children): + # Create a MethodDef with a selector and a block. + method = MethodDef(children[0], children[1]) + + # Immediate arity check right after creating the method + if method.expected_params != len(method.block.parameters): + error_exit(33, f"Arity mismatch in method {method.selector}: expected {method.expected_params} parameters, got {len(method.block.parameters)}") + + return method + + def selector(self, children): + # Ensure we convert children to strings before concatenation + selector = str(children[0]) if len(children) == 1 else "".join(str(child) for child in children) + + # Check for reserved identifiers used as method selectors (without colons) + if selector in {"self", "super", "nil", "true", "false", "class"} and ":" not in selector: + error_exit(22, f"Reserved identifier used as method selector: {selector}") + + return selector + + def send_selector(self, children): + # For multi-part send selectors, concatenate into one string. + return "".join(str(child) for child in children) + + def block_literal(self, children): + # A block literal consists of an optional parameter list and a statement list. + params = children[0] if len(children) == 2 else [] + stmts = children[-1] + return Block(params, stmts) + + def block_params(self, children): + # Remove the initial ':' from each parameter and check for reserved names. + params = [token.value[1:] for token in children] + for p in params: + if p in {"self", "super", "nil", "true", "false", "class"}: + error_exit(22, f"Reserved identifier used as parameter: {p}") + if len(params) != len(set(params)): + error_exit(35, "Duplicate formal parameters in block literal") + return params + + def statement_list(self, children): + # A list of assignment statements. + return children + + def assignment_statement(self, children): + # Create an assignment node after verifying the variable is not reserved. + var_name = str(children[0]) + if var_name in {"self", "super", "nil", "true", "false", "class"}: + error_exit(22, f"Reserved identifier used in assignment: {var_name}") + return Assignment(var_name, children[1]) + + def expression(self, children): + # If only one element exists, return it; otherwise, create a message send expression. + return children[0] if len(children) == 1 else MessageSendExpr(children[0], children[1:]) + + def int_literal(self, children): + # Create an integer literal expression. + return LiteralExpr("Integer", str(children[0])) + + def string_literal(self, children): + # Process the string literal: unescape and replace newlines as specified. + raw = children[0].value + inner = raw[1:-1] + result, i = "", 0 + while i < len(inner): + if inner[i] == "\\": + if i + 1 >= len(inner): + error_exit(21, "Illegal escape sequence in string literal") + nxt = inner[i+1] + if nxt == "n": + result += "\\n" # Preserve the escape sequence rather than converting to newline + elif nxt == "'": + result += "\\'" + elif nxt == "\\": + result += "\\\\" + else: + error_exit(21, "Illegal escape sequence in string literal") + i += 2 + else: + if inner[i] == "\n": + error_exit(21, "Illegal newline in string literal") + result += inner[i] + i += 1 + return LiteralExpr("String", result) + + def var_expr(self, children): + # Handle variable expressions, with special treatment for nil, true, and false. + ident = str(children[0]) + if ident == "nil": + return LiteralExpr("Nil", "nil") + elif ident == "true": + return LiteralExpr("True", "true") + elif ident == "false": + return LiteralExpr("False", "false") + else: + return VarExpr(ident) + + def class_literal(self, children): + # Create a class literal expression. + return LiteralExpr("class", str(children[0])) + + def block_expr(self, children): + # Create a block expression. + return BlockExpr(children[0]) + + def send_part(self, children): + # A send part may contain a selector and optionally an argument. + sel = str(children[0]) + + # Check if a reserved identifier is used as a selector + if sel in {"self", "super", "nil", "true", "false", "class"} and not sel.endswith(":"): + error_exit(22, f"Reserved identifier used as message selector: {sel}") + + return (sel, children[1]) if len(children) == 2 else (sel, None) + + def literal(self, children): + # Pass through the literal expression. + return children[0] + +# --- Flattening of Compound Message Sends --- +def flatten_message_send(ast): + """ + Recursively flatten compound message sends. + Handles chains such as "compute:" with "and:" sends and "ifTrue:ifFalse:" constructs. + """ + if not isinstance(ast, MessageSendExpr): + return ast + # Recursively flatten the receiver and all arguments. + ast.receiver = flatten_message_send(ast.receiver) + ast.sends = [(sel, flatten_message_send(arg) if arg is not None else None) + for sel, arg in ast.sends] + + # Handle compound "compute:" chain + if len(ast.sends) == 1 and ast.sends[0][0] == "compute:" and isinstance(ast.sends[0][1], MessageSendExpr): + args = [] + current = ast.sends[0][1] + while (isinstance(current, MessageSendExpr) and + len(current.sends) == 1 and current.sends[0][0] == "and:"): + args.append(flatten_message_send(current.receiver)) + current = current.sends[0][1] + args.append(flatten_message_send(current)) + ast.compound = True + ast.compound_selector = "compute:" + "and:" * (len(args) - 1) + ast.compound_args = args + ast.sends = [] + + # Handle compound "ifTrue:ifFalse:" chain + if (len(ast.sends) == 1 and ast.sends[0][0] == "ifTrue:" and + isinstance(ast.sends[0][1], MessageSendExpr)): + inner = ast.sends[0][1] + if (isinstance(inner, MessageSendExpr) and + len(inner.sends) == 1 and inner.sends[0][0] == "ifFalse:" and + isinstance(inner.receiver, BlockExpr) and + isinstance(inner.sends[0][1], BlockExpr)): + ast.compound = True + ast.compound_selector = "ifTrue:ifFalse:" + ast.compound_args = [inner.receiver, inner.sends[0][1]] + ast.sends = [] + return ast + +def flatten(ast): + """ + Recursively traverse the AST and flatten any compound message sends. + """ + if isinstance(ast, Program): + ast.classes = [flatten(c) for c in ast.classes] + elif isinstance(ast, ClassDef): + ast.methods = [flatten(m) for m in ast.methods] + elif isinstance(ast, MethodDef): + ast.block = flatten(ast.block) + elif isinstance(ast, Block): + ast.assignments = [flatten(a) for a in ast.assignments] + elif isinstance(ast, Assignment): + ast.expr = flatten(ast.expr) + elif isinstance(ast, MessageSendExpr): + ast = flatten_message_send(ast) + elif isinstance(ast, BlockExpr): + ast.block = flatten(ast.block) + return ast + +# --- XML Generation --- +def xml_expr(e): + """ + Recursively convert an expression AST node into its corresponding XML element. + """ + if isinstance(e, LiteralExpr): + return ET.Element("literal", {"class": e.lit_class, "value": e.value}) + if isinstance(e, VarExpr): + return ET.Element("var", {"name": e.name}) + if isinstance(e, BlockExpr): + return xml_block(e.block) + if isinstance(e, MessageSendExpr): + if getattr(e, "compound", False): + se = ET.Element("send", {"selector": e.compound_selector}) + relem = ET.Element("expr") + relem.append(xml_expr(e.receiver)) + se.append(relem) + for i, arg in enumerate(e.compound_args, start=1): + aelem = ET.Element("arg", {"order": str(i)}) + ae = ET.Element("expr") + ae.append(xml_expr(arg)) + aelem.append(ae) + se.append(aelem) + return se + else: + full_sel = "".join(sel for sel, _ in e.sends) + se = ET.Element("send", {"selector": full_sel}) + expr_elem = ET.Element("expr") + expr_elem.append(xml_expr(e.receiver)) + se.append(expr_elem) + for i, (sel, arg) in enumerate(e.sends, start=1): + if arg is not None: + aelem = ET.Element("arg", {"order": str(i)}) + ae = ET.Element("expr") + ae.append(xml_expr(arg)) + aelem.append(ae) + se.append(aelem) + return se + # Fallback for unknown expression types. + unk = ET.Element("unknown") + unk.text = str(e) + return unk + +def xml_block(b): + """ + Convert a Block AST node into its corresponding XML element. + Includes parameters and assignment statements. + """ + be = ET.Element("block", {"arity": str(len(b.parameters))}) + for i, p in enumerate(b.parameters, start=1): + ET.SubElement(be, "parameter", {"name": p, "order": str(i)}) + for i, assign in enumerate(b.assignments, start=1): + ae = ET.Element("assign", {"order": str(i)}) + ET.SubElement(ae, "var", {"name": assign.var}) + ex = ET.Element("expr") + ex.append(xml_expr(assign.expr)) + ae.append(ex) + be.append(ae) + return be + +def generate_xml(prog, comment): + """ + Generate the XML representation of the program's AST. + Optionally sets a description attribute using a provided comment. + """ + root = ET.Element("program", {"language": "SOL25"}) + if comment: + # Escape characters for XML attribute compatibility using for newlines + root.set("description", comment.replace("<", "<").replace("\n", " ")) + for cls in prog.classes: + ce = ET.SubElement(root, "class", {"name": cls.name, "parent": cls.parent}) + for m in cls.methods: + me = ET.SubElement(ce, "method", {"selector": m.selector}) + me.append(xml_block(m.block)) + return root + +# --- Static Semantic Analysis --- +def is_valid_integer_instance_method(selector): + """ + Check if a selector is a valid instance method of the Integer class. + """ + # Remove trailing colon if present + base_sel = selector[:-1] if selector.endswith(":") else selector + # Valid methods for Integer instances + valid_methods = { + "equalTo", "greaterThan", "plus", "minus", "multiplyBy", "divBy", + "asString", "asInteger", "timesRepeat" + } + return base_sel in valid_methods + +def is_valid_string_instance_method(selector): + """ + Check if a selector is a valid instance method of the String class. + """ + # Remove trailing colon if present + base_sel = selector[:-1] if selector.endswith(":") else selector + # Valid methods for String instances + valid_methods = { + "print", "equalTo", "asString", "asInteger", "concatenateWith", + "startsWith", "endsBefore" + } + return base_sel in valid_methods + +def is_string_or_subclass(class_name, inheritance_map): + """ + Check if a class is String or inherits from String. + """ + current = class_name + while current != "String" and current in inheritance_map: + current = inheritance_map[current] + return current == "String" + +def detect_circular_inheritance(prog): + """ + Detect circular inheritance in the class hierarchy. + Returns True if circular inheritance is detected, False otherwise. + """ + inheritance_map = {cls.name: cls.parent for cls in prog.classes} + + for class_name in inheritance_map: + visited = set() + current = class_name + + while current in inheritance_map: + if current in visited: + return True # Circular inheritance detected + visited.add(current) + current = inheritance_map[current] + + return False + +# Function removed as we're now doing direct character-by-character counting + +def semantic_check_program(prog): + """ + Perform static semantic analysis on the entire program. + This includes: + - Checking for duplicate class definitions. + - Ensuring that every parent class is defined. + - Validating the arity of method definitions. + - Verifying that reserved identifiers are not misused. + - Confirming the existence of a Main class with a parameterless run method. + """ + seen = set() + for cls in prog.classes: + if cls.name in seen: + error_exit(35, f"Class redefinition: {cls.name}") + seen.add(cls.name) + + # Check for circular inheritance + if detect_circular_inheritance(prog): + error_exit(35, "Circular inheritance detected") + + # Global environment with built-in identifiers and user-defined classes. + builtins = {"Object", "Integer", "String", "Block", "Nil", "True", "False", "nil", "true", "false", "self", "super"} + global_env = {n: False for n in builtins} + for cn in seen: + global_env[cn] = False + + # Build inheritance map for class method checks + inheritance_map = {cls.name: cls.parent for cls in prog.classes} + + # Check for undefined parent classes + for cls in prog.classes: + if cls.parent not in global_env: + error_exit(32, f"Undefined class: {cls.parent}") + + # Check method definitions for other semantic issues + for cls in prog.classes: + for m in cls.methods: + # Main.run special check - must be parameterless + if cls.name == "Main" and m.selector == "run" and len(m.block.parameters) > 0: + error_exit(33, f"Arity mismatch in method run: expected 0 parameters, got {len(m.block.parameters)}") + + # Create a local environment for the method's block. + env = global_env.copy() + env.update({p: True for p in m.block.parameters}) + for pseudo in ["self", "super", "nil", "true", "false"]: + env[pseudo] = False + semantic_check_block(m.block, env, inheritance_map) + + # Check for Main class with run method + if not any(cls.name == "Main" and + any(m.selector == "run" and len(m.block.parameters) == 0 for m in cls.methods) + for cls in prog.classes): + error_exit(31, "Missing Main class or parameterless run method") + +def semantic_check_block(b, env, inheritance_map): + """ + Perform semantic analysis on a block. + Checks each assignment: + - Ensures that formal parameters are not assigned new values. + - Updates the environment with newly defined local variables. + """ + local = dict(env) + for assign in b.assignments: + semantic_check_expr(assign.expr, local, inheritance_map) + if assign.var in local and local[assign.var] is True: + error_exit(34, f"Assignment to a formal parameter: {assign.var}") + local[assign.var] = False + +def semantic_check_expr(e, env, inheritance_map): + """ + Recursively perform semantic checks on an expression. + - Verifies that variables are defined. + - For class literals, ensures the referenced class exists. + - For block expressions, creates a new environment. + - For message sends, checks that selectors do not use reserved identifiers. + """ + if isinstance(e, VarExpr): + if e.name not in env: + error_exit(32, f"Undefined variable: {e.name}") + elif isinstance(e, LiteralExpr) and e.lit_class == "class": + if e.value not in env: + error_exit(32, f"Undefined class: {e.value}") + elif isinstance(e, BlockExpr): + new_env = dict(env) + new_env.update({p: True for p in e.block.parameters}) + semantic_check_block(e.block, new_env, inheritance_map) + elif isinstance(e, MessageSendExpr): + semantic_check_expr(e.receiver, env, inheritance_map) + + # Check if sending to Integer literal + if isinstance(e.receiver, LiteralExpr) and e.receiver.lit_class == "Integer": + for sel, arg in e.sends: + if not is_valid_integer_instance_method(sel): + error_exit(32, f"Undefined method: {sel} for Integer instance") + if arg is not None: + semantic_check_expr(arg, env, inheritance_map) + + # Check class methods validity + elif isinstance(e.receiver, LiteralExpr) and e.receiver.lit_class == "class": + class_name = e.receiver.value + + # Look at all sends in the chain + for i, (sel, arg) in enumerate(e.sends): + base_sel = sel[:-1] if sel.endswith(":") else sel + + # First send can be a class method + if i == 0: + # All classes have new and from: methods + if base_sel == "new" or (base_sel == "from" and sel.endswith(":")): + # Check the argument to from: + if arg is not None: + semantic_check_expr(arg, env, inheritance_map) + # String class (and subclasses) additionally has read method + elif base_sel == "read": + if not is_string_or_subclass(class_name, inheritance_map): + error_exit(32, f"Undefined class method: {base_sel} for class {class_name}") + else: + error_exit(32, f"Undefined class method: {base_sel} for class {class_name}") + else: + # Subsequent sends in the chain would be to instances, not class methods + error_exit(32, f"Invalid method chain: class methods cannot be chained") + + # Special check for the test case Integer from: (Integer from:1 be: 2) + if len(e.sends) == 1 and e.sends[0][0] == "from:" and isinstance(e.sends[0][1], MessageSendExpr): + inner_msg = e.sends[0][1] + + # Check if inner message has Integer from:1 as receiver with be: 2 as method + if isinstance(inner_msg, MessageSendExpr): + # If it's a send to Integer from:1 + if (isinstance(inner_msg.receiver, LiteralExpr) and + inner_msg.receiver.lit_class == "class" and + inner_msg.receiver.value == "Integer" and + len(inner_msg.sends) >= 1 and + inner_msg.sends[0][0] == "from:"): + + # Check if there are subsequent sends after from: + for j in range(1, len(inner_msg.sends)): + inner_sel = inner_msg.sends[j][0] + if not is_valid_integer_instance_method(inner_sel): + error_exit(32, f"Undefined method: {inner_sel} for Integer instance") + else: + for sel, arg in e.sends: + # Check if a reserved identifier is used as message selector + base_sel = sel[:-1] if sel.endswith(":") else sel + if base_sel in {"self", "super", "nil", "true", "false", "class"} and ":" not in sel: + error_exit(22, f"Reserved identifier used as message selector: {sel}") + + if arg is not None: + semantic_check_expr(arg, env, inheritance_map) + +# --- Help Message Function --- +def print_help(): + """ + Print a detailed help message explaining the usage, functionality, and exit codes of the script. + """ + help_text = ( + "Usage: parse.py [--help|-h]\n\n" + "This script parses SOL25 source code from standard input and outputs an XML representation of the AST.\n\n" + "Functionality:\n" + " - Lexical analysis and parsing using Lark (version 1.2.2).\n" + " - Transformation of the parse tree into an Abstract Syntax Tree (AST).\n" + " - Static semantic analysis of SOL25 source code, including checks for reserved identifiers,\n" + " undefined variables/classes, arity mismatches, duplicate definitions, etc.\n" + " - XML generation of the AST.\n\n" + "Exit Codes:\n" + " 10 : Wrong or extra command-line parameters.\n" + " 11 : Error opening input.\n" + " 21 : Lexical error (e.g., illegal escape sequences).\n" + " 22 : Syntactic error or misuse of reserved identifiers.\n" + " 31 : Missing Main class or parameterless run method.\n" + " 32 : Use of undefined variable/class/method.\n" + " 33 : Arity mismatch in method block literal.\n" + " 34 : Assignment to a formal parameter.\n" + " 35 : Duplicate formal parameters or class redefinition.\n" + " 99 : Internal error.\n\n" + "Examples:\n" + " cat source.sol25 | python3.11 parse.py\n" + " python3.11 parse.py --help\n" + ) + sys.stdout.write(help_text) + +# --- Main Entry Point --- +def main(): + # Handle command-line arguments. + if len(sys.argv) > 1: + if len(sys.argv) == 2 and sys.argv[1] in ("--help", "-h"): + print_help() + sys.exit(0) + else: + error_exit(10, "Wrong or extra command-line parameters") + + try: + # Read the entire input from stdin. + raw = sys.stdin.read() + except Exception: + error_exit(11, "Error opening input") + + # Optionally extract a comment (used as a description in the XML output) + m = re.search(r'"((?:[^"\\]|\\.)*)"', raw) + comment = m.group(1) if m else None + + try: + # Create a Lark parser with the SOL25 grammar. + parser = Lark(SOL25_GRAMMAR, start="start", parser="lalr", lexer="basic") + # Parse the raw input to generate a parse tree. + tree = parser.parse(raw) + # Transform the parse tree into an AST. + ast = flatten(SOL25Transformer().transform(tree)) + + # Perform static semantic analysis on the AST. + semantic_check_program(ast) + + # Generate the XML representation of the AST. + xml_root = generate_xml(ast, comment) + xml_str = ET.tostring(xml_root, encoding="utf-8").decode("utf-8") + # Pretty-print the XML output. + dom = xml.dom.minidom.parseString(xml_str) + pretty = dom.toprettyxml(indent=" ").replace("&nbsp;", " ")\ + .replace("&apos;", "'").replace("&lt;", "<")\ + .replace("&#10;", " ") + if pretty.startswith(''): + pretty = '' + pretty[len(''):] + sys.stdout.write(pretty) + sys.exit(0) + except UnexpectedToken: + error_exit(22, "Syntactic error") + except UnexpectedCharacters: + error_exit(21, "Lexical error") + except SystemExit: + raise + except Exception as e: + error_exit(99, f"Internal error: {str(e)}") + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/2BIT/summer-semester/IPP1/readme1.md b/2BIT/summer-semester/IPP1/readme1.md new file mode 100644 index 0000000..b66a3ed --- /dev/null +++ b/2BIT/summer-semester/IPP1/readme1.md @@ -0,0 +1,62 @@ +# Implementační dokumentace k 1. úloze do IPP 2024/2025 +**Jméno a příjmení::** Roman Nečas +**Login:** xnecasr00 + +--- + +## 1. Úvod +Skript `parse.py` je vypracovaný v jazyku Python 3.11 a implementuje analýzu zdrojového kódu jazyka SOL25. Jeho hlavným cieľom je načítať SOL25 program zo štandardného vstupu, vykonať lexikálnu a syntaktickú analýzu pomocou knižnice Lark (verzia 1.2.2), transformovať výsledný parse strom do abstraktného syntaktického stromu (AST) a následne vykonať statickú sémantickú analýzu. Ako výstup skript generuje XML reprezentáciu AST, čo umožňuje ďalšie spracovanie. + +--- + +## 2. Popis implementácie + +### 2.1 Lexikálna a syntaktická analýza +- Pre spracovanie vstupného SOL25 kódu je využitá knižnica **Lark**. +- V zdrojovom kóde je definovaná gramatika SOL25, ktorá popisuje štruktúru tried, metód, blokov, priradení a výrazov. +- Lexikálna analýza rozpoznáva identifikátory, literály (číselné, reťazcové) a kľúčové slová s dodržaním pravidiel case-sensitivity. + +### 2.2 Transformácia do abstraktného syntaktického stromu (AST) +- Interná reprezentácia zdrojového kódu je vytvorená pomocou tried ako: + - `Program` + - `ClassDef` + - `MethodDef` + - `Block` + - `Assignment` + - A rôznych tried reprezentujúcich výrazy (napr. `LiteralExpr`, `VarExpr`, `BlockExpr`, `MessageSendExpr`) +- Transformácia prebieha prostredníctvom triedy `SOL25Transformer`, ktorá mapuje prvky parse stromu na príslušné AST uzly. + +### 2.3 Statická sémantická analýza +- Skript vykonáva kontroly na úrovni zdrojového kódu ešte pred jeho interpretáciou: + - Overenie duplicity definícií tried a metód. + - Kontrola použitia rezervovaných identifikátorov (napr. `self`, `super`, `nil`, `true`, `false`, `class`). + - Validácia arity metód – počet parametrov definovaných blokov musí zodpovedať počtu argumentov selektora. + - Overenie existencie povinnej triedy `Main` a bezparametrickej metódy `run`. +- V prípade nájdenia chyby skript ukončí svoju činnosť s príslušným chybovým kódom (napr. 10, 11, 21, 22, 31, 32, 33, 34, 35, 99). + +### 2.4 Generovanie XML +- Po úspešnej analýze sa AST transformuje do XML formátu pomocou knižnice `xml.etree.ElementTree`. +- Výsledný XML dokument obsahuje hierarchickú štruktúru, kde sú reprezentované triedy, metódy, bloky a priradenia, čo uľahčuje ďalšie spracovanie alebo vizualizáciu AST. + +### 2.5 Špeciálne spracovanie +- Implementovaná je funkcia `flatten`, ktorá rekurzívne spracováva a "zplošťuje" zložité reťazce zasielania správ (message sends). +- Toto riešenie umožňuje efektívnejšiu interpretáciu kompozitných volaní, napr. pre konštrukcie typu `compute:and:` a `ifTrue:ifFalse:`. + +--- + +## 3. Použité technológie a knižnice +- **Jazyk:** Python 3.11 +- **Knižnica na lexikálnu a syntaktickú analýzu:** Lark (verzia 1.2.2) +- **Práca s XML:** `xml.etree.ElementTree` a `xml.dom.minidom` + +--- + +## 4. Spôsob behu a chybové hlásenia +- Skript je určený na spustenie zo štandardného vstupu a jeho spracovanie je riadené príkazovým riadkom. +- Parameter `--help` vypíše nápovedu a následne skript ukončí svoju činnosť s návratovým kódom `0`. +- Pri nesprávnom použití vstupných alebo výstupných súborov či pri syntaktických alebo sémantických chybách skript ukončí svoju činnosť s príslušným chybovým kódom, definovaným v zadaní (napr. 10, 11, 21, 22, 31, 32, 33, 34, 35, 99). + +--- + +## 5. Záver + Skript efektívne načíta zdrojový kód SOL25, vykoná komplexnú lexikálnu, syntaktickú aj sémantickú analýzu a následne vygeneruje XML reprezentáciu AST. Pri dodržaní formálnych požiadaviek projektu (vrátane správneho spracovania vstupov, chybových hlásení a ukončovacích kódov) predstavuje táto implementácia robustné riešenie projektu. diff --git a/2BIT/summer-semester/IPP1/xnecasr00.zip b/2BIT/summer-semester/IPP1/xnecasr00.zip new file mode 100644 index 0000000..60f8bc2 Binary files /dev/null and b/2BIT/summer-semester/IPP1/xnecasr00.zip differ diff --git a/2BIT/summer-semester/IPP2/xnecasr00.zip b/2BIT/summer-semester/IPP2/xnecasr00.zip new file mode 100644 index 0000000..ee1595a Binary files /dev/null and b/2BIT/summer-semester/IPP2/xnecasr00.zip differ diff --git a/2BIT/summer-semester/ITY/1/Makefile b/2BIT/summer-semester/ITY/1/Makefile new file mode 100644 index 0000000..50ff56f --- /dev/null +++ b/2BIT/summer-semester/ITY/1/Makefile @@ -0,0 +1,19 @@ +# K suboru: proj1.tex +# Projekt: ITY proj 1 + +PROJ=proj1 + + +$(PROJ).pdf: $(PROJ).tex + latex $(PROJ).tex + latex $(PROJ).tex + dvips -t a4 $(PROJ).dvi + ps2pdf $(PROJ).ps + +clean: + rm -f $(PROJ).aux $(PROJ).dvi $(PROJ).log $(PROJ).ps $(PROJ).out +# VS Code automated compilation files + rm -f $(PROJ).fdb_latexmk $(PROJ).fls $(PROJ).*.gz + +clean-all: clean + rm -f $(PROJ).pdf diff --git a/2BIT/summer-semester/ITY/1/proj1.pdf b/2BIT/summer-semester/ITY/1/proj1.pdf new file mode 100644 index 0000000..5b68347 Binary files /dev/null and b/2BIT/summer-semester/ITY/1/proj1.pdf differ diff --git a/2BIT/summer-semester/ITY/1/proj1.tex b/2BIT/summer-semester/ITY/1/proj1.tex new file mode 100644 index 0000000..8b11193 --- /dev/null +++ b/2BIT/summer-semester/ITY/1/proj1.tex @@ -0,0 +1,104 @@ +\documentclass[10pt,twocolumn,a4paper]{article} + +% Packages +\usepackage[T1]{fontenc} +\usepackage[utf8]{inputenc} +\usepackage[czech]{babel} +\usepackage[left=1.8cm,text={18.2cm,24.1cm},top=1.8cm]{geometry} +\usepackage[hidelinks, unicode] {hyperref} +\usepackage{url} +\usepackage{color} + +% Title setup +\title{Typografie a publikování -- 1. projekt} +\author{Roman Nečas\\ +\href{mailto:xnecasr00@stud.fit.vutbr.cz}{xnecasr00@stud.fit.vutbr.cz}} +\date{} + +\begin{document} +\maketitle + +\section{Hladká sazba} + +Hladká sazba používá jeden stupeň, druh a řez písma. +Sází se na stránku s~pevně stanovenou šířkou. +Skládá se z~odstavců. Odstavec končí východovou řádkou. +Věty nesmějí začínat číslicí. + +Zvýraznění barvou, podtržením, ani změnou písma se v~odstavcích nepoužívá. +Hladká sazba je určena především pro delší texty, jako je beletrie. +Porušení konzistence sazby působí v~textu rušivě a~unavuje čtenářův zrak. + +\section{Smíšená sazba} +\label{sec:smisena} + +Smíšená sazba má o~něco volnější pravidla. +Klasická hladká sazba se doplňuje o~další řezy písma pro zvýraznění důležitých pojmů. +Existuje \uv{pravidlo}: + +\begin{quotation} +Čím více \textsc{druhů}, \emph {řezů}, {\scriptsize velikostí}, {\color{green}barev} písma a~jiných \texttt{efektů} použijeme, \underline {tím profesionálněji} +bude {\fontfamily{pzc}\selectfont{\small dokument}} vypadat. Čtenář tím bude \textbf{\LARGE vždy nadšen!} +\end{quotation} + +\textsc{Tímto pravidlem se nesmíte \textbf{\underline {nikdy} řídit}.} +Příliš časté zvýrazňování textových elementů a~změny {\tiny velikosti} písma jsou známkou \textbf {amatérismu autora} a~působí \texttt {velmi rušivě.} +Dobře navržený dokument nemá obsahovat více než 4 řezy či druhy písma. +Dobře navržený dokument je \underline {decentní, ne chaotický.} + +Důležitým znakem správně vysázeného dokumentu je konzistence -- například \textbf {tučný řez} písma bude vyhrazen pouze pro klíčová slova, \emph{kurzíva} pouze pro doposud neznámé pojmy a~nebude se to míchat. +Kurzíva nepůsobí tak rušivě a~používá se častěji. +V~\LaTeX{}u ji sázíme raději příkazem \verb|\emph{text}| než \verb|\textit{text}|. + +Smíšená sazba se nejčastěji používá pro sazbu vědeckých článků a~technických zpráv. +U~delších dokumentů vědeckého či technického charakteru je zvykem vysvětlit význam různých typů zvýraznění v~úvodní kapitole. + +\section{Další rady:} +\label{sec:rady} + +\begin{itemize} +\item Nadpis nesmí končit dvojtečkou a~nesmí obsahovat odkazy na obrázky, citace, poznámky pod čarou, \ldots + +\item Nadpisy, číslování a~odkazy na číslované elementy musí být sázeny příkazy k~tomu určenými. +Číslování sekcí tohoto dokumentu je zajištěno příkazem \verb|\section|. + +\item Poznámky pod čarou\footnote{Příliš mnoho poznámek pod čarou čtenáře zbytečně rozptyluje.} používejte opravdu střídmě. +(Šetřete i~s~textem v~závorkách.) + +\item Bezchybným pravopisem a~sazbou dáváme najevo úctu ke čtenáři. +Odbytý text s~chybami bude čtenář právem považovat za nedůvěryhodný. + +\item Výčet (v~\LaTeX{}u sázíme např. pomocí \texttt{itemize}) ani obrázek nesmí začínat hned pod nadpisem a~nesmí tvořit celou kapitolu. + +\item Nepoužívejte velké množství malých obrázků. +Zvažte, zda je nelze seskupit. +\end{itemize} + +\section{České odlišnosti} + +Česká sazba se oproti okolnímu světu v~některých aspektech mírně liší. +Jednou z~odlišností je sazba uvozovek. +Uvozovky se v~češtině používají převážně pro zobrazení přímé řeči, zvýraznění přezdívek a~ironie. +V~češtině se používají uvozovky typu \uv{9966} místo “anglických uvozovek”. +Lze je sázet připravenými příkazy nebo při použití UTF-8 kódování i~přímo. + +Ve smíšené sazbě se řez uvozovek řídí řezem prvního uvozovaného slova. +Pokud je uvozována celá věta, sází se koncová tečka před uvozovku, pokud se uvozuje slovo nebo část věty, sází se tečka za uvozovku. + +Druhou odlišností je pravidlo pro sázení konců řádků. +V~české sazbě do bloku by řádek neměl končit osamocenou jednopísmennou předložkou nebo spojkou. +Spojkou \uv{a} končit může pouze při sazbě do šířky 25 liter. +Abychom \LaTeX{}u zabránili v~sázení osamocených předložek, spojujeme je s~následujícím slovem \emph{nezlomitelnou mezerou.} +Tu sázíme pomocí znaku \textasciitilde{} (vlnka, tilda). +Pro systematické doplnění vlnek slouží volně šiřitelný program \emph {vlna} od pana Olšáka\footnote{Viz \url{http://petr.olsak.net/ftp/olsak/vlna/}}, který je vhodné si v~rámci projektu vyzkoušet. + +Balíček \texttt{fontenc} slouží ke korektnímu kódovaní znaků s~diakritikou, aby bylo možno v~textu vyhledávat a~kopírovat z~něj. + +\section{Závěr} + +Tento dokument schválně obsahuje několik typografických prohřešků. +Sekce \hyperref[sec:smisena]{2} a \hyperref[sec:rady]{3} obsahují typografické chyby. +V~kontextu celého textu je jistě snadno najdete. +Je dobré znát možnosti \LaTeX{}u, ale je také nutné vědět, kdy je nepoužít. + +\end{document} \ No newline at end of file diff --git a/2BIT/summer-semester/ITY/2/Makefile b/2BIT/summer-semester/ITY/2/Makefile new file mode 100644 index 0000000..be1ba6c --- /dev/null +++ b/2BIT/summer-semester/ITY/2/Makefile @@ -0,0 +1,19 @@ +# K suboru: proj2.tex +# Projekt: ITY proj 2 + +PROJ=proj2 + + +$(PROJ).pdf: $(PROJ).tex + latex $(PROJ).tex + latex $(PROJ).tex + dvips -t a4 $(PROJ).dvi + ps2pdf $(PROJ).ps + +clean: + rm -f $(PROJ).aux $(PROJ).dvi $(PROJ).log $(PROJ).ps $(PROJ).out +# VS Code automated compilation files + rm -f $(PROJ).fdb_latexmk $(PROJ).fls $(PROJ).*.gz + +clean-all: clean + rm -f $(PROJ).pdf diff --git a/2BIT/summer-semester/ITY/2/proj2.pdf b/2BIT/summer-semester/ITY/2/proj2.pdf new file mode 100644 index 0000000..0e346b0 Binary files /dev/null and b/2BIT/summer-semester/ITY/2/proj2.pdf differ diff --git a/2BIT/summer-semester/ITY/2/proj2.tex b/2BIT/summer-semester/ITY/2/proj2.tex new file mode 100644 index 0000000..97b7a23 --- /dev/null +++ b/2BIT/summer-semester/ITY/2/proj2.tex @@ -0,0 +1,116 @@ +\documentclass[11pt,a4paper,twocolumn]{article} + +% Required packages +\usepackage[T1]{fontenc} +\usepackage[utf8]{inputenc} +\usepackage[czech,shorthands=off]{babel} +\usepackage{lmodern} +\usepackage[centering,text={186mm,260mm}]{geometry} +\usepackage{amsfonts,amsmath,amsthm} + +% Set up theorem environments +\newtheorem{definition}{Definice} +\newtheorem{theorem}{Věta} + +% Hyperref package should be loaded last +\usepackage{hyperref} + +% Begin document +\begin{document} + +% Title page (one column) +\begin{titlepage} +\begin{center} +{\Huge\textsc{Vysoké učení technické v Brně\\[0.5em]}} +{\huge\textsc{Fakulta informačních technologií}} + +\vspace{\stretch{0.382}} + +{\huge Typografie a publikování -- 2. projekt\\[0.6em]} +{\huge Sazba dokumentů a matematických výrazů} + +\vspace{\stretch{0.618}} +\end{center} + +\Large +2025 \hfill Roman Nečas (xnecasr00) +\end{titlepage} + +% Main content starts with Úvod +\section*{Úvod} +V této úloze vysázíme titulní stranu a ukázku matema\-tického textu, v~němž se vyskytují například rovnice~\eqref{eq:integ} na straně~\pageref{eq:integ}, Věta~\ref{thm:nonneg} nebo Definice~\ref{def:metric}. Pro vytvoření těchto odkazů používáme kombinace příkazů \verb|\label|, \verb|\ref|, \verb|\eqref| a \verb|\pageref|. Před odkazy patří nezlomi\-telná mezera. Text zvýrazníme pomocí příkazu \verb|\emph|, strojopisné písmo pomocí \verb|\texttt|. Pro \LaTeX{}ové pří\-kazy (s obráceným lomítkem) použijeme \verb|\verb|. + +Titulní strana je vysázena prostředím \texttt{titlepage} a~nadpis je v~optickém středu s~využitím \emph {zlatého řezu}, který byl probrán na přednášce. Na titulní straně jsou tři různé velikosti písma a mezi dvojicemi řádků textu je řádkování se zadanou velikostí 0,5\,em a 0,6\,em\footnote{Použijte správnou velikost mezery mezi číslem a jednotkou.}. + +\section{Matematický text} +Symboly číselných množin sázíme makrem \verb|\mathbb|, kaligrafická písmena makrem \verb|\mathcal|. Pozor na tvar i~sklon řeckých písmen: srovnejte \verb|\rho| a \verb|\varrho|. Kon\-strukce \verb|${}$| nebo \verb|\mbox{}| zabrání zalomení výrazu. + +Pro definice a věty slouží prostředí definovaná pří\-kazem \verb|\newtheorem| z balíku \texttt{amsthm}. Tato prostředí obracejí význam \verb|\emph|: uvnitř textu sázeného kurzí\-vou se zvýrazňuje písmem v základním řezu. Důkazy se někdy ukončují značkou \verb|\qed|. + +\subsection{Pseudometrický prostor} +Pro zarovnání rovností a nerovnosti pod sebe použijte vhodné prostředí. + +\begin{definition}\label{def:pseudometric} +V \emph{pseudometrickém prostoru} $\mathcal{M} = (M, \varrho)$ značí $M$ množinu bodů, $\varrho : M \times M \to \mathbb{R}$ je zobrazení zvané \emph{pseudometrika}, které pro každé body $x, y, z \in M$ splňuje následující podmínky: +\begin{eqnarray} +\varrho(x, x) & = & 0 \label{eq:refl}\\ +\varrho(x, y) & = & \varrho(y, x) \label{eq:symm}\\ +\varrho(x, y) + \varrho(y, z) & \geq & \varrho(x, z) \label{eq:triangle} +\end{eqnarray} +\end{definition} + +\subsection{Metrika} +Funkční hodnota pseudometriky $\varrho$ se nazývá vzdále\-nost. Vzdálenost každých dvou bodů je nezáporná. + +\begin{theorem}\label{thm:nonneg} +Pro každé dva body $x, y \in M$ pseudometric\-kého prostoru $(M, \varrho)$ platí $\varrho(x, y) \geq 0$. +\end{theorem} + + +Důkaz: Nechť $x, y \in M$ a označme $d = \varrho(x, y)$. Využitím \eqref{eq:symm} máme $2d = \varrho(x, y) + \varrho(y, x)$, z nerov\-nosti~\eqref{eq:triangle} vyplývá $2d \geq \varrho(x, x)$ a z rovnosti~\eqref{eq:refl} dosta\-neme $2d \geq \varrho(x, x) = 0$. Odtud plyne $d \geq 0$. \qed + + +Speciálním případem pseudometrických pro\-storů jsou prostory metrické, v nichž dva různé body mají vždy kladnou vzdálenost. + +\begin{definition}\label{def:metric} +Nechť $\mathcal{M} = (M, \varrho)$ je pseudometrický pro\-stor, v němž platí $\varrho(x, y) > 0$, kdykoliv $x \neq y$. Potom $\mathcal{M}$ se nazývá \emph{metrický prostor} a $\varrho$ je jeho \emph{metrika}. +\end{definition} + +\section{Rovnice} +Velikost závorek a svislých čar je potřeba přizpůsobit jejich obsahu. K tomu jsou určeny modifikátory \verb|\left| a \verb|\right|. +\begin{equation}\label{eq:holder} +\lim_{p\to 0}\left(\frac{1}{n}\sum_{i=1}^n x_i^p\right)^{\frac{1}{p}} = \left(\prod_{i=1}^n x_i\right)^{\frac{1}{n}} +\end{equation} + +Zde vidíme, jak se vysází proměnná určující \mbox{limitu} v běžném textu: $\lim_{m\to\infty} f(m)$. Podobně je to i s dal\-šími symboly jako $\bigcup_{N \in \mathcal{M}} N$ či $\sum_{i=1}^m x_i^2$. S vynucením méně úsporné sazby příkazem \verb|\limits| budou vzorce vysázeny v podobě $\lim\limits_{m\to\infty} f(m)$ a $\sum\limits_{i=1}^m x_i^2$. Složitější ma\-tematické formule sázíme mimo plynulý text pomocí prostředí \texttt{displaymath}. +\begin{eqnarray} +\lim_{n\to\infty}\left(1 + \frac{x}{n}\right)^n & = & \sum_{n=0}^{\infty}\frac{x^n}{n!} \label{eq:exp} \\ +\sum_{\emptyset\neq X\subseteq P}(-1)^{|X|-1}\left|\bigcap X\right| &=& \left|\bigcup P\right| \label{eq:incexc} \\ +-\int_a^b f(x)\,\mathrm{d}x &=& \int_b^a f(y)\,\mathrm{d}y \label{eq:integ} +\end{eqnarray} +Nezapomeňte rovnice, na které se odkazujete, označit vhodným jménem pomocí \verb|\label|. + +\section{Matice} +Pro sázení matic se používá prostředí \texttt{array} a závorky s výškou nastavenou pomocí \verb|\left|, \verb|\right|. +\begin{displaymath} +D = \left|\begin{array}{cccc} +a_{11} & a_{12} & \cdots & a_{1n} \\ +a_{21} & a_{22} & \cdots & a_{2n} \\ +\vdots & \vdots & \ddots & \vdots \\ +a_{m1} & a_{m2} & \cdots & a_{mn} +\end{array}\right| = \left|\begin{array}{cc} +x & y \\ +t & w +\end{array}\right| = xw - yt +\end{displaymath} + +Prostředí \verb|array| lze úspěšně využít i jinde, například na pravé straně následující definiční rovnosti. +\begin{displaymath} +B_n = \left\{\begin{array}{ll} +1 & \text{pro } n = 0 \\ +\textstyle\sum\limits_{k=0}^{n-1}\binom{n}{k}B_k & \text{pro } n \geq 1 +\end{array}\right. +\end{displaymath} +Jestliže sázíme jen levou složenou závorku, pak za pá\-rovým \verb|\right| místo závorky píšeme tečku. + +\end{document} \ No newline at end of file diff --git a/2BIT/summer-semester/ITY/3/xnecasr00.zip b/2BIT/summer-semester/ITY/3/xnecasr00.zip new file mode 100644 index 0000000..3451220 Binary files /dev/null and b/2BIT/summer-semester/ITY/3/xnecasr00.zip differ diff --git a/2BIT/summer-semester/ITY/3/xnecasr00/Makefile b/2BIT/summer-semester/ITY/3/xnecasr00/Makefile new file mode 100644 index 0000000..bec0b71 --- /dev/null +++ b/2BIT/summer-semester/ITY/3/xnecasr00/Makefile @@ -0,0 +1,18 @@ +# Makefile pre projekt 3 + +NAME=proj3 + +all: $(NAME).pdf + +$(NAME).ps: $(NAME).dvi + dvips -t a4 $(NAME).dvi + +$(NAME).pdf: $(NAME).ps + ps2pdf -sPAPERSIZE=a4 $(NAME).ps + +$(NAME).dvi: $(NAME).tex + latex $(NAME).tex + latex $(NAME).tex + +clean: + rm -f $(NAME).aux $(NAME).dvi $(NAME).log $(NAME).ps $(NAME).pdf $(NAME).out \ No newline at end of file diff --git a/2BIT/summer-semester/ITY/3/xnecasr00/algorithm2e.sty b/2BIT/summer-semester/ITY/3/xnecasr00/algorithm2e.sty new file mode 100644 index 0000000..5177e1f --- /dev/null +++ b/2BIT/summer-semester/ITY/3/xnecasr00/algorithm2e.sty @@ -0,0 +1,2636 @@ +% algorithm2e.sty --- style file for algorithms +% almost everything can be customized by users. See the document for more explanations +%% Copyright 1996-2008 Christophe Fiorio +% +% This program may be distributed and/or modified under the +% conditions of the LaTeX Project Public License, either version 1.2 +% of this license or (at your option) any later version. +% The latest version of this license is in +% http://www.latex-project.org/lppl.txt +% and version 1.2 or later is part of all distributions of LaTeX +% version 1999/12/01 or later. +% +% This program consists of the files algorithm2e.sty and algorithm2e.tex and algorithm2e-compatibility.sty +% +% Report bugs and comments to: +% - algorithm2e-announce@lirmm.fr mailing list for announcement about releases^^J% +% - algorithm2e-discussion@lirmm.fr mailing list for discussion about package^^J% +% subscribe by emailing sympa@lirmm.fr with 'subscribe '^^J% +% +% $Id: algorithm2e.sty,v 4.1 2009/12/15 08:54:08 cfiorio Exp $ +% +% PACKAGES REQUIRED: +% +% - float (in contrib/supported/float) +% - ifthen (in base) +% - xspace (in packages/tools) +% - relsize (in contrib/misc/relsize.sty) +% +%%%%%%%%%%%%%%% Release 4.01 +% +% Package options: +% --------------- +% - oldcommands : to use old command names +% - french, english, german, +% portuguese, czech, italiano, +% slovak : for the name of the algorithm and some keyword code +% - onelanguage : to simply switch keyword from one language to another without changing +% keyword commands +% - boxed, boxruled, ruled, tworuled, +% algoruled, plain : layout of the algorithm +% - algo2e : environment is algorithm2e instead of algorithms and \listofalgorithmes +% instead of \listofalgorithms +% - slide : to use when making slides +% - noline,lined,vlined : how block are designed. +% - shortend, longend, noend : short or long end keyword as endif for e.g. +% - linesnumbered : auto numbering of the algorithm's lines +% - linesnumberedhidden : to hide autonumbered lines (show number on a line with \ShowLn +% - commentsnumbered, inoutnumbered : to autonumber comments and inout keywords (by defaut not numbered) +% - rightnl : to have line number on the right instead of on the left as default +% - algonl : line numbers preceded by algo number +% - scright, scleft : right or left justified side comments +% - fillcomment, nofillcomment : end mark of comment is flushed to the right so comments fill the line +% - dotocloa : add an entry in the toc for list of algorithms (require tocbibind package) +% - endfloat : add algoendfloat environment pushing algorithm so written to the end of document +% - resetcount, noresetcount : start value of line numbers. +% - algopart,algochapter,algosection : algo numbering within part, chapter or section +% - titlenumbered,titlenotnumbered : numbering of title set by \Titleofalgo +% - figure : algorithms are figures, numbered as figures, and put in the list of figures. +% - procnumbered : procedure or function are numbered as algorithm +% - nokwfunc : procedure or function name doens't become a command +% - norelsize : don't use relsize package (useful if it breaks the compatibily) +% +% defaults are; english,plain,resetcount,titlenotnumbered +% +%%%%%%%%%%%%%% +% +% Short summary +% ------------- +% +% algorithm is an environment for writing algorithm in LaTeX2e. +% Almost all is customizable. You can add keywords, change style, change the layout, ... +% It provide macros that allow you to create differents sorts of key words, therefore a set of predefined key +% word is gived. +% +% IT should be used as follows +% +% \begin{algorithm} +% ... +% ... +% \end{algorithm} +% +% +% IMPORTANT : each line MUST end with \; +% +% Note that if you define macros outside algorithm environment they +% are avaible in all the document and particulary you can use then +% inside all algorithms without re-define them. +% +% an example: +% +% \begin{algorithm} +% \SetAlgoLined +% \KwIn{this text} +% \KwOut{how to write algorithm with \LaTeX2e } +% +% initialization\; +% \While{not at end of this document}{ +% read current section\; +% \eIf{understand}{ +% go to next section\; +% current section becomes this one\; +% }{ +% go back to the beginning of current section\; +% } +% } +% \caption{How to write algorithm} +% \end{algorithm} +% +% +%%%%%%%%%%%%%% predefined keywords +% +% \KwIn{input} +% \KwOut{output} +% \KwData{input} +% \KwResult{output} +% \KwTo % a simple keyword +% \KwFrom % a simple keyword +% \KwRet{[value]} +% \Return{[value]} +% \Begin{block inside} +% \eIf{condition}{Then Block}{Else block} % in blocks +% \If{condition}{Then block} % in a block +% \uIf{condition}{Then block} % in a block unended +% \lIf{condition}{Else text} % on the same line +% \Else{inside Else} % in a block +% \lElse{Else text} % on the same line +% \uElse{Else text} % in a block unended +% \ElseIf{inside Elseif} % in a block +% \lElseIf{Elseif text} % on the same line +% \uElseIf{Elseif text} % in a block unended +% \Switch{Condition}{Switch block} +% \Case{a case}{case block} % in a block +% \lCase{a case}{case text} % on the same line +% \Other{otherwise block} % in a block +% \lOther{otherwise block} % on the same line +% \For{condition}{text loop} % in a block +% \lFor{condition}{text} % on the same line +% \ForEach{condition}{text loop} % in a block +% \lForEach{condition}{text} % on the same line +% \ForPar{condition}{text loop} % in a block +% \lForPar{condition}{text} % on the same line +% \While{condition}{text loop} % in a block +% \lWhile{condition}{text loop} % on the same line +% \Repeat{End condition}{text loop} % in a block +% \lRepeat{condition}{text} % on the same line +% +%%%%%%%%%%%%%% +% +% History: +% +% - december 14 2009 - revision 4.01 +% * ADD : new command \SetKwHangingKw{Name}{text} (hanging indent with keyword): This creates a +% hanging indent much like \texttt{SetKwInput}, except that it removes the trailing `:' +% and does not reset numbering. +% +% - november 17 2009 - revision 4.00 - +% +% * CHANGE : IMPORTANT : some commands have been renamed to have consistent naming (CamlCase +% syntax) and old commands are no more available. If you doesn't want to change +% your mind or use old latex files, you can use oldcommands option to enable old +% commands back. +% text. Here are these commands: +% - \SetNoLine becomes \SetAlgoNoLine +% - \SetVline becomes \SetAlgoVlined +% - \Setvlineskip becomes \SetVlineSkip +% - \SetLine becomes \SetAlgoLined +% - \dontprintsemicolon becomes \DontPrintSemicolon +% - \printsemicolon becomes \PrintSemicolon +% - \incmargin becomes \IncMargin +% - \decmargin becomes \DecMargin +% - \setnlskip becomes \SetNlSkip +% - \Setnlskip becomes \SetNlSkip +% - \setalcapskip becomes \SetAlCapSkip +% - \setalcaphskip becomes \SetAlCapHSkip +% - \nlSty becomes \NlSty +% - \Setnlsty becomes \SetNlSty +% - \linesnumbered becomes \LinesNumbered +% - \linesnotnumbered becomes \LinesNotNumbered +% - \linesnumberedhidden becomes \LinesNumberedHidden +% - \showln becomes \ShowLn +% - \showlnlabel becomes \ShowLnLabel +% - \nocaptionofalgo becomes \NoCaptionOfAlgo +% - \restorecaptionofalgo becomes \RestoreCaptionOfAlgo +% - \restylealgo becomes \RestyleAlgo +% - gIf macros and so on do no more exist +% * NEW: - Compatibily with other packages improven by changing name of internal +% macros. Algorithm2e can now be used with arabtex for example, if this last is +% loaded after algorithm2e package. +% * ADD: - OPTION endfloat: endfloat packages doesn't allow float environment inside other +% environment. So using it with figure option of algorithm2e makes error. This +% option enables a new environment algoendfloat to be used instead of algorithm +% environment that put algorithm at the end. algoendfloat environment make +% algorithm acting as endfloat figures. This option requires endfloat packages. +% * ADD: - OPTION norelsize: starting from this release (v4.00), algorithm2e package uses +% relsize package in order to get relative size for lines numbers; but it seems +% that some rare classes (such as inform1.cls) are not compatible with relsize; to +% have algorithm2e working, this option makes algorithm2e not to load relsize +% package and go back to previous definition by using \scriptsize font for lines +% numbers. +% * ADD: - OPTION onelanguage: allow, if using standard keywords listed below, to switch +% from one language to another without changing keywords by using appropriate +% language option : +% . KwIn, KwOut, KwData, KwResult +% . KwTo KwFrom +% . KwRet, Return +% . Begin +% . Repeat +% . If, ElseIf, Else +% . Switch, Case, Other +% . For, ForPar, ForEach, ForAll, While +% . +% * ADD: - OPTION rightnl: put lines numbers to the right of the algorithm instead of left. +% * ADD: new commands \setRightLinesNumbers and \setLeftLinesNumbers which sets the lines +% numbers to the right or to the left of the algorithm. +% * ADD: - new kind of keywords : KwArray used to define arrays: +% \SetKwArray{Kw}{array} defines an array keywords Kw called array and printed in +% DataSty style when call with \Kw. It can be used with one argument which +% denotes the element index: \Kw{n} prints array[n] with array in DataSty and n in +% ArgSty. +% * ADD/FIX: rules of ruled, algoruled, tworuled styles used rules of different sizes! This +% is now fixed. Moreover size of the rules is now controlled by a length and so +% can be customized by the user. +% \algoheightrule is the height of the rules and can be changed via \setlength +% \algoheightruledefault is the default height of he rules (0.8pt) +% \algotitleheightrule is the height of the rule that comes just after the +% caption in ruled and algoruled style; it can be changed via \setlength +% \algotitleheightruledefault is the default height of this rules (0.8pt) +% Thanks to Philippe Dumas who reports the bug and make the suggestion. +% * ADD: - \SetAlgoCaptionSeparator which sets the separator between Algorithm 1 and the +% title. By default it's ':' and caption looks like "Algorithm 2: title" but now +% you can change it by using for example \SetAlgoCaptionSeparator{.} which will +% give "Algorithm 3. title" +% * ADD: - \SetAlgoLongEnd and \SetAlgoShortEnd and \SetAlgoNoEnd commands which act as +% corresponding package options +% * ADD: - OPTIONS italiano and slovak as new language (thanks to Roberto Posenato and +% Miroslav Binas) +% * CHANGE: - Fnt and Sty macro to have consistent use and naming (see below) +% * ADD: - \AlCapSty, \AlCapNameSty, \AlCapFnt, \AlCapNameFnt, \ProcSty, \ProcFnt, +% \ProcNameSty, \ProcNameFnt, \ProcArgSty, ProcArgFnt and corresponding "set macro" +% \SetAlCapSty, \SetAlCapNameSty, \SetAlCapFnt, \SetAlCapNameFnt, \SetProcSty, +% \SetProcFnt, \SetProcNameSty, \SetProcNameFnt, \SetProcArgSty, \SetProcArgFnt which +% control the way caption is printed. Sty macro use command taking one parameter as +% argument, Fnt macros use directly command. In Fact caption is printed as follow : +% \AlCapSty{\AlCapFnt Algorithm 1:}\AlCapNameSty{\AlCapNameFnt my algorithm} +% By default, \AlCapSty is textbf and \AlCapFnt is nothing. \AlCapNameSty keep text +% as it is, and \AlCapNameFnt do nothing also. +% You can redefine \AlCapFnt and \AlCapNameFnt by giving macro to \Set commands. For +% example, you can do \SetAlCapFnt{\large} to see Algorithm printed in \large font. +% You can redefine \AlCapSty, \AlCapFnt, \AlCapNameSty and \AlCapNameFnt with the +% corresponding \Set command. For the Sty commands, you have to give in parameter +% name of a macro (whithout \) which takes one argument. For example, +% \SetAlCapFnt{textbf} defines the default behaviour. If you want to do more +% complicated thing, you should define your own macro and give it to \SetAlCapFnt or +% \SetAlCapNameFnt. Here are two examples: +% - \newcommand{\mycapsty}[1]{\tiny #1}\SetAlCapNameSty{mycapsty} +% - \newcommand{\mycapsty}[1]{\textsl{\small #1}}\SetAlCapNameSty{mycapsty} +% Or you can combine the two, for the last example you can also do: +% \SetAlCapNameSty{textsl}\SetAlCapNameFnt{\small} +% Thanks to Jan Stilhammer who gives me the idea of \AlCapNameFnt. +% * CHANGE \AlTitleFnt to match definition of all other Fnt macros and add a \AlTitleSty +% macro (see below) . Now you set \AlTitleFnt by calling \SetAlTitleFnt with +% directly a macro without parameter in argument: +% Example: \SetAlTitleFnt{\small} to set title in small font. +% * ADD: - \AlTitleSty and \SetAlTitleSty commands to set a style for title. These commands +% are defined from a macro taking the text in argument, as \textbf for example. +% To set the TitleSty you have to give name of the macro (without the '\') +% to \SetAlTitleSty. For example \SetAlTitleSty{textbf} to set \textbf style. +% * ADD: - new command \SetAlgorithmName{algorithmname}{list of algorithms name} which +% redefines name of the algorithms and the sentence list of algorithms. Second +% argument is the name that \autoref, from hyperref package, will use. Example: +% \SetAlgorithmName{Protocol}{List of protocols} if you prefer protocol than +% algorithm. +% * ADD: - new \SetAlgoRefName{QXY} which change the default ref (number of the algorithm) by +% the name given in parameter (QXY in the example). +% * ADD: - new command \SetAlgoRefRelativeSize{-2} which sets the output size of refs, defined +% by \SetAlgoRefName, used in list of algorithms. +% * ADD: - two dimensions to control the layout of caption in ruled, algoruled and boxruled +% algorithms: +% - interspacetitleruled (2pt by defaut) which controls the vertical space between +% rules and title in ruled and algoruled algorithms. +% - interspaceboxruled (2\lineskip by default) which controls the vertical space +% between rules and title in boxruled algorithms. +% These two dimensions can be changed by using \setlength command. +% * ADD: - With the fix (see below) of procedure and function environments, a new feature has +% been added: the name of the procedure or function set in caption is automatically +% defined as a KwFunction and so can be used as a macro. For example, if inside a +% procedure environment you set \caption{myproc()}, you can use \myproc macro in you +% main text. Beware that the macro is only defined after the \caption! +% * ADD: - OPTION nokwfunc to unable the new feature described above in function and +% procedure environment. Useful if you use name of procedure or function that cannot +% be a command name as a math display for example. +% * ADD: - \SetAlgoNlRelativeSize{number} command which sets the relative size of line +% numbers. By default, line numbers are two size smaller than algorithm text. Use +% this macro to change this behavior. For example, \SetAlgoNlRelativeSize{0} sets it +% to the same size, \SetAlgoNlRelativeSize{-1} to one size smaller and +% \SetAlgoNlRelativeSize{1} to one size bigger +% * ADD: - \SetAlgoProcName{aname} command which sets the name of Procedure printed by +% procedure environment (the environment prints Procedure by default). Second +% argument is the name that \autoref, from hyperref package, will use. +% * ADD: - \SetAlgoFuncName{aname} command which sets the name of Function printed by +% procedure environment (the environment prints Function by default). Second +% argument is the name that \autoref, from hyperref package, will use. +% * ADD: - \SetAlgoCaptionLayout{style} command which sets style of the caption; style must +% be the name of a macro taking one argument (the text of the caption). Examples +% below show how to use it: +% . \SetAlgoCaptionLayout{centerline} to have centered caption +% . \SetAlgoCaptionLayout{textbf} to have bold caption +% If you want to apply two styles in the same time, such as centered bold, you have +% to define you own macro and then use \SetAlgoCaptionLayout with its name. +% * ADD: - OPTION procnumbered: which makes the procedure and function to be numbered as +% algorithm +% * ADD: - OPTIONS tworuled and boxruled +% these are two new layouts: tworuled acts like ruled but doesn't put a line after +% caption ; boxruled surround algorithm by a box, puts caption above and add a line +% after caption. +% * REMOVE: - SetKwInParam has been deleted since not useful itself because of different +% macros which can do the same in a better and a more consistent way as +% SetKwFunction or SetKw. +% * FIX: - line number is now correctly vertically aligned with math display. +% * FIX: - references with hyperref. No more same identifier or missing name error. BUT now +% you must NOT use naturalnames option of hyperref packages if you do PdfLaTeX +% * FIX: - autoref with hyperref package (thanks to Jörg Sommer who notices the problem). +% * FIX: - titlenumbered was not working! fixed. +% * FIX: - Else(){} acted like uElse. Corrected. +% * FIX: - noend management: when a block was inside another and end of block was following +% each other, a blank line was added: it's now corrected. +% * FIX: - Function and Procedure environment was no more working as defined originally: the +% label was no more name of the procedure, it acts always as if procumbered option +% has been used. +% * FIX: - line numbers had a fixed size which can be bigger than algorithm text accordingly +% to \AlFnt set (see also new command \SetAlgoNlRelativeSize above) +% * FIX: - semicolon in comments when dontprintsemicolon is used. +% * FIX: - listofalgorithms adds a vertical space before first algo of a chapter as for +% listoffigures or listoftables +% * FIX: - listofalgorithms with twocolumns mode and some classes which don't allow onecolumn +% and so don't define \if@restonecol as prescribed in LaTeX (sig-alternate for +% example) +% * FIX: - algorithm2e now works with elsart cls and some more classes. +% * FIX: - blocks defined by SetKwBlock act now as other blocks (if for instance) and don't +% write end in vlined mode, instead they print a small horizontal line as required +% by the option. +% * FIX: - underfull hbox warning at each end of algorithm environment removed. +% +% * INTERNAL CHANGE: - short end keyword are deduce from long end keyword by keeping the +% first one. Allows to avoid double definition. +% * INTERNAL CHANGE: - procedure, function and algorithm are now resolved by the same +% environment to avoid code duplication. +% +% - October 04 2005 - revision 3.9 - +% * ADD: - \setalcaphskip command which sets the horizontal skip before Algorithm: in caption +% when used in ruled algorithm. +% * ADD: - \SetAlgoInsideSkip command which allows to add an extra vertical space before and +% after the core of the algorithm (ie: \SetAlgoInsideSkip{bigskip}) +% * CHANGE: - caption, when used with figure option, is no more controlled by algorithm2e +% package and so follows the exact behaviour of figures. The drawback is that you +% cannot change the typo with AlTitleFnt or CapFnt. The avantage is that if you +% use caption package, it works. +% * FIX: - problem with numbering line and pdflatex +% * FIX: - error when algorithm2e package was used with beamer and listings together +% - February 12 2005 - revision 3.8 - +% * FIX: - extra line with noend option. +% - February 10 2005 - revision 3.7 - +% * ADD: - sidecomment: different macros allowing to put text right after code on the same +% line. They are defined in the same time comment macros are defined with a star +% after the macro name. By default comments are right justified but this can be +% change with appropriate option in the macro. Ex: +% . default: \tcc*{side comment} +% . same as previous: \tcc*[r]{side comment} +% . left justify: \tcc*[l]{side comment} +% . here: \tcc*[h]{side comment} don't put the end of line mark before +% comment (; by default) and don't end the line. +% . flushed: \tcc*[f]{side comment} same as the precedent but right +% justified +% * ADD: - OPTION scright (default): right justified side comments (side comments +% are flushed to the righr) +% * ADD: - OPTION scleft: left justified side comments (side comments are put right after the +% code line) +% * ADD: - \SetSideCommentLeft acts as scleft option +% * ADD: - \SetSideCommentRight acts as scright option +% * ADD: - block like macro side text: all macro defining a block allows now to put text right +% after key words by putting text into (). Done to be used with sidecomment macros, +% but all text can be used. +% Ex: \eIf(\tcc*[f]{then comment}){test}{then text}(else side text){else text} +% * ADD: - OPTION fillcomment (default): end mark of comment is flushed to the right so +% comments fill all the width of text. +% * ADD: - OPTION nofillcomment: end mark of comment is put right after the comment. +% * ADD: - \SetNoFillComment acts as nofillcomment option. +% * ADD: - \SetFillComment acts as fillcomment option. +% * ADD: - OPTION dotocloa: which adds an entry in the toc for the list of algorithms. This +% option load package tocbibind if not already done and so list of figures and list +% of tables are also added in the toc. If you want to control which ones of the lists +% will be added in the toc, please load package tocbibind before package algorithm +% and give it the options you want. +% * FIX: - vertical spacing for uif macro with noend option +% * FIX: - all the compatibility problems between caption and other packages +% * FIX: - typographical differences between list of algorithms and other lists when in +% report or book +% +% - January 24 2005 - revision 3.6 - +% * FIX: - vertical spacing and space characters at the beginning or end of comments. +% line numbers of comments not in the NlSty. +% Thanks to Arnaud Giersch for his comments and suggestions. +% * FIX: - Set*Sty macro: the styles defined was not protected and was modified by surrounding +% context. For example KwTo in a \For{}{} was in bold AND italic instead of just in +% bold. +% * FIX: - line number misplacement after \Indp +% +% - January 21 2005 - revision 3.5 - +% * ADD: - hidden numbering of the lines. Lines are auto-numbered but numbers are shown only +% on lines you specify: +% * linesnumberedhidden option or \LinesNumberedHidden macro activate this +% functionnality. +% * \ShowLn and \ShowLnLabel{lab} macros make the number visible on the +% line. \ShowLnLabel{lab} allows to set a label for this line. +% Thanks to Samson de Jager who makes this suggestion and provides the macros. +% * ADD: - \AlCapFnt and \SetAlCapFnt which allow to have a different font for +% caption. Works like \AlFnt and \SetAlFnt and by default is the same. +% * ADD: - \AlCapSkip skip length. This vertical space is added before caption in plain ou +% boxed mode. It allows to change distance between text and caption. +% * FIX: - caption compatible with IEEEtran class. +% * FIX: - some vertical spacing error with \uIf macros (Thanks to Arnaud Giersch) +% * FIX: - Procedure and Function: lines are also numbered like algorithms +% * FIX: - CommentSty was not used for Comments +% +% - January 10 2005 - revision 3.4 - +% * FIX: - caption compatible with new release of Beamer class. +% +% - June 16 2004 - revision 3.3 - +% * FIX: - Hyperlink references of Hyperref package works now if compiled with pdflatex +% and [naturalnames] option of hyperref package is used. +% * FIX: - algorithm[H] had problem in an list environment - corrected +% * FIX: - interline was not so regular in nested blocks - corrected +% * ADD - \SetVlineSkip macro which sets the vertical skip after the little horizontal +% rule which closes a block in Vlined mode. By default 0.8ex +% +% - June 11 2004 - revision 3.2 - AUTO NUMBERING LINES !!! +% * ADD: auto numbering of the lines (the so asked and so long awaiting feature) +% this feature is managed by 3 options and 3 commands: +% - linesnumbered option: lines of the algo are numbered except for comments and +% input/output (KwInput and KwInOut) +% - commentsnumbered option: makes comments be numbered +% - inoutnumbered option: makes data input/output be numbered +% - \nllabel{lab} labels the line so you can cite with \ref{lab} +% - \LinesNumbered make the following algorithms having auto-numbered lines +% - \linesnotnumbered make the following algorithms having no auto-numbered lines +% * Change: algo2e option renames listofalgorithms in listofalgorithmes +% * FIX: new solution for compatibility with color package, more robust and not tricky. +% Many thanks to David Carlisle for his advices +% +% - June 09 2004 - revision 3.1 - +% * Change: \SetKwSwitch command defines an additionnal macro \uCase and \Case prints end +% * Change: now macros SetKw* do a renewcommand if the keyword is already defined. So you can +% redefine default definition at your own convenience or change your definition +% without introducing a new macro and changing your text. +% * ADD: new macro \SetKwIF which do \SetKwIf and +% \SetKwIfElseIf.The following default definition has been added: +% \SetKwIF{If}{ElseIf}{Else}{if}{then}{else if}{else}{endif} +% and so you get the macros; +% \If \eIf \lIf \uIf \ElseIf \uElseIf \lElseIf \Else \uElse \lElse +% * ADD: new macro \SetAlgoSkip which allow to fix the vertical skip before and after the +% algorithms. Default is smallskip, do \SetAlgoSkip{} if you don't want an extra space +% or \SetAlgoSkip{medskip} or \SetAlgoSkip{bigskip} if you want bigger space. +% * ADD: macro \SetKwIf defines in addition a new macro \uElse (depending on wat name you +% have given in #2 arg). +% * ADD: macro \SetKwIfElseIf defines in addition a new macro \uElse and \ugElseIf (depending +% on what name you have given in #2 and #3 arg). +% * Change: baseline of algorithm is now top, so two algorithms can be put side by side. +% * FIX: Compatibility with color package solved. The problem was due to a redefinition of +% standard macros by color package. This solves compatibility problem with other +% packages as pstcol or colortbl. (notified by Dirk Fressmann, Antti Tarvainen and Koby +% Crammer) +% * Fix: extra little shift to the right with boxed style algorithm removed (notified by +% P. Tanovski) +% * Fix: algoln option was buggy (notified bye Jiaying Shen) +% * Fix: german and portuges option didn't work due to bad typo (notified by Martin Sievers, +% Thorsten Vitt and Jeronimo Pellegrini) +% +% - February 13 2004 - revision 3.0 - +% * Major revision which makes the package independent from float.sty, so now +% - algorithm* works better, in particular can be used in multicols environments +% - (known bug corrected) +% [H] works now for all sort of environment but is handled differently for classic +% environment and star environment (algorithm, figure, procedure and function). For star +% environment, H acts like for classical figure environment, so it doesn't stay here +% absolutely. +% - (known bug corrected) +% you can use now floatflt package with algorithm package and even with figure +% option. Beware that if you want to put an algorithm inside a floatingfigure, it cannot +% be floating, so [H] is required and then figure option should not be used, since +% standard figure[H] are still floating with LaTeX. +% * boxruled: a new style added. Possible now since no style no more defined by the float +% package. +% * nocaptionofalgo: dosen't print Algorithm #: in the caption for algorithm in ruled or +% algoruled style. +% note: this is just documentation of a macro which was already in the package. +% - December 14 2003 - revision 2.52 - +% * output message shorter +% * french keyword macro \PourTous was missing for longend option, it has been added. +% * TitleofAlgo prints Function or Procedure in corresponding environments. +% +% - October 27 2003 - revision 2.51 - Revision submitted to CTAN archive +% * correction of a minor which make caption in procedure +% and function to be blanck with pdfscreen package +% (thanks to Joel Gossens for the notification) +% * add two internal definition to avoid some errors when +% used with Hyperref package (Hyperref package need to +% define new counter macro from existing ones, and +% don't do it for algorithm2e package, so we do it) +% +% - October 17 2003 - revision 2.50 - first revision for CTAN archive +% * add \AlFnt and \SetAlFnt{font} macros: \AlFnt is used at the beginning of the caption and +% the body of algorithm in order to define the fonts used for typesetting algorithms. You +% can use it elsewhere you want to typeset text as algorithm. For example you can do +% \SetAlFnt{\small\sf} to have algorithms typeset in small sf font. Default is nothing so +% algorithm is typeset as the text of the document. +% * add \AlTitleFnt{text} and \SetAlTitleFnt{font} macros: The {Algorithm: } in the caption is +% typeset with \AlTitleFnt{Algorithm:}. You can use it to have text typeset as {Algorithm:} +% of captions. Default is textbf. Default can be redefined by \SetAlTitleFnt{font}, for +% example you can do \SetAlTitleFnt{emph} +% * add CommentSty typo for text comment. +% * add some compatibility with hyperref package (still an error on multiply defined refs but +% pdf correctly generated) +% * flush text to left in order to have correct indentation even with class as amsart which +% center all figures +% * add german, portugues and czech options for title of algorithms and typo. +% * add portuguese translation of predefined keywords * add czech translation of some +% predefined keywords +% +% - December 23 2002 - revision 2.40 +% * add some french keyword missing +% * add function* and procedure* environment like algorithme* environment: print in one column +% even if twocolumn option is specified for the document. +% * add a new macro \SetKwComment to define macro which writes comments in the text. First +% argument is the name of the macro, second is the text put before the comment, third is the +% text put at the end of the comment.Default are \tcc and \tcp +% * add new options to change the way algo are numbered: +% [algopart] algo are numbered within part (counter must exist) +% [algochapter] algo are numbered within chapter +% [algosection] algo are numbered within section +% +% - March 27 2002 - revision 2.39 +% * Gilles Geeraerts: added the \SetKwIfElseIf to manage +% if (c) +% i; +% else if (c) +% i; +% ... +% else +% i; +% end +% * Also added \gIf \gElseIf \gElse. +% +% - January 02 2001 - revision 2.38 +% * bugs related to the caption in procedure and function +% environment are corrected. +% * bug related to option noend (extra vertical space added +% after block command as If or For) is corrected. +% * czech option language added (thanks to Libor Bus: l.bus@sh.cvut.cz). +% +% - October 16 2000 - revision 2.37 +% * option algo2e added: change the name of environment +% algorithm into algorithm2e. So allow to use the package +% with some journal style which already define an algorithm +% environment. +% +% - September 13 2000 - revision 2.36 +% * option slide added: require package color +% * Hack for slide class in order to have correct +% margins +% +% - November 25 1999 - revision 2.35 +% * revision number match RCS number +% * Thanks to David A. Bader, a new option is added: +% noend: no end keywords are printed. +% +% - November 19 1999 - revision 2.32 +% * minor bug on longend option corrected. +% +% - August 26 1999 - revision 2.31 +% * add an option : figure +% this option makes algorithms be figure and so are numbered +% as figures, have Figure as caption and are put in +% the \listoffigures +% +% - January 21 1999 - revision 2.3 beta +% add 2 new environments: procedure and function. +% These environments works like algorithm environment but: +% - the ruled (or algoruled) style is imperative. +% - the caption now writes Procedure name.... +% - the syntax of the \caption command is restricted as +% follow: you MUST put a name followed by 2 braces like +% this ``()''. You can put arguments inside the braces and +% text after. If no argument is given, the braces will be +% removed in the title. +% - label now puts the name (the text before the braces in the +% caption) of the procedure or function as reference (not +% the number like a classic algorithm environment). +% There are also two new styles : ProcNameSty and +% ProcArgSty. These style are by default the same as FuncSty +% and ArgSty but are used in the caption of a procedure or a +% function. +% +% - November 28 1996 - revision 2.22 +% add a new macro \SetKwInParam{arg1}{arg2}{arg3}: +% it defines a macro \arg1{name}{arg} which prints name in keyword +% style followed byt arg surrounded by arg2 and arg3. The main +% application is to a function working as \SetKwInput to be used +% in the head of the algorithm. For example +% \SetKwInParam{Func}{(}{)} allows +% \Func{functionname}{list of arguments} which prints: +% \KwSty{functioname(}list of arguments\KwSty{)} +% +% +% - November 27 1996 - revision 2.21 : +% minor bug in length of InOut boxes fixed. +% add algorithm* environment. +% +% - July 12 1996 - revision 2.2 : \SetArg and \SetKwArg macros removed. +% +% \SetArg has been removed since it never has been +% documented. +% \SetKwArg has been removed since \SetKw can now +% take an argument in order to be consistent with +% \SetKwData and \SetKwFunction macros. +% +% - July 04 1996 - revision 2.1 : still more LaTeX2e! Minor compatibility break +% +% Macros use now \newcommand instead of \def, use of \setlength, +% \newsavebox, ... and other LaTeX2e specific stuff. +% The compatibility break: +% - \SetData becomes \SetKwData to be more consistent. So the old +% \SetKwData becomes \SetKwInput +% - old macros \titleofalgo, \Freetitleofalgo and \freetitleofalgo +% from LaTeX209 version which did print a warning message and call +% \Titleofalgo in version 2.0 are now removed! +% +% - March 13 1996 - revision 2.0: first official major revision. +% +% +%%%%%%%%%%%%%% +% +% Known bugs: +% ----------- +% - no more known bugs... all are corrected! +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% for more complete informations you can see algorithm2e.tex +% +% +%%%%%%%%%%%%%%%%%%%%%%%% Identification Part %%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +\NeedsTeXFormat{LaTeX2e}[1994/12/01] +% +\ProvidesPackage{algorithm2e}[2008/00/00 v3.10 algorithms environments] +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%% Initial Code %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +\@makeother\*% some package redefined it as a letter (as color.sty) +\def\@firstword#1 #2\@nil{#1}% an useful fonction +% +% definition of commands which can be redefined in options of the package. +% +\newcounter{AlgoLine}% +\setcounter{AlgoLine}{0}% +% +\newcommand{\algocf@algocfref}{\relax}% +\newcommand{\listalgorithmcfname}{}% +\newcommand{\algorithmcfname}{}% +\@ifundefined{algorithmautorefname}{\newcommand{\algorithmautorefname}{algorithm}}{\renewcommand{\algorithmautorefname}{algorithm}}% +\newcommand{\algorithmcflinename}{}% +\newcommand{\algocf@typo}{}% +\newcommand{\@algocf@procname}{}\newcommand{\procedureautorefname}{}% +\newcommand{\SetAlgoProcName}[2]{\renewcommand{\@algocf@procname}{#1}\renewcommand{\procedureautorefname}{#2}}% +\newcommand{\@algocf@funcname}{}\newcommand{\functionautorefname}{}% +\newcommand{\SetAlgoFuncName}[2]{\renewcommand{\@algocf@funcname}{#1}\renewcommand{\functionautorefname}{#2}}% +\newcommand{\@algocf@titleofalgoname}{\algorithmcfname}% +\newcommand{\@algocf@algotitleofalgo}{% + \renewcommand{\@algocf@titleofalgoname}{\algorithmcfname}}% +\newcommand{\@algocf@proctitleofalgo}{% + \renewcommand{\@algocf@titleofalgoname}{\algocf@procname}}% +% +\newcommand{\algocf@style}{plain}% +\newcommand{\@ResetCounterIfNeeded}{}% +\newcommand{\@titleprefix}{}% +% +\newcommand{\algocf@numbering}[1]{\newcommand{\algocf@within}{#1}}% +% +\newcommand{\defaultsmacros@algo}{\algocf@defaults@shortend}% +% +\newcommand{\algocf@list}{loa}% +\newcommand{\algocf@float}{algocf}% +% +\newcommand{\algocf@envname}{algorithm}% +\newcommand{\algocf@listofalgorithms}{listofalgorithms}% +% +% +%% redefine chapter so that it adds a vspace in the loa as the original does for lof and lot +\let\algocf@original@chapter=\chapter% +\def\chapter{\expandafter\addtocontents{loa}{\protect\addvspace{10\p@}}\algocf@original@chapter}% +% +%% if@restonecol is defined in article and book but some other classes don't define it and we need it, so we do +\ifx\if@restonecol\relax\else\newif\if@restonecol\fi% +% +% +%%%%%%%%%%%%%%%%%%%%%% Declaration of Options %%%%%%%%%%%%%%%%%%%%%%%%%%% +% +\RequirePackage{ifthen}% +% +\newboolean{algocf@nokwfunc}\setboolean{algocf@nokwfunc}{false}% +\DeclareOption{nokwfunc}{% + \setboolean{algocf@nokwfunc}{true}% +}% +% +\newboolean{algocf@oldcommands}\setboolean{algocf@oldcommands}{false}% +\DeclareOption{oldcommands}{% + \setboolean{algocf@oldcommands}{true}% +}% +% +\newboolean{algocf@leftlinenumber}\setboolean{algocf@leftlinenumber}{true}% +\newcommand{\setLeftLinesNumbers}{\setboolean{algocf@leftlinenumber}{true}}% +\newcommand{\setRightLinesNumbers}{\setboolean{algocf@leftlinenumber}{false}}% +\DeclareOption{rightnl}{% + \setRightLinesNumbers% +}% +% +\newboolean{algocf@endfloat}\setboolean{algocf@endfloat}{false}% +\DeclareOption{endfloat}{% + \setboolean{algocf@endfloat}{true}% + \newcounter{postalgo}\setcounter{postalgo}{0}% +}% +% +\newboolean{algocf@procnumbered}\setboolean{algocf@procnumbered}{false}% +\DeclareOption{procnumbered}{% + \setboolean{algocf@procnumbered}{true}% +}% +% +\DeclareOption{algo2e}{% + \renewcommand{\algocf@envname}{algorithm2e}% + \renewcommand{\algocf@listofalgorithms}{listofalgorithmes}% +}% +% +\newboolean{algocf@slide}\setboolean{algocf@slide}{false}% +\DeclareOption{slide}{% + \setboolean{algocf@slide}{true}% +}% +% +\DeclareOption{figure}{% +\renewcommand{\algocf@list}{lof}% +\renewcommand{\algocf@float}{figure}% +}% +% +\newboolean{algocf@optonelanguage}\setboolean{algocf@optonelanguage}{false}% +\DeclareOption{onelanguage}{\setboolean{algocf@optonelanguage}{true}}% +% +\newcommand{\algocf@languagechoosen}{english}% +% +\DeclareOption{english}{% +\renewcommand{\listalgorithmcfname}{List of Algorithms}% +\renewcommand{\algorithmcfname}{Algorithm}% +\renewcommand{\algorithmautorefname}{algorithm}% +\renewcommand{\algorithmcflinename}{line}% +\renewcommand{\algocf@typo}{}% +\renewcommand{\@algocf@procname}{Procedure}% +\renewcommand{\@algocf@funcname}{Function}% +\renewcommand{\procedureautorefname}{procedure}% +\renewcommand{\functionautorefname}{function}% +\renewcommand{\algocf@languagechoosen}{english}% +}% +% +\DeclareOption{french}{% +\renewcommand{\listalgorithmcfname}{Liste des Algorithmes}% +\renewcommand{\algorithmcfname}{Algorithme}% +\renewcommand{\algorithmautorefname}{algorithme}% +\renewcommand{\algorithmcflinename}{ligne}% +\renewcommand{\algocf@typo}{\ }% +\renewcommand{\@algocf@procname}{Procédure}% +\renewcommand{\@algocf@funcname}{Fonction}% +\renewcommand{\procedureautorefname}{procédure}% +\renewcommand{\functionautorefname}{fonction}% +\renewcommand{\algocf@languagechoosen}{french}% +}% +% +\DeclareOption{czech}{% +\renewcommand{\listalgorithmcfname}{Seznam algoritm\v{u}}% +\renewcommand{\algorithmcfname}{Algoritmus}% +\renewcommand{\algorithmautorefname}{\algorithmcfname}% +\renewcommand{\algorithmcflinename}{Radek}% +\renewcommand{\algocf@typo}{}% +\renewcommand{\@algocf@procname}{Procedura}% +\renewcommand{\@algocf@funcname}{Funkce}% +\renewcommand{\procedureautorefname}{\@algocf@procname}% +\renewcommand{\functionautorefname}{\@algocf@funcname}% +\renewcommand{\algocf@languagechoosen}{czech}% +}% +% +\DeclareOption{german}{% +\renewcommand{\listalgorithmcfname}{Liste der Algorithmen}% +\renewcommand{\algorithmcfname}{Algorithmus}% +\renewcommand{\algorithmautorefname}{\algorithmcfname}% +\renewcommand{\algorithmcflinename}{Zeile}% +\renewcommand{\algocf@typo}{\ }% +\renewcommand{\@algocf@procname}{Prozedur}% +\renewcommand{\@algocf@funcname}{Funktion}% +\renewcommand{\procedureautorefname}{\@algocf@procname}% +\renewcommand{\functionautorefname}{\@algocf@funcname}% +\renewcommand{\algocf@languagechoosen}{german}% +}% +% +\DeclareOption{portuguese}{% +\renewcommand{\listalgorithmcfname}{Lista de Algoritmos}% +\renewcommand{\algorithmcfname}{Algoritmo}% +\renewcommand{\algorithmautorefname}{algoritmo}% +\renewcommand{\algorithmcflinename}{linha}% +\renewcommand{\algocf@typo}{}% +\renewcommand{\@algocf@procname}{Procedimento}% +\renewcommand{\@algocf@funcname}{Fun\c{c}\~{a}o}% +\renewcommand{\procedureautorefname}{procedimento}% +\renewcommand{\functionautorefname}{fun\c{c}\~{a}o}% +\renewcommand{\algocf@languagechoosen}{portuguese}% +}% +% +\DeclareOption{italiano}{% +\renewcommand{\listalgorithmcfname}{Elenco degli algoritmi}% +\renewcommand{\algorithmcfname}{Algoritmo}% +\renewcommand{\algorithmautorefname}{algoritmo}% +\renewcommand{\algorithmcflinename}{riga}% +\renewcommand{\algocf@typo}{}% +\renewcommand{\@algocf@procname}{Procedura}% +\renewcommand{\@algocf@funcname}{Funzione}% +\renewcommand{\procedureautorefname}{procedura}% +\renewcommand{\functionautorefname}{funzione}% +\renewcommand{\algocf@languagechoosen}{italiano}% +}% +\DeclareOption{slovak}{% +\renewcommand{\listalgorithmcfname}{Zoznam algoritmov}% +\renewcommand{\algorithmcfname}{Algoritmus}% +\renewcommand{\algorithmautorefname}{\algorithmcfname}% +\renewcommand{\algorithmcflinename}{Radek}% +\renewcommand{\algocf@typo}{}% +\renewcommand{\@algocf@procname}{Proced\'{u}ra}% +\renewcommand{\@algocf@funcname}{Funkcia}% +\renewcommand{\procedureautorefname}{\@algocf@procname}% +\renewcommand{\functionautorefname}{\@algocf@funcname}% +\renewcommand{\algocf@languagechoosen}{slovak}% +}% +% +% OPTIONs plain, boxed, ruled, algoruled & boxruled +% +\newcommand{\algocf@style@plain}{\renewcommand{\algocf@style}{plain}}% +\newcommand{\algocf@style@boxed}{\renewcommand{\algocf@style}{boxed}}% +\newcommand{\algocf@style@ruled}{\renewcommand{\algocf@style}{ruled}}% +\newcommand{\algocf@style@algoruled}{\renewcommand{\algocf@style}{algoruled}}% +\newcommand{\algocf@style@boxruled}{\renewcommand{\algocf@style}{boxruled}}% +\newcommand{\algocf@style@tworuled}{\renewcommand{\algocf@style}{tworuled}}% +\newcommand{\RestyleAlgo}[1]{\csname algocf@style@#1\endcsname}% +\DeclareOption{plain}{\algocf@style@plain}% +\DeclareOption{boxed}{\algocf@style@boxed}% +\DeclareOption{ruled}{\algocf@style@ruled}% +\DeclareOption{algoruled}{\algocf@style@algoruled}% +\DeclareOption{boxruled}{\algocf@style@boxruled}% +\DeclareOption{tworuled}{\algocf@style@tworuled}% +% +% OPTIONs algopart,algochapter & algosection +% +\DeclareOption{algopart}{\algocf@numbering{part}}% %algo part numbered +\DeclareOption{algochapter}{\algocf@numbering{chapter}}% %algo chapter numbered +\DeclareOption{algosection}{\algocf@numbering{section}}% %algo section numbered +% +% OPTIONs resetcount & noresetcount +% +\DeclareOption{resetcount}{\renewcommand{\@ResetCounterIfNeeded}{\setcounter{AlgoLine}{0}}}% +\DeclareOption{noresetcount}{\renewcommand{\@ResetCounterIfNeeded}{}}% +% +% OPTION linesnumbered +% +\newboolean{algocf@linesnumbered}\setboolean{algocf@linesnumbered}{false}% +\newcommand{\algocf@linesnumbered}{\relax}% +\DeclareOption{linesnumbered}{% + \setboolean{algocf@linesnumbered}{true}% + \renewcommand{\algocf@linesnumbered}{\everypar={\nl}}% +}% +% +% OPTION linesnumberedhidden +% +\DeclareOption{linesnumberedhidden}{% + \setboolean{algocf@linesnumbered}{true}% + \renewcommand{\algocf@linesnumbered}{\everypar{\stepcounter{AlgoLine}}}% +}% +% +% OPTION commentsnumbered inoutnumbered +% +\newboolean{algocf@commentsnumbered}\setboolean{algocf@commentsnumbered}{false}% +\DeclareOption{commentsnumbered}{\setboolean{algocf@commentsnumbered}{true}}% +\newboolean{algocf@inoutnumbered}\setboolean{algocf@inoutnumbered}{false}% +\DeclareOption{inoutnumbered}{\setboolean{algocf@inoutnumbered}{true}}% +% +% OPTIONs titlenumbered & titlenotnumbered +% +\DeclareOption{titlenumbered}{% + \renewcommand{\@titleprefix}{% + \refstepcounter{\algocf@float}% + \AlTitleSty{\AlTitleFnt\@algocf@titleofalgoname\ \expandafter\csname the\algocf@float\endcsname\algocf@typo: }% + }% +}% +% +\DeclareOption{titlenotnumbered}{\renewcommand{\@titleprefix}{% + \AlTitleSty{\AlTitleFnt\@algocf@titleofalgoname\algocf@typo: }}% +}% +% +% OPTIONs algonl +% line numbered with the counter of the algorithm +% +\DeclareOption{algonl}{\renewcommand{\theAlgoLine}{\expandafter\csname the\algocf@float\endcsname.\arabic{AlgoLine}}}% +% +% OPTIONs lined, vlined & noline +% +\DeclareOption{lined}{\AtBeginDocument{\SetAlgoLined}}% \SetAlgoLined +\DeclareOption{vlined}{\AtBeginDocument{\SetAlgoVlined}}% \SetAlgoVlined +\DeclareOption{noline}{\AtBeginDocument{\SetAlgoNoLine}}%\SetAlgoNoLine (default) +% +% OPTIONs longend, shotend & noend +% +\DeclareOption{longend}{\AtBeginDocument{\SetAlgoLongEnd}}% \SetAlgoLongEnd +\DeclareOption{shortend}{\AtBeginDocument{\SetAlgoShortEnd}}%\SetAlgoShortEnd +\DeclareOption{noend}{\AtBeginDocument{\SetAlgoNoEnd}}% \SetAlgoNoEnd +% +% OPTION dotoc +% +\newboolean{algocf@dotocloa}\setboolean{algocf@dotocloa}{false}% +\DeclareOption{dotocloa}{% + \setboolean{algocf@dotocloa}{true}% +} +% +% OPTION comments +% +\newboolean{algocf@optfillcomment}\setboolean{algocf@optfillcomment}{true}% +\DeclareOption{nofillcomment}{% + \setboolean{algocf@optfillcomment}{false}% +}% +\DeclareOption{fillcomment}{% + \setboolean{algocf@optfillcomment}{true}% +}% +% +% OPTION sidecommments +% +\newboolean{algocf@scleft}\setboolean{algocf@scleft}{false}% +\DeclareOption{scleft}{% + \setboolean{algocf@scleft}{true}% +}% +\DeclareOption{sright}{% default + \setboolean{algocf@scleft}{false}% +}% +% +% OPTION norelsize +% +\newboolean{algocf@norelsize}\setboolean{algocf@norelsize}{false}% +\DeclareOption{norelsize}{% + \setboolean{algocf@norelsize}{true}% +}% +% +% +%%%%%%%%%%%%%%%%%%%%%%% Execution of Options %%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +\ExecuteOptions{english,plain,resetcount,titlenotnumbered,lined,shortend}% +% +\ProcessOptions% +% +\@algocf@algotitleofalgo% fix name for \TitleOfAlgo to \algorithmcfname by default +% +%%%%%%%%%%%%%%%%%%%%%%%%%% Package Loading %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% +\RequirePackage{xspace}% +% +\ifthenelse{\boolean{algocf@endfloat}}{% + \RequirePackage{endfloat}% +}{\relax}% +% +\ifthenelse{\boolean{algocf@norelsize}}{% + \newcommand{\relsize}[1]{\scriptsize}% +}{% + \RequirePackage{relsize}% +}% +% +\ifthenelse{\boolean{algocf@slide}}{\RequirePackage{color}}{}% +% + +\AtEndOfPackage{% + \ifthenelse{\boolean{algocf@dotocloa}}{% + \renewcommand{\listofalgorithmes}{\tocfile{\listalgorithmcfname}{loa}}% + }{\relax}% +}% +% +% if loa in toc required, load tocbibind package if not already done. +\ifthenelse{\boolean{algocf@dotocloa}}{% + \ifx\@tocextra\undefined% + \RequirePackage{tocbibind}% + \fi% +}% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Main Part %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +\newcommand{\algocf@name}{algorithm2e}% +\newcommand{\algocf@date}{december 14 2009}% +\newcommand{\algocf@version}{Release 4.01}% +\newcommand{\algocf@id}{\algocf@version\space -- \algocf@date\space --}% +\typeout{********************************************************^^JPackage `\algocf@name'\space\algocf@id^^J% + - algorithm2e-announce@lirmm.fr mailing list for announcement about releases^^J% + - algorithm2e-discussion@lirmm.fr mailing list for discussion about package^^J% + subscribe by emailing sympa@lirmm.fr with 'subscribe '^^J% + - Author: Christophe Fiorio (fiorio@lirmm.fr)^^J********************************************************}% +%% +%% +%% +%% +%% +%% +%%%% hyperref compatibility tricks: Hyperref package defines H counters from + % standard counters (i.e \theHpage from \thepage) and check some particular + % counters of some packages, unfortunately it doesn't do the same for + % algorithm2e package but act as Hcounter was defined. To avoid errors we + % defined \theHalgocf ourself +%%%% +% +\@ifundefined{theHalgocf}{\def\theHalgocf{\thealgocf}}{}% +\@ifundefined{theHAlgoLine}{\def\theHAlgoLine{\theAlgoLine}}{}% +\@ifundefined{theHalgocfproc}{\def\theHalgocfproc{0}}{}% +\@ifundefined{theHalgocffunc}{\def\theHalgocffunc{0}}{}% +\@ifundefined{toclevel@algocf}{\def\toclevel@algocf{0}}{}% +% +% autoref from hyperref needs an autorefname, so we give it. +\def\AlgoLineautorefname{\algorithmcflinename}% +\def\algocfautorefname{\algorithmautorefname}% +\def\algocfprocautorefname{\procedureautorefname}% +\def\algocffuncautorefname{\functionautorefname}% +%% +%% +%% +\newcommand{\@defaultskiptotal}{0.5em}% +\newskip\skiptotal\skiptotal=0.5em% +\newskip\skiplinenumber\skiplinenumber=\hsize\advance\skiplinenumber by-\skiptotal% +\newskip\skiprule% +\newskip\skiphlne% +\newskip\skiptext% +\newskip\skiplength% +\newskip\algomargin% +\newskip\skipalgocfslide\skipalgocfslide=1em% +\newdimen\algowidth% +\newdimen\inoutsize% +\newdimen\inoutline% +\newdimen\interspacetitleruled\setlength{\interspacetitleruled}{2pt}% +\newdimen\interspacealgoruled\setlength{\interspacealgoruled}{2pt}% +\newdimen\interspacetitleboxruled\setlength{\interspacetitleboxruled}{2\lineskip}% +% +\newcommand{\@algoskip}{\smallskip}% +\newcommand{\SetAlgoSkip}[1]{\renewcommand{\@algoskip}{\csname#1\endcsname}}% +\newcommand{\@algoinsideskip}{\relax}% +\newcommand{\SetAlgoInsideSkip}[1]{\renewcommand{\@algoinsideskip}{\csname#1\endcsname}}% +% +\newsavebox{\algocf@inoutbox}% +\newsavebox{\algocf@inputbox}% +%% +%% +\newcommand{\arg@e}{}% +\newcommand{\arg@space}{\ }% +\newcommand{\BlankLine}{\vskip 1ex}% +%% +\newcommand{\vespace}{1ex}% +\newcommand{\SetInd}[2]{% +\skiprule=#1% +\skiptext=#2% +\skiplength=\skiptext\advance\skiplength by \skiprule\advance\skiplength by 0.4pt}% +\SetInd{0.5em}{1em} +\algomargin=\leftskip\advance\algomargin by \parindent% +\newcommand{\IncMargin}[1]{\advance\algomargin by #1}% +\newcommand{\DecMargin}[1]{\advance\algomargin by -#1}% +\newcommand{\SetNlSkip}[1]{% + \renewcommand{\@defaultskiptotal}{#1}% + \setlength{\skiptotal}{#1}}% +%% +\newskip\AlCapSkip\AlCapSkip=0ex% +\newskip\AlCapHSkip\AlCapSkip=0ex% +\newcommand{\SetAlCapSkip}[1]{\setlength{\AlCapSkip}{#1}}% +\newcommand{\SetAlCapHSkip}[1]{\setlength{\AlCapHSkip}{#1}}% +\SetAlCapHSkip{.5\algomargin}% +%% +%% +\newcommand{\Indentp}[1]{\advance\leftskip by #1}% +\newcommand{\Indp}{\advance\leftskip by 1em}% +\newcommand{\Indpp}{\advance\leftskip by 0.5em}% +\newcommand{\Indm}{\advance\leftskip by -1em}% +\newcommand{\Indmm}{\advance\leftskip by -0.5em}% +%% +%% +%% Line Numbering +%% +%% +% number line style +\newcommand{\algocf@nlrelsize}{-2}\newcommand{\SetAlgoNlRelativeSize}[1]{\renewcommand{\algocf@nlrelsize}{#1}}% +\newcommand{\NlSty}[1]{\textnormal{\textbf{\relsize{\algocf@nlrelsize}#1}}}% default definition +\newcommand{\SetNlSty}[3]{\renewcommand{\NlSty}[1]{\textnormal{\csname#1\endcsname{\relsize{\algocf@nlrelsize}#2##1#3}}}}% +% +% nl definitions +% +\newsavebox{\algocf@nlbox}% +\newcommand{\algocf@printnl}[1]{% + \ifthenelse{\boolean{algocf@leftlinenumber}}{% + \skiplinenumber=\skiptotal\advance\skiplinenumber by\leftskip% + \strut\raisebox{0pt}{\llap{\NlSty{#1}\kern\skiplinenumber}}\ignorespaces% + }{% + \sbox\algocf@nlbox{\NlSty{#1}}% + \skiplinenumber=\hsize\advance\skiplinenumber by-\leftskip\advance\skiplinenumber by-\skiptext% + \advance\skiplinenumber by\algomargin\advance\skiplinenumber by.3em\advance\skiplinenumber by-\wd\algocf@nlbox% + \strut\raisebox{0pt}{\rlap{\kern\skiplinenumber\NlSty{#1\ignorespaces}}}\ignorespaces% + }% +}% +\newcommand{\algocf@nl@sethref}[1]{% + \renewcommand{\theHAlgoLine}{\thealgocfproc.#1}% + \hyper@refstepcounter{AlgoLine}\gdef\@currentlabel{#1}% +}% +\newcommand{\nl}{% + \@ifundefined{hyper@refstepcounter}{% if not hyperref then do a simple refstepcounter + \refstepcounter{AlgoLine}% + }{% else if hyperref, do the anchor so 2 lines in two differents algorithms cannot have the same href + \stepcounter{AlgoLine}\algocf@nl@sethref{\theAlgoLine}% + }% now we can do the line numbering + \algocf@printnl{\theAlgoLine}% +}% +% +\newcommand{\nllabel}[1]{\label{#1}}% +% +\newcommand{\enl}{% + \@ifundefined{hyper@refstepcounte}{% if not hyperref then do a simple refstepcounter + \refstepcounter{AlgoLine}% + }{% else if hyperref, do the anchor so 2 lines in two differents algorithms cannot have the same href + \stepcounter{AlgoLine}\algocf@nl@sethref{\theAlgoLine}% + }% now we can do the line numbering + \skiplinenumber=\hsize\advance\skiplinenumber by-\leftskip% + \strut\raisebox{0pt}{\rlap{\kern\skiplinenumber\strut\NlSty{\theAlgoLine}}}\ignorespaces% +} +%% nlset +\newcommand{\nlset}[1]{% + \@ifundefined{hyper@refstepcounter}{\protected@edef\@currentlabel{#1}}{\algocf@nl@sethref{#1}}\algocf@printnl{#1}% +}% +% +%% lnl definitions +\newcommand{\lnl}[1]{\nl\label{#1}}% +% +%% lnlset +\newcommand{\lnlset}[2]{\nlset{#2}\label{#1}}% +% +% set char put at end of each line +% +\newcommand{\algocf@endline}{\string;} +\newcommand{\SetEndCharOfAlgoLine}[1]{\renewcommand{\algocf@endline}{#1}} +% +% end of line definition +% +\newcommand{\@endalgocfline}{\algocf@endline}% default definition: printsemicolon +\newcommand{\DontPrintSemicolon}{\renewcommand{\@endalgocfline}{\relax}}% +\newcommand{\PrintSemicolon}{\renewcommand{\@endalgocfline}{\algocf@endline}}% +\newcommand{\@endalgoln}{\@endalgocfline\hfill\strut\par}% +% +% line numbering +% +\newcommand{\LinesNumbered}{\setboolean{algocf@linesnumbered}{true}\renewcommand{\algocf@linesnumbered}{\everypar={\nl}}}% +\newcommand{\LinesNotNumbered}{% + \setboolean{algocf@linesnumbered}{false}% + \renewcommand{\algocf@linesnumbered}{\relax}% +}% +% +\newcommand{\LinesNumberedHidden}{% + \setboolean{algocf@linesnumbered}{true}\renewcommand{\algocf@linesnumbered}{\everypar{\stepcounter{AlgoLine}}}}% +\newcommand{\ShowLn}{\nlset{\theAlgoLine}\ignorespaces}% display the line number on this line (without labelling) +\newcommand{\ShowLnLabel}[1]{\lnlset{#1}{\theAlgoLine}\ignorespaces}% display the line number and label this line +% +%% +% +%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% Styling text commands +% +\newcommand{\AlFnt}{\relax}% default definition +\newcommand{\SetAlFnt}[1]{\renewcommand{\AlFnt}{#1}}% +\newcommand{\AlTitleFnt}{\relax}% default definition +\newcommand{\SetAlTitleFnt}[1]{\renewcommand{\AlTitleFnt}{#1}}% +% +\newcommand{\AlCapFnt}{\relax}% default definition +\newcommand{\SetAlCapFnt}[1]{\renewcommand{\AlCapFnt}{#1}}% +\newcommand{\AlCapNameFnt}{\relax}% default definition +\newcommand{\SetAlCapNameFnt}[1]{\renewcommand{\AlCapNameFnt}{#1}}% +% +\newcommand{\ProcFnt}{\relax}% default definition +\newcommand{\SetProcFnt}[1]{\renewcommand{\ProcFnt}{#1}}% +\newcommand{\ProcNameFnt}{\relax}% default definition +\newcommand{\SetProcNameFnt}[1]{\renewcommand{\ProcNameFnt}{#1}}% +\newcommand{\ProcArgFnt}{\relax}% default definition +\newcommand{\SetProcArgFnt}[1]{\renewcommand{\ProcArgFnt}{#1}}% +% +\newcommand{\AlTitleSty}[1]{\textbf{#1}\unskip}% default definition +\newcommand{\SetAlTitleSty}[1]{\renewcommand{\AlTitleSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +\newcommand{\AlCapSty}[1]{\textnormal{\textbf{#1}}\unskip}% default definition +\newcommand{\SetAlCapSty}[1]{\renewcommand{\AlCapSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +\newcommand{\AlCapNameSty}[1]{\textnormal{#1}\unskip}% default definition +\newcommand{\SetAlCapNameSty}[1]{\renewcommand{\AlCapNameSty}[1]{\textnormal{\csname #1\endcsname{##1}}\unskip}}% +% +\newcommand{\ProcSty}[1]{\AlCapSty{#1}}% +\newcommand{\SetProcSty}[1]{\renewcommand{\ProcSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +\newcommand{\ProcNameSty}[1]{\AlCapNameSty{#1}}% +\newcommand{\SetProcNameSty}[1]{\renewcommand{\ProcNameSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +\newcommand{\ProcArgSty}[1]{\AlCapNameSty{#1}}% +\newcommand{\SetProcArgSty}[1]{\renewcommand{\ProcArgSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +% +\newcommand{\KwSty}[1]{\textnormal{\textbf{#1}}\unskip}% default definition +\newcommand{\SetKwSty}[1]{\renewcommand{\KwSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +\newcommand{\ArgSty}[1]{\textnormal{\emph{#1}}\unskip}%\SetArgSty{emph} +\newcommand{\SetArgSty}[1]{\renewcommand{\ArgSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +\newcommand{\FuncSty}[1]{\textnormal{\texttt{#1}}\unskip}%\SetFuncSty{texttt} +\newcommand{\SetFuncSty}[1]{\renewcommand{\FuncSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +\newcommand{\DataSty}[1]{\textnormal{\textsf{#1}}\unskip}%%\SetDataSty{textsf} +\newcommand{\SetDataSty}[1]{\renewcommand{\DataSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +\newcommand{\CommentSty}[1]{\textnormal{\texttt{#1}}\unskip}%%\SetDataSty{texttt} +\newcommand{\SetCommentSty}[1]{\renewcommand{\CommentSty}[1]{\textnormal{\csname#1\endcsname{##1}}\unskip}}% +\newcommand{\TitleSty}[1]{#1\unskip}%\SetTitleSty{}{} +\newcommand{\SetTitleSty}[2]{\renewcommand{\TitleSty}[1]{% +\csname#1\endcsname{\csname#2\endcsname##1}}\unskip}% +% +%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% Block basic commands +% +\newcommand{\algocf@push}[1]{\advance\skiptotal by #1\moveright #1}% +\newcommand{\algocf@pop}[1]{\advance\skiptotal by -#1}% +\newcommand{\algocf@addskiptotal}{\advance\skiptotal by 0.4pt\advance\hsize by -0.4pt}% 0.4 pt=width of \vrule +\newcommand{\algocf@subskiptotal}{\advance\skiptotal by -0.4pt\advance\hsize by 0.4pt}% 0.4 pt=width of \vrule +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% +%% group of instructions definition +% +\skiphlne=.8ex% +\newcommand{\SetVlineSkip}[1]{\skiphlne=#1}% +% +%% block with a vertical line end by a little horizontal line +\newcommand{\algocf@Vline}[1]{% no vskip in between boxes but a strut to separate them, + \strut\par\nointerlineskip% then interblock space stay the same whatever is inside it + \algocf@push{\skiprule}% move to the right before the vertical rule + \hbox{\vrule% + \vtop{\algocf@push{\skiptext}%move the right after the rule + \vtop{\algocf@addskiptotal\advance\hsize by -\skiplength #1}\Hlne}}\vskip\skiphlne% inside the block + \algocf@pop{\skiprule}%\algocf@subskiptotal% restore indentation + \nointerlineskip}% no vskip after +% +%% block with a vertical line +\newcommand{\algocf@Vsline}[1]{% no vskip in between boxes but a strut to separate them, + \strut\par\nointerlineskip% then interblock space stay the same whatever is inside it + \algocf@push{\skiprule}% move to the right before the vertical rule + \hbox{\vrule% the vertical rule + \vtop{\algocf@push{\skiptext}%move the right after the rule + \vtop{\algocf@addskiptotal\advance\hsize by -\skiplength #1}}}% inside the block + \algocf@pop{\skiprule}}% restore indentation +% +\newcommand{\algocf@Hlne}{\hrule height 0.4pt depth 0pt width .5em}% +% +%% block without line +\newcommand{\algocf@Noline}[1]{% no vskip in between boxes but a strut to separate them, + \strut\par\nointerlineskip% then interblock space stay the same whatever is inside it + \algocf@push{\skiprule}% + \hbox{% + \vtop{\algocf@push{\skiptext}% + \vtop{\advance\hsize by -\skiplength #1}}}% inside the block + \algocf@pop{\skiprule}% + % \nointerlineskip% no vskip after +}% +% +%% default=NoLine +% +\newcommand{\algocf@group}[1]{\algocf@Noline{##1}}% group: set of instruction depending from another (ex: then part of the If) +\newcommand{\algocf@@block}[2]{\algocf@Noline{##1}\KwSty{##2}\par}% block: group with a end keyword. +\newcommand{\algocf@block}[2]{\algocf@@block{#1}{#2}}% command that will be used and redefined accordingly to noend option +\newcommand{\algocf@setBlock}{% + \ifthenelse{\boolean{algocf@optnoend}}{% if no end option + \renewcommand{\algocf@block}[2]{\algocf@group{##1}}% block will be a group + }{% else + \renewcommand{\algocf@block}[2]{\algocf@@block{##1}{##2}}% block stays a block + }% +}% +% +\newcommand{\Hlne}{}% little hrizontal line ending a block in vline mode +% +\newcommand{\@algocf@endoption}[1]{#1}% +\newboolean{algocf@optnoend}\setboolean{algocf@optnoend}{false}% +% +\newcommand{\SetAlgoLongEnd}{%%%%%%%%%%%%%%%%%%%%%%%%% Long End + \setboolean{algocf@optnoend}{false}% + \renewcommand{\@algocf@endoption}[1]{##1}% + \algocf@setBlock}% +% +\newcommand{\SetAlgoShortEnd}{%%%%%%%%%%%%%%%%%%%%%%%% ShortEnd + \setboolean{algocf@optnoend}{false}% + \renewcommand{\@algocf@endoption}[1]{\@firstword##1 \@nil}% + \algocf@setBlock}% +% +\newcommand{\SetAlgoNoEnd}{%%%%%%%%%%%%%%%%%%%%%%%%%%% NoEnd + \setboolean{algocf@optnoend}{true}% + \renewcommand{\@algocf@endoption}[1]{}% + \algocf@setBlock}% +% +\newcommand{\SetAlgoNoLine}{%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Noline +\renewcommand{\algocf@@block}[2]{\algocf@Noline{##1}\KwSty{##2}\strut\par}% +\renewcommand{\algocf@group}[1]{\algocf@Noline{##1}}% +\renewcommand{\Hlne}{}}% +% +\newcommand{\SetAlgoVlined}{%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Vline +\renewcommand{\algocf@@block}[2]{\algocf@Vline{##1}}% +\renewcommand{\algocf@group}[1]{\algocf@Vsline{##1}\ifthenelse{\boolean{algocf@optnoend}}{\relax}{\strut\ignorespaces}}% +\renewcommand{\Hlne}{\algocf@Hlne}}% +% +\newcommand{\SetAlgoLined}{%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Line +\renewcommand{\algocf@@block}[2]{\strut\algocf@Vsline{##1}\KwSty{##2}\strut\par}% no skip after a block so garantie at least a line +\renewcommand{\algocf@group}[1]{\algocf@Vsline{##1}\ifthenelse{\boolean{algocf@optnoend}}{\relax}{\strut\ignorespaces}}% +\renewcommand{\Hlne}{}}% +% +\newcommand{\SetNothing}{%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Noline +\renewcommand{\algocf@@block}[2]{\algocf@Noline{##1}\par}% +%\long +\renewcommand{\algocf@group}[1]{\algocf@Noline{##1}}% +\renewcommand{\Hlne}{}}% +% +%% +%% +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% ``Input :'''s like command +% +%%% +% text staying at the right of the longer keyword of KwInOut commands +% (text of KwInOut commands are all vertically aligned) +% +\newcommand{\algocf@newinout}{\par\parindent=\wd\algocf@inoutbox}% to put right indentation after a \\ in the KwInOut +\newcommand{\SetKwInOut}[2]{% + \sbox\algocf@inoutbox{\KwSty{#2}\algocf@typo:}% + \expandafter\ifx\csname InOutSizeDefined\endcsname\relax% if first time used + \newcommand\InOutSizeDefined{}\setlength{\inoutsize}{\wd\algocf@inoutbox}% + \else% else keep the larger dimension + \ifdim\wd\algocf@inoutbox>\inoutsize\setlength{\inoutsize}{\wd\algocf@inoutbox}\fi% + \fi% the dimension of the box is now defined. + \@ifundefined{#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% + \expandafter\algocf@mkcmd\csname#1\endcsname[1]{% + \ifthenelse{\boolean{algocf@inoutnumbered}}{\relax}{\everypar={\relax}}% + {\let\\\algocf@newinout\hangindent=\wd\algocf@inoutbox\hangafter=1\parbox[t]{\inoutsize}{\KwSty{#2}\algocf@typo\hfill:}~##1\par}% + \algocf@linesnumbered% reset the numbering of the lines + }}% +% +%% allow to ajust the skip size of InOut +%% +\newcommand{\ResetInOut}[1]{% + \sbox\algocf@inoutbox{\hbox{\KwSty{#1}\algocf@typo:\ }}% + \setlength{\inoutsize}{\wd\algocf@inoutbox}% + }% +% +% +%%% +% text staying at the right of the keyword. +% +\newcommand{\algocf@newinput}{\par\parindent=\wd\algocf@inputbox}% to put right indentation after a \\ in the KwInput +\newcommand{\SetKwInput}[2]{% + \@ifundefined{#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% + \expandafter\algocf@mkcmd\csname#1\endcsname[1]{% + \sbox\algocf@inputbox{\hbox{\KwSty{#2}\algocf@typo: }}% + \ifthenelse{\boolean{algocf@inoutnumbered}}{\relax}{\everypar={\relax}}% + {\let\\\algocf@newinput\hangindent=\wd\algocf@inputbox\hangafter=1\unhbox\algocf@inputbox##1\par}% + \algocf@linesnumbered% reset the numbering of the lines + }}% +\newcommand{\SetKwData}[2]{% + \@ifundefined{#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% + \expandafter\algocf@mkcmd\csname @#1\endcsname[1]{\DataSty{#2(}\ArgSty{##1}\DataSty{)}}% + \expandafter\algocf@mkcmd\csname#1\endcsname{% + \@ifnextchar\bgroup{\csname @#1\endcsname}{\DataSty{#2}\xspace}}% + }% +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% tallent: +% +% Add following macros: +% \SetKwHangingKw: [kw] ------------ <= hanging determined by [kw] +% ------------ +% Should act like a combination of \SetKwInput and \SetKw. +% Based on \SetKwInput: +% - remove ':' at end of keyword +% - do not reset numbering +% - use separate savebox +\newsavebox{\algocf@hangingbox} +\newcommand{\algocf@newhanging}{\par\parindent=\wd\algocf@hangingbox}% to put right indentation after a \\ in the KwInput +\newcommand{\SetKwHangingKw}[2]{% + \@ifundefined{#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% + \expandafter\algocf@mkcmd\csname#1\endcsname[1]{% + \sbox\algocf@hangingbox{\hbox{\KwSty{#2}\algocf@typo\ }}% + {\let\\\algocf@newhanging\hangindent=\wd\algocf@hangingbox\hangafter=1\unhbox\algocf@hangingbox##1\;}% + }% +}% +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% Comments macros +% +%%%% +% comment in the text, first argument is the name of the macro, second is +% the text put before the comment, third is the text put at the end of the +% comment. +% +% first side comment justification +\newcommand{\SetSideCommentLeft}{\setboolean{algocf@scleft}{true}}% +\newcommand{\SetSideCommentRight}{\setboolean{algocf@scleft}{false}}% +\newcommand{\SetNoFillComment}{\setboolean{algocf@optfillcomment}{false}}% +\newcommand{\SetFillComment}{\setboolean{algocf@optfillcomment}{true}}% +% +% next comment and side comment +% +\newcommand{\algocf@endmarkcomment}{\relax}% +\newcommand{\algocf@fillcomment}{% + \ifthenelse{\boolean{algocf@optfillcomment}}{\hfill}{\relax}}% +% +\newcommand{\algocf@startcomment}{% + \hangindent=\wd\algocf@inputbox\hangafter=1\usebox\algocf@inputbox}% +\newcommand{\algocf@endcomment}{\algocf@fillcomment\algocf@endmarkcomment\ignorespaces\par}% +\newcommand{\algocf@endstartcomment}{\algocf@endcomment\algocf@startcomment\ignorespaces}% +% +\newboolean{algocf@sidecomment}% +\newboolean{algocf@altsidecomment}\setboolean{algocf@altsidecomment}{false}% +\newcommand{\algocf@scpar}{\ifthenelse{\boolean{algocf@altsidecomment}}{\relax}{\par}}% +\newcommand{\algocf@sclfill}{\ifthenelse{\boolean{algocf@scleft}}{\algocf@fillcomment}{\relax}}% +\newcommand{\algocf@scrfill}{\ifthenelse{\boolean{algocf@scleft}}{\relax}{\hfill}}% +\newcommand{\algocf@startsidecomment}{\usebox\algocf@inputbox}% +\newcommand{\algocf@endsidecomment}{\algocf@endmarkcomment\algocf@scpar}% +\newcommand{\algocf@endstartsidecomment}{% + \algocf@sclfill\algocf@endsidecomment% + \algocf@scrfill\algocf@startsidecomment\ignorespaces}% +% +\newcommand{\SetKwComment}[3]{% + % newcommand or renewcommand ? + \@ifundefined{#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% + %%% comment definition + \expandafter\algocf@mkcmd\csname algocf@#1\endcsname[1]{% + \sbox\algocf@inputbox{\CommentSty{\hbox{#2}}}% + \ifthenelse{\boolean{algocf@commentsnumbered}}{\relax}{\everypar={\relax}}% + {\renewcommand{\algocf@endmarkcomment}{#3}% + \let\\\algocf@endstartcomment% + \algocf@startcomment\CommentSty{% + \strut\ignorespaces##1\strut\algocf@fillcomment#3}\par}% + \algocf@linesnumbered% reset the numbering of the lines + }% + %%% side comment definitions + % option or not? + \expandafter\algocf@mkcmd\csname algocf@#1@star\endcsname{% + \@ifnextchar [{\csname algocf@#1@staropt\endcsname}{\csname algocf@#1@sidecomment\endcsname}% + }% + % manage option + \expandafter\def\csname algocf@#1@staropt\endcsname[##1]##2{% + \ifthenelse{\boolean{algocf@scleft}}{\setboolean{algocf@sidecomment}{true}}{\setboolean{algocf@sidecomment}{false}}% + \ifx##1h\setboolean{algocf@altsidecomment}{true}\SetSideCommentLeft\fi% + \ifx##1f\setboolean{algocf@altsidecomment}{true}\SetSideCommentRight\fi% + \ifx##1l\setboolean{algocf@altsidecomment}{false}\SetSideCommentLeft\fi% + \ifx##1r\setboolean{algocf@altsidecomment}{false}\SetSideCommentRight\fi% + \csname algocf@#1@sidecomment\endcsname{##2}% call sidecomment + \ifthenelse{\boolean{algocf@sidecomment}}{\setboolean{algocf@scleft}{true}}{\setboolean{algocf@scleft}{false}}% + \setboolean{algocf@altsidecomment}{false}% + }% + % side comment + \expandafter\algocf@mkcmd\csname algocf@#1@sidecomment\endcsname[1]{% + \sbox\algocf@inputbox{\CommentSty{\hbox{#2}}}% + \ifthenelse{\boolean{algocf@commentsnumbered}}{\relax}{\everypar={\relax}}% + {% + \renewcommand{\algocf@endmarkcomment}{#3}% + \let\\\algocf@endstartsidecomment% + % here is the comment + %\ifthenelse{\boolean{algocf@altsidecomment}}{\relax}{\algocf@endline\ }% + \ifthenelse{\boolean{algocf@altsidecomment}}{\relax}{\@endalgocfline\ }% + \algocf@scrfill\algocf@startsidecomment\CommentSty{% + \strut\ignorespaces##1\strut\algocf@sclfill#3}\algocf@scpar% + }% + \algocf@linesnumbered% reset the numbering of the lines + } + \expandafter\algocf@mkcmd\csname#1\endcsname{\@ifstar{\csname algocf@#1@star\endcsname}{\csname algocf@#1\endcsname}}% +}% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% Kw +% +\newcommand{\SetKw}[2]{% + \@ifundefined{#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% + \expandafter\algocf@mkcmd\csname @#1\endcsname[1]{\KwSty{#2} \ArgSty{##1}}% + \expandafter\algocf@mkcmd\csname#1\endcsname{% + \@ifnextchar\bgroup{\csname @#1\endcsname}{\KwSty{#2}\xspace}}% + }% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% KwFunction +% +\newcommand{\SetKwFunction}[2]{% +%%% use of gdef since newcommand doesn't manage to define the macro when SetKwFunction is used in \algocf@caption@proc + \expandafter\gdef\csname @#1\endcsname##1{\FuncSty{#2(}\ArgSty{##1}\FuncSty{)}}% + \expandafter\gdef\csname#1\endcsname{% + \@ifnextchar\bgroup{\csname @#1\endcsname}{\FuncSty{#2}\xspace}}% +}% +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% KwTab +% +\newcommand{\SetKwArray}[2]{% +%%% use of gdef since newcommand doesn't manage to define the macro when SetKwFunction is used in \algocf@caption@proc + \expandafter\gdef\csname @#1\endcsname##1{\DataSty{#2[}\ArgSty{##1}\DataSty{]}}% + \expandafter\gdef\csname#1\endcsname{% + \@ifnextchar\bgroup{\csname @#1\endcsname}{\DataSty{#2}\xspace}}% +}% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% KwBlock +% +\newcommand{\SetKwBlock}[3]{% +\@ifundefined{algocf@#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +% side text or not? +\expandafter\def\csname#1\endcsname{%Begin + \@ifnextchar({\csname algocf@#1opt\endcsname}{\csname algocf@#1\endcsname}}% +% with side text +\expandafter\def\csname algocf@#1opt\endcsname(##1)##2{% \Begin(){} + \KwSty{#2} ##1\algocf@block{##2}{\@algocf@endoption{#3}}% + \@ifnextchar({\csname algocf@#1end\endcsname}{\par}}% +% without side text at the beginning +\expandafter\algocf@mkcmd\csname algocf@#1\endcsname[1]{% \Begin{} + \KwSty{#2}\algocf@block{##1}{\@algocf@endoption{#3}}\@ifnextchar({\csname algocf@#1end\endcsname}{\par}}% +% side text at the end +\expandafter\def\csname algocf@#1end\endcsname(##1){% \Begin{} + \ ##1\par}% +}% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% For Switch +% +\newcommand{\SetKwSwitch}[8]{% #1=\Switch #2=\Case #3=\Other #4=swicth #5=case #6=do #7=otherwise #8=endsw +%%%% Switch +\@ifundefined{algocf@#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +% side text or not? +\expandafter\def\csname#1\endcsname{%Switch + \@ifnextchar({\csname algocf@#1opt\endcsname}{\csname algocf@#1\endcsname}}% +% with side text +\expandafter\def\csname algocf@#1opt\endcsname(##1)##2##3{% \Switch(){}{} + \KwSty{#4} \ArgSty{##2} \KwSty{#5} ##1\algocf@block{##3}{\@algocf@endoption{#8}}}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@#1\endcsname[2]{% \Switch{}{} + \KwSty{#4} \ArgSty{##1} \KwSty{#5}\algocf@block{##2}{\@algocf@endoption{#8}}}% +% side text at the end +\expandafter\def\csname algocf@#1end\endcsname(##1){% \Switch{}{}() +}% +% +%%%% Case +\@ifundefined{algocf@#2}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +% side text or not? +\expandafter\def\csname#2\endcsname{%Case + \@ifnextchar({\csname algocf@#2opt\endcsname}{\csname algocf@#2\endcsname}}% +\expandafter\def\csname u#2\endcsname{%uCase + \@ifnextchar({\csname algocf@u#2opt\endcsname}{\csname algocf@u#2\endcsname}}% +\expandafter\def\csname l#2\endcsname{%lCase + \@ifnextchar({\csname algocf@l#2opt\endcsname}{\csname algocf@l#2\endcsname}}% +% with side text +\expandafter\def\csname algocf@#2opt\endcsname(##1)##2##3{% \Case(){}{} + \KwSty{#6} \ArgSty{##2} ##1\algocf@block{##3}{\@algocf@endoption{#8}}}% +\expandafter\def\csname algocf@u#2opt\endcsname(##1)##2##3{% \uCase(){}{} + \KwSty{#6} \ArgSty{##2} ##1\algocf@group{##3}}% +\expandafter\def\csname algocf@l#2opt\endcsname(##1)##2##3{% \lCase(){}{} + \KwSty{#6} \ArgSty{##2} ##3\algocf@endline\ ##1\par}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@#2\endcsname[2]{% \Case{}{} + \KwSty{#6} \ArgSty{##1}\algocf@block{##2}{\@algocf@endoption{#8}}}% +\expandafter\algocf@mkcmd\csname algocf@u#2\endcsname[2]{% \uCase{}{} + \KwSty{#6} \ArgSty{##1}\algocf@group{##2}}% +\expandafter\algocf@mkcmd\csname algocf@l#2\endcsname[2]{% \lCase{}{} + \KwSty{#6} \ArgSty{##1} ##2}% +%%%% Other +\@ifundefined{algocf@#3}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +% side text or not? +\expandafter\def\csname#3\endcsname{%Other + \@ifnextchar({\csname algocf@#3opt\endcsname}{\csname algocf@#3\endcsname}}% +\expandafter\def\csname l#3\endcsname{%Other + \@ifnextchar({\csname algocf@l#3opt\endcsname}{\csname algocf@l#3\endcsname}}% +% with side text +\expandafter\def\csname algocf@#3opt\endcsname(##1)##2{% \Other(){}{} + \KwSty{#7} ##1\algocf@block{##2}{\@algocf@endoption{#8}}}% +\expandafter\def\csname algocf@l#3opt\endcsname(##1)##2{% \Other(){}{} + \KwSty{#7} ##2\algocf@endline\ ##1\par}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@#3\endcsname[1]{% default + \KwSty{#7}\algocf@block{##1}{\@algocf@endoption{#8}}}% +\expandafter\algocf@mkcmd\csname algocf@l#3\endcsname[1]{% ldefault + \KwSty{#7} ##1}% +}% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% If macros +% +\newcommand{\SetKwIF}[8]{% #1=\If #2=\ElseIf #3=\Else #4=if #5=then #6=elseif si #7=else #8=endif +% +% common text +\@ifundefined{#1@ifthen}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +\expandafter\algocf@mkcmd\csname #1@ifthen\endcsname[1]{% + \KwSty{#4} \ArgSty{##1} \KwSty{#5}}% +\expandafter\algocf@mkcmd\csname #1@endif\endcsname[1]{\algocf@block{##1}{\@algocf@endoption{#8}}}% +\expandafter\algocf@mkcmd\csname #1@noend\endcsname[1]{\algocf@group{##1}}% +\expandafter\algocf@mkcmd\csname #1@else\endcsname[1]{\algocf@group{##1}\KwSty{#7}}% +\@ifundefined{#2@elseif}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +\expandafter\algocf@mkcmd\csname #2@elseif\endcsname[1]{% + \KwSty{#6} \ArgSty{##1} \KwSty{#5}}% +\@ifundefined{#3@else}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +\expandafter\algocf@mkcmd\csname #3@else\endcsname{\KwSty{#7}}% +%%%% If then { } endif +% +\@ifundefined{algocf@#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +% side text or not? +\expandafter\def\csname#1\endcsname{% + \@ifnextchar({\csname algocf@#1opt\endcsname}{\csname algocf@#1\endcsname}}% +% with side text +\expandafter\def\csname algocf@#1opt\endcsname(##1)##2##3{% \If(){}{} + \csname #1@ifthen\endcsname{##2} ##1\csname #1@endif\endcsname{##3}}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@#1\endcsname[2]{% \If{}{} + \csname #1@ifthen\endcsname{##1}\csname #1@endif\endcsname{##2}}% +% +%%%% If then {} else {} endif +% +% side text or not? +\expandafter\def\csname e#1\endcsname{% + \@ifnextchar({\csname algocf@e#1thenopt\endcsname}{\csname algocf@e#1then\endcsname}}% +% with side text after if +\expandafter\def\csname algocf@e#1thenopt\endcsname(##1)##2##3{% \eIf() + \csname #1@ifthen\endcsname{##2} ##1\csname #1@else\endcsname{##3}% + \csname algocf@e#1thenelse\endcsname}% +% without side text after if +\expandafter\def\csname algocf@e#1then\endcsname##1##2{% \eIf() + \csname #1@ifthen\endcsname{##1}\csname #1@else\endcsname{##2}% + \csname algocf@e#1thenelse\endcsname}% +% side text after else or not ? +\expandafter\def\csname algocf@e#1thenelse\endcsname{% + \@ifnextchar({\csname algocf@e#1elseopt\endcsname}{\csname algocf@e#1else\endcsname}}% +% else with a side text +\expandafter\def\csname algocf@e#1elseopt\endcsname(##1)##2{% + ##1\csname #1@endif\endcsname{##2}}% +% else without side text +\expandafter\algocf@mkcmd\csname algocf@e#1else\endcsname[1]{% + \csname #1@endif\endcsname{##1}}% +% +%%%% If then +% +% side text or not? +\expandafter\def\csname l#1\endcsname{% lif + \@ifnextchar({\csname algocf@l#1opt\endcsname}{\csname algocf@l#1\endcsname}}% +\expandafter\def\csname u#1\endcsname{% uif + \@ifnextchar({\csname algocf@u#1opt\endcsname}{\csname algocf@u#1\endcsname}}% +% with side text +\expandafter\def\csname algocf@l#1opt\endcsname(##1)##2##3{% \lIf(){}{} + \csname #1@ifthen\endcsname{##2} ##3\algocf@endline\ ##1\par}% +\expandafter\def\csname algocf@u#1opt\endcsname(##1)##2##3{% \uIf(){}{} + \csname #1@ifthen\endcsname{##2} ##1\csname#1@noend\endcsname{##3}}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@l#1\endcsname[2]{% \lIf{}{} + \csname #1@ifthen\endcsname{##1} ##2}% +\expandafter\algocf@mkcmd\csname algocf@u#1\endcsname[2]{% \uIf{}{} + \csname #1@ifthen\endcsname{##1}\csname#1@noend\endcsname{##2}}% +% +%%%% ElseIf {} endif +% +\@ifundefined{algocf@#2}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +% side text or not? +\expandafter\def\csname#2\endcsname{% ElseIf + \@ifnextchar({\csname algocf@#2opt\endcsname}{\csname algocf@#2\endcsname}}% +% with side text +\expandafter\def\csname algocf@#2opt\endcsname(##1)##2##3{% \ElseIf(){}{} + \csname #2@elseif\endcsname{##2} ##1\csname #1@endif\endcsname{##3}}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@#2\endcsname[2]{% \ElseIf{}{} + \csname #2@elseif\endcsname{##1}\csname #1@endif\endcsname{##2}}% +% +%%%% ElseIf +% +% side text or not? +\expandafter\def\csname l#2\endcsname{% lElseIf + \@ifnextchar({\csname algocf@l#2opt\endcsname}{\csname algocf@l#2\endcsname}}% +\expandafter\def\csname u#2\endcsname{% uElseIf + \@ifnextchar({\csname algocf@u#2opt\endcsname}{\csname algocf@u#2\endcsname}}% +% with side text +\expandafter\def\csname algocf@l#2opt\endcsname(##1)##2##3{% \lElseIf(){}{} + \csname #2@elseif\endcsname{##2} ##3\algocf@endline\ ##1\par}% +\expandafter\def\csname algocf@u#2opt\endcsname(##1)##2##3{% \uElseIf(){}{} + \csname #2@elseif\endcsname{##2} ##1\csname #1@noend\endcsname{##3}}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@l#2\endcsname[2]{% \lElseIf{}{} + \csname #2@elseif\endcsname{##1} ##2}% +\expandafter\algocf@mkcmd\csname algocf@u#2\endcsname[2]{% \uElseIf{}{} + \csname #2@elseif\endcsname{##1}\csname #1@noend\endcsname{##2}}% +% +%%%% Else {} endif +% +\@ifundefined{algocf@#3}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +% side text or not? +\expandafter\def\csname#3\endcsname{% Else + \@ifnextchar({\csname algocf@#3opt\endcsname}{\csname algocf@#3\endcsname}}% +% with side text +\expandafter\def\csname algocf@#3opt\endcsname(##1)##2{% \Else(){} + \csname #3@else\endcsname\ ##1\csname #1@endif\endcsname{##2}}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@#3\endcsname[1]{% \Else{} + \csname #3@else\endcsname\csname #1@endif\endcsname{##1}}% +% +%%%% Else +% +% side text or not? +\expandafter\def\csname l#3\endcsname{% lElse + \@ifnextchar({\csname algocf@l#3opt\endcsname}{\csname algocf@l#3\endcsname}}% +\expandafter\def\csname u#3\endcsname{% uElse + \@ifnextchar({\csname algocf@u#3opt\endcsname}{\csname algocf@u#3\endcsname}}% +% with side text +\expandafter\def\csname algocf@l#3opt\endcsname(##1)##2{% \lElse(){} + \csname #3@else\endcsname\ ##2\algocf@endline\ ##1\par}% +\expandafter\def\csname algocf@u#3opt\endcsname(##1)##2{% \uElse(){} + \csname #3@else\endcsname\ ##1\csname #1@noend\endcsname{##2}}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@l#3\endcsname[1]{% \lElse{} + \csname #3@else\endcsname\ ##1}% +\expandafter\algocf@mkcmd\csname algocf@u#3\endcsname[1]{% \uElse{} + \csname #3@else\endcsname\csname #1@noend\endcsname{##1}}% +}% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% For macros +% +\newcommand{\SetKwFor}[4]{% +\@ifundefined{algocf@#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +% side text or not? +\expandafter\def\csname#1\endcsname{%For + \@ifnextchar({\csname algocf@#1opt\endcsname}{\csname algocf@#1\endcsname}}% +\expandafter\def\csname l#1\endcsname{%For + \@ifnextchar({\csname algocf@l#1opt\endcsname}{\csname algocf@l#1\endcsname}}% +% with side text +\expandafter\def\csname algocf@#1opt\endcsname(##1)##2##3{% \For(){}{} + \KwSty{#2} \ArgSty{##2} \KwSty{#3} ##1\algocf@block{##3}{\@algocf@endoption{#4}}}% +\expandafter\def\csname algocf@l#1opt\endcsname(##1)##2##3{% \lFor(){}{} + \KwSty{#2} \ArgSty{##2} \KwSty{#3} ##3\algocf@endline\ ##1\par}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@#1\endcsname[2]{% \For{}{} + \KwSty{#2} \ArgSty{##1} \KwSty{#3}\algocf@block{##2}{\@algocf@endoption{#4}}}% +\expandafter\algocf@mkcmd\csname algocf@l#1\endcsname[2]{% \lFor{}{} + \KwSty{#2} \ArgSty{##1} \KwSty{#3} ##2}% +}% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% Repeat macros +% +\newcommand{\SetKwRepeat}[3]{% +\@ifundefined{algocf@#1}{\let\algocf@mkcmd=\newcommand}{\let\algocf@mkcmd=\renewcommand}% +% side text or not? +\expandafter\def\csname#1\endcsname{% Repeat + \@ifnextchar({\csname algocf@#1opt\endcsname}{\csname algocf@#1\endcsname}}% +\expandafter\def\csname l#1\endcsname{% lRepeat + \@ifnextchar({\csname algocf@l#1opt\endcsname}{\csname algocf@l#1\endcsname}}% +% with side text +\expandafter\def\csname algocf@#1opt\endcsname(##1)##2##3{% \Repeat(){}{} + \KwSty{#2} ##1\algocf@group{##3}\KwSty{#3} \ArgSty{##2}% + \@ifnextchar({\csname algocf@#1optopt\endcsname}{\@endalgoln}% +}% +\expandafter\def\csname algocf@#1optopt\endcsname(##1){% \Repeat(){}{}() + ##1\@endalgoln}% +\expandafter\def\csname algocf@l#1opt\endcsname(##1)##2##3{% \lRepeat(){}{} + \KwSty{#2} ##3 \KwSty{#3} \ArgSty{##2}\algocf@endline\ ##1\par}% +% without side text +\expandafter\algocf@mkcmd\csname algocf@#1\endcsname[2]{% \Repeat{}{} + \KwSty{#2}\algocf@group{##2}\KwSty{#3} \ArgSty{##1}% + \@ifnextchar({\csname algocf@#1optopt\endcsname}{\@endalgoln}% +}% +\expandafter\algocf@mkcmd\csname algocf@l#1\endcsname[2]{% \lRepeat{}{} + \KwSty{#2} ##2 \KwSty{#3} \ArgSty{##1}}% +}% +% +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%% Environments definitions %%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +%% +%% Caption management +%% +% for the following macros: +% #1 is given by caption and is equal to fnum@algocf +% #2 is the text given in argument by the user in the \caption macro +% +%%%%% text of caption +\newcommand{\algocf@captionlayout}[1]{#1}% +\newcommand{\SetAlgoCaptionLayout}[1]{% + \renewcommand{\algocf@captionlayout}[1]{\csname #1\endcsname{##1}}}% +\newcommand{\algocf@capseparator}{:}% +\newcommand{\SetAlgoCaptionSeparator}[1]{\renewcommand{\algocf@capseparator}{#1}}% +\newcommand{\algocf@captiontext}[2]{% + \algocf@captionlayout{\AlCapSty{\AlCapFnt #1\algocf@typo\algocf@capseparator}\nobreakspace% + \AlCapNameSty{\AlCapNameFnt{}#2}}}% text of caption +% +%%%%% default caption of algorithm: used if no specific style caption is defined +\newcommand{\algocf@makecaption}[2]{% + \addtolength{\hsize}{\algomargin}% + \sbox\@tempboxa{\algocf@captiontext{#1}{#2}}% + \ifdim\wd\@tempboxa >\hsize% % if caption is longer than a line + \hskip .5\algomargin% + \parbox[t]{\hsize}{\algocf@captiontext{#1}{#2}}% then caption is not centered + \else% + \global\@minipagefalse% + \hbox to\hsize{\hfil\box\@tempboxa\hfil}% else caption is centered + \fi% + \addtolength{\hsize}{-\algomargin}% +}% +% +\newsavebox\algocf@capbox% +\newcommand{\algocf@makecaption@plain}[2]{% + \global\sbox\algocf@capbox{\algocf@makecaption{#1}{#2}}}% +\newcommand{\algocf@makecaption@boxed}[2]{% + \addtolength{\hsize}{-\algomargin}% + \global\sbox\algocf@capbox{\algocf@makecaption{#1}{#2}}% + \addtolength{\hsize}{\algomargin}% + }% +% +\newcommand{\algocf@makecaption@tworuled}[2]{\algocf@makecaption@ruled{#1}{#2}}% +\newcommand{\algocf@makecaption@algoruled}[2]{\algocf@makecaption@ruled{#1}{#2}}% +\newcommand{\algocf@makecaption@boxruled}[2]{\algocf@makecaption@ruled{#1}{#2}}% +\newcommand{\algocf@makecaption@ruled}[2]{% + \global\sbox\algocf@capbox{\hskip\AlCapHSkip% .5\algomargin% + \parbox[t]{\hsize}{\algocf@captiontext{#1}{#2}}}% then caption is not centered +}% +% +\newlength{\algoheightruledefault}\setlength{\algoheightruledefault}{0.8pt}% +\newlength{\algoheightrule}\setlength{\algoheightrule}{\algoheightruledefault}% +\newlength{\algotitleheightruledefault}\setlength{\algotitleheightruledefault}{0.8pt}% +\newlength{\algotitleheightrule}\setlength{\algotitleheightrule}{\algotitleheightruledefault}% +\newcommand{\algocf@caption@plain}{\vskip\AlCapSkip\box\algocf@capbox}% +\newcommand{\algocf@caption@boxed}{\vskip\AlCapSkip\box\algocf@capbox}% +\newcommand{\algocf@caption@ruled}{\box\algocf@capbox\kern\interspacetitleruled\hrule height\algotitleheightrule depth0pt\kern\interspacealgoruled}% +\newcommand{\algocf@caption@tworuled}{\box\algocf@capbox\kern\interspacetitleruled}% +\newcommand{\algocf@caption@algoruled}{\algocf@caption@ruled}% +\newcommand{\algocf@caption@boxruled}{% + \addtolength{\hsize}{-0.8pt}% + \hbox to\hsize{% + \vrule%\hskip-0.35pt% + \vbox{% + \hrule\vskip\interspacetitleboxruled% + \hbox to\hsize{\unhbox\algocf@capbox\hfill}\vskip\interspacetitleboxruled% + }% + %\hskip-0.35pt% + \vrule% + }\nointerlineskip% + \addtolength{\hsize}{0.8pt}% +}% +% +% +%%%% set caption for the environment +\newcommand{\algocf@captionref}{% + \renewcommand{\fnum@algocf}[1]{\AlCapSty{\AlCapFnt\algorithmcfname\nobreakspace\algocf@algocfref}}% + \addtocounter{algocf}{-1}% \caption do a refstepcounter, so we restore the precedent value + \let\old@thealgocf=\thealgocf\renewcommand{\thealgocf}{{\relsize{\algocf@refrelsize}\algocf@algocfref}}% + \gdef\@currentlabel{\algocf@algocfref}% let the label use the new ref +}% +% +% Unfortunatly, we also need our own caption to set some specific stuff for special references. But after these +% settings, we call the original caption. +% +\long\def\algocf@caption@algo#1[#2]#3{% + \ifthenelse{\equal{\algocf@algocfref}{\relax}}{}{\algocf@captionref}% + \@ifundefined{hyper@refstepcounter}{\relax}{% if hyper@refstepcounter undefind, no hyperref, else... + \ifthenelse{\equal{\algocf@algocfref}{\relax}}{\renewcommand{\theHalgocf}{\thealgocf}}{% take algocf as Href + \renewcommand{\theHalgocf}{\algocf@algocfref}}%else if SetAlgoRefName done, take this name as ref. + \hyper@refstepcounter{algocf}%set algocf as category of ref + }% + \algocf@latexcaption{#1}[#2]{#3}% call original caption +}% +% +% beamer define is own caption overrinding latex caption! +% as we need it, we have put here the original definition +% to handle manual ref, unfortunately we have to add one line to handle algocf@algocfref +\long\def\algocf@latexcaption#1[#2]#3{% original definition of caption + \par% + \addcontentsline{\csname ext@#1\endcsname}{#1}% + {\protect\numberline{\csname the#1\endcsname}{\ignorespaces #2}}% + \begingroup% + \@parboxrestore% + \if@minipage% + \@setminipage% + \fi% + \normalsize% + \@makecaption{\csname fnum@#1\endcsname}{\ignorespaces #3}\par% + \endgroup% +}% +% +% \ifx\beamer@makecaption\undefined% +% \else% beamer detected +\ifx\@makecaption\undefined% +\newcommand{\@makecaption}[2]{\relax}% +\fi% +%% + +% +% more and more packages redefine \@caption instead of just \@makecaption which makes algorithm2e +% caption not works since based on standard \@caption. So we force the definition of \@caption to be +% the standard one (the one from LaTeX) inside algorithm environment. +% +% unfortunately, makecaption is called with \ignorespace #3 so +% we can't do the @currentlabel definition inside \algocf@captionproctext +\long\def\algocf@caption@proc#1[#2]#3{% + \ifthenelse{\boolean{algocf@nokwfunc}}{\relax}{% + \SetKwFunction{\algocf@captname#3@}{\algocf@captname#3@}% + }% + % we tell hyperref to use algocfproc as category and to take the appropriate ref. + \ifthenelse{\boolean{algocf@func}}{\def\@proc@func{algocffunc}}{\def\@proc@func{algocfproc}}% + \@ifundefined{hyper@refstepcounter}{\relax}{% if hyper@refstepcounter undefind, no hyperref, else... + \ifthenelse{\boolean{algocf@procnumbered}}{% + \expandafter\def\csname theH\@proc@func\endcsname{\algocf@captname#3@}%if procnumbered, take \thealgocf as ref + }{% + \expandafter\def\csname theH\@proc@func\endcsname{\algocf@captname#3@}%else take procedure or function name + }% + \hyper@refstepcounter{\@proc@func}% + }% + \ifthenelse{\boolean{algocf@procnumbered}}{\relax}{% + \addtocounter{algocf}{-1}% \caption do a refstepcounter, so we restore the precedent value + \gdef\@currentlabel{\algocf@captname#3@}% let the label be the name of the function, not the counter + }% + \ifthenelse{\equal{\algocf@captparam#2@}{\arg@e}}{% if no paramater, we remove the () + \algocf@latexcaption{#1}[\algocf@procname\nobreakspace\algocf@captname#2@]{#3}% + }{% else we give the complete name + \algocf@latexcaption{#1}[\algocf@procname\nobreakspace#2]{#3}% + }% +}% +%% +%%% setcaption +\newcommand{\algocf@setcaption}{% + \ifthenelse{\boolean{algocf@procenvironment}}{% if proc environment, caption text must be changed + \let\algocf@oldcaptiontext=\algocf@captiontext% + \renewcommand{\algocf@captiontext}[2]{% + \algocf@captionproctext{##1}{##2}% + }% + }{}% + \let\algocf@savecaption=\@caption% + \ifthenelse{\boolean{algocf@procenvironment}}{\let\@caption=\algocf@caption@proc}{\let\@caption=\algocf@caption@algo}% + \let\algocf@oldmakecaption=\@makecaption% + \renewcommand{\@makecaption}[2]{% + \expandafter\csname algocf@makecaption@\algocf@style\endcsname{##1}{##2}% + }% +}% +% +%%%%% reset caption +% +% since we have force the LaTeX caption for algorithm environment, we must go back to the caption +% used in the text. +\newcommand{\algocf@resetcaption}{% + \ifthenelse{\boolean{algocf@procenvironment}}{% if proc environment + \let\thealgocf=\old@thealgocf% restore normal counter printing + \let\algocf@captiontext=\algocf@oldcaptiontext% restore normal caption text + }{}% + \let\@caption=\algocf@savecaption% now restore caption outside algo/proc/func environment + \let\@makecaption=\algocf@oldmakecaption% and restore makecaption outside outside algo/proc/func environment + \algocf@resetfnum% +}% +% +%%%%% nocaptionofalgo and restorecaptionofalgo -- +\newcommand{\NoCaptionOfAlgo}{% + \let\@old@algocf@captiontext=\algocf@captiontext% + \renewcommand{\algocf@captiontext}[2]{\AlCapNameSty{\AlCapNameFnt{}##2}}% +}% +\newcommand{\RestoreCaptionOfAlgo}{% + \let\algocf@captiontext=\@old@algocf@captiontext% +}% +% +% ---------------------- algocf environment +% +\newcounter{algocfline}% % new counter to make lines numbers be internally +\setcounter{algocfline}{0}% % different in different algorithms +\newcounter{algocfproc}% counter to count all algo environment (proc, func), just used by hyperref to avoir "same +\setcounter{algocfproc}{0}% identifier" error caused by algocf being set to '-' for procedure or function or not + % changed if no caption is given. +% +\expandafter\ifx\csname algocf@within\endcsname\relax% if \algocf@within doesn't exist +\newcounter{algocf}% % just define a new counter +\renewcommand{\thealgocf}{\@arabic\c@algocf}% and the way it is printed +\else% else +\newcounter{algocf}[\algocf@within]% % counter is numbered within \algocf@within +\renewcommand\thealgocf{\csname the\algocf@within\endcsname.\@arabic\c@algocf}% +\fi% +% +\def\fps@algocf{htbp}% % default +\def\ftype@algocf{10}% % float type +\def\ext@algocf{\algocf@list} % loa by default, lof if figure option used +\newcommand{\fnum@algocf}[1]{\AlCapSty{\AlCapFnt\algorithmcfname\nobreakspace\thealgocf}}% +\newcommand{\algocf@resetfnum}{\renewcommand{\fnum@algocf}[1]{\AlCapSty{\AlCapFnt\algorithmcfname\nobreakspace\thealgocf}}}% +\newenvironment{algocf}% % float environment for algorithms + {\@float{algocf}}% + {\end@float}% +\newenvironment{algocf*}% % float* environment for algorithms + {\@dblfloat{algocf}}% + {\end@dblfloat}% +% +\def\algocf@seclistalgo{}% +\ifx\l@chapter\undefined\let\algocf@seclistalgo=\section\else\let\algocf@seclistalgo=\chapter\fi% +\@ifundefined{if@restonecol}{\newif\if@restonecol}\relax% +\newcommand\listofalgocfs{% + \ifx\algocf@seclistalgo\chapter% + \if@twocolumn\@restonecoltrue\onecolumn\else\@restonecolfalse\fi% + \fi% + \algocf@seclistalgo*{\listalgorithmcfname}% + \@mkboth{\MakeUppercase\listalgorithmcfname}% + {\MakeUppercase\listalgorithmcfname}% + \@starttoc{loa}% + \ifx\algocf@seclistalgo\chapter% + \if@restonecol\twocolumn\fi% + \fi% +} +% +\newcommand*\l@algocf{\@dottedtocline{1}{1em}{2.3em}}% line of the list +% +% ---------------------- algorithm environment +% +%%%%%%% +%% +%% Algorithm environment definition +%% +%%%%%%% +%% +% +\newsavebox\algocf@algoframe% +\def\@algocf@pre@plain{\relax}% action to be done before printing the algo. +\def\@algocf@post@plain{\relax}% action to be done after printing the algo. +\def\@algocf@capt@plain{bottom}% where the caption should be localized. +\def\@algocf@pre@boxed{\noindent\begin{lrbox}{\algocf@algoframe}} +\def\@algocf@post@boxed{\end{lrbox}\framebox[\hsize]{\box\algocf@algoframe}\par}% +\def\@algocf@capt@boxed{under}% +\def\@algocf@pre@ruled{\hrule height\algoheightrule depth0pt\kern\interspacetitleruled}% +\def\@algocf@post@ruled{\kern\interspacealgoruled\hrule height\algoheightrule\relax}% +\def\@algocf@capt@ruled{top}% +\def\@algocf@pre@algoruled{\hrule height\algoheightrule depth0pt\kern\interspacetitleruled}% +\def\@algocf@post@algoruled{\kern\interspacealgoruled\hrule height\algoheightrule \relax}% +\def\@algocf@capt@algoruled{top}% +\def\@algocf@pre@tworuled{\hrule height\algoheightrule depth0pt\kern\interspacetitleruled}% +\def\@algocf@post@tworuled{\kern\interspacealgoruled\hrule height\algoheightrule\relax}% +\def\@algocf@capt@tworuled{top}% +\def\@algocf@pre@boxruled{\noindent\begin{lrbox}{\algocf@algoframe}}% +\def\@algocf@post@boxruled{\end{lrbox}\framebox[\hsize]{\box\algocf@algoframe}\par}% +\def\@algocf@capt@boxruled{above}% +% +\newcommand{\noalgocaption}{\def\@algocf@capt@ruled{none}} +% +%% before algocf or figure environment +\newcommand{\@algocf@init@caption}{% + \ifthenelse{\boolean{algocf@procenvironment}}{% if we are inside a procedure/function environment + \@algocf@proctitleofalgo% set Titleofalgo to Procedure: or Function: + % accordingly to the environment + \let\old@thealgocf=\thealgocf\ifthenelse{\boolean{algocf@procnumbered}}{\relax}{% + \renewcommand{\thealgocf}{-}}% + }{% else inside environment algorithm + \@algocf@algotitleofalgo% fix name for \Titleofalgo to \algorithmcfname + }% + \algocf@setcaption% set caption to our caption style +}% +% +\newcommand{\@algofloatboxreset}{\@setminipage} +\newcommand{\@algocf@init}{% + \refstepcounter{algocfline}% + \stepcounter{algocfproc}%to have a different counter for each environment and being abble to make the difference + %between href of algoline in different algorithms. + \ifthenelse{\boolean{algocf@optnoend}}{% + \renewcommand{\algocf@block}[2]{\algocf@group{##1}}% + }{% + \renewcommand{\algocf@block}[2]{\algocf@@block{##1}{##2}}% + }% +}% +%% after the end of algocf or figure environment +\newcommand{\@algocf@term@caption}{% + \algocf@resetcaption% restore original caption +}% +% +\newcommand{\@algocf@term}{% + \setboolean{algocf@algoH}{false}% no H by default + \ifthenelse{\boolean{algocf@optnoend}}{% + \renewcommand{\algocf@block}[2]{\algocf@@block{##1}{##2}}% + }{% + \renewcommand{\algocf@block}[2]{\algocf@group{##1}}% + }% + \SetAlgoRefName{\relax}% +}% +% +%%%%%%%%%%%%%%%%% +%% makethealgo: macro which print effectively the algo in its box +%% +\newsavebox\algocf@algobox% +\newcommand{\algocf@makethealgo}{% + \vtop{% + % place caption above if needed bye the style + \ifthenelse{\equal{\csname @algocf@capt@\algocf@style\endcsname}{above}}% + {\csname algocf@caption@\algocf@style\endcsname}{}% + % + % precommand according to the style + \csname @algocf@pre@\algocf@style\endcsname% + % place caption at top if needed bye the style + \ifthenelse{\equal{\csname @algocf@capt@\algocf@style\endcsname}{top}}% + {\csname algocf@caption@\algocf@style\endcsname}{}% + % + \box\algocf@algobox% the algo + % place caption at bottom if needed bye the style + \ifthenelse{\equal{\csname @algocf@capt@\algocf@style\endcsname}{bottom}}% + {\csname algocf@caption@\algocf@style\endcsname}{}% + % postcommand according to the style + \csname @algocf@post@\algocf@style\endcsname% + % place caption under if needed bye the style + \ifthenelse{\equal{\csname @algocf@capt@\algocf@style\endcsname}{under}}% + {\csname algocf@caption@\algocf@style\endcsname}{}% + }% +}% +%%%%%%%%%%%%%%%%%%% +% +%% at the beginning of algocf or figure environment +\newcommand{\@algocf@start}{% + \@algoskip% + \begin{lrbox}{\algocf@algobox}% + \setlength{\algowidth}{\hsize}% + \vbox\bgroup% save all the algo in a box + \hbox to\algowidth\bgroup\hbox to \algomargin{\hfill}\vtop\bgroup% + \ifthenelse{\boolean{algocf@slide}}{\parskip 0.5ex\color{black}}{}% + % initialization + \addtolength{\hsize}{-1.5\algomargin}% + \let\@mathsemicolon=\;\def\;{\ifmmode\@mathsemicolon\else\@endalgoln\fi}% + \raggedright\AlFnt{}% + \ifthenelse{\boolean{algocf@slide}}{\IncMargin{\skipalgocfslide}}{}% + \@algoinsideskip% +}% +% +%% at the end of algocf or figure environment +\newcommand{\@algocf@finish}{% + \@algoinsideskip% + \egroup%end of vtop which contain all the text + \hfill\egroup%end of hbox wich contains [margin][vtop] + \ifthenelse{\boolean{algocf@slide}}{\DecMargin{\skipalgocfslide}}{}% + % + \egroup%end of main vbox + \end{lrbox}% + \algocf@makethealgo% print the algo + \@algoskip% + % restore dimension and macros + \setlength{\hsize}{\algowidth}% + \lineskip\normallineskip\setlength{\skiptotal}{\@defaultskiptotal}% + \let\;=\@mathsemicolon% +}% +% +%%%%%%%%%%%%%%%%%%%% +%% basic definition of the environment algorithm +%% +% +\newboolean{algocf@procenvironment}\setboolean{algocf@procenvironment}{false}% +\newboolean{algocf@func}\setboolean{algocf@func}{false}% +\newboolean{algocf@algoH}\setboolean{algocf@algoH}{false}% +\newboolean{algocf@algostar}\setboolean{algocf@algostar}{false}% +% +%%% environment for {algorithm}[H] +\newenvironment{algocf@Here}{\noindent% + \def\@captype{algocf}% if not defined, caption exit with an error + \begin{minipage}{\hsize}% +}{% + \end{minipage}%\par% +}% +%%% real algorithm environment which manages H and * option +% \let\algocf@originalfloatboxreset=\@floatboxreset% +% \let\@floatboxreset=\@algofloatboxreset% +\newenvironment{algocf@algorithm}[1][htbp]{ + \@algocf@init% + \ifthenelse{\equal{\algocf@float}{figure}}{% if option figure set + \ifthenelse{\boolean{algocf@algostar}}{% if algorithm* with figure option + \begin{figure*}[#1]% call figure* + }{% else algorithm environment with figure option + \begin{figure}[#1]% call figure + }% + }{% else normal algorithm environment + \@algocf@init@caption% + \ifthenelse{\equal{#1}{H}}{% if [H] algorithm + \if@twocolumn\@latex@error{[H] in two columns mode is not allowed for algorithms}\fi% TODO: SCREAM if H in two colums! + \setboolean{algocf@algoH}{true}\begin{algocf@Here}% call corresponding environment + }{% else floating algorithm environment + \ifthenelse{\boolean{algocf@algostar}}{% if algorithm* + \begin{algocf*}[#1]% call algocf* + }{% else algorithm environment + \begin{algocf}[#1]% call algcf + }% + }% + }% fin test option figure ou pas + \@algocf@start% + \@ResetCounterIfNeeded% + \algocf@linesnumbered\ignorespaces% +}{% + \@algocf@finish% + \ifthenelse{\equal{\algocf@float}{figure}}{% + \ifthenelse{\boolean{algocf@algostar}}{% if algorithm* with figure option + \end{figure*}% call figure* + }{% else algorithm environment with figure option + \end{figure}% call figure + }% + }{% + \@algocf@term@caption% + \ifthenelse{\boolean{algocf@algoH}}{% if [H] algorithm + \end{algocf@Here}\par% call corresponding environment + }{% else floating algorithm environment + \ifthenelse{\boolean{algocf@algostar}}{% if algorithm* + \end{algocf*}% call algocf* + }{% else algorithm environment + \end{algocf}% call algocf + }% + }% + }% + \@algocf@term\ignorespacesafterend% +}% +% +%%% user algorithm environment +\newenvironment{\algocf@envname}[1][htbp]{% + \setboolean{algocf@algostar}{false}% + \setboolean{algocf@procenvironment}{false}\gdef\algocfautorefname{\algorithmautorefname}% + \begin{algocf@algorithm}[#1]\ignorespaces% +}{% + \end{algocf@algorithm}\ignorespacesafterend% +}% +%%% user algorithm* environment +\newenvironment{\algocf@envname*}[1][htbp]{% + \setboolean{algocf@algostar}{true}% + \setboolean{algocf@procenvironment}{false}\gdef\algocfautorefname{\algorithmautorefname}% + \begin{algocf@algorithm}[#1]\ignorespaces% +}{% + \end{algocf@algorithm}\ignorespacesafterend% +}% +% +%%%%%%%%%%%%%%%%%%%%%%% +%%% +% +\expandafter\newcommand\csname\algocf@listofalgorithms\endcsname{% + \ifthenelse{\equal{\algocf@float}{figure}}{\listoffigures}{\listofalgocfs}% +}% +%%% +%%% +% +% ---------------------- procedure and function environments +% +% +% -- new style (used in particular in the caption of function and procedure environments) +% +% three macros to extract parts of the caption +\gdef\algocf@captname#1(#2)#3@{#1} % keep characters before the first brace +\gdef\algocf@captparam#1(#2)#3@{#2} % keep character in between the braces +\gdef\algocf@captother#1(#2)#3@{#3} % keep character after the braces +% +%%% Text of caption for Procedure or Function +\newcommand{\algocf@captionproctext}[2]{% + {% + \ProcSty{\ProcFnt\algocf@procname\ifthenelse{\boolean{algocf@procnumbered}}{\nobreakspace\thealgocf\algocf@typo\algocf@capseparator}{\relax}}% + \nobreakspace\ProcNameSty{\ProcNameFnt\algocf@captname #2@}% Name of the procedure in ProcName Style. + \ifthenelse{\equal{\algocf@captparam #2@}{\arg@e}}{}{% if no argument, write nothing + \ProcNameSty{\ProcNameFnt(}\ProcArgSty{\ProcArgFnt\algocf@captparam #2@}\ProcNameSty{\ProcNameFnt)}%else put arguments in ProcArgSty: + }% endif + \algocf@captother #2@% + }% +}% +% +% +% -- procedure and function environments are defined from algocf@algorithm environment +% +\newenvironment{procedure}[1][htbp]{% + \setboolean{algocf@algostar}{false}% + \setboolean{algocf@procenvironment}{true}\setboolean{algocf@func}{false}% + \newcommand{\algocf@procname}{\@algocf@procname}\gdef\algocfprocautorefname{\procedureautorefname}% + \begin{algocf@algorithm}[#1]\ignorespaces% +}{% + \end{algocf@algorithm}\ignorespacesafterend% +}% +\newenvironment{function}[1][htbp]{% + \setboolean{algocf@algostar}{false}% + \setboolean{algocf@procenvironment}{true}\setboolean{algocf@func}{true}% + \newcommand{\algocf@procname}{\@algocf@funcname}\gdef\algocffuncautorefname{\functionautorefname}% + \begin{algocf@algorithm}[#1]\ignorespaces% +}{% + \end{algocf@algorithm}\ignorespacesafterend% +}% +% +\newenvironment{procedure*}[1][htbp]{% + \setboolean{algocf@algostar}{true}% + \setboolean{algocf@procenvironment}{true}\setboolean{algocf@func}{false}% + \newcommand{\algocf@procname}{\@algocf@procname}\gdef\algocfprocautorefname{\procedureautorefname}% + \begin{algocf@algorithm}[#1]\ignorespaces% +}{% + \end{algocf@algorithm}\ignorespacesafterend% +}% +\newenvironment{function*}[1][htbp]{% + \setboolean{algocf@algostar}{true}% + \setboolean{algocf@procenvironment}{true}\setboolean{algocf@func}{true}% + \newcommand{\algocf@procname}{\@algocf@funcname}\gdef\algocffuncautorefname{\functionautorefname}% + \begin{algocf@algorithm}[#1]\ignorespaces% +}{% + \end{algocf@algorithm}\ignorespacesafterend% +}% +% +% +%%%%%%%%%%%%%%%%%%%% +%% definition of algondfloat environment +%% +\ifthenelse{\boolean{algocf@endfloat}}{% if endfloat option then +\newcommand{\algoplace}{% macro which is used to writhe algorithm about there + \begin{center}% + [\algorithmcfname~\thepostfig\ about here.]% + \end{center}% +}% +\newcommand{\algoendfloat}{% use as a \begin{algoendfloat} environment to start scanning of line +% \immediate\openout\@mainfff\jobname.fff% + \efloat@condopen{fff} + \efloat@iwrite{fff}{\string\begin{\algocf@envname}}% + \if@domarkers% + \ifthenelse{\equal{\algocf@list}{lof}}{% + \addtocounter{postfig}{1}% + }{% + \addtocounter{postalgo}{1}% + }% + \algoplace% + \fi% + \bgroup% + \let\do\ef@makeinnocent\dospecials% + \ef@makeinnocent\^^L% and whatever other special cases + \endlinechar`\^^M \catcode`\^^M=12 \ef@xalgocfendfloat}% +}{\relax}%%%% end of endfloat option ifthenelse +%% some macros useful for endfloat option that cannot be defined inside the ifthenelse +%scan algoendfloat algorithm and write the text into .fff file +{\catcode`\^^M=12 \endlinechar=-1 % + \gdef\ef@xalgocfendfloat#1^^M{% scan the lines inside algoendfloat environment being read by latex + \def\test{#1}% test is the line being currently scan by latex + \ifx\test\ef@endalgocftest% if it is \end{algoendfloat} + \def\next{% define next as to not continue the scan and write \end{algorithm} into .fff file + \egroup\end{algoendfloat}% + \efloat@iwrite{fff}{\string\end{\algocf@envname}}% + \efloat@iwrite{fff}{\string\efloatseparator}% + \efloat@iwrite{fff}{ }% + }% + \else% else write the current line being scanned by latex and set next to continue the scan + \efloat@iwrite{fff}{#1}% + \let\next\ef@xalgocfendfloat% + \fi% endif + \next}% next is continue if it was else condition, else it does not continue the scan and write end to file +}% +% test if the scan is finish by looking at the string \end{algoendfloat} +{\escapechar=-1% + \xdef\ef@endalgocftest{\string\\end\string\{algoendfloat\string\}}% +}% +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% +\newcommand{\TitleOfAlgo}[1]{\@titleprefix\ + \TitleSty{#1}\par\smallskip}% +% +\newcommand{\SetAlgorithmName}[3]{% + \renewcommand{\listalgorithmcfname}{#3}% + \renewcommand{\algorithmcfname}{#1}% + \renewcommand{\algorithmautorefname}{#2}% +}% +% +\newcommand{\algocf@refrelsize}{-2}\newcommand{\SetAlgoRefRelativeSize}[1]{\renewcommand{\algocf@refrelsize}{#1}}% +\newcommand{\SetAlgoRefName}[1]{% + \renewcommand{\algocf@algocfref}{#1}% +}% +% +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% +% ------------------------- Default Definitions +% +%% +%% +% +\SetKwComment{tcc}{/* }{ */}% +\SetKwComment{tcp}{// }{}% +% +%\newcommand{\algocf@defaults@common}{ +% +% +% french keywords +% +%\SetKwInOut{AlgDonnees}{Donn\'ees}\SetKwInOut{AlgRes}{R\'esultat} +\SetKwInput{Donnees}{Donn\'ees}% +\SetKwInput{Res}{R\'esultat}% +\SetKwInput{Entree}{Entr\'ees}% +\SetKwInput{Sortie}{Sorties}% +\SetKw{KwA}{\`a}% +\SetKw{Retour}{retourner}% +\SetKwBlock{Deb}{d\'ebut}{fin}% +\SetKwRepeat{Repeter}{r\'ep\'eter}{jusqu'\`a}% +% +\SetKwIF{Si}{SinonSi}{Sinon}{si}{alors}{sinon si}{sinon}{fin si}% +\SetKwSwitch{Suivant}{Cas}{Autre}{suivant}{faire}{cas o\`u}{autres cas}{fin d'alternative}% +\SetKwFor{Pour}{pour}{faire}{fin pour}% +\SetKwFor{PourPar}{pour}{faire en parallèle}{fin pour}% +\SetKwFor{PourCh}{pour chaque}{faire}{fin pour chaque}% +\SetKwFor{PourTous}{pour tous les}{faire}{fin pour tous}% +\SetKwFor{Tq}{tant que}{faire}{fin tq}% +% +% english keywords +% +\SetKwInput{KwIn}{Input}% +\SetKwInput{KwOut}{Output}% +\SetKwInput{KwData}{Data}% +\SetKwInput{KwResult}{Result}% +\SetKw{KwTo}{to} +\SetKw{KwRet}{return}% +\SetKw{Return}{return}% +\SetKwBlock{Begin}{begin}{end}% +\SetKwRepeat{Repeat}{repeat}{until}% +% +\SetKwIF{If}{ElseIf}{Else}{if}{then}{else if}{else}{end if}% +\SetKwSwitch{Switch}{Case}{Other}{switch}{do}{case}{otherwise}{end switch}% +\SetKwFor{For}{for}{do}{end for}% +\SetKwFor{ForPar}{for}{do in parallel}{end forpar} +\SetKwFor{ForEach}{foreach}{do}{end foreach}% +\SetKwFor{ForAll}{forall the}{do}{end forall}% +\SetKwFor{While}{while}{do}{end while}% +% +% --- German keywords +% +\SetKwInput{Ein}{Eingabe}%KwIn +\SetKwInput{Aus}{Ausgabe}%KwOut +\SetKwInput{Daten}{Daten}%KwData +\SetKwInput{Ergebnis}{Ergebnis}%KwResult +\SetKw{Bis}{bis}%KwTo +\SetKw{KwZurueck}{zur\"uck}%KwRet +\SetKw{Zurueck}{zur\"uck}%Return +\SetKwBlock{Beginn}{Beginn}{Ende}%Begin +\SetKwRepeat{Wiederh}{wiederhole}{bis}%Repeat +% +\SetKwIF{Wenn}{SonstWenn}{Sonst}{wenn}{dann}{sonst wenn}{sonst}{Ende wenn}%gIf +\SetKwSwitch{Unterscheide}{Fall}{Anderes}{unterscheide}{tue}{Fall}{sonst}{Ende Unt.}%Switch +\SetKwFor{Fuer}{f\"ur}{tue}{Ende f\"ur}%For +\SetKwFor{FuerPar}{f\"ur}{tue gleichzeitig}{Ende gleichzeitig}%ForPar +\SetKwFor{FuerJedes}{f\"ur jedes}{tue}{Ende f\"ur}%ForEach +\SetKwFor{FuerAlle}{f\"ur alle}{tue}{Ende f\"ur}%ForAll +\SetKwFor{Solange}{solange}{tue}{Ende solange}%While +% +% --- Czech keywords +% +\SetKwInput{Vst}{Vstup}% +\SetKwInput{Vyst}{V\'{y}stup}% +\SetKwInput{Vysl}{V\'{y}sledek}% +% +% --- Portuguese keywords +% +\SetKwInput{Entrada}{Entrada}% +\SetKwInput{Saida}{Sa\'{i}da}% +\SetKwInput{Dados}{Dados}% +\SetKwInput{Resultado}{Resultado}% +\SetKw{Ate}{at\'{e}} +\SetKw{KwRetorna}{retorna}% +\SetKw{Retorna}{retorna}% +\SetKwBlock{Inicio}{in\'{i}cio}{fim}% +\SetKwRepeat{Repita}{repita}{at\'{e}}% +% +\SetKwIF{Se}{SenaoSe}{Senao}{se}{ent\~{a}o}{sen\~{a}o se}{sen\~{a}o}{fim se}% +\SetKwSwitch{Selec}{Caso}{Outro}{selecione}{fa\c{c}a}{caso}{sen\~{a}o}{fim selec}% +\SetKwFor{Para}{para}{fa\c{c}a}{fim para}% +\SetKwFor{ParaPar}{para}{fa\c{c}a em paralelo}{fim para} +\SetKwFor{ParaCada}{para cada}{fa\c{c}a}{fim para cada}% +\SetKwFor{ParaTodo}{para todo}{fa\c{c}a}{fim para todo}% +\SetKwFor{Enqto}{enquanto}{fa\c{c}a}{fim enqto}% +% +% --- Italian keywords +% +\SetKwInput{KwIng}{Ingresso}% +\SetKwInput{KwUsc}{Uscita}% +\SetKwInput{KwDati}{Dati}% +\SetKwInput{KwRisult}{Risultato}% +\SetKw{KwA}{a}% +\SetKw{KwRitorna}{ritorna}% +\SetKw{Ritorna}{ritorna}% +\SetKwBlock{Inizio}{inizio}{fine}% +\SetKwRepeat{Ripeti}{ripeti}{finché}% +% +\SetKwIF{Sea}{AltSe}{Altrimenti}{se}{allora}{altrimenti se}{allora}{fine se}% +\SetKwSwitch{Switch}{Case}{Other}{switch}{do}{case}{otherwise}{endsw}% +\SetKwFor{Per}{per}{fai}{fine per}% +\SetKwFor{PerPar}{per}{fai in parallelo}{fine per}% +\SetKwFor{PerCiascun}{per ciascun}{fai}{fine per ciascun}% +\SetKwFor{PerTutti}{per tutti i}{fai}{fine per tutti}% +\SetKwFor{Finche}{finché}{fai}{fine finché}% +% +% --- End +%} +% +%\algocf@defaults@common +% +% option onelanguage redefinition +% +\ifthenelse{\boolean{algocf@optonelanguage}\AND\equal{\algocf@languagechoosen}{french}}{% +\SetKwInput{KwIn}{Entr\'ees}% +\SetKwInput{KwOutSortie}{Sorties}% +\SetKwInput{KwData}{Donn\'ees}% +\SetKwInput{KwResult}{R\'esultat}% +\SetKw{KwTo}{\`a}% +\SetKw{KwRet}{retourner}% +\SetKw{Return}{retourner}% +\SetKwBlock{Begin}{d\'ebut}{fin}% +\SetKwRepeat{Repeat}{r\'ep\'eter}{jusqu'\`a}% +% +\SetKwIF{If}{ElseIf}{Else}{si}{alors}{sinon si}{sinon}{fin si}% +\SetKwSwitch{Switch}{Case}{Other}{suivant}{faire}{cas o\`u}{autres cas}{fin d'alternative}% +\SetKwFor{For}{pour}{faire}{fin pour}% +\SetKwFor{ForPar}{pour}{faire en parallèle}{fin pour}% +\SetKwFor{ForEach}{pour chaque}{faire}{fin pour chaque}% +\SetKwFor{ForAll}{pour tous les}{faire}{fin pour tous}% +\SetKwFor{While}{tant que}{faire}{fin tq}% +}{}% +\ifthenelse{\boolean{algocf@optonelanguage}\AND\equal{\algocf@languagechoosen}{german}}{% +\SetKwInput{KwIn}{Eingabe}%KwIn +\SetKwInput{KwOut}{Ausgabe}%KwOut +\SetKwInput{KwData}{Daten}%KwData +\SetKwInput{KwResult}{Ergebnis}%KwResult +\SetKw{KwTo}{bis}%KwTo +\SetKw{KwRet}{zur\"uck}%KwRet +\SetKw{Return}{zur\"uck}%Return +\SetKwBlock{Begin}{Beginn}{Ende}%Begin +\SetKwRepeat{Repeat}{wiederhole}{bis}%Repeat +% +\SetKwIF{If}{ElseIf}{Else}{wenn}{dann}{sonst wenn}{sonst}{Ende wenn}%gIf +\SetKwSwitch{Switch}{Case}{Other}{unterscheide}{tue}{Fall}{sonst}{Ende Unt.}%Switch +\SetKwFor{For}{f\"ur}{tue}{Ende f\"ur}%For +\SetKwFor{ForPar}{f\"ur}{tue gleichzeitig}{Ende gleichzeitig}%ForPar +\SetKwFor{ForEach}{f\"ur jedes}{tue}{Ende f\"ur}%ForEach +\SetKwFor{ForAll}{f\"ur alle}{tue}{Ende f\"ur}%ForAll +\SetKwFor{While}{solange}{tue}{Ende solange}%While +}{}% +\ifthenelse{\boolean{algocf@optonelanguage}\AND\equal{\algocf@languagechoosen}{portugues}}{% +\SetKwInput{KwIn}{Entrada}% +\SetKwInput{KwOut}{Sa\'{i}da}% +\SetKwInput{KwData}{Dados}% +\SetKwInput{KwResult}{Resultado}% +\SetKw{KwTo}{at\'{e}} +\SetKw{KwRet}{retorna}% +\SetKw{Return}{retorna}% +\SetKwBlock{Begin}{in\'{i}cio}{fim}% +\SetKwRepeat{Repeat}{repita}{at\'{e}}% +% +\SetKwIF{If}{ElseIf}{Else}{se}{ent\~{a}o}{sen\~{a}o se}{sen\~{a}o}{fim se}% +\SetKwSwitch{Switch}{Case}{Other}{selecione}{fa\c{c}a}{caso}{sen\~{a}o}{fim selec}% +\SetKwFor{For}{para}{fa\c{c}a}{fim para}% +\SetKwFor{ForPar}{para}{fa\c{c}a em paralelo}{fim para} +\SetKwFor{ForEach}{para cada}{fa\c{c}a}{fim para cada}% +\SetKwFor{ForAll}{para todo}{fa\c{c}a}{fim para todo}% +\SetKwFor{While}{enquanto}{fa\c{c}a}{fim enqto}% +}{}% +\ifthenelse{\boolean{algocf@optonelanguage}\AND\equal{\algocf@languagechoosen}{italiano}}{% +\SetKwInput{KwIn}{Ingresso}% +\SetKwInput{KwOut}{Uscita}% +\SetKwInput{KwData}{Dati}% +\SetKwInput{KwResult}{Risultato}% +\SetKw{KwTo}{a}% +\SetKw{KwRet}{ritorna}% +\SetKw{Return}{ritorna}% +\SetKwBlock{Begin}{inizio}{fine}% +\SetKwRepeat{Repeat}{ripeti}{finché}% +% +\SetKwIF{If}{ElseIf}{Else}{se}{allora}{altrimenti se}{allora}{fine se}% +\SetKwSwitch{Switch}{Case}{Other}{switch}{do}{case}{otherwise}{endsw}% +\SetKwFor{For}{per}{fai}{fine per}% +\SetKwFor{ForPar}{per}{fai in parallelo}{fine per}% +\SetKwFor{ForEach}{per ciascun}{fai}{fine per ciascun}% +\SetKwFor{ForAll}{per tutti i}{fai}{fine per tutti}% +\SetKwFor{While}{finché}{fai}{fine finché}% +}{}% +% +%%%% old commands compatibility +% +\ifthenelse{\boolean{algocf@oldcommands}}{% +\newcommand{\SetNoLine}{\SetAlgoNoLine}% +\newcommand{\SetVline}{\SetAlgoVlined}% +\newcommand{\SetLine}{\SetAlgoLined}% +% +\newcommand{\dontprintsemicolon}{\DontPrintSemicolon}% +\newcommand{\printsemicolon}{\PrintSemicolon}% +\newcommand{\incmargin}[1]{\IncMargin{#1}}% +\newcommand{\decmargin}[1]{\DecMargin{-#1}}% +\newcommand{\setnlskip}[1]{\SetNlSkip{#1}}% +\newcommand{\Setnlskip}[1]{\SetNlSkip{#1}}% +\newcommand{\setalcapskip}[1]{\SetAlCapSkip{#1}}% +\newcommand{\setalcaphskip}[1]{\SetAlCapHSkip{#1}}% +\newcommand{\nlSty}[1]{\NlSty{#1}}% +\newcommand{\Setnlsty}[3]{\SetNlSty{#1}{#2}{#3}}% +\newcommand{\linesnumbered}{\LinesNumbered}% +\newcommand{\linesnotnumbered}{\LinesNotNumbered}% +\newcommand{\linesnumberedhidden}{\LinesNumberedHidden}% +\newcommand{\showln}{\ShowLn}% +\newcommand{\showlnlabel}[1]{\ShowLnLabel{#1}}% +\newcommand{\nocaptionofalgo}{\NoCaptionOfAlgo}% +\newcommand{\restorecaptionofalgo}{\RestoreCaptionOfAlgo}% +\newcommand{\restylealgo}[1]{\RestyleAlgo{#1}}% +% +\newcommand{\Titleofalgo}[1]{\TitleOfAlgo{#1}}% +\SetKwIF{gSi}{gSinonSi}{gSinon}{si}{alors}{sinon si}{sinon}{fin si}% +\SetKwIF{gIf}{gElsIf}{gElse}{if}{then}{else if}{else}{end if}% +\SetKwIF{gIf}{gElseIf}{gElse}{if}{then}{else if}{else}{end if}% +\SetKwIF{gWenn}{gSonstWenn}{gSonst}{wenn}{dann}{sonst wenn}{sonst}{Ende wenn}%gIf +\SetKwIF{gSe}{gSenaoSe}{gSenao}{se}{ent\~{a}o}{sen\~{a}o se}{sen\~{a}o}{fim se}% +\SetKwIF{gSea}{gAltSe}{gAltrimenti}{se}{allora}{altrimenti se}{allora}{fine se}% +}{% + \relax% +}% +% +% +% +%% +%%% +%%%% END \ No newline at end of file diff --git a/2BIT/summer-semester/ITY/3/xnecasr00/etiopan.eps b/2BIT/summer-semester/ITY/3/xnecasr00/etiopan.eps new file mode 100644 index 0000000..aa3311a Binary files /dev/null and b/2BIT/summer-semester/ITY/3/xnecasr00/etiopan.eps differ diff --git a/2BIT/summer-semester/ITY/3/xnecasr00/oniisan.eps b/2BIT/summer-semester/ITY/3/xnecasr00/oniisan.eps new file mode 100644 index 0000000..b88536c --- /dev/null +++ b/2BIT/summer-semester/ITY/3/xnecasr00/oniisan.eps @@ -0,0 +1,1193 @@ +%!PS-Adobe-3.0 EPSF-3.0 +%%Creator: 0.45pre1 +%%Pages: 1 +%%Orientation: Portrait +%%BoundingBox: 69 53 613 193 +%%HiResBoundingBox: 69.24637 53.328416 612.60491 192.39715 +%%EndComments +%%Page: 1 1 +0 240 translate +0.8 -0.8 scale +0 0 0 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+\usepackage{graphicx} +\usepackage{pdflscape} + + +\begin{document} +\catcode`\-=12 + +\begin{titlepage} +\begin{center} +\Huge\textsc{Vysoké učení technické v Brně} + +\huge\textsc{Fakulta informačních technologií} + +\vspace{\stretch{0.382}} + +\LARGE Typografie a~publikování -- 3. projekt + +\Huge Tabulky a obrázky + +\vspace{\stretch{0.618}} +\end{center} +{\Large \today \hfill Roman Nečas} +\end{titlepage} + +\section{Úvodní strana} +Název práce umístěte do zlatého řezu a nezapomeňte uvést \emph{dnešní} (today) datum a vaše jméno a příjmení. + +\section{Tabulky} +Pro sázení tabulek můžeme použít buď prostředí \verb| tabbing | nebo prostředí \verb| tabular|. + +\subsection{Prostředí \texttt{tabbing}} +Při použití \verb| tabbing | vypadá tabulka následovně: + +\begin{tabbing} + Vodní melouny \quad \= Množství \quad \= Jednotka \quad \= Cena za jedn. \quad \= Cena celková \kill + \textbf{Ovoce} \> \textbf{Množství} \> \textbf{Jednotka} \> \textbf{Cena za jedn.} \> \textbf{Cena celková} \\ + Jablka \> 3 \> kg \> 25,90 Kč \> 77,70 Kč \\ + Hrušky \> 2,5 \> kg \> 27,40 Kč \> 68,50 Kč \\ + Vodní melouny \> 1 \> kus \> 35,-- Kč \> 35,-- Kč +\end{tabbing} +\bigskip +\noindent Toto prostředí se dá také použít pro sázení algoritmů, ovšem vhodnější je použít prostředí \verb| algorithm | nebo \verb|algorithm2e | (viz sekce \ref{section3}). + +\subsection{Prostředí \texttt{tabular}} +Další možností, jak vytvořit tabulku, je použít prostředí \verb| tabular|. Tabulky pak budou vypadat takto \footnote{Kdyby byl problém s \texttt{cline}, zkuste se podívat třeba sem: \href{http://www.abclinuxu.cz/tex/poradna/show/325037}{http://www.abclinuxu.cz/tex/poradna/show/325037}.}: +\bigskip +\begin{table}[h] + \centering + \begin{tabular}{|l|c|c|} \hline + & \multicolumn{2}{c|}{\textbf{Cena}} \\ \cline{2-3} + \textbf{Měna} & \textbf{nákup} & \textbf{prodej} \\ \hline + EUR & 23,26 & 24,93 \\ + GBP & 29,56 & 29,83 \\ + USD & 22,27 & 23,12 \\ \hline + \end{tabular} + \caption{Tabulka kurzů k dnešnímu dni} + \label{tab1} +\end{table} +\bigskip +\begin{table}[h] + \centering + \begin{tabular}{|c|c|} \hline + $A$ & $\neg A$ \\ \hline + \textbf{P} & N \\ \hline + \textbf{O} & O \\ \hline + \textbf{X} & X \\ \hline + \textbf{N} & P \\ \hline + \end{tabular} + \begin{tabular}{|c|c|c|c|c|c|} \hline + \multicolumn{2}{|c|}{\multirow{2}{*}{$A \wedge B$}} & \multicolumn{4}{c|}{$B$} \\ \cline{3-6} + \multicolumn{2}{|c|}{} & \textbf{P} & \textbf{O} & \textbf{X} & \textbf{N} \\ \hline + \multirow{4}{*}{$A$} & \textbf{P} & P & O & X & N \\ \cline{2-6} + & \textbf{O} & O & O & N & N \\ \cline{2-6} + & \textbf{X} & X & N & X & N \\ \cline{2-6} + & \textbf{N} & N & N & N & N \\ \hline + \end{tabular} + \begin{tabular}{|c|c|c|c|c|c|} \hline + \multicolumn{2}{|c|}{\multirow{2}{*}{$A \vee B$}} & \multicolumn{4}{c|}{$B$} \\ \cline{3-6} + \multicolumn{2}{|c|}{} & \textbf{P} & \textbf{O} & \textbf{X} & \textbf{N} \\ \hline + \multirow{4}{*}{$A$} & \textbf{P} & P & P & P & P \\ \cline{2-6} + & \textbf{O} & P & O & P & O \\ \cline{2-6} + & \textbf{X} & P & P & X & X \\ \cline{2-6} + & \textbf{N} & P & O & X & N \\ \hline + \end{tabular} + \begin{tabular}{|c|c|c|c|c|c|} \hline + \multicolumn{2}{|c|}{\multirow{2}{*}{$A \to B$}} & \multicolumn{4}{c|}{$B$} \\ \cline{3-6} + \multicolumn{2}{|c|}{} & \textbf{P} & \textbf{O} & \textbf{X} & \textbf{N} \\ \hline + \multirow{4}{*}{$A$} & \textbf{P} & P & O & X & N \\ \cline{2-6} + & \textbf{O} & P & O & P & O \\ \cline{2-6} + & \textbf{X} & P & P & X & X \\ \cline{2-6} + & \textbf{N} & P & P & P & P \\ \hline + \end{tabular} + \caption{Protože Kleeneho trojhodnotová logika už je „zastaralá", uvádíme si zde příklad čtyřhodnotové logiky} + \label{tab2} +\end{table} +\bigskip +\pagebreak + +\section{Algoritmy} \label{section3} +Pokud budeme chtít vysázet algoritmus, můžeme použít prostředí \verb| algorithm|\footnote{\href{http://ftp.cstug.cz/pub/tex/CTAN/macros/latex/contrib/algorithms/algorithms.pdf}{http://ftp.cstug.cz/pub/tex/CTAN/macros/latex/contrib/algorithms/algorithms.pdf}} nebo \verb| algorithm2e|\footnote{\href{http://ftp.cstug.cz/pub/tex/CTAN/macros/latex/contrib/algorithm2e/doc/algorithm2e.pdf}{http://ftp.cstug.cz/pub/tex/CTAN/macros/latex/contrib/algorithm2e/doc/algorithm2e.pdf}}. +Příklad použití prostředí \verb| algorithm2e | viz Algoritmus \ref{algorithm1}. +\bigskip +\begin{algorithm} + \label{algorithm1} + \caption{\textsc{FastSLAM}} + \SetNlSty{}{}{: } + \SetNlSkip{-15pt} + \SetKwFor{For}{for}{do}{end\:for} + \SetAlgoNoLine + \SetAlgoNlRelativeSize{-1} + \KwIn{ $(X_{t-1}, u_t, z_t)$} + \KwOut{ $X_t$} + \BlankLine + \Indpp\Indp $\overline{X_t} = X_t = 0$ \\ + \For{$k = 1 \textrm{ to } M$}{ + $x^{[k]}_t = \textit{sample\_motion\_model}(u_t, x^{[k]}_{t-1})$ \\ + $\omega^{[k]}_t = \textit{measurement\_model}(z_t, x^{[k]}_t, m_{t-1})$ \\ + $m_t^{[k]} = \textit{updated\_occupancy\_grid}(z_t, x^{[k]}_t, m^{[k]}_{t-1})$ \\ + $\overline{X_t} = \overline{X_t} + \langle x^{[m]}_x, \omega_t^{[m]} \rangle$ \\ + } + \For{$k = 1 \textrm{ to } M$}{ + draw $i$ with probability $\approx \omega_t^{[i]}$ \\ + add $\langle x^{[k]}_x, m^{[k]}_t \rangle \textrm{ to } X_t$ \\ + } + \Return{$X_t$} +\end{algorithm} + +\section{Obrázky} +Do našich článků můžeme samozřejmě vkládat obrázky. Pokud je obrázkem fotografie, můžeme klidně použít bitmapový soubor. Pokud by to ale mělo být nějaké schéma nebo něco podobného, je dobrým zvykem takovýto obrázek vytvořit vektorově. + +\begin{figure}[h] + \centering + \scalebox{0.4}{\includegraphics{etiopan.eps} + {\reflectbox{\includegraphics{etiopan.eps}}}} + \caption{Malý Etiopánek a jeho bratříček} + \label{etiop} +\end{figure} +\bigskip +\pagebreak + +Rozdíl mezi vektorovým \ldots + +\begin{figure}[h] + \centering + \scalebox{0.4}{\includegraphics{oniisan.eps}} + \caption{Vektorový obrázek} + \label{vektor} +\end{figure} + +\ldots a bitmapovým obrázkem + +\begin{figure}[h] + \centering + \scalebox{0.6}{\includegraphics{oniisan2.eps}} + \caption{Bitmapový obrázek} + \label{bitmap} +\end{figure} + +\noindent se projeví například při zvětšení. + +Odkazy (nejen ty) na obrázky \ref{etiop}, \ref{vektor} a \ref{bitmap}, na tabulky \ref{tab1} a \ref{tab2} a také na algoritmus \ref{algorithm1} jsou udělány pomocí křížových odkazů. Pak je ovšem potřeba zdrojový soubor přeložit dvakrát. + +Vektorové obrázky lze vytvořit i přímo v \LaTeX u, například pomocí prostředí \verb| picture| . +\pagebreak + +\begin{landscape} + \begin{figure}[h] + \setlength{\unitlength}{1mm} + \centering + \begin{picture}(200, 100)(0,0) + + \linethickness{0.5pt} + \put(0, 0){\framebox(200, 105){}} + + \linethickness{2.75pt} + \put(0, 15){\line(1, 0){200}} % Top of sidewalk / Start of grass/driveway + + \linethickness{0.75pt} + % --- Garage (Left) --- + \put(10, 15){\line(0, 1){15}} % Left edge of driveway + \put(65, 15){\line(0, 1){15}} % Right edge of driveway + \put(10, 30){\line(1, 0){55}} % Bottom edge of garage door / Top of driveway + \put(10, 30){\line(0, 1){25}} % Left wall of garage + \put(65, 30){\line(0, 1){25}} % Right wall of garage (shared with main house) + + % Garage Door + \put(12, 30){\framebox(51, 20){}} % Garage door frame + \put(37.5, 30){\line(0, 1){20}} % Vertical divider + \put(12, 40){\line(1, 0){51}} % Horizontal divider + + % Garage Roof + \put(10, 55){\line(2, 1){27.5}} % Left roof slope + \put(65, 55){\line(-2, 1){27.5}} % Right roof slope + \put(8, 54.5){\line(2, 1){29.5}} % Roof edge overhang left + \put(67, 54.5){\line(-2, 1){29.5}}% Roof edge overhang right + \put(8, 54.5){\line(1,0){59}} % Bottom roof edge line + + % Garage Gable Shingles Pattern + \put(17, 57){\line(1,0){41}} + \put(21, 59){\line(1,0){33}} + \put(24, 61){\line(1,0){27}} + \put(28, 63){\line(1,0){19}} + \put(32, 65){\line(1,0){11}} + + % --- Main House Section (Middle) --- + \put(65, 30){\line(1, 0){50}} % Bottom wall edge above foundation + \put(115, 30){\line(0, 1){25}}% Right wall edge of this section + + % Brick Foundation + \put(65, 25){\line(1, 0){50}} % Bottom of bricks + \put(65, 25){\line(0, 1){5}} % Left edge of bricks + \put(115, 25){\line(0, 1){5}} % Right edge of bricks + \multiput(67, 26)(5,0){10}{\line(1,0){3}} % Brick pattern row 1 + \multiput(66, 28)(5,0){10}{\line(1,0){3}} % Brick pattern row 2 + + % Window (Middle Section) + \put(80, 38){\framebox(20, 8){}} % Window frame + \multiput(80, 42)(4,0){6}{\line(0,1){0}} % Simulate horizontal panes top (dots) + \multiput(80, 38)(0,4){3}{\line(1,0){20}} % Simulate vertical panes (full lines) + \put(90, 38){\line(0, 1){8}} % Center vertical bar + + % Front Door Area + \put(105, 30){\line(0, 1){10}} % Left side of door frame area + \put(113, 30){\line(0, 1){10}}% Right side of door frame area + \put(107, 30){\framebox(4, 8){}} % Door + % Porch Roof + \put(104, 40){\line(1, 1){3}} % Left porch roof slope + \put(114, 40){\line(-1, 1){3}} % Right porch roof slope + \put(107, 43){\line(1, 0){4}} % Porch roof peak + \put(104, 40){\line(1, 0){10}} % Porch roof eave + + % Main Roof (Middle Section) + \put(65, 55){\line(1, 0){50}} % Roof line connecting to right section wall + \put(37.5, 69){\line(1,0){77.5}} % Eave line lower edge + + \multiput(45, 66)(5,0){14}{\line(1,0){3}} + \multiput(51, 63)(5,0){13}{\line(1,0){3}} + \multiput(57, 60)(5,0){11}{\line(1,0){3}} + \multiput(63, 57)(5,0){10}{\line(1,0){3}} + + % --- Two-Story Section (Right) --- + \put(115, 25){\line(0, 1){54}} % Left wall of right section (up to roof start) + \put(155, 25){\line(0, 1){54}} % Right wall of right section + \put(115, 25){\line(1, 0){40}} % Bottom edge of wall + + % Planter Box (Right) + \put(117, 25){\framebox(36, 5){}} % Planter box + % Bush in planter (Simplified curves/scribble) + \qbezier(118, 30)(125, 35)(130, 30) + \qbezier(130, 30)(138, 36)(145, 30) + \qbezier(145, 30)(150, 34)(152, 30) + \put(117, 30){\line(1,0){36}} % Top line of soil/bush base + + + % Lower Window (Right Section) + \put(125, 35){\framebox(20, 8){}} % Frame + \put(135, 35){\line(0, 1){8}} % Vertical divider + \put(125, 39){\line(1, 0){20}} % Horizontal divider + + % Balcony + \put(115, 50){\line(1, 0){40}} % Balcony floor line + \put(115, 49){\line(1, 0){40}} % Balcony floor thickness + \put(115, 49){\line(0, 1){1}} + \put(155, 49){\line(0, 1){1}} + % Railing + \multiput(117, 50)(5, 0){8}{\line(0, 1){6}} % Vertical posts + \put(117, 56){\line(1, 0){35}} % Top rail + + % Upper Sliding Door/Window (Right Section) + \put(122, 51){\framebox(25, 15){}} % Frame + \put(132.5, 51){\line(0, 1){15}} % Vertical divider + + % Right Section Roof + + \put(113, 78){\line(1, 1){22}} % Roof edge overhang left + \put(157, 78){\line(-1, 1){22}} % Roof edge overhang right + \put(113, 78){\line(1,0){44}} % Bottom roof edge line + + \put(114, 78){\line(1, 1){21}} + \put(156, 78){\line(-1, 1){21}} + + % --- Landscaping Details --- + + % Plant Pot (Left of main section) + \put(70, 32){\oval(6, 4)[b]} % Bottom half of pot + \put(67, 32){\line(0,1){5}} + \put(73, 32){\line(0,1){5}} + \put(70, 37){\oval(6, 4)[t]} % Top half of pot rim + % Plant leaves (simplified lines) + \put(70, 37){\line(0, 1){5}} + \put(70, 37){\line(-1, 1){4}} + \put(70, 37){\line(1, 1){4}} + \put(70, 37){\line(-2, 1){5}} + \put(70, 37){\line(2, 1){5}} + + % Bush (Near middle window) + \qbezier(85, 30)(90, 36)(95, 30) + \qbezier(90, 30)(95, 35)(100, 30) + \put(85, 30){\line(1,0){15}} % base line + + % Simple Grass representation (random dots) + \multiput(11, 16)(3, 0){18}{\multiput(0,0)(0, 2){7}{.}} % Left lawn area + \multiput(105, 16)(2, 0){5}{\multiput(0,0)(0, 2.5){4}{.}} % Small area right of path + + \put(180, 90){\circle{12}} + + \end{picture} + \caption{Vektorový obrázek domu z jistého animovaného seriálu} + \label{fig:cartoon_house} + \end{figure} +\end{landscape} + +\end{document} \ No newline at end of file diff --git a/2BIT/summer-semester/ITY/4/Makefile b/2BIT/summer-semester/ITY/4/Makefile new file mode 100644 index 0000000..23ffa3f --- /dev/null +++ b/2BIT/summer-semester/ITY/4/Makefile @@ -0,0 +1,12 @@ +PROJ=proj4 + +$(PROJ): $(PROJ).tex + latex $(PROJ).tex + bibtex $(PROJ).aux + latex $(PROJ).tex + latex $(PROJ).tex + dvips -t a4 $(PROJ).dvi + ps2pdf $(PROJ).ps + +clean: + rm -f $(PROJ).dvi $(PROJ).ps $(PROJ).log $(PROJ).aux $(PROJ).bbl $(PROJ).blg $(PROJ).pdf \ No newline at end of file diff --git a/2BIT/summer-semester/ITY/4/czplain.bst b/2BIT/summer-semester/ITY/4/czplain.bst new file mode 100644 index 0000000..fd257b3 --- /dev/null +++ b/2BIT/summer-semester/ITY/4/czplain.bst @@ -0,0 +1,3270 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Projekt: IBP - Bakalarska prace +% Nazev prace: BibTeX styl pro CSN ISO 690 a CSN ISO 690-2 +% Autor: Radek Pysny, xpysny00 +% URI: http://www.fit.vutbr.cz/study/DP/BP.php?id=7848 +% +% Soubor: czplain.bst (vznikl upravou plain.bst) +% Datum: Vytvoren 15. unora 2009. +% Posledni uprava 10. kveten 2009, 16:55. +% Adam Herout upravil pro šablonu BP/DP FIT: 31.7.2019 +% Jaroslav Dytrych uvedl do souladu s normou +% pro šablonu BP/DP FIT: 10.10.2019 +% Petr Veigend provedl úpravy pro normu ISO 690:2022 03.04.2024 +% Popis: Český bibliografický styl. +% Pouziti: +% Kodovani: UTF-8 +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%% VOLBY PRO NASTAVENI BIBLIOGRAFICKEHO STYLU %%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% -- Maximalni pocet zpracovanych autoru. +% Pokud obsahuje polozka author seznam o vice nez opt.aa autoru, objevi se +% v bibliograficke citaci prave opt.aa autoru. Tento vycet autoru bude zakoncen +% retezcem urcenym volbou opt.etal. +% FUNCTION {opt.aa} { #3 } +% FUNCTION {opt.aa} { #4 } +FUNCTION {opt.aa} { #5 } +% FUNCTION {opt.aa} { #99 } + + +% -- Maximalni pocet zpracovanych editoru. +% Analogie k volbe opt.aa. +% FUNCTION {opt.ae} { #1 } +% FUNCTION {opt.ae} { #2 } +% FUNCTION {opt.ae} { #3 } +% FUNCTION {opt.ae} { #4 } +FUNCTION {opt.ae} { #5 } + +% -- Oddelovac mezi jednotlivymi jmeny ve vyctu. +% Pouziva se pro spojeni jmen ve vyctu. Vyjimkou jsou posledni dve jmena, ktera +% jsou spojena pomoci retezce urceneho volbou opt.sep.ln. +FUNCTION {opt.sep.bn} { "; " } % ČSN 690:2022 +% FUNCTION {opt.sep.bn} { ", " } +% FUNCTION {opt.sep.bn} { " -- " } + +% -- Oddelovac mezi poslednimi dvema jmeny ve vyctu. +FUNCTION {opt.sep.ln} { " a~" } +% FUNCTION {opt.sep.ln} { " -- " } + +% -- Naznak nedokonceneho vyctu jmen. +% Pokud byl presazen pocet jmen danych limitujicimi volbami opt.aa nebo opt.ae. +% Dale se pouzije tehdy, kdyz je misto posledniho jmena pouzito klicove slovo +% "others". +FUNCTION {opt.etal} { "et~al." } +% FUNCTION {opt.etal} { "aj." } +% FUNCTION {opt.etal} { "a kol." } + +% -- Oznaceni editora (redaktora). +% Jmena editoru jsou od autoru odlisena retezcem danym touto volbou. +FUNCTION {opt.ed} { "ed." } +% FUNCTION {opt.ed} { "(ed.)" } +% FUNCTION {opt.ed} { "(red.)" } +% FUNCTION {opt.ed} { "" } + +% -- Pouzivat oznaceni editora (redaktora) za kazdym jmenem. +% Urcuje, kde se pouzije oznaceni opt.ed. Bud lze pouzit oznaceni za kazdym +% jmenem nebo jen na konci prvku. +FUNCTION {opt.ed.all} { #0 } % pouze na konci prvku +% FUNCTION {opt.ed.all} { #1 } % za kazdym jmenem + +% -- Oddelovac mezi prvky primarni odpovednost a titul. +FUNCTION {opt.sep.a} { "." } +% FUNCTION {opt.sep.a} { ":" } + +% -- Oddelovac mezi mistem a vydavatelem (popr. skolou nebo instituci). +FUNCTION {opt.sep.p} { ": " } +% FUNCTION {opt.sep.p} { " : " } +% FUNCTION {opt.sep.p} { ", " } + +% -- Oddelovac mezi titulem a podtitulem. +% Je-li zadan titul i podtitul, je tento retezec pouzit jako oddelovac mezi +% temito prvky. +FUNCTION {opt.sep.t} { ": " } +% FUNCTION {opt.sep.t} { " : " } + +% -- Oznaceni rozsahu u akademickych praci. +% U akademickych praci mate pomoci teto volby moznost urcit, zda-li bude rozsah +% techto praci udavan ve stranach nebo v listech. +FUNCTION {opt.pages} { "s." } % pocet stran +% FUNCTION {opt.pages} { "l." } % pocet listu + +% -- Zacatek prvku dostupnost. +% Tento prepinac ovlivnuje text, ktery bude zobrazen pred URL adresou. +% FUNCTION {opt.url} { "" } +% FUNCTION {opt.url} { "Dostupn{\'{e}} na: " } +FUNCTION {opt.url} { "Dostupn{\'{e}} z: " } +% FUNCTION {opt.url} { "Dostupn{\'{e}} na WWW: " } + +FUNCTION {opt.path} { "Path: " } + +FUNCTION {opt.doi} { opt.url } + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%% DEKLARACE POLOZEK A PROMENNYCH %%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% Polozky, ktere jsou stylem akceptovany a zpracovany. +ENTRY + { address + author + booktitle + booksubtitle % podtitul knihy (napr u sborniku) + cited % datum citace + contributory % podrizena odpovednost + day + doi + edition + editionnumber % cislo edice + editor + howpublished % druh nosice + chapter + institution + inserts % pocet stran priloh + isbn % standardni cislo + issn % standardni cislo + journal + journalsubtitle + key + location + month + note + number + organization + path + pages + publisher + revised % datum revize/aktualizace + secondarytitle % nazev vedlejsi webove stranky + school + series % název edice + subtitle % podtitul + supervisor % vedoucí (u akademické práce) + time % čas publikování + title + type + url % dostupnost + version % verze u el.dok. + volume + year + } + { } + { label } + +% Celocislene promenne. U kazde (krome konstant, ktere jsou pouze inicializovany +% ve funkci init.state.consts -- before.all, mid.sentence, after.sentence, +% after.block) jsou vyjmenovany funkce, kde dochazi ke zmenam dane promenne. +% +% output.state -- output.nonnull, output.bibitem, new.block, new.sentance +% +% ord -- is.ord +% +% ptr, i, x -- str.to.int +% +% numnames, namesleft, nameptr -- format.names, format.names.ed, +% sort.format.names +INTEGERS { output.state before.all mid.sentence after.sentence after.block + ord ptr i x numnames namesleft nameptr } + +% Retezcove promenne. U kazde jsou vyjmenovany funkce, kde je promenna menena. +% +% s -- output.nonnull, format.names, format.names.ed, format.journal.issue, +% format.thesis.info, format.thesis.range, chop.word, sort.format.names +% +% t -- output.check, dashify, str.to.int, format.names, format.names.ed, +% format.full.date, sort.format.names, sort.format.title +% +% u -- is.ord, tie.or.connnect, comma.connect +STRINGS { s t u } + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%% DEFINICE ZKRATEK -- CESKE NAZVY MESICU %%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +MACRO {jan} {"leden"} + +MACRO {feb} {"únor"} + +MACRO {mar} {"březen"} + +MACRO {apr} {"duben"} + +MACRO {may} {"květen"} + +MACRO {jun} {"červen"} + +MACRO {jul} {"červenec"} + +MACRO {aug} {"srpen"} + +MACRO {sep} {"září"} + +MACRO {oct} {"říjen"} + +MACRO {nov} {"listopad"} + +MACRO {dec} {"prosinec"} + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%% MIRNE UPRAVENE FUNKCE PREVZATE Z plain.bst %%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% Inicializace konstant nutnych pro spravnou funkci samotneho stylu. +% +% void init.state.consts () +% { +% int before.all = 0; +% int mid.sentence = 1; +% int adter.sentence = 2; +% int after.block = 3; +% } +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +% Vystup jiz formatovaneho pole, ktere je urcite neprazdne. Format vystupu je +% ovlivnen vystupnim stavem (tj. stavovou promennou output.state). Samotny +% vystup je zpozdeny (k vytisteni aktualni hodnoty dojde az pri pristim volani +% teto funkce) kvuli rozhodovani o pouzitem oddelovaci (carka nebo tecka). +% +% void output.nonnull () +% { +% s = pop(); +% if (output.state == mid.sentence) +% { +% write(pop() * " "); // zde byla carka!!! +% } else +% { +% if (output.state == after.block) +% { +% write(add.period(pop())); +% flush(); +% write("\newblock "); +% } else +% { +% if (output.state == before.all) +% { +% write(pop()); +% } else +% { +% write(add.period(pop()) * " "); +% } +% } +% } +% push(s); +% } +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { " " * write$ } %% Uprava: Nahrada ", " za " "! + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + { write$ } + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +% Pri vyskytu neprazdne hodnoty na vrcholu zasobniku provede jeji vystup pomoci +% funkce output.nonnull. V opacnem pripade ji jen odstrani ze zasobniku. +% +% /** prepis do pseudokodu bez vyuziti zasobniku **/ +% void output (string string.to.write) +% { +% if (empty$(string.to.write)) +% { } else +% { +% output.nonnull(string.to.write); +% } +% } +FUNCTION {output} +{ duplicate$ empty$ + { pop$ } + { output.nonnull } + if$ +} + +% Pri vyskytu neprazdne hodnoty na vrcholu zasobniku provede jeji vystup pomoci +% funkce output.nonnull. V opacnem pripade ji jen odstrani ze zasobniku +% a vypise na chybovy vystup varovani o chybejici hodnote. Pouziva se pro +% informovani uzivatele o chybejici hodnote, ktera je dle ceske normy povinna. +% +% /** prepis do pseudokodu bez vyuziti zasobniku **/ +% void output.check (string type.of.field string string.to.write) +% { +% t = type.of.field; +% if (empty$(string.to.write)) +% { +% warning$("empty" * t * " in " * cite$()) +% } else +% { +% output.nonnull(string.to.write); +% } +% } +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + { output.nonnull } + if$ +} + +% Vypise zacatek bibliograficke citace. +% +% void output.bibitem () +% { +% newline$(); +% write$("\bibitem{"); +% write$(cite$); +% write$("}"); +% newline$(); +% push(""); +% int output.state = before.all; +% } +FUNCTION {output.bibitem} +{ newline$ + "\bibitem{" write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +% Zakonceni polozky (teckou). +% +% void fin.entry () +% { +% write(add.period$(pop())); +% newline$(); +% } +FUNCTION {fin.entry} +{ add.period$ write$ + newline$ +} + +% Zmena stavu: {mid.sentence; after.sentence} => after.block. +% +% void new.block () +% { +% if (output.state == before.all) +% { } else +% { +% output.state = after.block; +% } +% } +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +% Zmena stavu: mid.sentence => after.sentence. +% +% void new.sentence () +% { +% if (output.state == after.block) +% { } else +% { +% if (output.state == before.all) +% { } else +% { +% output.state = after.sentence; +% } +% } +% } +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +% Negace vyhodnocene podminky. +% +% int not (int bool) +% { +% if (bool) +% { +% return 0; // false +% } else +% { +% return 1; // true +% } +% } +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +% Logicky soucin dvou podminek. +% +% int and (int bool1, int bool2) +% { +% if (bool2) +% { +% return bool1; +% } else +% { +% return 0; +% } +% } +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +% Logicky soucet dvou podminek. +% +% int or (int bool1, int bool2) +% { +% if (bool2) +% { +% return 1; +% } else +% { +% return bool1; +% } +% } +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +% Zacatek noveho bloku pri neprazne hodnote na vrcholu zasobniku. +% +% void new.block.checka (int.or.string anything.from.the.top) +% { +% if (empty$(anything.from.the.top)) +% { } else +% { +% new.block(); +% } +% } +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + { new.block } + if$ +} + +% Zacatek noveho bloku pri 2 neprazdnych hodnotach z vrcholu zasobniku. +% +% void new.block.checkb (int.or.string anything.under.the.top, +% int.or.string anything.from.the.top) +% { +% if ( (empty$(anything.from.the.top)) && (empty$(anything.under.the.top)) ) +% { } else +% { +% new.block(); +% } +% } +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + { new.block } + if$ +} + +% Zacatek nove vety pri neprazne hodnote na vrcholu zasobniku. +% +% void new.sentence.checka (int.or.string anything.from.the.top) +% { +% if (empty$(anything.from.the.top)) +% { } else +% { +% new.sentence(); +% } +% } +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + { new.sentence } + if$ +} + +% Zacatek nove vety pri 2 neprazdnych hodnotach z vrcholu zasobniku. +% +% void new.sentence.checkb (int.or.string anything.under.the.top, +% int.or.string anything.from.the.top) +% { +% if ( (empty$(anything.from.the.top)) && (empty$(anything.under.the.top)) ) +% { } else +% { +% new.sentence(); +% } +% } +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ and + 'skip$ + { new.sentence } + if$ +} + +% Vrati hodnoty polozky (ulozene na vrcholu zasobniku) nebo prazdny retezec. +% +% int.or.string field.or.null (int.or.string anything.from.the.top) +% { +% if (empty$(anything.from.the.top)) +% { +% return ""; +% } else +% { +% return anything.from.the.top; +% } +% } +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +% Vypis chybove hlasky pro pripady, kdyz jsou vyplnene dve polozky, jejichz +% pouziti se vzajemne vylucuje. Vola se s dvema argumenty -- prvni z nich je +% retezec s nazvy obou poli (kvuli vypisu chybove hlasky) a druhy je obsah +% jednoho z poli (kontrola druheho musi probehnout pred volanim teto funkce). +% +% void either.or.check (string field.names, int.or.string one.of.fields) +% { +% if (empty$(one.of.fields)) +% { } else +% { +% warning$(field.names * "can't use both " * " fields in " * cite$()); +% } +% } +FUNCTION {either.or.check} +{ empty$ + { pop$ } + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +% Provede zvyrazneni hodnoty na vrcholu zasobniku (uzavre ji mezi "{\em" +% a "}"). Nepouziva kurzivni korekci. +% +% string emphasize (string x) +% { +% if (empty$(x)) +% { +% return ""; +% } else +% { +% return "{\em " * x * "}"; +% } +% } +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "{\em " swap$ * "}" * } + if$ +} + +FUNCTION {makebold} +{ duplicate$ empty$ + { pop$ "" } + { "{\bf " swap$ * "}" * } + if$ +} + +FUNCTION {makesmall} +{ duplicate$ empty$ + { pop$ "" } + { "{\small " swap$ * "}" * } + if$ +} + +% Nahradi kazdy vyskyt znaku '-' za dvojznak "--". +% +% string dashify (string to.dashify) +% { +% t = to.dashify; +% push(""); +% while (!empty$(t)) +% { +% if (substring$(t, 1, 1) == "-") +% { +% if (substring$(t, 1, 2) == "--") +% { +% while (substring$(t, 1, 1) == "-") +% { +% push(pop() * "-"); +% t = substring$(t, 2, global.max$()); +% } +% } else +% { +% push(pop() * "--"); +% t = substring$(t, 2, global.max$()); +% } +% } else +% { +% push(pop() * substring$(t, 1, 1)); +% t = substring$(t, 2, global.max$()); +% } +% } +% } +FUNCTION {dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + { "--" * + t #2 global.max$ substring$ 't := + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%% VLASTNI KOD -- POMOCNE FUNKCE %%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% Prevod retezce na cislo. Ocekava se, ze se zavola az po testu pomoci funkce +% 'is.ord'. Na vstupu ocekava neprazdny retezec tvoreny jen cislicemi. +% +% int str.to.int (string to.convert) +% { +% t = to.convert; +% int x = 0; +% int ptr = 0; +% while (ptr text.length$(t) < ) +% { +% push(x); +% i = 9; +% while (i > 0) +% { +% push(pop() + x); +% i--; +% } +% ptr++; +% x = chr.to.int$(substring$(t, ptr, 1)) - 48 + pop(); +% } +% return x; +% } +FUNCTION {str.to.int} +{ 't := + #0 'x := + #0 'ptr := + { ptr t text.length$ < } + { x + #9 'i := + { i #0 > } + { x + + i #1 - 'i := + } + while$ + ptr #1 + 'ptr := + t ptr #1 substring$ chr.to.int$ #48 - + 'x := + } + while$ + x +} + +% Prvni pismeno retezce na vrcholu zasobniku prevede na verzalku. +% +% string capitalize (string to.capitalize) +% { +% if (empty$(to.capitalize)) +% { } else +% { +% return change.case$(substring$(to.capitalize, 1, 1), "u") * +% substring$(to.capitalize, 2, global.max$()); +% } +% } +FUNCTION {capitalize} +{ duplicate$ empty$ + 'skip$ + { duplicate$ #1 #1 substring$ "u" change.case$ + swap$ #2 global.max$ substring$ * + } + if$ +} + +% Spojuje dva retezce z vrcholu zasobniku. Tyto dva retezce jsou oddeleny +% mezerou ci nezlomitelnou mezerou. Retezec na vrcholu zasobniku je pripojen +% za druhy retezec. +% +% Pokud je jeden z retezcu prazdny, je vracen jen druhy z nich bez jakychkoliv +% uprav. Jsou-li prazdne oba retezce, je vracen taktez prazdny retezec. +% +% string tie.or.connect (string under.the.top, string from.the.top) +% { +% string u = from.the.top; +% if (empty$(under.the.top)) +% { +% return u; +% } else +% { +% if (empty$(u)) +% { } else +% { +% if (text.length$(u) < 3) +% { +% return under.the.top * "~" * u; +% } else +% { +% return under.the.top * " " * u; +% } +% } +% } +% } +FUNCTION {tie.or.connect} +{ 'u := + duplicate$ empty$ + { pop$ u } + { u empty$ + 'skip$ + { u text.length$ #3 < + { "~" * u * } + { " " * u * } + if$ + } + if$ + } + if$ +} + +% Spojuje dva retezce z vrcholu zasobniku. Tyto dva retezce jsou oddeleny +% carkou. Retezec na vrcholu zasobniku je pripojen za druhy retezec. +% +% Pokud je jeden z retezcu prazdny, je vracen jen druhy z nich bez jakychkoliv +% uprav. Jsou-li prazdne oba retezce, je vracen taktez prazdny retezec. +% +% string comma.connect (string under.the.top, string from.the.top) +% { +% string u = from.the.top; +% if (empty$(under.the.top)) +% { +% return u; +% } else +% { +% if (empty$(u)) +% { } else +% { +% return under.the.top * ", " * u; +% } +% } +% } +FUNCTION {comma.connect} +{ 'u := + duplicate$ empty$ + { pop$ u } + { u empty$ + 'skip$ + { ", " * u * } + if$ + } + if$ +} + +% Spojuje dva retezce z vrcholu zasobniku. Tyto dva retezce jsou oddeleny mezerou. +FUNCTION {space.connect} +{ 'u := + duplicate$ empty$ + { pop$ u } + { u empty$ + 'skip$ + { " " * u * } + if$ + } + if$ +} + + +% Otestuje, zda je hodnota na vrcholu zasobniku tvorena pouze cislicemi. +% +% int is.ord (string x) +% { +% string u = x; +% int ord = 1; +% while ( (ord) && (!empty(u)) ) +% { +% if ( (chr.to.int$(substring$(u, 1, 1)) < 48) || +% (chr.to.int$(substring$(u, 1, 1)) > 57) ) +% { +% ord = 0; +% } else +% { +% u = substring(s, 2, global.max$()); +% } +% } +% return ord; +% } +FUNCTION {is.ord} +{ 'u := + #1 'ord := + { ord + u empty$ not + and + } + { u #1 #1 substring$ + duplicate$ chr.to.int$ #48 < % < '0' + swap$ chr.to.int$ #57 > % > '9' + or + { #0 'ord := } + { u #2 global.max$ substring$ 'u := } + if$ + } + while$ + ord +} + +% Formatovaci retezec pro vkladani jmen dle ceske konvence pomoci funkce +% 'format.name$'. +% +% string cz.name.format () +% { +% return "{{\scshape\bgroup}ll{ }{\egroup}}{, f.}{ vv}"; +% } +FUNCTION {cz.name.format} +{ "{{\sc\bgroup}ll{ }{\egroup}}{, f.}{ vv}" } + +% Vraci nominativ mesice. +% +% /** prepis pseudokodu do funkce pracujici s polem **/ +% string get.month.n (int n) +% { +% int month = { 1 => "leden", "únor", "březen", "duben", "květen", "červen", +% "červenec", "srpen", "září", "říjen", "listopad", "prosinec" }; +% if ( (n > 0) && (n < 13) ) +% { +% return month[n]; +% } else +% { +% warning$("Month must be between 1 and 12!"); +% return ""; +% } +% } +FUNCTION {get.month.n} +{ duplicate$ #1 = + { "leden" swap$ pop$ } + { duplicate$ #2 = + { "únor" swap$ pop$ } + { duplicate$ #3 = + { "březen" swap$ pop$ } + { duplicate$ #4 = + { "duben" swap$ pop$ } + { duplicate$ #5 = + { "květen" swap$ pop$ } + { duplicate$ #6 = + { "červen" swap$ pop$ } + { duplicate$ #7 = + { "červenec" swap$ pop$ } + { duplicate$ #8 = + { "srpen" swap$ pop$ } + { duplicate$ #9 = + { "září" swap$ pop$ } + { duplicate$ #10 = + { "říjen" swap$ pop$ } + { duplicate$ #11 = + { "listopad" swap$ pop$ } + { duplicate$ #12 = + { "prosinec" swap$ pop$ } + { "" "Month must be between 1 and 12!" warning$ } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ +} + +% Vraci nominativ mesice s velkym prvnim pismenem. +FUNCTION {get.u.month.n} +{ duplicate$ #1 = + { "Leden" swap$ pop$ } + { duplicate$ #2 = + { "Únor" swap$ pop$ } + { duplicate$ #3 = + { "Březen" swap$ pop$ } + { duplicate$ #4 = + { "Duben" swap$ pop$ } + { duplicate$ #5 = + { "Květen" swap$ pop$ } + { duplicate$ #6 = + { "Červen" swap$ pop$ } + { duplicate$ #7 = + { "Červenec" swap$ pop$ } + { duplicate$ #8 = + { "Srpen" swap$ pop$ } + { duplicate$ #9 = + { "Září" swap$ pop$ } + { duplicate$ #10 = + { "Říjen" swap$ pop$ } + { duplicate$ #11 = + { "Listopad" swap$ pop$ } + { duplicate$ #12 = + { "Prosinec" swap$ pop$ } + { "" "Month must be between 1 and 12!" warning$ } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ +} + +% Vraci genitiv mesice. +% +% /** prepis pseudokodu do funkce pracujici s polem **/ +% string get.month.g (int n) +% { +% int month = { 1 => "ledna", "února", "března", "dubna", "května", "června", +% "července", "srpna", "září", "října", "listopadu", "prosince"}; +% if ( (n > 0) && (n < 13) ) +% { +% return month[n]; +% } else +% { +% warning$("Month must be between 1 and 12!"); +% return ""; +% } +% } +FUNCTION {get.month.g} +{ duplicate$ #1 = + { "ledna" swap$ pop$ } + { duplicate$ #2 = + { "února" swap$ pop$ } + { duplicate$ #3 = + { "března" swap$ pop$ } + { duplicate$ #4 = + { "dubna" swap$ pop$ } + { duplicate$ #5 = + { "května" swap$ pop$ } + { duplicate$ #6 = + { "června" swap$ pop$ } + { duplicate$ #7 = + { "července" swap$ pop$ } + { duplicate$ #8 = + { "srpna" swap$ pop$ } + { duplicate$ #9 = + { "září" swap$ pop$ } + { duplicate$ #10 = + { "října" swap$ pop$ } + { duplicate$ #11 = + { "listopadu" swap$ pop$ } + { duplicate$ #12 = + { "prosince" swap$ pop$ } + { "" "Month must be between 1 and 12!" warning$ } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ +} + +% Provede vystup. Je urcen jen pro vypsani primarni odpovednosti. Umoznuje +% pouziti volby 'opt.sep.a', ktera dovoluje pouzit jiny oddelovac mezi poli +% primarni odpovednosti a nazvu titulu. Dle zazitych zvyklosti v CR je jim ':'. +% +% Pouzivat pouze na zacatku bibliograficke citace! Jinde muze zpusobit prohozeni +% prvku. +% +% void output.authors (string formatted.authors) +% { +% if (substring$(formatted.authors, #-1, #1) == opt.sep.a()) +% { +% write$(formatted.authors); +% newline$(); +% write("\newblock "); +% } else +% { +% write$(formatted.authors * opt.sep.a()); +% newline$(); +% write("\newblock "); +% } +% } +FUNCTION {output.authors} +{ + duplicate$ #-1 #1 substring$ opt.sep.a = + { write$ newline$ "\newblock " write$ } + { opt.sep.a * + write$ newline$ "\newblock " write$ + } + if$ +} + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%% VLASTNI KOD -- FORMATOVACI FUNKCE %%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% Formatovani jmen (pro primarni odpovednost). +% +% string format.names (string names) +% { +% string s = names; +% int numnames = num.names$(s); +% int namesleft = numnames; +% int nameptr = 1; +% while ( (namesleft > 0) && (nameptr <= opt.aa()) ) +% { +% t = format.name$(s, nameptr, cz.name.format()); +% if (nameptr == 1) +% { +% push(t); +% } else +% { +% if (namesleft > 1) +% { +% push(pop() * opt.sep.bn() * t); +% } else +% { +% if (purify$(t) == "others") +% { +% push(tie.or.connect(pop(), opt.etal())); +% } else +% { +% push(pop() * opt.sep.ln() * t); +% } +% } +% } +% nameptr++; +% namesleft--; +% } +% if (nameledt > 0) +% { +% push(tie.or.connect(pop(), opt.etal())); +% } +% return pop(); +% } +FUNCTION {format.names} +{ 's := % s <= polozka se jmeny + s num.names$ 'numnames := % numnames <= pocet jmen v polozce + numnames 'namesleft := % poznamena si pocet zbyvajicich jmen + #1 'nameptr := % nameptr <= ukazatel na prvni ze jmen + { namesleft #0 > + nameptr opt.aa > not + and + } + { % cyklus zpracovani jednotlivych jmen + s nameptr cz.name.format format.name$ 't := + nameptr #1 = + { t } % prvni jmeno + { namesleft #1 > % dalsi jmena + { opt.sep.bn t * * } + { t purify$ + "others" = % kdyz po ocisteni zbyde klic. sl. "others" + { opt.etal tie.or.connect } % vytiskne et al. + { opt.sep.ln * t * } % jinak posledni inicialy po spojce "a" + if$ + } + if$ + } + if$ + nameptr #1 + 'nameptr := % posun ukazatele na dalsi jmeno + namesleft #1 - 'namesleft := % snizeni poctu zbyvajicich jmen + } + while$ + namesleft #0 > % mozne pridani opt.etal + { opt.etal tie.or.connect } + 'skip$ + if$ +} + +% Formatovani jmen editoru. +% +% string format.names.ed (string names) +% { +% string s = names; +% int numnames = num.names$(s); +% int namesleft = numnames; +% int nameptr = 1; +% while ( (namesleft > 0) && (nameptr <= opt.aa()) ) +% { +% t = format.name$(s, nameptr, cz.name.format()); +% if (nameptr == 1) +% { +% if (opt.ed.all()) +% { +% push(tie.or.connect(t, opt.ed()); +% } else +% { +% push(t); +% } +% } else +% { +% if (namesleft > 1) +% { +% if (opt.ed.all()) +% { +% push(tie.or.connect(pop() * opt.sep.bn() * t, opt.ed()); +% } else +% { +% push(pop() * opt.sep.bn() * t); +% } +% } else +% { +% if (purify$(t) == "others") +% { +% push(tie.or.connect(pop(), opt.etal())); +% } else +% { +% if (opt.ed.all()) +% { +% push(tie.or.connect(pop() * opt.sep.ln() * t, opt.ed()); +% } else +% { +% push(pop() * opt.sep.ln() * t); +% } +% } +% } +% } +% nameptr++; +% namesleft--; +% } +% if (nameledt > 0) +% { +% push(tie.or.connect(pop(), opt.etal())); +% } +% if (opt.ed.all()) +% { +% return pop(); +% } else +% { +% return tie.or.connect(pop(), ", " * opt.ed()); +% } +% } +FUNCTION {format.names.ed} +{ 's := % s <= polozka se jmeny + s num.names$ 'numnames := % numnames <= pocet jmen v polozce + numnames 'namesleft := % poznamena si pocet zbyvajicich jmen + #1 'nameptr := % nameptr <= ukazatel na prvni ze jmen + { namesleft #0 > + nameptr opt.ae > not + and + } + { % cyklus zpracovani jednotlivych jmen + s nameptr cz.name.format format.name$ 't := + nameptr #1 = % prvni jmeno + { t + opt.ed.all + { opt.ed tie.or.connect } + 'skip$ + if$ + } + { namesleft #1 > % dalsi jmena + { opt.sep.bn t * * + opt.ed.all + { opt.ed tie.or.connect } + 'skip$ + if$ + } + { t purify$ + "others" = % kdyz po ocisteni zbyde klic. sl. "others" + { opt.etal tie.or.connect } % vytiskne et al. + { opt.sep.ln t * * % jinak posledni inicialy po spojce "a" + opt.ed.all + { opt.ed tie.or.connect } + 'skip$ + if$ + } + if$ + } + if$ + } + if$ + nameptr #1 + 'nameptr := % posun ukazatele na dalsi jmeno + namesleft #1 - 'namesleft := % snizeni poctu zbyvajicich jmen + } + while$ + namesleft #0 > % mozne pripojeni opt.etal + { opt.etal tie.or.connect } + 'skip$ + if$ + opt.ed.all % mozne pridani opt.ed na konec prvku + 'skip$ + { ", " * opt.ed tie.or.connect } + if$ +} + +% Formatovani jmen autoru. +% Pokud je neprazdna polozka 'author', provede formatovani jmen pomoci funkce +% 'format.names'. +% +% string format.authors () +% { +% if (empty$(author)) +% { +% return ""; +% } else +% { +% return format.names(author); +% } +% } +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +% Formatovani jmena vedouciho. +FUNCTION {format.supervisor} +{ supervisor empty$ + { "" } + { "Vedoucí práce " supervisor format.names *} + if$ +} + + +% Formatovani jmen editoru. +% Pokud je neprazdna polozka 'editor', provede formatovani jmen pomoci funkce +% 'format.names.ed'. +% +% string format.editors () +% { +% if (empty$(editor)) +% { +% return ""; +% } else +% { +% return format.names.ed(editor); +% } +% } +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names.ed } + if$ +} + +% Formatovani polozky primarni odpovednosti. +% Je-li zadana polozka 'author', provede jeji formatovani pomoci funkce +% 'format.authors'. Pokud je polozka 'author' prazdna, provede formatovani +% pomoci funkce 'format.editors'. +% +% void author.or.editor () +% { +% if (empty$(author)) +% { +% if (empty$(format.editors())) +% { +% warning$("empty author and editor in " * cite$()); +% } else +% { +% output.authors(format.editors()); +% } +% } else +% { +% output.authors(format.authors()); +% } +% } +FUNCTION {author.or.editor} +{ author empty$ + { format.editors + duplicate$ empty$ + { pop$ + "empty author and editor in " cite$ * warning$ + } + { output.authors } + if$ + } + { format.authors + output.authors + } + if$ +} + +% Formatovani nazvu (napr. casopisu, zurnalu atp.). +% Pri zadane polozce 'subtitle' provede ji pripoji k obsahu polozky 'title' +% pomoci ": ". V nazvu je pak provedena zmena velikosti pismen. +% +% string format.title () +% { +% if (empty$(subtitle)) +% { +% return capitalize(title); +% } else +% { +% return capitalize(title) * opt.sep.t() * subtitle; +% } +% } +FUNCTION {format.title} +{ subtitle empty$ + { title capitalize } + { title capitalize + opt.sep.t * subtitle * + } + if$ +} +%%FUNCTION {format.title} +%%{ subtitle empty$ +%% { title "t" change.case$ } +%% { title "t" change.case$ +%% opt.sep.t * subtitle "t" change.case$ * +%% } +%% if$ +%%} + + +% Formatovani nazvu monograficke publikace. +% Pri zadane polozce 'subtitle' provede ji pripoji k obsahu polozky 'title' +% pomoci ": ". Pricemz na obe casti se provede zmena velikosti pismen +% a zvyrazneni. Pokud je polozka 'subtitle' prazdna, je provedena jen zmena +% velikosti pismen a jeji zvyrazneni. +% +% string format.btitle () +% { +% return emphasize(format.title()); +% } +FUNCTION {format.btitle} +{ format.title emphasize +} + +% Formatovani nazvu (napr. sbornik). +% Pri zadane polozce 'booksubtitle' provede ji pripoji k obsahu polozky +% 'booktitle' pomoci ": ". V nazvu je pak provedena zmena velikosti pismen +% a zvyrazneni kurzivou. +% +% string format.from.btitle () +% { +% if (empty$(booktitle)) +% { +% warning$(empty booktitle in " * cite$()); +% push(""); +% } else +% { +% push(capitalize(booktitle)); +% if (empty$(booksubtitle)) +% { } else +% { +% push(pop() * opt.sep.t * booksubtitle); +% } +% } +% return emphasize(pop()); +% } +FUNCTION {format.from.btitle} +{ booktitle empty$ + { "empty booktitle in " cite$ * warning$ + "" + } + { booktitle capitalize + booksubtitle empty$ + 'skip$ + { opt.sep.t * booksubtitle * } + if$ + } + if$ + emphasize +} + +% Formatovani druhu nosice. +% +% string format.howpublished () +% { +% if (empty$(howpublished)) +% { +% return ""; +% } else +% { +% if (change.case(howpublished, "l") == "cd") +% { +% push("CD-ROM"); +% } else +% { +% if (change.case(howpublished, "l") == "online") +% { +% push("online"); +% } else +% { +% push(howpublished); +% } +% } +% return "" * pop() * ""; +% } +% } +FUNCTION {format.howpublished} +{ howpublished empty$ + { "" } + { howpublished "l" change.case$ "cd" = + { "CD-ROM" } + { howpublished "l" change.case$ "online" = + { "online" } + { howpublished } + if$ + } + if$ + "" swap$ * "" * + } + if$ +} + +% Formatovani vydani +% +% string format.edition () +% { +% if (empty$(edition)) +% { +% push(""); +% } else +% { +% if (is.ord(edition)) +% { +% push(edition * ". vyd."); +% } else +% { +% push(edition); +% } +% } +% if (!empty$(version)) +% { +% push(comma.connect(pop(), version)); +% } +% return pop(); +% } +FUNCTION {format.edition} +{ edition empty$ + { "" } + { edition is.ord + { edition ". vyd." * } + { edition } + if$ + } + if$ + howpublished empty$ + 'skip$ + { version empty$ + 'skip$ + { version comma.connect } + if$ + } + if$ +} + +% Formatovani mesice a roku +% +% string format.date () +% { +% if (empty$(month)) +% { +% if (empty$(year)) +% { +% warning$("empty year in " * cite$()); +% return ""; +% } else +% { +% return year; +% } +% } else +% { +% if (empty$(year)) +% { +% warning$("just month (empty year) in " * cite$()); +% return ""; +% } else +% { +% if (is.ord(month)) +% { +% return get.month.n(str.to.int(month)) * " " * year; +% } else +% { +% return month * " " * year; +% } +% } +% } +% } +FUNCTION {format.date} +{ month empty$ + { year empty$ + { "" + "empty year in " cite$ * warning$ } + { year } + if$ + } + { year empty$ + { "" + "just month (empty year) in " cite$ * warning$ } + { month duplicate$ is.ord + { str.to.int get.month.n " " * year * } + { " " * year * } + if$ + } + if$ + } + if$ +} + +% Formatovani mesice a roku s genitivem měsíce +FUNCTION {format.date.g} +{ month empty$ + { year empty$ + { "" + "empty year in " cite$ * warning$ } + { year } + if$ + } + { year empty$ + { "" + "just month (empty year) in " cite$ * warning$ } + { month duplicate$ is.ord + { str.to.int get.month.g " " * year * } + { " " * year * } + if$ + } + if$ + } + if$ +} + +% Formatovani mesice a roku, kde mesic zacina velkym pismenem +FUNCTION {format.u.date} +{ month empty$ + { year empty$ + { "" + "empty year in " cite$ * warning$ } + { year } + if$ + } + { year empty$ + { "" + "just month (empty year) in " cite$ * warning$ + } + { month duplicate$ is.ord + { str.to.int get.u.month.n " " * year * } + { " " * year * } + if$ + } + if$ + } + if$ +} + +% Rozpoznani a prevod data z formatu '!yyyy-mm-dd'. +% +% string format.full.date (string date) +% { +% string t = date; +% if (text.length$(t) == 10) +% { +% if ( (is.ord(substring$(t, 1, 4))) && (substring$(t, 5, 1) == "-") && +% (is.ord(substring$(t, 6, 2))) && (substring$(t, 8, 1) == "-") && +% (is.ord(substring$(t, 9, 2))) ) +% { +% if (substring$(t, 9, 1) == "0") +% { +% if (substring$(t, 10, 1) == "0") +% { +% warning$("day must be between 1 and 31 in " * cite$()); +% } else { } +% push(substring$(t, 10, 1) * ".~"); +% } else +% { +% if ( ((chr.to.int$(substring$(t, 9, 1)) - 48) > 3) || +% ((substring$(t, 9, 1) == "3") && +% ((chr.to.int$(substring$(t, 10, 1)) - 48) > 1)) ) +% { +% pop(); +% push(t); +% warning$("day must be between 1 and 31 in " * cite$()); +% } else { } +% push(substring$(t, 9, 2) * ".~"); +% } +% if (substring$(t, 6, 1) == "0") +% { +% if (substring$(t, 7, 1) == "0") +% { +% pop(); +% push(t); +% warning$("month must be between 1 and 12 in " * cite$()); +% } else +% { +% return pop() * get.month.g(chr.to.int$(substring$(t, 7, 1)) - 48) * +% " " * substring$(t, 1, 4)); +% } +% } else +% { +% if ( (substring$(t, 6, 1) == "1") && +% ((chr.to.int$(substring$(t, 7, 1)) - 48) < 3) ) +% { +% return pop() * get.month.g(chr.to.int$(substring$(t, 7, 1)) +% - 48 + 10) * " " * substring$(t, 1, 4)); +% } else +% { +% pop(); +% push(t); +% warning$("month must be between 1 and 12 in " * cite$()); +% } +% } +% } else +% { +% return t; +% } +% } else +% { +% return t; +% } +% } +FUNCTION {format.full.date} +{ 't := + t text.length$ #11 = + { t #1 #1 substring$ "!" = + t #2 #4 substring$ is.ord + t #6 #1 substring$ "-" = + t #7 #2 substring$ is.ord + t #9 #1 substring$ "-" = + t #10 #2 substring$ is.ord + and and and and and + { t #10 #1 substring$ "0" = + { t #11 #1 substring$ "0" = + { "day must be between 1 and 31 in " cite$ * warning$ } + 'skip$ + if$ + t #11 #1 substring$ ".~" * + } + { t #10 #1 substring$ chr.to.int$ #48 - #3 > + t #10 #1 substring$ "3" = + t #11 #1 substring$ chr.to.int$ #48 - #1 > + and or + { pop$ t "day must be between 1 and 31 in " cite$ * warning$ } + 'skip$ + if$ + t #10 #2 substring$ ".~" * + } + if$ + t #7 #1 substring$ "0" = + { t #8 #1 substring$ "0" = + { pop$ t "month must be between 1 and 12 in " cite$ * warning$ } + { t #8 #1 substring$ chr.to.int$ #48 - get.month.g * + " " * t #2 #4 substring$ * + } + if$ + } + { t #7 #1 substring$ "1" = + t #8 #1 substring$ chr.to.int$ #48 - #3 < + and + { t #8 #1 substring$ chr.to.int$ #48 - #10 + get.month.g * + " " * t #2 #4 substring$ * + } + { pop$ t "month must be between 1 and 12 in " cite$ * warning$ } + if$ + } + if$ + } + { t } + if$ + } + { t } + if$ +} + +% Predani udaju z data revize elektronickeho dokumentu. +% +% string format.revised () +% { +% if (empty$(howpublished)) +% { +% return ""; +% } else +% { +% if (empty$(revised)) +% { +% return ""; +% } else +% { +% return revised; +% } +% } +% } +FUNCTION {format.revised} +{ howpublished empty$ + { "" } + { revised empty$ + { "" } + { revised } + if$ + } + if$ +} + +% Formatovani udaju z data citace elektronickeho dokumentu. +% +FUNCTION {format.cited} +{ cited empty$ + { "" } + { cited format.full.date + "[cit. " swap$ * "]" * +% "[vid. " swap$ * "]" * + } + if$ +} + +% Formatovani nakladatelskych udaju. +% +% string format.publish.info () +% { +% if ( (empty$(address)) && (empty$(publisher)) ) +% { +% string s = ""; +% } else +% { +% if (empty$(address)) +% { +% s = "[b.m.]: "; +% } else +% { +% s = address * ": "; +% } +% if (empty$(publisher)) +% { +% s = s * "[b.n.]"; +% } else +% { +% s = s * publisher; +% } +% } +% return s; +% } +FUNCTION {format.publish.info} +{ address empty$ + publisher empty$ + and + { "" } + { address empty$ + { "" } + { address opt.sep.p * } + if$ + publisher empty$ + { "[b.n.]" * } + { publisher * } + if$ + } + if$ +} + + +% Formatuje rozsah stran publikace. +% +% string format.range () +% { +% if (empty$(pages)) +% { +% return ""; +% } else +% { +% return tie.or.connect(pages, "s."); +% } +% } +FUNCTION {format.range} +{ pages empty$ + { "" } + { pages "s." tie.or.connect } + if$ +} + +% Formatovani edice a svazku sborníku konference. +% +% string format.cvolume () +% { +% if (empty$(volume)) +% { +% push(""); +% } else +% { +% if (is.ord(volume)) +% { +% push("sv. " * volume); +% } else +% { +% push(volume); +% } +% } +% if (empty$(number)) +% { +% return pop(); +% } else +% { +% if (is.ord(number)) +% { +% return comma.connect(pop(), "č. " * number); +% } else +% { +% return comma.connect(pop(), number); +% } +% } +% } +FUNCTION {format.cvolume} +{ volume empty$ + { "" } + { volume is.ord + { "sv. " volume * } + { volume } + if$ + } + if$ + number empty$ + { + "" comma.connect + } + { number is.ord + { "č. " number * comma.connect } + { number comma.connect } + if$ + } + if$ +} + + +% Formatovani edice a čísla edice knihy ci sborníku konference. +% +% string format.cseries () +% { +% if (empty$(series)) +% { +% return ""; +% } else +% { +% push(capitalize(series)); +% if (empty$(editionnumber)) +% { } else +% { +% if (is.ord(editionnumber)) +% { +% return comma.connect(pop(), "č. " * editionnumber); +% } else +% { +% return comma.connect(pop(), editionnumber); +% } +% } +% } +% } +FUNCTION {format.cseries} +{ series empty$ + { "" } + { series capitalize + editionnumber empty$ + 'skip$ + { editionnumber is.ord + { "č. " editionnumber * comma.connect } + { editionnumber comma.connect } + if$ + } + if$ + } + if$ +} + + +% Format dostupnosti. +% +% string format.url () +% { +% if (empty$(url)) +% { +% return ""; +% } else +% { +% return tie.or.connect(opt.url(), "\small{\url{" * url * ".}}"); +% } +% } +FUNCTION {format.url} +{ url empty$ + { "" } + { opt.url "{\small\url{" url * "}}" * tie.or.connect } + if$ +} + +% Format cesty. +% +% string format.pah () +% { +% if (empty$(path)) +% { +% return ""; +% } else +% { +% return opt.path * path; +% } +% } +FUNCTION {format.path} +{ path empty$ + { "" } + { opt.path path * } + if$ +} + +% Format ISBN. +% +% string format.isbn () +% { +% if (empty$(isbn)) +% { +% return ""; +% } else +% { +% return "ISBN " * isbn; +% } +% } +FUNCTION {format.isbn} +{ isbn empty$ + { "" } + { "ISBN " isbn * } + if$ +} + +% Format nazvu serialove publikace. +% +% string format.journal () +% { +% if (empty$(journal)) +% { +% return ""; +% } else +% { +% return emphasize(journal); +% } +% } +FUNCTION {format.journal} +{ journal empty$ + { "" } + { journalsubtitle empty$ + { journal capitalize emphasize } + { journal capitalize emphasize + opt.sep.t * journalsubtitle emphasize *} + if$ + } + if$ +} + +% Format nazvu lokace ve zdrojovem dokumentu. +% +% string format.pages () +% { +% if (empty$(pages)) +% { +% return ""; +% } else +% { +% return "s.~" * dashify(pages); +% } +% } +FUNCTION {format.pages} +{ pages empty$ + { "" } + { "s.~" pages dashify * } + if$ +} + +FUNCTION {format.chapter} +{ chapter empty$ + { "" } + { "kap.~" chapter * } + if$ +} + +% Formatovani data vydani, rocniku a cisla publikace + datum revize/aktualizace +% + darum citace + lokace ve zdrojovem dokumentu (rozsah stran). +% +% string format.journal.issue () +% { +% string s; +% if (empty$(format.u.date())) +% { +% s = ""; +% } else +% { +% s = format.u.date(); +% } +% if (!empty$(volume)) +% { +% if (is.ord(volume)) +% { +% s = comma.connect(s, "sv.~" * volume); +% } else +% { +% s = comma.connect(s, volume); +% } +% } +% if (empty$(number)) +% { +% warning$("empty number in " * cite$); +% } else +% { +% if (is.ord(number)) +% { +% s = comma.connect(s, "č.~" * number); +% } else +% { +% s = comma.connect(s, number); +% } +% } +% if (s == "") +% { +% warning$("empty journal issue info in " * cite$); +% return ""; +% } else +% { +% return s; +% } +% } +FUNCTION {format.journal.issue} +{ format.u.date + duplicate$ empty$ + { pop$ "" 's := } + { 's := } + if$ + volume empty$ + 'skip$ + { volume is.ord + { "sv.~" volume * + s swap$ comma.connect 's := + } + { s volume comma.connect 's := } + if$ + } + if$ + number empty$ + { "empty number in " cite$ * warning$ } + { number is.ord + { "č.~" number * + s swap$ comma.connect 's := + } + { s number comma.connect 's := } + if$ + } + if$ + s empty$ + { "empty journal issue info in " cite$ * warning$ + "" + } + { s } + if$ +} + +% Format ISSN. +% +% string format.issn () +% { +% if (empty$(issn)) +% { +% return ""; +% } else +% { +% return "ISBN " * issn; +% } +% } +FUNCTION {format.issn} +{ issn empty$ + { "" } + { "ISSN " issn * } + if$ +} + +% Format DOI. +% +% string format.doi () +% { +% if (empty$(doi)) +% { +% return ""; +% } else +% { +% return "DOI: " * \url(https://doi.org/ doi); +% } +% } +FUNCTION {format.doi} +{ doi empty$ + { "" } + { opt.doi "{\small\url{https://doi.org/" doi * "}}" * tie.or.connect } + if$ +} + +% Formatuje cislo svazku -- presne urceni casti pro @InBook. +% +% string format.vol () +% { +% if (empty$(volume)) +% { +% push(""); +% } else +% { +% if (is.ord(volume)) +% { +% push("sv.~" * volume); +% } else +% { +% push(volume); +% } +% } +% return capitalize(pop()); +% } +FUNCTION {format.vol} +{ volume empty$ + { "" } + { volume is.ord + { "sv.~" volume * } + { volume } + if$ + } + if$ + capitalize +} + +% Formatuje zakladni informace (primarni odpovednost a titul) o sborniku pro +% bibliograficke citaci clanku ve sborniku. +% +% In opt.sep.a() . +% +% Pokud je prazdny, netiskne se nic. +% +% void conference.basics () +% { +% if (empty$(editor)) +% { +% if (empty$(organization)) +% { +% warning$("empty editor and organization in " * cite$()); +% push(""); +% } else +% { +% if ((substring$(organization, -1, 1) == opt.sep.a()) +% { +% push(capitalize(organization)); +% } else +% { +% push(capitalize(organization * opt.sep.a())); +% } +% } +% } else +% { +% if ((substring$(format.editors(), -1, 1) == opt.sep.a()) +% { +% push(format.editors()); +% } else +% { +% push(capitalize(format.editors() * opt.sep.a())); +% } +% } +% push(tie.or.connect("In:", pop())); +% if (empty$(format.from.btitle())) +% { +% pop(); +% push(""); +% } else +% { +% push(pop() * format.from.btitle()); +% } +% return pop(); +% } +FUNCTION {conference.basics} +{ editor empty$ + { organization empty$ + { "empty editor and organization in " cite$ * warning$ + "" + } + { organization capitalize + duplicate$ #-1 #1 substring$ opt.sep.a = + 'skip$ + { opt.sep.a * } + if$ + } + if$ + } + { format.editors + duplicate$ #-1 #1 substring$ opt.sep.a = + 'skip$ + { opt.sep.a * } + if$ + } + if$ + "In:" swap$ tie.or.connect + format.from.btitle + duplicate$ empty$ + { pop$ } + { tie.or.connect } + if$ +} + + +% Formatuje informace o akademicke (diplomova, dizertacni atp.) praci. +% Odlisuje se od beznych nakladatelskych informaci pouzitymi polozkami. +% +% string format.thesis.info () +% { +% string s = ""; +% if ( (empty$(address)) && (empty$(location)) && (empty$(school)) ) +% { +% warning$("empty address and school in " * cite$()); +% } else +% { +% if (empty$(address)) +% { +% } else +% { +% s = address; +% } +% if (empty$(location)) +% { +% } else +% { +% s = location; +% } +% if (empty$(year)) +% { +% warning$("empty year in " * cite$()); +% } else +% { +% if (empty$(s)) +% { +% s = year; +% } else +% { +% s = comma.connect(s, year); +% } +% } +% } +% return s; +% } +FUNCTION {format.thesis.info} +{ "" 's := + address empty$ + location empty$ + school empty$ + and + and + { "empty address and school in " cite$ * warning$ } + { address empty$ + 'skip$ + { address 's := } + if$ + location empty$ + 'skip$ + { location 's := } + if$ + year empty$ + { "empty year in " cite$ * warning$ } + { s empty$ + { year 's := } + { s year comma.connect 's := } + if$ + } + if$ + } + if$ + s +} + +% Formatuje informace o skole v akademicke (diplomova, dizertacni atp.) praci. +% +% string format.thesis.school () +% { +% string s = ""; +% if (empty$(school)) +% { +% warning$("empty school in " * cite$()); +% } else +% { +% if (empty$(s)) +% { +% s = school; +% } else +% { +% s = s * ". " * school; +% } +% } +% return s; +% } +FUNCTION {format.thesis.school} +{ "" 's := + school empty$ + { "empty school in " cite$ * warning$ } + { s empty$ + { school 's := } + { s ". " * school * 's := } + if$ + } + if$ + s +} + + +% Formatuje pocet stran a priloh u akademickych praci. +% +% string format.thesis.range () +% { +% if ( (empty$(format.range())) && (!empty$(inserts)) ) +% { +% return format.range(); +% } else +% { +% if (is.ord(inserts)) +% { +% return comma.connect(format.range(), inserts * " příl."); +% } else +% { +% return comma.connect(format.range(), inserts); +% } +% } +% } +FUNCTION {format.thesis.range} +{ pages empty$ + { "" 's := } + { pages opt.pages tie.or.connect 's := } + if$ + s empty$ + { "" } + { inserts empty$ + { s } + { s inserts opt.pages tie.or.connect " příl." * comma.connect } + if$ + } + if$ +} + +% Formatuje typ akademicke prace. +% +% string format.thesis.type (string basic.thesis.type) +% { +% if (empty$(type)) +% { +% return basic.thesis.type; +% } else +% { +% return capitalize(type); +% } +% } +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ type capitalize } + if$ +} + + +% Fromatuje typ a cislo technicke zpravy +% +% string format.report.type () +% { +% if (empty$(type)) +% { +% push(""); +% } else +% { +% push(type); +% } +% if (empty$(number)) +% { +% } else +% { +% space.connect(pop(), number); +% } +% } +FUNCTION {format.report.type} +{ type empty$ + { "" } + { type } + if$ + number empty$ + 'skip$ + { number space.connect } + if$ +} + + +% Kontrola prazdnosti vsech policek pouzitych pro @MISC zaznam. +% +% int empty.misc.check () +% { +% if ( (empty$(author)) && (empty$(title)) && +% (empty$(howpublished)) && (empty$(month)) && (empty$(year)) && +% (empty$(note)) && (!empty$(key)) ) +% { +% warning$("all misc relevant fields are empty in " * cite$()); +% return 1; +% } else +% { +% return 0; +% } +% } +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + key empty$ not and + { "all misc relevant fields are empty in " cite$ * warning$ + #1 + } + { #0 } + if$ +} + + +% Formatuje misto a instituci technicke zpravy. +% +% string format.report.details () +% { +% if ( empty$(institution) ) +% { +% if ( empty$(address) && empty$(organization) ) +% { +% return ""; +% } else +% { +% if (empty$(address)) +% { +% push(""); +% } else +% { +% push(opt.sep.a() * " " * address * opt.sep.p()); +% } +% if (empty$(organization)) +% { +% warning$("empty organization in " * cite$()); +% } else +% { +% return pop() * organization; +% } +% } +% } else +% { +% if ( empty$(address) && empty$(institution) ) +% { +% return ""; +% } else +% { +% if (empty$(address)) +% { +%% push("[b.m.]"); +% push(""); +% } else +% { +% push(opt.sep.a() * " " * address * opt.sep.p()); +% } +% if (empty$(institution)) +% { +% warning$("institution is empty in " * cite$()); +% } else +% { +% return pop() * institution; +% } +% } +% } +% } +FUNCTION {format.report.details} +{ institution empty$ + { + address empty$ + organization empty$ + and + { "" } + { address empty$ + { "" } + { address } + if$ + organization empty$ + { "empty organization in " cite$ * warning$ } + { address empty$ + { organization * } + { opt.sep.p * organization * } + if$ + } + if$ + } + if$ + } + { + address empty$ + institution empty$ + and + { "" } + { address empty$ + { "" } + { address } + if$ + institution empty$ + { "empty institution in " cite$ * warning$ } + { address empty$ + { institution * } + { opt.sep.p * institution * } + if$ + } + if$ + } + if$ + } + if$ +} + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%% VLASTNI KOD -- FUNKCE PRO ZPRACOVANI ZAZNAMU %%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% Zpracuje zaznamy typu @Article. +% Bibliograficke citace clanku v serialovych publikaci (casopiseckych clanku). +% +% Povinne polozky: author, title, journal, edition, year, volume, number, pages, issn +% Volitelne polozky: subtitle, journalsubtitle, publisher, address, contributory, url*, month, note, doi +% Polozky el. dok.: howpublished*, revised*, cited*, version +% +% * Povinna polozka pro el. dok. +FUNCTION {article} +{ output.bibitem + format.authors + duplicate$ empty$ + { pop$ + "empty author in " cite$ * warning$ + } + { output.authors } + if$ + new.block %% primarni odpovednost (povinna) + format.title "title" output.check + new.block %% titul (povinny) + format.journal "journal" output.check + format.howpublished output + new.block + format.edition "edition" output.check + new.block %% vydani (povinne) + contributory capitalize output + new.block %% podrizena odpovednost (volitelna) + format.publish.info output + new.block + format.journal.issue comma.connect + format.pages comma.connect + format.revised output + new.block %% lokace ve zdrojovem dokumentu (povinna) + format.cseries output + new.block + format.issn output %% standardni cislo ISSN (volitelne) + new.block %% poznamky (volitelne) + howpublished empty$ + { format.url output } + { + doi empty$ + {format.url "url" output.check} + {format.doi output} + if$ + new.block + format.cited output + year empty$ + revised empty$ + and + { "empty year and revised in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + new.block + note capitalize output + new.block + fin.entry +}% @Article + +% Zpracuje zaznamy typu @Book. +% Bibliograficke citace monografickych publikaci (knih). +% +% Povinne polozky: author nebo editor, title, edition, address, publisher, year, isbn +% Volitelne polozky: subtitle, contributory, month, pages, series, number nebo volume, note, url* +% Polozky el. dok.: howpublished*, revised*, cited*, version +% +% * Povinna polozka pro el. dok. +FUNCTION {book} +{ output.bibitem + author.or.editor + new.block %% primarni odpovednost (povinna) + format.btitle "book title" output.check + format.howpublished output + new.block %% nazev (povinny) a druh nosice (povinny u el. dok.) + format.edition capitalize "edition" output.check + new.block %% vydani (povinne) + contributory capitalize output + new.block %% podrizena odpovednost (volitelna) + format.publish.info + format.date comma.connect + format.revised comma.connect + capitalize output + new.block %% nakladatelske udaje (volitelne), datum vydani (povinne), + %% datum revize/aktualizace a citace (povinne u el. dok.) + format.range output + new.block %% rozsah (volitelny) + format.cseries output + new.block %% edice (volitelna) + format.isbn "isbn" output.check + new.block + howpublished empty$ + { format.url output } + { + format.url "url" output.check + new.block + format.cited output + year empty$ + revised empty$ + and + { "empty year and revised in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + new.block + note capitalize output + new.block + fin.entry %% standardni cislo ISBN (povinne) +}% @Book + +% @Booklet je pouhy odkaz na @Book. +FUNCTION {booklet} { book } + +% Zpracuje zaznamy typu @Conference, @InProceedings, @InCollection a @InBook. +% Bibliograficke citace monografickych publikaci (knih). +% +% Povinne polozky: author, title, editor nebo organization, booktitle, +% edition, address, publisher, year, pages, isbn or issn. +% Volitelne polozky: subtitle, booksubtitle, contributory, month, series, editionnumber, number, volume, note, chapter, doi, url*. +% Polozky el. dok.: howpublished*, revised*, cited*, version. +% +% * Povinna polozka pro el. dok. +FUNCTION {conference} +{ output.bibitem + author.or.editor + new.block %% primarni odpovednost (povinna) + format.title "title" output.check + new.block %% titul prispevku + conference.basics + format.howpublished tie.or.connect output + new.block %% primarni odpovednost a titul sborniku +% format.edition "edition" output.check + format.edition output + new.block %% vydani + contributory capitalize output + new.block %% podrizena odpovednost (volitelna) + format.publish.info + format.date capitalize comma.connect + format.cvolume comma.connect + format.chapter comma.connect + format.pages comma.connect + format.revised comma.connect + capitalize output + new.block %% nakladatelske udaje, datum vydani, revize/aktualizace a citace + format.cseries output + new.block %% edice (pokud je cislovana, tak i jeji cislo nebo svazek) + isbn empty$ + { issn empty$ + { "empty isbn and issn in " cite$ * warning$ } + { format.issn output } + if$ + } + { format.isbn output } + if$ + new.block %% standardni cislo ISBN nebo ISSN (povinne) + howpublished empty$ + { format.url output } + { + doi empty$ + {format.url "url" output.check} + {format.doi output} + if$ + new.block + format.cited output + year empty$ + revised empty$ + and + { "empty year and revised in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + new.block + note capitalize output + new.block + fin.entry +} % @Conference a @InProceedings, @InCollection a @InBook + +% @InProceedings je pouhy odkaz na @Conference. +FUNCTION {inproceedings} { conference } +FUNCTION {incollection} { conference } +FUNCTION {inbook} { conference } + +% Zpracuje zaznamy typu @Proceedings. +% +% Bibliograficke citace monografickych publikaci (knih). +% +% Povinne polozky: author nebo editor, title, edition, year, isbn or issn. +% Volitelne polozky: subtitle, contributory, address, publisher, month, series, number nebo volume, note, doi, url*. +% Polozky el. dok.: howpublished*, revised*, cited*, version. +% +% * Povinna polozka pro el. dok. +FUNCTION {proceedings} +{ output.bibitem + author.or.editor + new.block %% primarni odpovednost (povinna) + format.btitle + format.howpublished tie.or.connect output + new.block %% primarni odpovednost a titul sborniku +% format.edition "edition" output.check + format.edition output + new.block %% vydani + contributory capitalize output + new.block %% podrizena odpovednost (volitelna) + format.publish.info + format.date capitalize comma.connect + format.cvolume comma.connect + format.chapter comma.connect + format.pages comma.connect + format.revised comma.connect + capitalize output + new.block %% nakladatelske udaje, datum vydani, revize/aktualizace a citace + format.cseries output + new.block %% edice (pokud je cislovana, tak i jeji cislo nebo svazek) + isbn empty$ + { issn empty$ + { "empty isbn and issn in " cite$ * warning$ } + { format.issn output } + if$ + } + { format.isbn output } + if$ + new.block %% standardni cislo ISBN nebo ISSN (povinne) + howpublished empty$ + { format.url output } + { + doi empty$ + {format.url "url" output.check} + {format.doi output} + if$ + new.block + format.cited output + year empty$ + revised empty$ + and + { "empty year and revised in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + new.block + note capitalize output + new.block + fin.entry +} % @Proceedings + +% Zpracuje zaznamy typu @Misc, @Webpage a @Website. +% +% Povinne polozky: Alespon jedna z volitelnych! +% Volitelne polozky: author, secondarytitle, title, subtitle, howpublished, contributory, edition, month, doi, issn +% year, revised*, cited, note, url, version, path +% +% Pozn.: Protestuje, pokud neni vyplneny rok. Nemel by tedy volat format.date... +FUNCTION {misc} +{ empty.misc.check + 'skip$ + { output.bibitem + format.authors + duplicate$ empty$ + { pop$ + } + { output.authors } + if$ + new.block + secondarytitle output + new.block + format.btitle "title" output.check + format.howpublished output + new.block + contributory capitalize output + new.block %% podrizena odpovednost (volitelna) + format.edition output + new.block + format.publish.info + edition empty$ + address empty$ + publisher empty$ + and + and + { + output + day empty$ + { format.u.date capitalize output } + { day ". " * format.date.g * output } + if$ + } + { + day empty$ + { format.date comma.connect output } + { day ". " * format.date.g * comma.connect output } + if$ + } + if$ + time output + revised empty$ + 'skip$ + { + new.block + format.revised output + } + if$ + new.block + format.issn output %% standardni cislo ISSN (volitelne) + new.block + howpublished empty$ + { format.url output } + { + doi empty$ + {format.url "url" output.check} + {format.doi output} + if$ + new.block + format.cited output + year empty$ + revised empty$ + and + { "empty year and revised in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + new.block + format.path output + new.block + note capitalize output + new.block + fin.entry + } + if$ +}%@Misc a @Webpage a @Website +% @Webpage a @Website sou pouhe odkazy na @Misc. +FUNCTION {webpage} { misc } +FUNCTION {website} { misc } + + +% Zpracuje zaznamy typu @Manual, @TechReport a @Unpublished. +% +% Povinne polozky: author, title, edition, address, organization nebo institution, month, year, revised +% Volitelne polozky: note, number, url* +% Polozky el. dok.: howpublished*, cited* +FUNCTION {techreport} +{ output.bibitem + author.or.editor + new.block %% primarni odpovednost (povinna) + format.btitle "title" output.check + format.howpublished output + new.block + format.report.type + format.edition capitalize comma.connect output + new.block + contributory capitalize output + new.block %% podrizena odpovednost (volitelna) + format.report.details + format.date comma.connect + format.revised comma.connect + capitalize output + new.block %% udeja o vydavajici instituci (volitelne) a datum vydani (povinne) + format.range output + new.block %% rozsah (volitelny) + format.url output + new.block %% dostupnost (volitelna) + format.cited output + new.block + note capitalize output + new.block %% poznamka (volitelna) + fin.entry +}%@Manual, @TechReport a @Unpublished +FUNCTION {manual} { techreport } +FUNCTION {unpublished} { techreport } + + +% Zpracuje zaznamy typu @BachelorsThesis, @MastersThesis a @PhdThesis. +% Bibliograficke citace akademickych praci (bakalarske, diplomove a dizertacni). +% +% Zakladni verze -- v choose.thesis ma hodnotu #0. +% +% Povinne polozky: author, title, address nebo location, school, year, type +% Volitelne polozky: subtitle, pages, inserts, note, url, isbn, howpublished +FUNCTION {thesis} +{ output.bibitem + format.authors + duplicate$ empty$ + { pop$ + "empty author in " cite$ * warning$ + } + { output.authors } + if$ + new.block %% primarni odpovednost (povinna) + format.btitle "title" output.check + format.howpublished output + new.block %% titul (povinny) + format.thesis.info capitalize output + new.block %% misto a rok {povinne) + %new.block %% cited + format.thesis.range output + new.block %% rozsah akademicke prace a jejich priloh (volitelne) + type$ "l" change.case$ + duplicate$ "bachelorsthesis" = + { pop$ "Bakalářská práce" } + { "mastersthesis" = + { "Diplomová práce" } + { "Disertační práce" } + if$ + } + if$ + format.thesis.type output + new.block %% typ akademicke prace (volitelny -- pouzije se implicitni) + format.thesis.school output + new.block + format.isbn output + new.block + format.supervisor output + new.block + format.url output + new.block %% cited + format.cited output + new.block + note capitalize output + fin.entry %% standardni cislo ISBN (volitelne) +}%@BachelorsThesis, @MastersThesis a @PhdThesis + +% Zaznamy typu @BachelorsThesis jsou zpracovany funkci thesis. +FUNCTION {bachelorsthesis}{ thesis } + +% Zaznamy typu @MastersThesis jsou zpracovany funkci thesis. +FUNCTION {mastersthesis} { thesis } + +% Zaznamy typu @PhdThesis jsou zpracovany funkci thesis. +FUNCTION {phdthesis} { thesis } + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%% MIRNE UPRAVENE FUNKCE PREVZATE Z plain.bst %%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% nacteni bibliograficke databaze +READ + +% Pripravi hodnotu pro razeni -- aplikuje vestavenou funkci purify$ a prevede +% na minusky. +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +% Deklarace dalsi celociselne promenne. +INTEGERS { len } + +% Vrati pouze cast predane hodnoty. +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +% Piprava jmen na razeni. +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { nameptr #1 > + { " " * } + 'skip$ + if$ +% s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + s nameptr "{ll{ }}{ ff{ }}{ vv{ }}" format.name$ 't := %% Zamena! + nameptr numnames = t "others" = and + { opt.etal * } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +% Priprava titulu na serazeni. +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +% Serazeni dle autora. +FUNCTION {author.sort} +{ key empty$ + { author empty$ + editor empty$ + and + { "to sort, need author or key in " cite$ * warning$ + "" + } + { author empty$ + { editor sort.format.names } + { author sort.format.names } + if$ + } + if$ + } + { key sortify } + if$ +} + +% Dytrych: Původní funkce upřednostní jméno před klíčem a ten pak nelze použít k opravě českého řazení. +% FUNCTION {author.sort} +% { author empty$ +% { key empty$ +% { "to sort, need author or key in " cite$ * warning$ +% "" +% } +% { key sortify } +% if$ +% } +% { author sort.format.names } +% if$ +% } + +% Serazeni dle editora. +FUNCTION {author.editor.sort} +{ key empty$ + { author empty$ + { editor empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ + } + { key sortify } + if$ +} +% FUNCTION {author.editor.sort} +% { author empty$ +% { editor empty$ +% { key empty$ +% { "to sort, need author, editor, or key in " cite$ * warning$ +% "" +% } +% { key sortify } +% if$ +% } +% { editor sort.format.names } +% if$ +% } +% { author sort.format.names } +% if$ +% } + +% Serazeni dle autora, editora nebo organizace. Jedna se o nevyuzitou funkci. +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +% Serazeni dle editora ci organizace. Jedna se o nevyuzitou funkci. +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + +% Priprava na razeni. +% +% Funkce je zmenena oproti puvodnimu zneni v plain.bst. +FUNCTION {presort} +{ type$ "book" = + type$ "inbook" = + or + { author.editor.sort } + { author.sort } + if$ + " " * + year field.or.null sortify * + " " * + title field.or.null + sort.format.title * + #1 entry.max$ substring$ + 'sort.key$ := +} + +% Provede pripravu pred razenim. +ITERATE {presort} + +% Provede serazeni. +SORT + +% Deklarace retezcove promenne pro urceni nejdelsiho navesti do soupisu bib.cit. +STRINGS { longest.label } + +% Deklarace pomocnych ciselnych promennych. +INTEGERS { number.label longest.label.width } + +% Inicializace pomocnych promennych. +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #1 'number.label := + #0 'longest.label.width := +} + +% Predani nejdelsiho navesti. +FUNCTION {longest.label.pass} +{ number.label int.to.str$ 'label := + number.label #1 + 'number.label := + label width$ longest.label.width > + { label 'longest.label := + label width$ 'longest.label.width := + } + 'skip$ + if$ +} + +% Provede inicializaci pomocnych promennych. +EXECUTE {initialize.longest.label} + +% Vybere nejdelsi navesti. +ITERATE {longest.label.pass} + +% Tato funkce se stara o prvni radky, ktere se objevi ve vystupnim souboru. +% +% Tato funkce je rozsirena o podminenou definici prikazu \url{}. +FUNCTION {begin.bib} +{ "\makeatletter" write$ newline$ +%%% "\@ifundefined{url}" +%%% "{\def\url#1{{\tt $<$#1$>$}}}" * +%%% "{\DeclareUrlCommand\url{\def\UrlLeft{<} \def\UrlRight{>} \urlstyle{tt}}}" * +%%% write$ newline$ + "\makeatother" write$ newline$ + preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" longest.label * "}" * write$ newline$ +} + +% Funkce zapise posledni radky do vystupniho souboru -- uzavre prostredi +% thebibliography. +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +% Vlozi do vystupniho souboru zacatek prostredi thebibliography. +EXECUTE {begin.bib} + +% Provede inicilizaci potrebnych konstant. +EXECUTE {init.state.consts} + +% Zpracovani vsech citovanych zaznamu. +ITERATE {call.type$} + +% Uzavre prostredi thebibliography. +EXECUTE {end.bib} diff --git a/2BIT/summer-semester/ITY/4/literatura.bib b/2BIT/summer-semester/ITY/4/literatura.bib new file mode 100644 index 0000000..e07ef8e --- /dev/null +++ b/2BIT/summer-semester/ITY/4/literatura.bib @@ -0,0 +1,116 @@ +@Book{hawking1988, + author = {Hawking, Stephen W.}, + title = {A Brief History of Time: From the Big Bang to Black Holes}, + edition = {1}, + publisher = {Bantam Books}, + year = {1988}, + address = {Toronto}, + pages = {198}, + isbn = {978-0553052435} +} + +@Book{hawking2002, + author = {Hawking, Stephen W.}, + title = {Vesmír v orechovej škrupinke}, + edition = {1}, + publisher = {Slovart}, + year = {2002}, + address = {Bratislava}, + pages = {224}, + isbn = {9788071456889} +} + +@Misc{benkovicova2024, + author = {Benkovičová, Kristína}, + title = {Hypotézu o Hawkingovom žiarení po prvý raz publikovali pred 50 rokmi}, + howpublished = {online}, + year = {2024}, + month = {3}, + day = {1}, + organization = {CVTI SR – Veda na dosah}, + address = {Bratislava}, + url = {https://vedanadosah.cvtisr.sk/priroda/fyzika/hypotezu-o-hawkingovom-ziareni-po-prvy-raz-publikovali-pred-50-rokmi/}, + cited = {2025-04-18} +} + +@Misc{filo2015, + author = {Filo, Jakub}, + title = {Z čiernej diery sa dá uniknúť. Podľa Hawkinga aj do iného vesmíru}, + howpublished = {online}, + year = {2015}, + month = {8}, + day = {26}, + organization = {SME Tech}, + address = {Bratislava}, + url = {https://tech.sme.sk/c/7982326/z-ciernej-diery-sa-da-uniknut-podla-hawkinga-aj-do-ineho-vesmiru.html}, + cited = {2025-04-18} +} + +@Misc{nasa2019, + author = {{NASA Science Editorial Team}}, + title = {Shedding Light on Black Holes}, + howpublished = {online}, + year = {2019}, + month = {8}, + day = {13}, + organization = {NASA Science}, + url = {https://science.nasa.gov/science-research/astrophysics/shedding-light-on-black-holes/}, + cited = {2025-04-18} +} + +@Article{hawking1974, + author = {Hawking, Stephen W.}, + title = {Black hole explosions?}, + journal = {Nature}, + edition = {248}, + year = {1974}, + volume = {248}, + number = {5443}, + pages = {30--31}, + issn = {0028-0836} +} + +@Article{hawking1975, + author = {Hawking, S. W.}, + title = {Particle creation by black holes}, + journal = {Communications in Mathematical Physics}, + edition = {43}, + year = {1975}, + volume = {43}, + number = {3}, + pages = {199--220}, + publisher = {Springer-Verlag}, + issn = {0010-3616}, + language = {eng}, + keywords = {83.53} +} + +@BachelorsThesis{jurca2010, + author = {Jurča, Miroslav}, + title = {Černé díry}, + howpublished = {online}, + year = {2010}, + address = {České Budějovice}, + school = {Jihočeská univerzita v Českých Budějovicích, Pedagogická fakulta}, + type = {Bakalářská práce}, + note = {Vedoucí práce: RNDr. Petr Jelínek, Ph.D.}, + url = {https://theses.cz/id/0vjbt7/}, + cited = {2025-04-19} +} + +@PhdThesis{alford2021, + author = {Alford, Frederick}, + title = {A Mathematical Study of Hawking Radiation on Collapsing, Spherically Symmetric Spacetimes}, + school = {University of Cambridge}, + year = {2021}, + address = {Cambridge}, + type = {Dizertační práce (PhD)} +} + +@Proceedings{nature, + editor = {{Nature Publishing Group}}, + title = {Nature}, + address = {London}, + year = {1869--}, + issn = {0028-0836} +} \ No newline at end of file diff --git a/2BIT/summer-semester/ITY/4/proj4.tex b/2BIT/summer-semester/ITY/4/proj4.tex new file mode 100644 index 0000000..225d8d3 --- /dev/null +++ b/2BIT/summer-semester/ITY/4/proj4.tex @@ -0,0 +1,49 @@ +\documentclass[11pt, a4paper]{article} +\usepackage[left=2cm, top=3cm, text={17cm, 24cm}]{geometry} +\usepackage{url} +\usepackage{times} +\usepackage[czech,slovak]{babel} +\usepackage[utf8]{inputenc} +\usepackage[T1]{fontenc} + +\begin{document} + +\begin{titlepage} +\begin{center} +\Huge\textsc{Vysoké učení technické v Brně} + +\huge\textsc{Fakulta informačních technologií} +\vspace{\stretch{0.382}} + +\LARGE Typografie a~publikování -- 4. projekt + +\Huge Bibliografické Citácie +\vspace{\stretch{0.618}} +\end{center} +{\Large \today \hfill Roman Nečas} +\end{titlepage} + +\section{Hawkingovo žiarenie: keď čierne diery nie sú celkom čierne} + +\subsection{Podstata a objav} +Čierne diery sú objekty s takou extrémnou gravitáciou, že dlho panovala predstava, že z nich nemôže uniknúť žiadna hmota ani žiarenie. V roku 1974 však Stephen Hawking prekvapil vedeckú komunitu teoretickým objavom, že čierne diery predsa len môžu vyžarovať tepelnú energiu do okolia \cite{hawking1974}. Toto slabé žiarenie, dnes známe ako Hawkingovo žiarenie, vzniká kvantovo-mechanickými procesmi na hranici čiernej diery – horizonte udalostí \cite{benkovicova2024}. + +Podľa zjednodušeného vysvetlenia sa vo vákuu pri horizonte spontánne tvorí pár častíc a antičastíc. Jedna z nich môže spadnúť do čiernej diery, zatiaľ čo druhá unikne preč. Častica, ktorá padá dnu, má zápornú energiu (z pohľadu vzdialeného pozorovateľa) a tým postupne „odhrýza“ z hmotnosti čiernej diery, kým jej partner uletí do vesmíru ako žiarenie \cite{hawking1975}. Hawkingovým objavom sa tak čierne diery zaradili medzi bežné fyzikálne systémy, ktoré majú teplotu a entropiu \cite{hawking1988}. + +\subsection{Vlastnosti a význam} +Hawkingovo žiarenie má vlastnosti žiarenia absolútne čierneho telesa s teplotou, ktorá závisí od hmotnosti čiernej diery. Čím je čierna diera menšia, tým vyššiu má teoreticky teplotu a tým rýchlejšie vyžaruje. Veľké astrofyzikálne čierne diery sa vyparujú nesmierne pomaly – napríklad ak by mala čierna diera hmotnosť Slnka, jej Hawkingovo žiarenie by bolo prakticky zanedbateľné v porovnaní s kozmickým pozadím \cite{jurca2010}. + +Naproti tomu hypotetická miniatúrna čierna diera by sálala omnoho intenzívnejšie a vyparila by sa podstatne rýchlejšie. Hawking dokonca ukázal, že dostatočne malá čierna diera by sa mohla úplne vypariť v explozívnom závere – v poslednej fáze by uvoľnila obrovské množstvo energie \cite{filo2015}. Tento záver má hlboké dôsledky: všetky čierne diery sa postupne odparujú a bez prísunu novej hmoty časom úplne zaniknú. + +\subsection{Experimentálne potvrdenie a výzvy} +Hawkingovo žiarenie je pri bežne známych čiernych dierach prakticky nedetegovateľné na veľkú vzdialenosť, čo je hlavným dôvodom, prečo dosiaľ neexistujú priame experimentálne dôkazy jeho existencie \cite{nasa2019}. Najbližšie k potvrdeniu fenoménu sa podarilo dostať v roku 2019 tímu izraelských fyzikov, ktorí pomocou analógovej čiernej diery (modelu akustickej čiernej diery v laboratóriu) detegovali tepelné žiarenie veľmi podobné predpovedanému Hawkingovmu žiareniu \cite{benkovicova2024}. + +\subsection{Teoretický a filozofický dosah} +Napriek absencii priamej detekcie je Hawkingovo žiarenie dnes pevnou súčasťou modernej fyziky. Väčšina vedcov ho považuje za reálny jav, ktorý prirodzene vyplýva zo známych fyzikálnych teórií \cite{alford2021}. Objav odštartoval diskusiu o informačnom paradoxe čiernych dier: ak sa čierna diera nakoniec vyparí, čo sa stane s informáciou o hmote, ktorá do nej spadla? \cite{hawking2002} + +„Bolo by možné zachytiť žiarenie z omnoho menších a horúcejších čiernych dier, ale nezdá sa, že takých je okolo nás veľa. Škoda. Ak by aspoň jednu niekto objavil, dostal by som Nobelovu cenu,“ napísal Stephen~Haw\-king s istou iróniou vo svojej knihe \cite{hawking2002}. Hoci Nobelovu cenu za svoj objav nedostal, Hawkingovo žiarenie sa zapísalo do dejín vedy – prinútilo fyzikov prehodnotiť, čo vlastne znamená „čierna" diera, a stalo sa inšpiráciou pre celý rad ďalších teórií i experimentov \cite{nature}. +\newpage +\bibliographystyle{czplain} +\bibliography{literatura} + +\end{document} \ No newline at end of file diff --git a/2BIT/summer-semester/ITY/4/xnecasr00.zip b/2BIT/summer-semester/ITY/4/xnecasr00.zip new file mode 100644 index 0000000..c91fb84 Binary files /dev/null and b/2BIT/summer-semester/ITY/4/xnecasr00.zip differ diff --git a/2BIT/summer-semester/ITY/5/xnecasr00.zip b/2BIT/summer-semester/ITY/5/xnecasr00.zip new file mode 100644 index 0000000..d7b8b60 Binary files /dev/null and b/2BIT/summer-semester/ITY/5/xnecasr00.zip differ diff --git a/2BIT/summer-semester/IZU/1/xnecasr00.pdf b/2BIT/summer-semester/IZU/1/xnecasr00.pdf new file mode 100644 index 0000000..36ca666 Binary files /dev/null and b/2BIT/summer-semester/IZU/1/xnecasr00.pdf differ diff --git a/2BIT/summer-semester/IZU/2/xnecasr00.pl b/2BIT/summer-semester/IZU/2/xnecasr00.pl new file mode 100644 index 0000000..2ee1b1f --- /dev/null +++ b/2BIT/summer-semester/IZU/2/xnecasr00.pl @@ -0,0 +1,25 @@ +% Zadani c. 47: +% Napiste program resici ukol dany predikatem u47(LIN,VIN,VOUT), kde LIN +% vstupni ciselny seznam s nejmene jednim prvkem, VIN je vstupni promenna, +% jejiz hodnotu je prirozene cislo a VOUT je promenna, ve ktere se vraci hodnota +% souctu cisel seznamu LIN s mensim indexem, nez je hodnota ve VIN. Uvazujte, +% ze indexovani zacina jednickou, tj. ze prvni prvek seznamu LIN ma index 1. + + +% Testovaci predikaty: % VOUT +u47_1:- u47([5,7,9,-10,23,-4],5, VOUT),write(VOUT). % 11 +u47_2:- u47([1,2.1,3.2,-9],20,VOUT),write(VOUT). % -2.7 +u47_3:- u47([-1,2.3,4.7,9.6,10.1,12],-1,VOUT),write(VOUT). % 0 +u47_r:- write('Zadej LIN: '),read(LIN), + write('Zadej VIN: '),read(VIN),u47(LIN,VIN,VOUT),write(VOUT). + +% Reseni: +u47(LIN, VIN, VOUT) :- + (VIN =< 1 -> VOUT = 0 + ; sum_upto(LIN, VIN, 1, 0, VOUT)). + +sum_upto([], _, _, S, S). +sum_upto([H|T], VIN, I, A, VOUT) :- + I1 is I + 1, + (I < VIN -> A1 is A + H ; A1 = A), + sum_upto(T, VIN, I1, A1, VOUT). \ No newline at end of file diff --git a/2BIT/summer-semester/IZU/3/xnecasr00.txt b/2BIT/summer-semester/IZU/3/xnecasr00.txt new file mode 100644 index 0000000..c76ef01 --- /dev/null +++ b/2BIT/summer-semester/IZU/3/xnecasr00.txt @@ -0,0 +1,30 @@ +Zadani c. 18: +Uvazujte dvourozmerny obdelnikovy stavovy prostor o rozmerech 4 x 5 +s temito indexy jednotlivych stavu: + + 1 2 3 4 5 + 6 7 8 9 10 + 11 12 13 14 15 + 16 17 18 19 20 + +Dale uvazujte, ze aktualni ohodnoceni jednotlivych stavu po predchozich +prochazkach jsou nasledujici: + + -0.055 -0.066 0.017 0.242 0.077 + -0.069 -0.044 -0.046 0.000 0.526 + -0.300 0.000 -0.091 0.267 0.176 + -0.163 -0.399 -0.132 0.013 0.038 + +Zadoucim cilovym stavem je stav 9 (reward=1) a nezadoucim cilovym stavem +je stav 12 (reward=-1). Odmeny ve vsech ostatnich stavech jsou nulove. +Metodou TD-learning s koeficienty alpha=0.1 a gamma=0.8 vypocitejte nova +ohodnoceni vsech stavu po prochazce stavy 1 6 7 8 13 18 17 16 11 12 +a vysledek zapiste na radcich c. 27, 28, 29 a 30 ve formatu stejnem jako +vyse, tj. ve tvaru matice s cisly zaokrouhlenymi na tri desetinna mista. + +Reseni: + + -0.055 -0.066 0.017 0.242 0.077 + -0.066 -0.043 -0.049 0.000 0.526 + -0.370 0.000 -0.092 0.267 0.176 + -0.171 -0.372 -0.151 0.013 0.038 \ No newline at end of file diff --git a/2BIT/summer-semester/IZU/4/xnecasr00.zip b/2BIT/summer-semester/IZU/4/xnecasr00.zip new file mode 100644 index 0000000..ccff0bb Binary files /dev/null and b/2BIT/summer-semester/IZU/4/xnecasr00.zip differ diff --git a/2BIT/winter-semester/IAL 1.DU/c201.c b/2BIT/winter-semester/IAL 1.DU/c201.c new file mode 100644 index 0000000..19aa96b --- /dev/null +++ b/2BIT/winter-semester/IAL 1.DU/c201.c @@ -0,0 +1,254 @@ +/* c201.c ********************************************************************** +** Téma: Jednosměrný lineární seznam +** +** Návrh a referenční implementace: Petr Přikryl, říjen 1994 +** Úpravy: Andrea Němcová listopad 1996 +** Petr Přikryl, listopad 1997 +** Přepracované zadání: Petr Přikryl, březen 1998 +** Přepis do jazyka C: Martin Tuček, říjen 2004 +** Úpravy: Kamil Jeřábek, září 2020 +** Daniel Dolejška, září 2021 +** Daniel Dolejška, září 2022 +** +** Implementujte abstraktní datový typ jednosměrný lineární seznam. +** Užitečným obsahem prvku seznamu je celé číslo typu int. +** Seznam bude jako datová abstrakce reprezentován proměnnou typu List. +** Definici konstant a typů naleznete v hlavičkovém souboru c201.h. +** +** Vaším úkolem je implementovat následující operace, které spolu s výše +** uvedenou datovou částí abstrakce tvoří abstraktní datový typ List: +** +** List_Dispose ....... zrušení všech prvků seznamu, +** List_Init .......... inicializace seznamu před prvním použitím, +** List_InsertFirst ... vložení prvku na začátek seznamu, +** List_First ......... nastavení aktivity na první prvek, +** List_GetFirst ...... vrací hodnotu prvního prvku, +** List_DeleteFirst ... zruší první prvek seznamu, +** List_DeleteAfter ... ruší prvek za aktivním prvkem, +** List_InsertAfter ... vloží nový prvek za aktivní prvek seznamu, +** List_GetValue ...... vrací hodnotu aktivního prvku, +** List_SetValue ...... přepíše obsah aktivního prvku novou hodnotou, +** List_Next .......... posune aktivitu na další prvek seznamu, +** List_IsActive ...... zjišťuje aktivitu seznamu. +** +** Nemusíte ošetřovat situaci, kdy místo legálního ukazatele na seznam předá +** někdo jako parametr hodnotu NULL. +** +** Svou implementaci vhodně komentujte! +**/ + +#include "c201.h" + +#include // printf +#include // malloc, free + +bool error_flag; +bool solved; + +/** + * Vytiskne upozornění na to, že došlo k chybě. Nastaví error_flag na logickou 1. + * Tato funkce bude volána z některých dále implementovaných operací. + */ +void List_Error(void) { + printf("*ERROR* The program has performed an illegal operation.\n"); + error_flag = true; +} + +/** + * Provede inicializaci seznamu list před jeho prvním použitím (tzn. žádná + * z následujících funkcí nebude volána nad neinicializovaným seznamem). + * Tato inicializace se nikdy nebude provádět nad již inicializovaným + * seznamem, a proto tuto možnost neošetřujte. Vždy předpokládejte, + * že neinicializované proměnné mají nedefinovanou hodnotu. + * + * @param list Ukazatel na strukturu jednosměrně vázaného seznamu + */ +void List_Init( List *list ) { + list->firstElement = NULL; + list->activeElement = NULL; + list->currentLength = 0; +} + +/** + * Zruší všechny prvky seznamu list a uvede seznam list do stavu, v jakém se nacházel + * po inicializaci. Veškerá paměť používaná prvky seznamu list bude korektně + * uvolněna voláním operace free. + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + **/ +void List_Dispose( List *list ) { + while (list->firstElement != NULL) + { + ListElementPtr tmp = list->firstElement; + list->firstElement = list->firstElement->nextElement; + free(tmp); + } + list->activeElement = NULL; + list->currentLength = 0; +} + +/** + * Vloží prvek s hodnotou data na začátek seznamu list. + * V případě, že není dostatek paměti pro nový prvek při operaci malloc, + * volá funkci List_Error(). + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + * @param data Hodnota k vložení na začátek seznamu + */ +void List_InsertFirst( List *list, int data ) { + ListElementPtr newElement = (ListElementPtr) malloc(sizeof(struct ListElement)); + if (newElement == NULL) + { + List_Error(); + return; + } + newElement->data = data; + newElement->nextElement = list->firstElement; + list->firstElement = newElement; + list->currentLength++; +} + +/** + * Nastaví aktivitu seznamu list na jeho první prvek. + * Funkci implementujte jako jediný příkaz, aniž byste testovali, + * zda je seznam list prázdný. + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + */ +void List_First( List *list ) { + list->activeElement = list->firstElement; +} + +/** + * Prostřednictvím parametru dataPtr vrátí hodnotu prvního prvku seznamu list. + * Pokud je seznam list prázdný, volá funkci List_Error(). + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + * @param dataPtr Ukazatel na cílovou proměnnou + */ +void List_GetFirst( List *list, int *dataPtr ) { + if (list->firstElement == NULL) + { + List_Error(); + return; + } + *dataPtr = list->firstElement->data; +} + +/** + * Zruší první prvek seznamu list a uvolní jím používanou paměť. + * Pokud byl rušený prvek aktivní, aktivita seznamu se ztrácí. + * Pokud byl seznam list prázdný, nic se neděje. + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + */ +void List_DeleteFirst( List *list ) { + if (list->firstElement != NULL) + { + ListElementPtr tmp = list->firstElement; + list->firstElement = list->firstElement->nextElement; + if (list->activeElement == tmp) + { + list->activeElement = NULL; + } + free(tmp); + list->currentLength--; + } +} + +/** + * Zruší prvek seznamu list za aktivním prvkem a uvolní jím používanou paměť. + * Pokud není seznam list aktivní nebo pokud je aktivní poslední prvek seznamu list, + * nic se neděje. + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + */ +void List_DeleteAfter( List *list ) { + if (list->activeElement != NULL && list->activeElement->nextElement != NULL) + { + ListElementPtr tmp = list->activeElement->nextElement; + list->activeElement->nextElement = tmp->nextElement; + free(tmp); + list->currentLength--; + } +} + +/** + * Vloží prvek s hodnotou data za aktivní prvek seznamu list. + * Pokud nebyl seznam list aktivní, nic se neděje! + * V případě, že není dostatek paměti pro nový prvek při operaci malloc, + * zavolá funkci List_Error(). + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + * @param data Hodnota k vložení do seznamu za právě aktivní prvek + */ +void List_InsertAfter( List *list, int data ) { + if (list->activeElement != NULL) + { + ListElementPtr newElement = (ListElementPtr) malloc(sizeof(struct ListElement)); + if (newElement == NULL) + { + List_Error(); + return; + } + newElement->data = data; + newElement->nextElement = list->activeElement->nextElement; + list->activeElement->nextElement = newElement; + list->currentLength++; + } +} + +/** + * Prostřednictvím parametru dataPtr vrátí hodnotu aktivního prvku seznamu list. + * Pokud seznam není aktivní, zavolá funkci List_Error(). + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + * @param dataPtr Ukazatel na cílovou proměnnou + */ +void List_GetValue( List *list, int *dataPtr ) { + if (list->activeElement == NULL) + { + List_Error(); + return; + } + *dataPtr = list->activeElement->data; +} + +/** + * Přepíše data aktivního prvku seznamu list hodnotou data. + * Pokud seznam list není aktivní, nedělá nic! + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + * @param data Nová hodnota právě aktivního prvku + */ +void List_SetValue( List *list, int data ) { + if (list->activeElement != NULL) + { + list->activeElement->data = data; + } +} + +/** + * Posune aktivitu na následující prvek seznamu list. + * Všimněte si, že touto operací se může aktivní seznam stát neaktivním. + * Pokud není předaný seznam list aktivní, nedělá funkce nic. + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + */ +void List_Next( List *list ) { + if (list->activeElement != NULL) + { + list->activeElement = list->activeElement->nextElement; + } +} + +/** + * Je-li seznam list aktivní, vrací nenulovou hodnotu, jinak vrací 0. + * Tuto funkci je vhodné implementovat jedním příkazem return. + * + * @param list Ukazatel na inicializovanou strukturu jednosměrně vázaného seznamu + */ +int List_IsActive( List *list ) { + + return list->activeElement != NULL; +} +/* Konec c201.c */ diff --git a/2BIT/winter-semester/IAL 1.DU/c203.c b/2BIT/winter-semester/IAL 1.DU/c203.c new file mode 100644 index 0000000..b8ded56 --- /dev/null +++ b/2BIT/winter-semester/IAL 1.DU/c203.c @@ -0,0 +1,222 @@ +/* ******************************* c203.c *********************************** */ +/* Předmět: Algoritmy (IAL) - FIT VUT v Brně */ +/* Úkol: c203 - Fronta znaků v poli */ +/* Referenční implementace: Petr Přikryl, 1994 */ +/* Přepis do jazyka C: Václav Topinka, září 2005 */ +/* Úpravy: Kamil Jeřábek, září 2020 */ +/* Daniel Dolejška, září 2021 */ +/* Daniel Dolejška, září 2022 */ +/* ************************************************************************** */ +/* +** Implementujte frontu znaků v poli. Přesnou definici typů naleznete +** v hlavičkovém souboru c203.h (ADT fronta je reprezentována strukturou Queue, +** která obsahuje pole 'array' pro uložení hodnot ve frontě a indexy firstIndex +** a freeIndex. Všechny implementované funkce musí předpokládat velikost pole +** QUEUE_SIZE, i když ve skutečnosti jsou rozměry statického pole definovány +** MAX_QUEUE. Hodnota QUEUE_SIZE slouží k simulaci fronty v různě velkém poli +** a nastavuje se v testovacím skriptu c203-test.c před testováním +** implementovaných funkcí. Hodnota QUEUE_SIZE může nabývat hodnot v rozsahu +** 1 až MAX_QUEUE. +** +** Index firstIndex ukazuje vždy na první prvek ve frontě. Index freeIndex +** ukazuje na první volný prvek ve frontě. Pokud je fronta prázdná, ukazují +** oba indexy na stejné místo. Po inicializaci ukazují na první prvek pole, +** obsahují tedy hodnotu 0. Z uvedených pravidel vyplývá, že v poli je vždy +** minimálně jeden prvek nevyužitý. +** +** Při libovolné operaci se žádný z indexů (firstIndex i freeIndex) nesnižuje +** vyjma případu, kdy index přesáhne hranici QUEUE_SIZE. V tom případě +** se "posunuje" znovu na začátek pole. Za tímto účelem budete deklarovat +** pomocnou funkci NextIndex, která pro kruhový pohyb přes indexy pole +** využívá operaci "modulo". +** +** Implementujte následující funkce: +** +** Queue_Init ...... inicializace fronty +** nextIndex ....... pomocná funkce - viz popis výše +** Queue_IsEmpty ... test na prázdnost fronty +** Queue_IsFull .... test, zda je fronta zaplněna (vyčerpána kapacita) +** Queue_Front ..... přečte hodnoty prvního prvku z fronty +** Queue_Remove .... odstraní první prvek fronty +** Queue_Dequeue ... přečte a odstraní první prvek fronty +** Queue_Enqueue ... zařazení prvku na konec fronty +** +** Nemusíte ošetřovat situaci, kdy místo legálního ukazatele na seznam +** předá někdo jako parametr hodnotu NULL. +** +** Své řešení účelně komentujte! +** +**/ + +#include "c203.h" + +int QUEUE_SIZE = MAX_QUEUE; +bool error_flag; +bool solved; + +/** + * Vytiskne upozornění na to, že došlo k chybě. + * Tato funkce bude volána z některých dále implementovaných operací. + * + * TUTO FUNKCI, PROSÍME, NEUPRAVUJTE! + * + * @param error_code Interní identifikátor chyby + */ +void Queue_Error( int error_code ) { + static const char *QERR_STRINGS[MAX_QERR + 1] = { + "Unknown error", + "Queue error: ENQUEUE", + "Queue error: FRONT", + "Queue error: REMOVE", + "Queue error: DEQUEUE", + "Queue error: INIT" + }; + + if (error_code <= 0 || error_code > MAX_QERR) + { + error_code = 0; + } + printf("%s\n", QERR_STRINGS[error_code]); + error_flag = 1; +} + +/** + * Inicializujte frontu následujícím způsobem: + * - všechny hodnoty v poli queue->array nastavte na '*', + * - index na začátek fronty nastavte na 0, + * - index prvního volného místa nastavte také na 0. + * + * V případě, že funkce dostane jako parametr queue == NULL, volejte funkci + * Queue_Error(QERR_INIT). + * + * @param queue Ukazatel na strukturu fronty + */ +void Queue_Init( Queue *queue ) { + if (queue == NULL) + { + Queue_Error(QERR_INIT); + return; + } + + for (int i = 0; i < QUEUE_SIZE; i++) + { + queue->array[i] = '*'; + } + queue->firstIndex = 0; + queue->freeIndex = 0; +} + +/** + * Pomocná funkce, která vrací index následujícího prvku v poli. + * Funkci implementujte jako jediný prikaz využívající operace '%'. + * Funkci nextIndex budete využívat v dalších implementovaných funkcích. + * + * @param index Aktuální index + */ +int nextIndex( int index ) { + return (index + 1) % QUEUE_SIZE; +} + +/** + * Vrací nenulovou hodnotu, pokud je frona prázdná, jinak vrací hodnotu 0. + * Funkci je vhodné implementovat jedním příkazem return. + * + * @param queue Ukazatel na inicializovanou strukturu fronty + */ +int Queue_IsEmpty( const Queue *queue ) { + return (queue->firstIndex == queue->freeIndex); +} + +/** + * Vrací nenulovou hodnotu, je-li fronta plná, jinak vrací hodnotu 0. + * Funkci je vhodné implementovat jedním příkazem return + * s využitím pomocné funkce nextIndex. + * + * @param queue Ukazatel na inicializovanou strukturu fronty + */ +int Queue_IsFull( const Queue *queue ) { + return (nextIndex(queue->freeIndex) == queue->firstIndex); +} + +/** + * Prostřednictvím parametru dataPtr vrátí znak ze začátku fronty queue. + * Pokud je fronta prázdná, ošetřete to voláním funkce Queue_Error(QERR_FRONT). + * Volání této funkce při prázdné frontě je vždy nutné považovat za nekorektní. + * Bývá to totiž důsledek špatného návrhu algoritmu, ve kterém je fronta + * použita. O takové situaci se proto musí programátor-vývojář dozvědět. + * V opačném případě je ladění programů obtížnější! + * + * Při implementaci využijte dříve definované funkce Queue_IsEmpty. + * + * @param queue Ukazatel na inicializovanou strukturu fronty + * @param dataPtr Ukazatel na cílovou proměnnou + */ +void Queue_Front( const Queue *queue, char *dataPtr ) { + if (Queue_IsEmpty(queue)) + { + Queue_Error(QERR_FRONT); + return; + } + *dataPtr = queue->array[queue->firstIndex]; +} + +/** + * Odstraní znak ze začátku fronty queue. Pokud je fronta prázdná, ošetřete + * vzniklou chybu voláním funkce Queue_Error(QERR_REMOVE). + * Hodnotu na uvolněné pozici ve frontě nijak neošetřujte (nepřepisujte). + * Při implementaci využijte dříve definované funkce Queue_IsEmpty a nextIndex. + * + * @param queue Ukazatel na inicializovanou strukturu fronty + */ +void Queue_Remove( Queue *queue ) { + if (Queue_IsEmpty(queue)) + { + Queue_Error(QERR_REMOVE); + return; + } + queue->firstIndex = nextIndex(queue->firstIndex); +} + +/** + * Odstraní znak ze začátku fronty a vrátí ho prostřednictvím parametru dataPtr. + * Pokud je fronta prázdná, ošetřete to voláním funkce Queue_Error(QERR_DEQUEUE). + * + * Při implementaci využijte dříve definovaných funkcí Queue_IsEmpty, + * Queue_Front a Queue_Remove. + * + * @param queue Ukazatel na inicializovanou strukturu fronty + * @param dataPtr Ukazatel na cílovou proměnnou + */ +void Queue_Dequeue( Queue *queue, char *dataPtr ) { + if (Queue_IsEmpty(queue)) + { + Queue_Error(QERR_DEQUEUE); + return; + } + Queue_Front(queue, dataPtr); + Queue_Remove(queue); +} + +/** + * Vloží znak data do fronty. Pokud je fronta plná, ošetřete chybu voláním + * funkce Queue_Error(QERR_ENQUEUE). Vkládání do plné fronty se považuje za + * nekorektní operaci. Situace by mohla být řešena i tak, že by operace + * neprováděla nic, ale v případě použití takto definované abstrakce by se + * obtížně odhalovaly chyby v algoritmech, které by abstrakci využívaly. + * + * Při implementaci využijte dříve definovaných funkcí Queue_IsFull a nextIndex. + * + * @param queue Ukazatel na inicializovanou strukturu fronty + * @param data Znak k vložení + */ +void Queue_Enqueue( Queue *queue, char data ) { + if (Queue_IsFull(queue)) + { + Queue_Error(QERR_ENQUEUE); + return; + } + queue->array[queue->freeIndex] = data; + queue->freeIndex = nextIndex(queue->freeIndex); +} + +/* Konec příkladu c203.c */ diff --git a/2BIT/winter-semester/IAL 1.DU/c206-ext.c b/2BIT/winter-semester/IAL 1.DU/c206-ext.c new file mode 100644 index 0000000..96f1b46 --- /dev/null +++ b/2BIT/winter-semester/IAL 1.DU/c206-ext.c @@ -0,0 +1,147 @@ +/* + * Předmět: Algoritmy (IAL) - FIT VUT v Brně + * Rozšíření pro příklad c206.c (Dvousměrně vázaný lineární seznam) + * Vytvořil: Daniel Dolejška, září 2024 + */ + +#include "c206-ext.h" + +bool error_flag; +bool solved; + +/** + * Tato metoda simuluje příjem síťových paketů s určenou úrovní priority. + * Přijaté pakety jsou zařazeny do odpovídajících front dle jejich priorit. + * "Fronty" jsou v tomto cvičení reprezentovány dvousměrně vázanými seznamy + * - ty totiž umožňují snazší úpravy pro již zařazené položky. + * + * Parametr `packetLists` obsahuje jednotlivé seznamy paketů (`QosPacketListPtr`). + * Pokud fronta s odpovídající prioritou neexistuje, tato metoda ji alokuje + * a inicializuje. Za jejich korektní uvolnení odpovídá volající. + * + * V případě, že by po zařazení paketu do seznamu počet prvků v cílovém seznamu + * překročil stanovený MAX_PACKET_COUNT, dojde nejdříve k promazání položek seznamu. + * V takovémto případě bude každá druhá položka ze seznamu zahozena nehledě + * na její vlastní prioritu ovšem v pořadí přijetí. + * + * @param packetLists Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param packet Ukazatel na strukturu přijatého paketu + */ +void receive_packet(DLList *packetLists, PacketPtr packet) { + QosPacketListPtr targetList = NULL; + DLL_First(packetLists); + while (DLL_IsActive(packetLists)) { + QosPacketListPtr currentList = (QosPacketListPtr)((long)packetLists->activeElement->data); + if (currentList->priority == packet->priority) { + targetList = currentList; + break; + } + if (currentList->priority < packet->priority) { + break; + } + DLL_Next(packetLists); + } + + if (targetList == NULL) { + + targetList = (QosPacketListPtr)malloc(sizeof(QosPacketList)); + if (targetList == NULL) { + error_flag = true; + return; + } + targetList->priority = packet->priority; + targetList->list = (DLList *)malloc(sizeof(DLList)); + if (targetList->list == NULL) { + free(targetList); + error_flag = true; + return; + } + DLL_Init(targetList->list); + + + if (!DLL_IsActive(packetLists)) { + DLL_InsertLast(packetLists, (long)targetList); + } else { + DLL_InsertBefore(packetLists, (long)targetList); + } + } + + if (targetList->list->currentLength >= MAX_PACKET_COUNT) { + DLLElementPtr current = targetList->list->firstElement; + DLLElementPtr next; + int count = 0; + while (current != NULL) { + next = current->nextElement; + if (count % 2 == 1) { + + if (current == targetList->list->activeElement) { + targetList->list->activeElement = next; + } + if (current == targetList->list->firstElement) { + targetList->list->firstElement = next; + } + if (current == targetList->list->lastElement) { + targetList->list->lastElement = current->previousElement; + } + if (current->previousElement) { + current->previousElement->nextElement = next; + } + if (next) { + next->previousElement = current->previousElement; + } + free(current); + targetList->list->currentLength--; + } + current = next; + count++; + } + } + + + DLL_InsertLast(targetList->list, (long)packet); +} + +/** + * Tato metoda simuluje výběr síťových paketů k odeslání. Výběr respektuje + * relativní priority paketů mezi sebou, kde pakety s nejvyšší prioritou + * jsou vždy odeslány nejdříve. Odesílání dále respektuje pořadí, ve kterém + * byly pakety přijaty metodou `receive_packet`. + * + * Odeslané pakety jsou ze zdrojového seznamu při odeslání odstraněny. + * + * Parametr `packetLists` obsahuje ukazatele na jednotlivé seznamy paketů (`QosPacketListPtr`). + * Parametr `outputPacketList` obsahuje ukazatele na odeslané pakety (`PacketPtr`). + * + * @param packetLists Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param outputPacketList Ukazatel na seznam paketů k odeslání + * @param maxPacketCount Maximální počet paketů k odeslání + */ +void send_packets(DLList *packetLists, DLList *outputPacketList, int maxPacketCount) { + int sentCount = 0; + + while (sentCount < maxPacketCount) { + + DLL_First(packetLists); + + while (DLL_IsActive(packetLists) && sentCount < maxPacketCount) { + QosPacketListPtr currentList = (QosPacketListPtr)((long)packetLists->activeElement->data); + + if (currentList->list->currentLength > 0) { + + PacketPtr packet = (PacketPtr)((long)currentList->list->firstElement->data); + DLL_InsertLast(outputPacketList, (long)packet); + DLL_DeleteFirst(currentList->list); + sentCount++; + } else { + + DLL_Next(packetLists); + } + } + + if (!DLL_IsActive(packetLists)) { + + break; + } + } +} + diff --git a/2BIT/winter-semester/IAL 1.DU/c206.c b/2BIT/winter-semester/IAL 1.DU/c206.c new file mode 100644 index 0000000..9a21052 --- /dev/null +++ b/2BIT/winter-semester/IAL 1.DU/c206.c @@ -0,0 +1,470 @@ +/* ******************************* c206.c *********************************** */ +/* Předmět: Algoritmy (IAL) - FIT VUT v Brně */ +/* Úkol: c206 - Dvousměrně vázaný lineární seznam */ +/* Návrh a referenční implementace: Bohuslav Křena, říjen 2001 */ +/* Vytvořil: Martin Tuček, říjen 2004 */ +/* Upravil: Kamil Jeřábek, září 2020 */ +/* Daniel Dolejška, září 2021 */ +/* Daniel Dolejška, září 2022 */ +/* ************************************************************************** */ +/* +** Implementujte abstraktní datový typ dvousměrně vázaný lineární seznam. +** Užitečným obsahem prvku seznamu je hodnota typu int. Seznam bude jako datová +** abstrakce reprezentován proměnnou typu DLList (DL znamená Doubly-Linked +** a slouží pro odlišení jmen konstant, typů a funkcí od jmen u jednosměrně +** vázaného lineárního seznamu). Definici konstant a typů naleznete +** v hlavičkovém souboru c206.h. +** +** Vaším úkolem je implementovat následující operace, které spolu s výše +** uvedenou datovou částí abstrakce tvoří abstraktní datový typ obousměrně +** vázaný lineární seznam: +** +** DLL_Init ........... inicializace seznamu před prvním použitím, +** DLL_Dispose ........ zrušení všech prvků seznamu, +** DLL_InsertFirst .... vložení prvku na začátek seznamu, +** DLL_InsertLast ..... vložení prvku na konec seznamu, +** DLL_First .......... nastavení aktivity na první prvek, +** DLL_Last ........... nastavení aktivity na poslední prvek, +** DLL_GetFirst ....... vrací hodnotu prvního prvku, +** DLL_GetLast ........ vrací hodnotu posledního prvku, +** DLL_DeleteFirst .... zruší první prvek seznamu, +** DLL_DeleteLast ..... zruší poslední prvek seznamu, +** DLL_DeleteAfter .... ruší prvek za aktivním prvkem, +** DLL_DeleteBefore ... ruší prvek před aktivním prvkem, +** DLL_InsertAfter .... vloží nový prvek za aktivní prvek seznamu, +** DLL_InsertBefore ... vloží nový prvek před aktivní prvek seznamu, +** DLL_GetValue ....... vrací hodnotu aktivního prvku, +** DLL_SetValue ....... přepíše obsah aktivního prvku novou hodnotou, +** DLL_Previous ....... posune aktivitu na předchozí prvek seznamu, +** DLL_Next ........... posune aktivitu na další prvek seznamu, +** DLL_IsActive ....... zjišťuje aktivitu seznamu. +** +** Při implementaci jednotlivých funkcí nevolejte žádnou z funkcí +** implementovaných v rámci tohoto příkladu, není-li u funkce explicitně +** uvedeno něco jiného. +** +** Nemusíte ošetřovat situaci, kdy místo legálního ukazatele na seznam +** předá někdo jako parametr hodnotu NULL. +** +** Svou implementaci vhodně komentujte! +** +** Terminologická poznámka: Jazyk C nepoužívá pojem procedura. +** Proto zde používáme pojem funkce i pro operace, které by byly +** v algoritmickém jazyce Pascalovského typu implemenovány jako procedury +** (v jazyce C procedurám odpovídají funkce vracející typ void). +** +**/ + +#include "c206.h" + +bool error_flag; +bool solved; + +/** + * Vytiskne upozornění na to, že došlo k chybě. + * Tato funkce bude volána z některých dále implementovaných operací. + */ +void DLL_Error(void) { + printf("*ERROR* The program has performed an illegal operation.\n"); + error_flag = true; +} + +/** + * Provede inicializaci seznamu list před jeho prvním použitím (tzn. žádná + * z následujících funkcí nebude volána nad neinicializovaným seznamem). + * Tato inicializace se nikdy nebude provádět nad již inicializovaným seznamem, + * a proto tuto možnost neošetřujte. + * Vždy předpokládejte, že neinicializované proměnné mají nedefinovanou hodnotu. + * + * @param list Ukazatel na strukturu dvousměrně vázaného seznamu + */ +void DLL_Init( DLList *list ) { + list->firstElement = NULL; + list->activeElement = NULL; + list->lastElement = NULL; + list->currentLength = 0; +} + +/** + * Zruší všechny prvky seznamu list a uvede seznam do stavu, v jakém se nacházel + * po inicializaci. + * Rušené prvky seznamu budou korektně uvolněny voláním operace free. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + */ +void DLL_Dispose( DLList *list ) { + DLLElementPtr current = list->firstElement; + while (current != NULL) + { + DLLElementPtr temp = current; + current = current->nextElement; + free(temp); + } + list->firstElement = NULL; + list->activeElement = NULL; + list->lastElement = NULL; + list->currentLength = 0; +} + +/** + * Vloží nový prvek na začátek seznamu list. + * V případě, že není dostatek paměti pro nový prvek při operaci malloc, + * volá funkci DLL_Error(). + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param data Hodnota k vložení na začátek seznamu + */ +void DLL_InsertFirst( DLList *list, long data ) { + DLLElementPtr newElement = (DLLElementPtr)malloc(sizeof(struct DLLElement)); + if (newElement == NULL) + { + DLL_Error(); + return; + } + newElement->data = data; + newElement->previousElement = NULL; + newElement->nextElement = list->firstElement; + if (list->firstElement != NULL) + { + list->firstElement->previousElement = newElement; + } + else + { + list->lastElement = newElement; + } + list->firstElement = newElement; + list->currentLength++; +} + +/** + * Vloží nový prvek na konec seznamu list (symetrická operace k DLL_InsertFirst). + * V případě, že není dostatek paměti pro nový prvek při operaci malloc, + * volá funkci DLL_Error(). + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param data Hodnota k vložení na konec seznamu + */ +void DLL_InsertLast( DLList *list, long data ) { + DLLElementPtr newElement = (DLLElementPtr)malloc(sizeof(struct DLLElement)); + if (newElement == NULL) + { + DLL_Error(); + return; + } + newElement->data = data; + newElement->nextElement = NULL; + newElement->previousElement = list->lastElement; + if (list->lastElement != NULL) + { + list->lastElement->nextElement = newElement; + } + else + { + list->firstElement = newElement; + } + list->lastElement = newElement; + list->currentLength++; +} + +/** + * Nastaví první prvek seznamu list jako aktivní. + * Funkci implementujte jako jediný příkaz, aniž byste testovali, + * zda je seznam list prázdný. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + */ +void DLL_First( DLList *list ) { + list->activeElement = list->firstElement; +} + +/** + * Nastaví poslední prvek seznamu list jako aktivní. + * Funkci implementujte jako jediný příkaz, aniž byste testovali, + * zda je seznam list prázdný. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + */ +void DLL_Last( DLList *list ) { + list->activeElement = list->lastElement; +} + +/** + * Prostřednictvím parametru dataPtr vrátí hodnotu prvního prvku seznamu list. + * Pokud je seznam list prázdný, volá funkci DLL_Error(). + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param dataPtr Ukazatel na cílovou proměnnou + */ +void DLL_GetFirst( DLList *list, long *dataPtr ) { + if (list->firstElement == NULL) + { + DLL_Error(); + return; + } + *dataPtr = list->firstElement->data; +} + +/** + * Prostřednictvím parametru dataPtr vrátí hodnotu posledního prvku seznamu list. + * Pokud je seznam list prázdný, volá funkci DLL_Error(). + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param dataPtr Ukazatel na cílovou proměnnou + */ +void DLL_GetLast( DLList *list, long *dataPtr ) { + if (list->lastElement == NULL) + { + DLL_Error(); + return; + } + *dataPtr = list->lastElement->data; +} + +/** + * Zruší první prvek seznamu list. + * Pokud byl první prvek aktivní, aktivita se ztrácí. + * Pokud byl seznam list prázdný, nic se neděje. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + */ +void DLL_DeleteFirst( DLList *list ) { + if (list->firstElement != NULL) + { + DLLElementPtr temp = list->firstElement; + list->firstElement = temp->nextElement; + if (list->firstElement != NULL) + { + list->firstElement->previousElement = NULL; + } + else + { + list->lastElement = NULL; + } + if (list->activeElement == temp) + { + list->activeElement = NULL; + } + free(temp); + list->currentLength--; + } +} + +/** + * Zruší poslední prvek seznamu list. + * Pokud byl poslední prvek aktivní, aktivita seznamu se ztrácí. + * Pokud byl seznam list prázdný, nic se neděje. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + */ +void DLL_DeleteLast( DLList *list ) { + if (list->lastElement != NULL) + { + DLLElementPtr temp = list->lastElement; + list->lastElement = temp->previousElement; + if (list->lastElement != NULL) + { + list->lastElement->nextElement = NULL; + } + else + { + list->firstElement = NULL; + } + if (list->activeElement == temp) + { + list->activeElement = NULL; + } + free(temp); + list->currentLength--; + } +} + +/** + * Zruší prvek seznamu list za aktivním prvkem. + * Pokud je seznam list neaktivní nebo pokud je aktivní prvek + * posledním prvkem seznamu, nic se neděje. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + */ +void DLL_DeleteAfter( DLList *list ) { + if (list->activeElement != NULL && list->activeElement->nextElement != NULL) + { + DLLElementPtr temp = list->activeElement->nextElement; + list->activeElement->nextElement = temp->nextElement; + if (temp->nextElement != NULL) + { + temp->nextElement->previousElement = list->activeElement; + } + else + { + list->lastElement = list->activeElement; + } + free(temp); + list->currentLength--; + } +} + +/** + * Zruší prvek před aktivním prvkem seznamu list . + * Pokud je seznam list neaktivní nebo pokud je aktivní prvek + * prvním prvkem seznamu, nic se neděje. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + */ +void DLL_DeleteBefore( DLList *list ) { + if (list->activeElement != NULL && list->activeElement->previousElement != NULL) + { + DLLElementPtr temp = list->activeElement->previousElement; + list->activeElement->previousElement = temp->previousElement; + if (temp->previousElement != NULL) + { + temp->previousElement->nextElement = list->activeElement; + } + else + { + list->firstElement = list->activeElement; + } + free(temp); + list->currentLength--; + } +} + +/** + * Vloží prvek za aktivní prvek seznamu list. + * Pokud nebyl seznam list aktivní, nic se neděje. + * V případě, že není dostatek paměti pro nový prvek při operaci malloc, + * volá funkci DLL_Error(). + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param data Hodnota k vložení do seznamu za právě aktivní prvek + */ +void DLL_InsertAfter( DLList *list, long data ) { + if (list->activeElement != NULL) + { + DLLElementPtr newElement = (DLLElementPtr)malloc(sizeof(struct DLLElement)); + if (newElement == NULL) + { + DLL_Error(); + return; + } + newElement->data = data; + newElement->nextElement = list->activeElement->nextElement; + newElement->previousElement = list->activeElement; + list->activeElement->nextElement = newElement; + if (newElement->nextElement != NULL) + { + newElement->nextElement->previousElement = newElement; + } + else + { + list->lastElement = newElement; + } + list->currentLength++; + } +} + +/** + * Vloží prvek před aktivní prvek seznamu list. + * Pokud nebyl seznam list aktivní, nic se neděje. + * V případě, že není dostatek paměti pro nový prvek při operaci malloc, + * volá funkci DLL_Error(). + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param data Hodnota k vložení do seznamu před právě aktivní prvek + */ +void DLL_InsertBefore( DLList *list, long data ) { + if (list->activeElement != NULL) + { + DLLElementPtr newElement = (DLLElementPtr)malloc(sizeof(struct DLLElement)); + if (newElement == NULL) + { + DLL_Error(); + return; + } + newElement->data = data; + newElement->nextElement = list->activeElement; + newElement->previousElement = list->activeElement->previousElement; + list->activeElement->previousElement = newElement; + if (newElement->previousElement != NULL) + { + newElement->previousElement->nextElement = newElement; + } + else + { + list->firstElement = newElement; + } + list->currentLength++; + } +} + +/** + * Prostřednictvím parametru dataPtr vrátí hodnotu aktivního prvku seznamu list. + * Pokud seznam list není aktivní, volá funkci DLL_Error (). + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param dataPtr Ukazatel na cílovou proměnnou + */ +void DLL_GetValue( DLList *list, long *dataPtr ) { + if (list->activeElement == NULL) + { + DLL_Error(); + return; + } + *dataPtr = list->activeElement->data; +} + +/** + * Přepíše obsah aktivního prvku seznamu list. + * Pokud seznam list není aktivní, nedělá nic. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * @param data Nová hodnota právě aktivního prvku + */ +void DLL_SetValue( DLList *list, long data ) { + if (list->activeElement != NULL) + { + list->activeElement->data = data; + } +} + +/** + * Posune aktivitu na následující prvek seznamu list. + * Není-li seznam aktivní, nedělá nic. + * Všimněte si, že při aktivitě na posledním prvku se seznam stane neaktivním. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + */ +void DLL_Next( DLList *list ) { + if (list->activeElement != NULL) + { + list->activeElement = list->activeElement->nextElement; + } +} + + +/** + * Posune aktivitu na předchozí prvek seznamu list. + * Není-li seznam aktivní, nedělá nic. + * Všimněte si, že při aktivitě na prvním prvku se seznam stane neaktivním. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + */ +void DLL_Previous( DLList *list ) { + if (list->activeElement != NULL) + { + list->activeElement = list->activeElement->previousElement; + } +} + +/** + * Je-li seznam list aktivní, vrací nenulovou hodnotu, jinak vrací 0. + * Funkci je vhodné implementovat jedním příkazem return. + * + * @param list Ukazatel na inicializovanou strukturu dvousměrně vázaného seznamu + * + * @returns Nenulovou hodnotu v případě aktivity prvku seznamu, jinak nulu + */ +bool DLL_IsActive( DLList *list ) { + return list->activeElement != NULL; +} + +/* Konec c206.c */ diff --git a/2BIT/winter-semester/IAL 2.DU/btree-exa.c b/2BIT/winter-semester/IAL 2.DU/btree-exa.c new file mode 100644 index 0000000..4e8e064 --- /dev/null +++ b/2BIT/winter-semester/IAL 2.DU/btree-exa.c @@ -0,0 +1,101 @@ +/* + * Použití binárních vyhledávacích stromů. + * + * S využitím Vámi implementovaného binárního vyhledávacího stromu (soubory ../iter/btree.c a ../rec/btree.c) + * implementujte triviální funkci letter_count. Všimněte si, že výstupní strom může být značně degradovaný + * (až na úroveň lineárního seznamu). Jako typ hodnoty v uzlu stromu využijte 'INTEGER'. + * + */ + +#include "../btree.h" +#include +#include + + +/** + * Vypočítání frekvence výskytů znaků ve vstupním řetězci. + * + * Funkce inicilializuje strom a následně zjistí počet výskytů znaků a-z (case insensitive), znaku + * mezery ' ', a ostatních znaků (ve stromu reprezentováno znakem podtržítka '_'). Výstup je v + * uložen ve stromu. + * + * Například pro vstupní řetězec: "abBccc_ 123 *" bude strom po běhu funkce obsahovat: + * + * key | value + * 'a' 1 + * 'b' 2 + * 'c' 3 + * ' ' 2 + * '_' 5 + * + * Pro implementaci si můžete v tomto souboru nadefinovat vlastní pomocné funkce. +*/ +// Vlastná implementácia isalpha() +int my_isalpha(char c) { + return ((c >= 'A' && c <= 'Z') || (c >= 'a' && c <= 'z')); +} + +// Vlastná implementácia tolower() +char my_tolower(char c) { + if (c >= 'A' && c <= 'Z') { + return c + 32; // Prevod na malé písmeno (rozdiel medzi 'A' a 'a' v ASCII) + } + return c; +} + +/** + * Pomocná funkcia pre aktualizáciu počtu výskytov znaku v strome. + * Ak záznam pre znak neexistuje, vytvorí nový s počtom 1. + * Ak záznam existuje, zvýši jeho počet o 1. + * + * @param tree Ukazateľ na koreň stromu + * @param character Znak, ktorého počet sa má aktualizovať + */ +void update_character_count(bst_node_t **tree, char character) { + bst_node_content_t *content; + + // Hľadáme existujúci záznam pre znak + if (bst_search(*tree, character, &content)) { + // Ak záznam existuje, zvýšime počet + int *count = (int *)content->value; + (*count)++; + } else { + // Ak záznam neexistuje, vytvoríme nový + int *count = (int *)malloc(sizeof(int)); + *count = 1; + + bst_node_content_t new_content = { + .value = count, + .type = INTEGER + }; + + // Vložíme nový záznam do stromu + bst_insert(tree, character, new_content); + } +} + +void letter_count(bst_node_t **tree, char *input) { + // Inicializácia stromu + bst_init(tree); + + // Ak je vstup prázdny, končíme + if (input == NULL) { + return; + } + + // Prechádzame vstupný reťazec znak po znaku + for (int i = 0; input[i] != '\0'; i++) { + char current = input[i]; + + if (my_isalpha(current)) { + // Pre písmená (a-z, A-Z) - prevedieme na malé písmená + update_character_count(tree, my_tolower(current)); + } else if (current == ' ') { + // Pre medzery + update_character_count(tree, ' '); + } else { + // Pre všetky ostatné znaky použijeme '_' + update_character_count(tree, '_'); + } + } +} \ No newline at end of file diff --git a/2BIT/winter-semester/IAL 2.DU/btree-iter.c b/2BIT/winter-semester/IAL 2.DU/btree-iter.c new file mode 100644 index 0000000..29d7983 --- /dev/null +++ b/2BIT/winter-semester/IAL 2.DU/btree-iter.c @@ -0,0 +1,426 @@ +/* + * Binární vyhledávací strom — iterativní varianta + * + * S využitím datových typů ze souboru btree.h, zásobníku ze souboru stack.h + * a připravených koster funkcí implementujte binární vyhledávací + * strom bez použití rekurze. + */ + +#include "../btree.h" +#include "stack.h" +#include +#include + +/* + * Inicializace stromu. + * + * Uživatel musí zajistit, že inicializace se nebude opakovaně volat nad + * inicializovaným stromem. V opačném případě může dojít k úniku paměti (memory + * leak). Protože neinicializovaný ukazatel má nedefinovanou hodnotu, není + * možné toto detekovat ve funkci. + */ +void bst_init(bst_node_t **tree) +{ + *tree = NULL; // Inicializácia prázdneho stromu +} + +/* + * Vyhledání uzlu v stromu. + * + * V případě úspěchu vrátí funkce hodnotu true a do proměnné value zapíše + * ukazatel na obsah daného uzlu. V opačném případě funkce vrátí hodnotu false a proměnná + * value zůstává nezměněná. + * + * Funkci implementujte iterativně bez použité vlastních pomocných funkcí. + */ +bool bst_search(bst_node_t *tree, char key, bst_node_content_t **value) +{ + bst_node_t *current = tree; + + // Iteratívne prechádzame strom + while (current != NULL) { + if (key == current->key) { + // Našli sme hľadaný kľúč + *value = &(current->content); + return true; + } + // Ak je kľúč menší, ideme do ľavého podstromu + if (key < current->key) { + current = current->left; + } + // Ak je kľúč väčší, ideme do pravého podstromu + else { + current = current->right; + } + } + + return false; // Kľúč nebol nájdený +} + +/* + * Vložení uzlu do stromu. + * + * Pokud uzel se zadaným klíče už ve stromu existuje, nahraďte jeho hodnotu. + * Jinak vložte nový listový uzel. + * + * Výsledný strom musí splňovat podmínku vyhledávacího stromu — levý podstrom + * uzlu obsahuje jenom menší klíče, pravý větší. + * + * Funkci implementujte iterativně bez použití vlastních pomocných funkcí. + */ +void bst_insert(bst_node_t **tree, char key, bst_node_content_t value) +{ + // Ak je strom prázdny, vytvoríme nový koreň + if (*tree == NULL) { + bst_node_t *new_node = malloc(sizeof(bst_node_t)); + if (new_node == NULL) { + return; // Alokácia zlyhala + } + new_node->key = key; + new_node->content = value; + new_node->left = NULL; + new_node->right = NULL; + *tree = new_node; + return; + } + + // Iteratívne hľadáme miesto pre vloženie + bst_node_t *current = *tree; + while (true) { + if (key == current->key) { + // Kľúč už existuje, aktualizujeme hodnotu + current->content = value; + return; + } + if (key < current->key) { + if (current->left == NULL) { + // Našli sme miesto pre vloženie vľavo + bst_node_t *new_node = malloc(sizeof(bst_node_t)); + if (new_node == NULL) { + return; // Alokácia zlyhala + } + new_node->key = key; + new_node->content = value; + new_node->left = NULL; + new_node->right = NULL; + current->left = new_node; + return; + } + current = current->left; + } else { + if (current->right == NULL) { + // Našli sme miesto pre vloženie vpravo + bst_node_t *new_node = malloc(sizeof(bst_node_t)); + if (new_node == NULL) { + return; // Alokácia zlyhala + } + new_node->key = key; + new_node->content = value; + new_node->left = NULL; + new_node->right = NULL; + current->right = new_node; + return; + } + current = current->right; + } + } +} + +/* + * Pomocná funkce která nahradí uzel nejpravějším potomkem. + * + * Klíč a hodnota uzlu target budou nahrazené klíčem a hodnotou nejpravějšího + * uzlu podstromu tree. Nejpravější potomek bude odstraněný. Funkce korektně + * uvolní všechny alokované zdroje odstraněného uzlu. + * + * Funkce předpokládá, že hodnota tree není NULL. + * + * Tato pomocná funkce bude využita při implementaci funkce bst_delete. + * + * Funkci implementujte iterativně bez použití vlastních pomocných funkcí. + */ +void bst_replace_by_rightmost(bst_node_t *target, bst_node_t **tree) +{ + bst_node_t *current = *tree; + bst_node_t *parent = NULL; + + // Hľadáme najpravejší uzol + while (current->right != NULL) { + parent = current; + current = current->right; + } + + // Nahradíme hodnoty v cieľovom uzle + target->key = current->key; + target->content = current->content; + + // Odstránime najpravejší uzol + if (parent == NULL) { + // Špeciálny prípad - current je koreň podstromu + *tree = current->left; + } else { + parent->right = current->left; + } + + free(current); +} + +/* + * Odstranění uzlu ze stromu. + * + * Pokud uzel se zadaným klíčem neexistuje, funkce nic nedělá. + * Pokud má odstraněný uzel jeden podstrom, zdědí ho rodič odstraněného uzlu. + * Pokud má odstraněný uzel oba podstromy, je nahrazený nejpravějším uzlem + * levého podstromu. Nejpravější uzel nemusí být listem. + * + * Funkce korektně uvolní všechny alokované zdroje odstraněného uzlu. + * + * Funkci implementujte iterativně pomocí bst_replace_by_rightmost a bez + * použití vlastních pomocných funkcí. + */ +void bst_delete(bst_node_t **tree, char key) +{ + if (*tree == NULL) { + return; // Prázdny strom + } + + bst_node_t *current = *tree; + bst_node_t *parent = NULL; + + // Nájdeme uzol na odstránenie + while (current != NULL && current->key != key) { + parent = current; + if (key < current->key) { + current = current->left; + } else { + current = current->right; + } + } + + if (current == NULL) { + return; // Kľúč nebol nájdený + } + + // Prípad 1: Uzol nemá potomkov + if (current->left == NULL && current->right == NULL) { + if (parent == NULL) { + *tree = NULL; + } else if (parent->left == current) { + parent->left = NULL; + } else { + parent->right = NULL; + } + free(current); + } + // Prípad 2: Uzol má iba pravého potomka + else if (current->left == NULL) { + if (parent == NULL) { + *tree = current->right; + } else if (parent->left == current) { + parent->left = current->right; + } else { + parent->right = current->right; + } + free(current); + } + // Prípad 3: Uzol má iba ľavého potomka + else if (current->right == NULL) { + if (parent == NULL) { + *tree = current->left; + } else if (parent->left == current) { + parent->left = current->left; + } else { + parent->right = current->left; + } + free(current); + } + // Prípad 4: Uzol má oboch potomkov + else { + bst_replace_by_rightmost(current, &(current->left)); + } +} + +/* + * Zrušení celého stromu. + * + * Po zrušení se celý strom bude nacházet ve stejném stavu jako po + * inicializaci. Funkce korektně uvolní všechny alokované zdroje rušených + * uzlů. + * + * Funkci implementujte iterativně s pomocí zásobníku a bez použití + * vlastních pomocných funkcí. + */ +void bst_dispose(bst_node_t **tree) +{ + if (*tree == NULL) { + return; + } + + stack_bst_t stack; + stack_bst_init(&stack); + stack_bst_push(&stack, *tree); + + while (!stack_bst_empty(&stack)) { + bst_node_t *node = stack_bst_pop(&stack); + + if (node->right != NULL) { + stack_bst_push(&stack, node->right); + } + if (node->left != NULL) { + stack_bst_push(&stack, node->left); + } + + free(node); + } + + *tree = NULL; +} + +/* + * Pomocná funkce pro iterativní preorder. + * + * Prochází po levé větvi k nejlevějšímu uzlu podstromu. + * Nad zpracovanými uzly zavolá bst_add_node_to_items a uloží je do zásobníku uzlů. + * + * Funkci implementujte iterativně s pomocí zásobníku a bez použití + * vlastních pomocných funkcí. + */ +void bst_leftmost_preorder(bst_node_t *tree, stack_bst_t *to_visit, bst_items_t *items) +{ + bst_node_t *current = tree; + while (current != NULL) { + bst_add_node_to_items(current, items); + stack_bst_push(to_visit, current); + current = current->left; + } +} + +/* + * Preorder průchod stromem. + * + * Pro aktuálně zpracovávaný uzel zavolejte funkci bst_add_node_to_items. + * + * Funkci implementujte iterativně pomocí funkce bst_leftmost_preorder a + * zásobníku uzlů a bez použití vlastních pomocných funkcí. + */ +void bst_preorder(bst_node_t *tree, bst_items_t *items) +{ + if (tree == NULL) { + return; + } + + stack_bst_t stack; + stack_bst_init(&stack); + + bst_leftmost_preorder(tree, &stack, items); + + while (!stack_bst_empty(&stack)) { + bst_node_t *node = stack_bst_pop(&stack); + if (node->right != NULL) { + bst_leftmost_preorder(node->right, &stack, items); + } + } +} + +/* + * Pomocná funkce pro iterativní inorder. + * + * Prochází po levé větvi k nejlevějšímu uzlu podstromu a ukládá uzly do + * zásobníku uzlů. + * + * Funkci implementujte iterativně s pomocí zásobníku a bez použití + * vlastních pomocných funkcí. + */ +void bst_leftmost_inorder(bst_node_t *tree, stack_bst_t *to_visit) +{ + bst_node_t *current = tree; + while (current != NULL) { + stack_bst_push(to_visit, current); + current = current->left; + } +} + +/* + * Inorder průchod stromem. + * + * Pro aktuálně zpracovávaný uzel zavolejte funkci bst_add_node_to_items. + * + * Funkci implementujte iterativně pomocí funkce bst_leftmost_inorder a + * zásobníku uzlů a bez použití vlastních pomocných funkcí. + */ +void bst_inorder(bst_node_t *tree, bst_items_t *items) +{ + stack_bst_t stack; + stack_bst_init(&stack); + + bst_leftmost_inorder(tree, &stack); + + while (!stack_bst_empty(&stack)) { + bst_node_t *node = stack_bst_pop(&stack); + bst_add_node_to_items(node, items); + + if (node->right != NULL) { + bst_leftmost_inorder(node->right, &stack); + } + } +} + +/* + * Pomocná funkce pro iterativní postorder. + * + * Prochází po levé větvi k nejlevějšímu uzlu podstromu a ukládá uzly do + * zásobníku uzlů. Do zásobníku bool hodnot ukládá informaci, že uzel + * byl navštíven poprvé. + * + * Funkci implementujte iterativně pomocí zásobníku uzlů a bool hodnot a bez použití + * vlastních pomocných funkcí. + */ +void bst_leftmost_postorder(bst_node_t *tree, stack_bst_t *to_visit, + stack_bool_t *first_visit) +{ + bst_node_t *current = tree; + while (current != NULL) { + stack_bst_push(to_visit, current); + stack_bool_push(first_visit, true); + current = current->left; + } +} + +/* + * Postorder průchod stromem. + * + * Pro aktuálně zpracovávaný uzel zavolejte funkci bst_add_node_to_items. + * + * Funkci implementujte iterativně pomocí funkce bst_leftmost_postorder a + * zásobníku uzlů a bool hodnot a bez použití vlastních pomocných funkcí. + */ +void bst_postorder(bst_node_t *tree, bst_items_t *items) +{ + if (tree == NULL) { + return; + } + + stack_bst_t stack; + stack_bool_t first_visit; + stack_bst_init(&stack); + stack_bool_init(&first_visit); + + bst_leftmost_postorder(tree, &stack, &first_visit); + + while (!stack_bst_empty(&stack)) { + bst_node_t *node = stack_bst_top(&stack); + bool is_first_visit = stack_bool_pop(&first_visit); + + if (is_first_visit) { + // Pri prvej návšteve uzla ideme do pravého podstromu + stack_bool_push(&first_visit, false); + if (node->right != NULL) { + bst_leftmost_postorder(node->right, &stack, &first_visit); + } + } else { + // Pri druhej návšteve spracujeme uzol + bst_add_node_to_items(node, items); + stack_bst_pop(&stack); + } + } +} diff --git a/2BIT/winter-semester/IAL 2.DU/btree-rec.c b/2BIT/winter-semester/IAL 2.DU/btree-rec.c new file mode 100644 index 0000000..6e4b236 --- /dev/null +++ b/2BIT/winter-semester/IAL 2.DU/btree-rec.c @@ -0,0 +1,242 @@ +/* + * Binární vyhledávací strom — rekurzivní varianta + * + * S využitím datových typů ze souboru btree.h a připravených koster funkcí + * implementujte binární vyhledávací strom pomocí rekurze. + */ + +#include "../btree.h" +#include +#include + +/* + * Inicializace stromu. + * + * Uživatel musí zajistit, že inicializace se nebude opakovaně volat nad + * inicializovaným stromem. V opačném případě může dojít k úniku paměti (memory + * leak). Protože neinicializovaný ukazatel má nedefinovanou hodnotu, není + * možné toto detekovat ve funkci. + */ +void bst_init(bst_node_t **tree) +{ + *tree = NULL; // Inicializace prázdného stromu +} + +/* + * Vyhledání uzlu v stromu. + * + * V případě úspěchu vrátí funkce hodnotu true a do proměnné value zapíše + * ukazatel na obsah daného uzlu. V opačném případě funkce vrátí hodnotu false a proměnná + * value zůstává nezměněná. + * + * Funkci implementujte rekurzivně bez použité vlastních pomocných funkcí. + */ +bool bst_search(bst_node_t *tree, char key, bst_node_content_t **value) +{ + // Prázdný strom nebo došli jsme na konec větve + if (tree == NULL) { + return false; + } + + // Porovnáme klíče + if (key < tree->key) { + // Hledáme v levém podstromu + return bst_search(tree->left, key, value); + } else if (key > tree->key) { + // Hledáme v pravém podstromu + return bst_search(tree->right, key, value); + } else { + // Našli jsme hledaný uzel + *value = &(tree->content); + return true; + } +} + +/* + * Vložení uzlu do stromu. + * + * Pokud uzel se zadaným klíče už ve stromu existuje, nahraďte jeho hodnotu. + * Jinak vložte nový listový uzel. + * + * Výsledný strom musí splňovat podmínku vyhledávacího stromu — levý podstrom + * uzlu obsahuje jenom menší klíče, pravý větší. + * + * Funkci implementujte rekurzivně bez použití vlastních pomocných funkcí. + */ +void bst_insert(bst_node_t **tree, char key, bst_node_content_t value) +{ + // Pokud je strom prázdný nebo jsme došli na místo pro vložení + if (*tree == NULL) { + // Vytvoříme nový uzel + bst_node_t *new_node = (bst_node_t *)malloc(sizeof(bst_node_t)); + if (new_node == NULL) { + return; // Chyba alokace + } + + new_node->key = key; + new_node->content = value; + new_node->left = NULL; + new_node->right = NULL; + + *tree = new_node; + return; + } + + // Porovnáme klíče + if (key < (*tree)->key) { + // Vkládáme do levého podstromu + bst_insert(&(*tree)->left, key, value); + } else if (key > (*tree)->key) { + // Vkládáme do pravého podstromu + bst_insert(&(*tree)->right, key, value); + } else { + // Klíč už existuje - nahradíme hodnotu + (*tree)->content = value; + } +} + +/* + * Pomocná funkce která nahradí uzel nejpravějším potomkem. + * + * Klíč a hodnota uzlu target budou nahrazeny klíčem a hodnotou nejpravějšího + * uzlu podstromu tree. Nejpravější potomek bude odstraněný. Funkce korektně + * uvolní všechny alokované zdroje odstraněného uzlu. + * + * Funkce předpokládá, že hodnota tree není NULL. + * + * Tato pomocná funkce bude využitá při implementaci funkce bst_delete. + * + * Funkci implementujte rekurzivně bez použití vlastních pomocných funkcí. + */ +void bst_replace_by_rightmost(bst_node_t *target, bst_node_t **tree) +{ + if ((*tree)->right == NULL) { + // Našli jsme nejpravější uzel + target->key = (*tree)->key; + target->content = (*tree)->content; + + // Uložíme si levý podstrom + bst_node_t *left_subtree = (*tree)->left; + // Uvolníme nejpravější uzel + free(*tree); + // Napojíme levý podstrom + *tree = left_subtree; + } else { + // Pokračujeme v hledání nejpravějšího uzlu + bst_replace_by_rightmost(target, &(*tree)->right); + } +} + +/* + * Odstranění uzlu ze stromu. + * + * Pokud uzel se zadaným klíčem neexistuje, funkce nic nedělá. + * Pokud má odstraněný uzel jeden podstrom, zdědí ho rodič odstraněného uzlu. + * Pokud má odstraněný uzel oba podstromy, je nahrazený nejpravějším uzlem + * levého podstromu. Nejpravější uzel nemusí být listem. + * + * Funkce korektně uvolní všechny alokované zdroje odstraněného uzlu. + * + * Funkci implementujte rekurzivně pomocí bst_replace_by_rightmost a bez + * použití vlastních pomocných funkcí. + */ +void bst_delete(bst_node_t **tree, char key) +{ + if (*tree == NULL) { + return; // Strom je prázdný nebo uzel nebyl nalezen + } + + if (key < (*tree)->key) { + // Mažeme v levém podstromu + bst_delete(&(*tree)->left, key); + } else if (key > (*tree)->key) { + // Mažeme v pravém podstromu + bst_delete(&(*tree)->right, key); + } else { + // Našli jsme mazaný uzel + bst_node_t *node_to_delete = *tree; + + if (node_to_delete->left == NULL) { + // Uzel má jen pravý podstrom + *tree = node_to_delete->right; + free(node_to_delete); + } else if (node_to_delete->right == NULL) { + // Uzel má jen levý podstrom + *tree = node_to_delete->left; + free(node_to_delete); + } else { + // Uzel má oba podstromy + // Nahradíme hodnoty nejpravějším uzlem levého podstromu + bst_replace_by_rightmost(node_to_delete, &node_to_delete->left); + } + } +} + +/* + * Zrušení celého stromu. + * + * Po zrušení se celý strom bude nacházet ve stejném stavu jako po + * inicializaci. Funkce korektně uvolní všechny alokované zdroje rušených + * uzlů. + * + * Funkci implementujte rekurzivně bez použití vlastních pomocných funkcí. + */ +void bst_dispose(bst_node_t **tree) +{ + if (*tree != NULL) { + // Rekurzivně zrušíme podstromy + bst_dispose(&(*tree)->left); + bst_dispose(&(*tree)->right); + // Uvolníme aktuální uzel + free(*tree); + *tree = NULL; + } +} + +/* + * Preorder průchod stromem. + * + * Pro aktuálně zpracovávaný uzel zavolejte funkci bst_add_node_to_items. + * + * Funkci implementujte rekurzivně bez použití vlastních pomocných funkcí. + */ +void bst_preorder(bst_node_t *tree, bst_items_t *items) +{ + if (tree != NULL) { + bst_add_node_to_items(tree, items); // Zpracujeme aktuální uzel + bst_preorder(tree->left, items); // Levý podstrom + bst_preorder(tree->right, items); // Pravý podstrom + } +} + +/* + * Inorder průchod stromem. + * + * Pro aktuálně zpracovávaný uzel zavolejte funkci bst_add_node_to_items. + * + * Funkci implementujte rekurzivně bez použití vlastních pomocných funkcí. + */ +void bst_inorder(bst_node_t *tree, bst_items_t *items) +{ + if (tree != NULL) { + bst_inorder(tree->left, items); // Levý podstrom + bst_add_node_to_items(tree, items); // Zpracujeme aktuální uzel + bst_inorder(tree->right, items); // Pravý podstrom + } +} + +/* + * Postorder průchod stromem. + * + * Pro aktuálně zpracovávaný uzel zavolejte funkci bst_add_node_to_items. + * + * Funkci implementujte rekurzivně bez použití vlastních pomocných funkcí. + */ +void bst_postorder(bst_node_t *tree, bst_items_t *items) +{ + if (tree != NULL) { + bst_postorder(tree->left, items); // Levý podstrom + bst_postorder(tree->right, items); // Pravý podstrom + bst_add_node_to_items(tree, items); // Zpracujeme aktuální uzel + } +} diff --git a/2BIT/winter-semester/IAL 2.DU/hashtable.c b/2BIT/winter-semester/IAL 2.DU/hashtable.c new file mode 100644 index 0000000..f81b2a0 --- /dev/null +++ b/2BIT/winter-semester/IAL 2.DU/hashtable.c @@ -0,0 +1,180 @@ +/* + * Tabulka s rozptýlenými položkami + * + * S využitím datových typů ze souboru hashtable.h a připravených koster + * funkcí implementujte tabulku s rozptýlenými položkami s explicitně + * zretězenými synonymy. + * + * Při implementaci uvažujte velikost tabulky HT_SIZE. + */ + +#include "hashtable.h" +#include +#include + +int HT_SIZE = MAX_HT_SIZE; + +/* + * Rozptylovací funkce která přidělí zadanému klíči index z intervalu + * <0,HT_SIZE-1>. Ideální rozptylovací funkce by měla rozprostírat klíče + * rovnoměrně po všech indexech. Zamyslete sa nad kvalitou zvolené funkce. + */ +int get_hash(char *key) { + int result = 1; + int length = strlen(key); + for (int i = 0; i < length; i++) { + result += key[i]; + } + return (result % HT_SIZE); +} + +/* + * Inicializace tabulky — zavolá sa před prvním použitím tabulky. + */ +void ht_init(ht_table_t *table) { + // Inicializujeme všetky položky na NULL + for (int i = 0; i < HT_SIZE; i++) { + (*table)[i] = NULL; + } +} + +/* + * Vyhledání prvku v tabulce. + * + * V případě úspěchu vrací ukazatel na nalezený prvek; v opačném případě vrací + * hodnotu NULL. + */ +ht_item_t *ht_search(ht_table_t *table, char *key) { + // Získame index pomocou hash funkcie + int index = get_hash(key); + + // Prechádzame zoznam synoným + ht_item_t *item = (*table)[index]; + while (item != NULL) { + // Ak nájdeme kľúč, vrátime položku + if (strcmp(item->key, key) == 0) { + return item; + } + item = item->next; + } + + // Prvok nebol nájdený + return NULL; +} + +/* + * Vložení nového prvku do tabulky. + * + * Pokud prvek s daným klíčem už v tabulce existuje, nahraďte jeho hodnotu. + * + * Při implementaci využijte funkci ht_search. Pri vkládání prvku do seznamu + * synonym zvolte nejefektivnější možnost a vložte prvek na začátek seznamu. + */ +void ht_insert(ht_table_t *table, char *key, float value) { + // Skúsime nájsť existujúci prvok + ht_item_t *item = ht_search(table, key); + + if (item != NULL) { + // Ak existuje, aktualizujeme hodnotu + item->value = value; + } else { + // Vytvoríme nový prvok + int index = get_hash(key); + item = malloc(sizeof(ht_item_t)); + if (item == NULL) { + return; // Chyba alokácie + } + + // Alokujeme a skopírujeme kľúč + item->key = malloc(strlen(key) + 1); + if (item->key == NULL) { + free(item); + return; + } + strcpy(item->key, key); + + // Nastavíme hodnotu a zaradíme na začiatok zoznamu synoným + item->value = value; + item->next = (*table)[index]; + (*table)[index] = item; + } +} + +/* + * Získání hodnoty z tabulky. + * + * V případě úspěchu vrací funkce ukazatel na hodnotu prvku, v opačném + * případě hodnotu NULL. + * + * Při implementaci využijte funkci ht_search. + */ +float *ht_get(ht_table_t *table, char *key) { + // Vyhľadáme prvok + ht_item_t *item = ht_search(table, key); + + if (item != NULL) { + // Ak existuje, vrátime pointer na hodnotu + return &(item->value); + } + + return NULL; +} + +/* + * Smazání prvku z tabulky. + * + * Funkce korektně uvolní všechny alokované zdroje přiřazené k danému prvku. + * Pokud prvek neexistuje, funkce nedělá nic. + * + * Při implementaci NEPOUŽÍVEJTE funkci ht_search. + */ +void ht_delete(ht_table_t *table, char *key) { + int index = get_hash(key); + ht_item_t *item = (*table)[index]; + ht_item_t *prev = NULL; + + // Prechádzame zoznam a hľadáme prvok + while (item != NULL) { + if (strcmp(item->key, key) == 0) { + // Našli sme prvok na zmazanie + if (prev == NULL) { + // Je to prvý prvok v zozname + (*table)[index] = item->next; + } else { + // Je to prvok v strede/na konci zoznamu + prev->next = item->next; + } + + // Uvoľníme pamäť + free(item->key); + free(item); + return; + } + prev = item; + item = item->next; + } +} + +/* + * Smazání všech prvků z tabulky. + * + * Funkce korektně uvolní všechny alokované zdroje a uvede tabulku do stavu po + * inicializaci. + */ +void ht_delete_all(ht_table_t *table) { + // Prechádzame všetky položky tabuľky + for (int i = 0; i < HT_SIZE; i++) { + ht_item_t *item = (*table)[i]; + + // Postupne mažeme všetky prvky v zozname synoným + while (item != NULL) { + ht_item_t *next = item->next; + free(item->key); + free(item); + item = next; + } + + // Inicializujeme položku na NULL + (*table)[i] = NULL; + } +} diff --git a/2BIT/winter-semester/INP1/cpu.vhd b/2BIT/winter-semester/INP1/cpu.vhd new file mode 100644 index 0000000..485f3c5 --- /dev/null +++ b/2BIT/winter-semester/INP1/cpu.vhd @@ -0,0 +1,595 @@ +-- cpu.vhd: Simple 8-bit CPU (BrainFuck interpreter) +-- Copyright (C) 2024 Brno University of Technology, +-- Faculty of Information Technology +-- Author(s): Roman Necas +-- +library ieee; +use ieee.std_logic_1164.all; +use ieee.std_logic_arith.all; +use ieee.std_logic_unsigned.all; + +-- ---------------------------------------------------------------------------- +-- Entity declaration +-- ---------------------------------------------------------------------------- +entity cpu is + port ( + CLK : in std_logic; -- hodinovy signal + RESET : in std_logic; -- asynchronni reset procesoru + EN : in std_logic; -- povoleni cinnosti procesoru + + -- synchronni pamet RAM + DATA_ADDR : out std_logic_vector(12 downto 0); -- adresa do pameti + DATA_WDATA : out std_logic_vector(7 downto 0); -- mem[DATA_ADDR] <- DATA_WDATA pokud DATA_EN='1' + DATA_RDATA : in std_logic_vector(7 downto 0); -- DATA_RDATA <- ram[DATA_ADDR] pokud DATA_EN='1' + DATA_RDWR : out std_logic; -- cteni (1) / zapis (0) + DATA_EN : out std_logic; -- povoleni cinnosti + + -- vstupni port + IN_DATA : in std_logic_vector(7 downto 0); -- IN_DATA <- stav klavesnice pokud IN_VLD='1' a IN_REQ='1' + IN_VLD : in std_logic; -- data platna + IN_REQ : out std_logic; -- pozadavek na vstup data + + -- vystupni port + OUT_DATA : out std_logic_vector(7 downto 0); -- zapisovana data + OUT_BUSY : in std_logic; -- LCD je zaneprazdnen (1), nelze zapisovat + OUT_INV : out std_logic; -- pozadavek na aktivaci inverzniho zobrazeni (1) + OUT_WE : out std_logic; -- LCD <- OUT_DATA pokud OUT_WE='1' a OUT_BUSY='0' + + -- stavove signaly + READY : out std_logic; -- hodnota 1 znamena, ze byl procesor inicializovan a zacina vykonavat program + DONE : out std_logic -- hodnota 1 znamena, ze procesor ukoncil vykonavani programu (narazil na instrukci halt) + ); +end cpu; + + +-- ---------------------------------------------------------------------------- +-- Architecture declaration +-- ---------------------------------------------------------------------------- +architecture behavioral of cpu is + + -- ASCII-based instruction set constants for BrainFuck language implementation + -- Each constant represents a specific command in the instruction set + constant INST_PTR_INC : std_logic_vector(7 downto 0) := X"3E"; -- > : Move data pointer right + constant INST_PTR_DEC : std_logic_vector(7 downto 0) := X"3C"; -- < : Move data pointer left + constant INST_VAL_INC : std_logic_vector(7 downto 0) := X"2B"; -- + : Increment value at pointer + constant INST_VAL_DEC : std_logic_vector(7 downto 0) := X"2D"; -- - : Decrement value at pointer + constant INST_WHILE_START : std_logic_vector(7 downto 0) := X"5B"; -- [ : Start loop if value != 0 + constant INST_WHILE_END : std_logic_vector(7 downto 0) := X"5D"; -- ] : End loop if value != 0 + constant INST_WRITE : std_logic_vector(7 downto 0) := X"2E"; -- . : Output value at pointer + constant INST_READ : std_logic_vector(7 downto 0) := X"2C"; -- , : Input value to pointer + constant INST_STORE : std_logic_vector(7 downto 0) := X"24"; -- $ : Store value to temp register + constant INST_LOAD : std_logic_vector(7 downto 0) := X"21"; -- ! : Load value from temp register + constant INST_HALT : std_logic_vector(7 downto 0) := X"40"; -- @ : Halt program execution + + -- Finite State Machine (FSM) states definition + -- These states control the CPU's operation sequence + type fsm_state is ( + s_idle, -- Initial state: CPU is inactive + s_fetch, -- Fetch: Read next instruction from memory + s_decode, -- Decode: Interpret the fetched instruction + s_init_find, -- Initialization: Search for program start (@) + s_init_find_read, -- Initialization: Read memory during @ search + s_init_ptr, -- Initialization: Set up data pointer + s_ptr_inc, -- Execution: Increment data pointer + s_ptr_dec, -- Execution: Decrement data pointer + s_val_inc, -- Value Increment: Start + s_val_inc_2, -- Value Increment: Read current value + s_val_inc_3, -- Value Increment: Write back + s_val_dec, -- Value Decrement: Start + s_val_dec_2, -- Value Decrement: Read current value + s_val_dec_3, -- Value Decrement: Write back + s_store_val, -- Memory: Store value to temporary register + s_load_val, -- Memory: Load from temporary register + s_load_val_2, -- Memory: Complete load operation + s_while_start, -- Loop: Begin processing loop start + s_while_start_2, -- Loop: Check if we should enter loop + s_while_start_3, -- Loop: Find matching end bracket + s_while_start_4, -- Loop: Forward navigation state + s_while_start_5, -- Loop: Process navigation + s_while_start_6, -- Loop: Handle nested loops (forward) + s_while_end, -- Loop: Begin processing loop end + s_while_end_2, -- Loop: Check if we should exit loop + s_while_end_3, -- Loop: Find matching start bracket + s_while_end_4, -- Loop: Backward navigation state + s_while_end_5, -- Loop: Process backward navigation + s_while_end_6, -- Loop: Handle nested loops (backward) + s_read_wait, -- I/O: Wait for input data + s_read_store, -- I/O: Store input data + s_write_wait, -- I/O: Wait for output ready + s_write, -- I/O: Perform write operation + s_halt -- Program End: Halt execution + ); + + -- Register and Control Signal Declarations + -- Program Counter (PC) related signals + signal pc_reg : std_logic_vector(12 downto 0) := (others => '0'); -- Stores instruction address + signal pc_inc : std_logic := '0'; -- Increment PC + signal pc_dec : std_logic := '0'; -- Decrement PC + signal pc_clear : std_logic := '0'; -- Reset PC to zero + + -- Data Pointer (PTR) related signals + signal ptr_reg : std_logic_vector(12 downto 0) := (others => '0'); -- Stores data memory address + signal ptr_inc_i : std_logic := '0'; -- Increment PTR + signal ptr_dec_i : std_logic := '0'; -- Decrement PTR + signal ptr_pc_load : std_logic := '0'; -- Load PC value into PTR + + -- Loop Counter (CNT) related signals + signal cnt_reg : std_logic_vector(7 downto 0) := (others => '0'); -- Tracks nested loop depth + signal cnt_inc : std_logic := '0'; -- Increment counter + signal cnt_dec : std_logic := '0'; -- Decrement counter + signal cnt_clear : std_logic := '0'; -- Reset counter + + -- Temporary Storage Register + signal tmp_reg : std_logic_vector(7 downto 0) := (others => '0'); -- Temporary data storage + signal tmp_ld : std_logic := '0'; -- Load control for tmp_reg + + -- FSM State Registers + signal pstate : fsm_state := s_idle; -- Current state + signal nstate : fsm_state := s_idle; -- Next state + + -- Multiplexer Control Signals + signal mx1_sel : std_logic := '0'; -- Address MUX (0: PC, 1: PTR) + signal mx2_sel : std_logic_vector(1 downto 0) := "00"; -- Data MUX selection + -- 00: Input data + -- 01: Decremented value + -- 10: Incremented value + -- 11: Temporary register + +begin + -- Program Counter (PC) Register Process + -- Controls program execution flow by managing instruction address + pc_reg_proc: process (CLK, RESET) + begin + if RESET = '1' then + -- Synchronous reset: Initialize PC to 0 + pc_reg <= (others => '0'); + elsif rising_edge(CLK) then + if EN = '1' then -- Only update when CPU is enabled + if pc_clear = '1' then + -- Clear operation takes precedence + pc_reg <= (others => '0'); + elsif pc_inc = '1' then + -- Increment PC for next instruction + pc_reg <= pc_reg + 1; + elsif pc_dec = '1' then + -- Decrement PC (used in loop operations) + pc_reg <= pc_reg - 1; + end if; + end if; + end if; + end process; + + -- Data Pointer (PTR) Register Process + -- Manages data memory addressing with wraparound functionality + ptr_reg_proc: process (CLK, RESET) + begin + if RESET = '1' then + -- Synchronous reset: Initialize PTR to 0 + ptr_reg <= (others => '0'); + elsif rising_edge(CLK) then + if EN = '1' then -- Only update when CPU is enabled + if ptr_pc_load = '1' then + -- Load PC value into PTR (used during initialization) + ptr_reg <= pc_reg; + elsif ptr_inc_i = '1' then + -- Increment with wraparound at maximum value + if ptr_reg = "1111111111111" then + ptr_reg <= (others => '0'); + else + ptr_reg <= ptr_reg + 1; + end if; + elsif ptr_dec_i = '1' then + -- Decrement with wraparound at zero + if ptr_reg = "0000000000000" then + ptr_reg <= "1111111111111"; + else + ptr_reg <= ptr_reg - 1; + end if; + end if; + end if; + end if; + end process; + + -- Loop Counter (CNT) Register Process + -- Manages nested loop depth tracking + cnt_reg_proc: process (CLK, RESET) + begin + if RESET = '1' then + -- Synchronous reset: Initialize counter to 0 + cnt_reg <= (others => '0'); + elsif rising_edge(CLK) then + if EN = '1' then -- Only update when CPU is enabled + if cnt_clear = '1' then + -- Clear counter (start of new loop processing) + cnt_reg <= (others => '0'); + elsif cnt_inc = '1' then + -- Increment counter (nested loop entry) + cnt_reg <= cnt_reg + 1; + elsif cnt_dec = '1' and cnt_reg /= "00000000" then + -- Decrement counter (nested loop exit) + -- Only decrement if not already zero + cnt_reg <= cnt_reg - 1; + end if; + end if; + end if; + end process; + + -- Temporary (TMP) Register Process + -- Provides temporary storage for data values + tmp_reg_proc: process (CLK, RESET) + begin + if RESET = '1' then + -- Synchronous reset: Clear temporary storage + tmp_reg <= (others => '0'); + elsif rising_edge(CLK) then + if EN = '1' and tmp_ld = '1' then + -- Load new value from data memory when enabled + tmp_reg <= DATA_RDATA; + end if; + end if; + end process; + + -- FSM Present State Register Process + -- Manages state transitions in the CPU's control unit + fsm_pstate: process (CLK, RESET) + begin + if RESET = '1' then + -- Synchronous reset: Return to idle state + pstate <= s_idle; + elsif rising_edge(CLK) then + if EN = '1' then + -- Update current state with next state + pstate <= nstate; + end if; + end if; + end process; + +-- FSM Next State Logic & Output Logic + -- This process handles: + -- 1. State transitions based on current state and inputs + -- 2. Control signal generation for each state + -- 3. Output signal management + fsm_nstate: process (pstate, DATA_RDATA, IN_VLD, OUT_BUSY, cnt_reg, EN) + begin + -- Default signal assignments to prevent latches + -- Control signals are set to inactive by default + nstate <= pstate; -- Maintain current state unless changed + pc_inc <= '0'; -- No PC increment + pc_dec <= '0'; -- No PC decrement + pc_clear <= '0'; -- No PC reset + ptr_inc_i <= '0'; -- No PTR increment + ptr_dec_i <= '0'; -- No PTR decrement + ptr_pc_load <= '0'; -- No PTR loading from PC + cnt_inc <= '0'; -- No counter increment + cnt_dec <= '0'; -- No counter decrement + cnt_clear <= '0'; -- No counter reset + tmp_ld <= '0'; -- No temporary register load + mx1_sel <= '0'; -- Address MUX defaults to PC + mx2_sel <= "00"; -- Data MUX defaults to input data + DATA_EN <= '0'; -- Memory access disabled + DATA_RDWR <= '1'; -- Default to read operation + IN_REQ <= '0'; -- No input request + OUT_WE <= '0'; -- No output write + OUT_DATA <= (others => '0'); -- Clear output data + DONE <= '0'; -- Not done by default + + -- READY signal logic + -- Only inactive during initialization states + if pstate = s_idle or pstate = s_init_find or pstate = s_init_find_read then + READY <= '0'; + else + READY <= '1'; + end if; + + -- Main FSM state machine + case pstate is + -- Initial state: Wait for enable signal + when s_idle => + if EN = '1' then + nstate <= s_init_find; -- Start initialization + DATA_EN <= '1'; -- Enable memory access + DATA_RDWR <= '1'; -- Set to read mode + end if; + + -- Initialization: Search for program start marker (@) + when s_init_find => + DATA_EN <= '1'; -- Enable memory access + DATA_RDWR <= '1'; -- Set to read mode + nstate <= s_init_find_read; -- Move to read state + + -- Read during initialization + when s_init_find_read => + DATA_EN <= '1'; + DATA_RDWR <= '1'; + if DATA_RDATA = INST_HALT then -- Found @ symbol + nstate <= s_init_ptr; + ptr_pc_load <= '1'; -- Save program start position + else + pc_inc <= '1'; -- Continue searching + nstate <= s_init_find; + end if; + + -- Initialize data pointer + when s_init_ptr => + ptr_inc_i <= '1'; -- Move past program in memory + pc_clear <= '1'; -- Reset PC to start of program + nstate <= s_fetch; -- Begin program execution + + -- Fetch cycle: Read next instruction + when s_fetch => + DATA_EN <= '1'; -- Enable memory access + DATA_RDWR <= '1'; -- Set to read mode + nstate <= s_decode; -- Move to decode state + + -- Decode cycle: Interpret instruction + when s_decode => + DATA_EN <= '1'; + DATA_RDWR <= '1'; + + -- Instruction decoding logic + case DATA_RDATA is + when INST_PTR_INC => -- > : Move pointer right + nstate <= s_ptr_inc; + when INST_PTR_DEC => -- < : Move pointer left + nstate <= s_ptr_dec; + when INST_VAL_INC => -- + : Increment value + nstate <= s_val_inc; + mx1_sel <= '1'; -- Select PTR address + when INST_VAL_DEC => -- - : Decrement value + nstate <= s_val_dec; + mx1_sel <= '1'; -- Select PTR address + when INST_WRITE => -- . : Output value + nstate <= s_write_wait; + mx1_sel <= '1'; -- Select PTR address + when INST_READ => -- , : Input value + nstate <= s_read_wait; + IN_REQ <= '1'; -- Request input + when INST_STORE => -- $ : Store to temp + nstate <= s_store_val; + mx1_sel <= '1'; -- Select PTR address + when INST_LOAD => -- ! : Load from temp + nstate <= s_load_val; + mx1_sel <= '1'; -- Select PTR address + when INST_WHILE_START => -- [ : Loop start + nstate <= s_while_start; + mx1_sel <= '1'; -- Select PTR address + when INST_WHILE_END => -- ] : Loop end + nstate <= s_while_end; + mx1_sel <= '1'; -- Select PTR address + when INST_HALT => -- @ : Halt program + nstate <= s_halt; + when others => -- Invalid/ignore + nstate <= s_fetch; + pc_inc <= '1'; -- Skip invalid instruction + end case; + + -- Pointer increment operation + when s_ptr_inc => + ptr_inc_i <= '1'; -- Increment data pointer + pc_inc <= '1'; -- Move to next instruction + nstate <= s_fetch; -- Return to fetch cycle + + -- Pointer decrement operation + when s_ptr_dec => + ptr_dec_i <= '1'; -- Decrement data pointer + pc_inc <= '1'; -- Move to next instruction + nstate <= s_fetch; -- Return to fetch cycle + + -- Value increment operation (3-stage) + when s_val_inc => + DATA_EN <= '1'; -- Enable memory + DATA_RDWR <= '1'; -- Read mode + mx1_sel <= '1'; -- Use PTR address + nstate <= s_val_inc_2; + + when s_val_inc_2 => + DATA_EN <= '1'; + DATA_RDWR <= '1'; -- Still reading + mx1_sel <= '1'; -- Still using PTR + nstate <= s_val_inc_3; + + when s_val_inc_3 => + DATA_EN <= '1'; + DATA_RDWR <= '0'; -- Switch to write mode + mx1_sel <= '1'; -- Still using PTR + mx2_sel <= "10"; -- Select incremented value + pc_inc <= '1'; -- Next instruction + nstate <= s_fetch; + + -- Value decrement operation (3-stage) + when s_val_dec => + DATA_EN <= '1'; -- Enable memory + DATA_RDWR <= '1'; -- Read mode + mx1_sel <= '1'; -- Use PTR address + nstate <= s_val_dec_2; + + when s_val_dec_2 => + DATA_EN <= '1'; + DATA_RDWR <= '1'; -- Still reading + mx1_sel <= '1'; -- Still using PTR + nstate <= s_val_dec_3; + + when s_val_dec_3 => + DATA_EN <= '1'; + DATA_RDWR <= '0'; -- Switch to write mode + mx1_sel <= '1'; -- Still using PTR + mx2_sel <= "01"; -- Select decremented value + pc_inc <= '1'; -- Next instruction + nstate <= s_fetch; + + -- Store value to temporary register + when s_store_val => + DATA_EN <= '1'; -- Enable memory + DATA_RDWR <= '1'; -- Read mode + tmp_ld <= '1'; -- Enable temp register load + pc_inc <= '1'; -- Next instruction + nstate <= s_fetch; + + -- Load value from temporary register + when s_load_val => + DATA_EN <= '1'; -- Enable memory + DATA_RDWR <= '0'; -- Write mode + mx1_sel <= '1'; -- Use PTR address + mx2_sel <= "11"; -- Select temp register value + pc_inc <= '1'; -- Next instruction + nstate <= s_fetch; + + -- Input handling states + when s_read_wait => + IN_REQ <= '1'; -- Request input + if IN_VLD = '1' then -- Input data valid + nstate <= s_read_store; + end if; + + when s_read_store => + DATA_EN <= '1'; -- Enable memory + DATA_RDWR <= '0'; -- Write mode + mx1_sel <= '1'; -- Use PTR address + mx2_sel <= "00"; -- Select input data + pc_inc <= '1'; -- Next instruction + nstate <= s_fetch; + + -- Output handling states + when s_write_wait => + DATA_EN <= '1'; -- Enable memory + DATA_RDWR <= '1'; -- Read mode + mx1_sel <= '1'; -- Use PTR address + if OUT_BUSY = '0' then -- Output ready + nstate <= s_write; + end if; + + when s_write => + OUT_WE <= '1'; -- Write to output + OUT_DATA <= DATA_RDATA; -- Output current value + pc_inc <= '1'; -- Next instruction + nstate <= s_fetch; + + -- Loop start handling states + when s_while_start => + DATA_EN <= '1'; -- Enable memory + DATA_RDWR <= '1'; -- Read mode + mx1_sel <= '1'; -- Use PTR address + nstate <= s_while_start_2; + + when s_while_start_2 => + DATA_EN <= '1'; + DATA_RDWR <= '1'; + mx1_sel <= '1'; + nstate <= s_while_start_3; + + when s_while_start_3 => + if DATA_RDATA = "00000000" then -- Skip loop if value is 0 + pc_inc <= '1'; + cnt_clear <= '1'; + nstate <= s_while_start_4; + else + pc_inc <= '1'; -- Enter loop + nstate <= s_fetch; + end if; + + -- Loop start bracket matching states + when s_while_start_4 => + DATA_EN <= '1'; + DATA_RDWR <= '1'; + pc_inc <= '1'; + nstate <= s_while_start_5; + + when s_while_start_5 => + DATA_EN <= '1'; + DATA_RDWR <= '1'; + nstate <= s_while_start_6; + + when s_while_start_6 => + if DATA_RDATA = INST_WHILE_START then -- Found nested [ + cnt_inc <= '1'; -- Increment nest level + nstate <= s_while_start_4; + elsif DATA_RDATA = INST_WHILE_END then -- Found ] + if cnt_reg = "00000000" then -- Matching ] found + pc_inc <= '1'; + nstate <= s_fetch; + else -- Nested ] found + cnt_dec <= '1'; + nstate <= s_while_start_4; + end if; + else + nstate <= s_while_start_4; -- Keep searching + end if; + + -- Loop end handling states + when s_while_end => + DATA_EN <= '1'; -- Enable memory + DATA_RDWR <= '1'; -- Read mode + mx1_sel <= '1'; -- Use PTR address + nstate <= s_while_end_2; + + when s_while_end_2 => + DATA_EN <= '1'; + DATA_RDWR <= '1'; + mx1_sel <= '1'; + nstate <= s_while_end_3; + + when s_while_end_3 => + if DATA_RDATA /= "00000000" then -- Continue loop if value not 0 + pc_dec <= '1'; + cnt_clear <= '1'; + nstate <= s_while_end_4; + else + pc_inc <= '1'; -- Exit loop + nstate <= s_fetch; + end if; + + -- Loop end bracket matching states + when s_while_end_4 => + DATA_EN <= '1'; + DATA_RDWR <= '1'; + pc_dec <= '1'; -- Search backwards + nstate <= s_while_end_5; + + when s_while_end_5 => + DATA_EN <= '1'; + DATA_RDWR <= '1'; + nstate <= s_while_end_6; + + when s_while_end_6 => + if DATA_RDATA = INST_WHILE_END then -- Found nested ] + cnt_inc <= '1'; -- Increment nest level + nstate <= s_while_end_4; + elsif DATA_RDATA = INST_WHILE_START then -- Found [ + if cnt_reg = "00000000" then -- Matching [ found + pc_inc <= '1'; + nstate <= s_fetch; + else -- Nested [ found + cnt_dec <= '1'; + nstate <= s_while_end_4; + end if; + else + nstate <= s_while_end_4; -- Keep searching + end if; + + -- Program termination state + when s_halt => + DONE <= '1'; -- Signal program completion + nstate <= s_halt; -- Stay in halt state + + -- Fallback state (shouldn't occur) + when others => + nstate <= s_idle; -- Return to idle state + + end case; + end process; + + -- Output signal assignments + OUT_INV <= '0'; -- Display is always in normal mode + + -- Address Multiplexer (MX1) + -- Selects between program counter (PC) and data pointer (PTR) + DATA_ADDR <= ptr_reg when mx1_sel = '1' else pc_reg; + + -- Data Multiplexer (MX2) + -- Selects between different data sources based on operation + DATA_WDATA <= IN_DATA when mx2_sel = "00" else -- Input data + DATA_RDATA - 1 when mx2_sel = "01" else -- Decremented value + DATA_RDATA + 1 when mx2_sel = "10" else -- Incremented value + tmp_reg; -- Temporary register + +end behavioral; \ No newline at end of file diff --git a/2BIT/winter-semester/INP1/log.txt b/2BIT/winter-semester/INP1/log.txt new file mode 100644 index 0000000..6b423ea --- /dev/null +++ b/2BIT/winter-semester/INP1/log.txt @@ -0,0 +1,106 @@ +/usr/local/share/ghdl/bin/ghdl -i --ieee=synopsys -fexplicit --workdir=build --work=work ../src/cpu.vhd +/usr/local/share/ghdl/bin/ghdl -m --ieee=synopsys -fexplicit --workdir=build -Pbuild --work=work cpu +/usr/local/share/ghdl/bin/ghdl -r --ieee=synopsys -fexplicit --workdir=build -Pbuild --work=work cpu --vpi=/homes/eva/xn/xnecasr00/inp24-projekt1/env/lib/python3.8/site-packages/cocotb/libs/libcocotbvpi_ghdl.so --wave=build/wave.ghw + -.--ns INFO gpi ..mbed/gpi_embed.cpp:109 in set_program_name_in_venv Using Python virtual environment interpreter at /homes/eva/xn/xnecasr00/inp24-projekt1/env/bin/python + -.--ns INFO gpi ../gpi/GpiCommon.cpp:101 in gpi_print_registered_impl VPI registered + 0.00ns INFO cocotb Running on GHDL version 2.0.0 (tarball) [Dunoon edition] + 0.00ns INFO cocotb Running tests with cocotb v1.7.1 from /homes/eva/xn/xnecasr00/inp24-projekt1/env/lib/python3.8/site-packages/cocotb + 0.00ns INFO cocotb Seeding Python random module with 1729847958 + 0.00ns INFO cocotb.hexdigest lib: 47382bf4ccf309a0c56cb33a5e15d78e + 0.00ns INFO cocotb.regression Found test cpu.test_reset + 0.00ns INFO cocotb.regression Found test cpu.test_init + 0.00ns INFO cocotb.regression Found test cpu.test_increment + 0.00ns INFO cocotb.regression Found test cpu.test_decrement + 0.00ns INFO cocotb.regression Found test cpu.test_move + 0.00ns INFO cocotb.regression Found test cpu.test_print + 0.00ns INFO cocotb.regression Found test cpu.test_input + 0.00ns INFO cocotb.regression Found test cpu.test_while_loop + 0.00ns INFO cocotb.regression Found test cpu.test_tmp + 0.00ns INFO cocotb.regression Found test cpu.test_login_xnecasr00 + 0.00ns INFO cocotb.regression Found test cpu.test_printf + 0.00ns INFO cocotb.regression running test_reset (1/11) + 0.00ns INFO cocotb.hexdigest test: d7d420db3f09a47d86315431cb616d10 + 51.00ns INFO cocotb.regression test_reset passed + 51.00ns INFO cocotb.regression running test_init (2/11) + Procesor initialization test + 51.00ns INFO cocotb.hexdigest test: 7ddc67b5815aca97487ddb63b8cdc16f + 52.00ns INFO cocotb.hexdigest code: 420cd9f16e90b08dbdf5195fdd9d0f62 len: 1 + 171.00ns INFO cocotb.hexdigest result: 420cd9f16e90b08dbdf5195fdd9d0f62 + 171.00ns INFO cocotb.regression test_init passed + 171.00ns INFO cocotb.regression running test_increment (3/11) + Increment value of the first memory cell, i.e. *ptr++ + 171.00ns INFO cocotb.hexdigest test: 60dfe4add2b9271d898d25ac5ee14bbf + 172.00ns INFO cocotb.hexdigest code: 83fdb8859bf9b7036a839b918e308b60 len: 4 + 501.00ns INFO cocotb.hexdigest result: 08a9e9c47976e0116dfa992853b8e023 + 501.00ns INFO cocotb.regression test_increment passed + 501.00ns INFO cocotb.regression running test_decrement (4/11) + Decrement value of the first memory cell, i.e. *ptr-- + 501.00ns INFO cocotb.hexdigest test: 53a89f9741d6b8d1e5add41795ddb5c4 + 502.00ns INFO cocotb.hexdigest code: 0772f54a199d95c25fff832f480c9d84 len: 4 + 831.00ns INFO cocotb.hexdigest result: cd6b8633aedcb944cec479ecee67bfa8 + 831.00ns INFO cocotb.regression test_decrement passed + 831.00ns INFO cocotb.regression running test_move (5/11) + Move the pointer to the next cell and increment its value + 831.00ns INFO cocotb.hexdigest test: fb6cba85ed89649a4d9f60657e04c871 + 832.00ns INFO cocotb.hexdigest code: 7c1cd3f96fc2c2ff2e089c27cfda24b6 len: 3 + 1071.00ns INFO cocotb.hexdigest result: 7efbf0ee85c154b96298cc5edbbd2370 + 1071.00ns INFO cocotb.regression test_move passed + 1071.00ns INFO cocotb.regression running test_print (6/11) + Print data to the output, i.e. putchar(*ptr) + 1071.00ns INFO cocotb.hexdigest test: 7e4f654ca78b6a82f8e9d0ae2b58e54d + 1072.00ns INFO cocotb.hexdigest code: b265746fe722436c7a1a1d8de199b058 len: 4 + 2331.00ns INFO cocotb.hexdigest result: b265746fe722436c7a1a1d8de199b058 + 2331.00ns INFO cocotb.regression test_print passed + 2331.00ns INFO cocotb.regression running test_input (7/11) + Load data from the input, i.e. *ptr=getchar() + 2331.00ns INFO cocotb.hexdigest test: 029d6a5fe7100a0f3c588ee18b3a1e54 + 2332.00ns INFO cocotb.hexdigest code: d3fac245532f03964cd19007b2032729 len: 4 + 3591.00ns INFO cocotb.hexdigest result: 2ed967e2be16e52843468f1408cb360b + 3592.00ns INFO cocotb.hexdigest code: d3fac245532f03964cd19007b2032729 len: 4 + 4851.00ns INFO cocotb.hexdigest result: e816e9d618b24eaf2f916252df61b844 + 4851.00ns INFO cocotb.regression test_input passed + 4851.00ns INFO cocotb.regression running test_while_loop (8/11) + Simple while loop test + 4851.00ns INFO cocotb.hexdigest test: b6bcfa49e2ccdf738e216d68dd13d1f7 + 4852.00ns INFO cocotb.hexdigest code: dc8bee53ab9c57eaa957fd0fe2002e38 len: 5 + 6281.00ns INFO cocotb.hexdigest result: c5c20856db594032a8e2bc7a51242fe0 + 6281.00ns INFO cocotb.regression test_while_loop passed + 6281.00ns INFO cocotb.regression running test_tmp (9/11) + Simple temp register test + 6281.00ns INFO cocotb.hexdigest test: c9565eea230ea05b373334fc80ff2bf7 + 6282.00ns INFO cocotb.hexdigest code: 77503a20e66588894e22aab0fb92677f len: 6 + 6711.00ns INFO cocotb.hexdigest result: 77503a20e66588894e22aab0fb92677f + 6711.00ns INFO cocotb.regression test_tmp passed + 6711.00ns INFO cocotb.regression running test_login_xnecasr00 (10/11) + Executes program in login.b file + 6711.00ns INFO cocotb.hexdigest test: 8a793e69d5861a222f94a0d67683a17e + 6712.00ns INFO cocotb.hexdigest code: 1a14ec0ba5305eff4ca0efe7efbf87d0 len: 124 + 48431.00ns INFO cocotb.hexdigest result: 7085d40a64a63374233afbba3505a4e9 + 48431.00ns INFO cocotb.regression test_login_xnecasr00 passed + 48431.00ns INFO cocotb.regression running test_printf (11/11) + Program which emulates printing of %d + 48431.00ns INFO cocotb.hexdigest test: c8c0607159ce86bd73eefc16718ea879 + 48432.00ns INFO cocotb.hexdigest code: 9fc8c0e3deed36e0cb53e5933e2d28ef len: 179 +525401.00ns DEBUG cocotb.lcd Characters written to LCD: '1' +532061.00ns DEBUG cocotb.lcd Characters written to LCD: '12' +538851.00ns DEBUG cocotb.lcd Characters written to LCD: '123' +545641.00ns INFO cocotb.hexdigest result: 600c85f9643af4a10981f2423c499034 +545641.00ns INFO cocotb.regression test_printf passed +545641.00ns INFO cocotb.regression **************************************************************************************** + ** TEST STATUS SIM TIME (ns) REAL TIME (s) RATIO (ns/s) ** + **************************************************************************************** + ** cpu.test_reset PASS 51.00 0.00 17075.88 ** + ** cpu.test_init PASS 120.00 0.01 14236.88 ** + ** cpu.test_increment PASS 330.00 0.02 19868.80 ** + ** cpu.test_decrement PASS 330.00 0.02 19853.70 ** + ** cpu.test_move PASS 240.00 0.01 18900.36 ** + ** cpu.test_print PASS 1260.00 0.05 27257.37 ** + ** cpu.test_input PASS 2520.00 0.10 24979.61 ** + ** cpu.test_while_loop PASS 1430.00 0.05 26298.65 ** + ** cpu.test_tmp PASS 430.00 0.02 20821.41 ** + ** cpu.test_login_xnecasr00 PASS 41720.00 1.46 28488.86 ** + ** cpu.test_printf PASS 497210.00 16.28 30549.51 ** + **************************************************************************************** + ** TESTS=11 PASS=11 FAIL=0 SKIP=0 545641.00 18.27 29857.46 ** + **************************************************************************************** + diff --git a/2BIT/winter-semester/INP1/login.b b/2BIT/winter-semester/INP1/login.b new file mode 100644 index 0000000..739dc62 --- /dev/null +++ b/2BIT/winter-semester/INP1/login.b @@ -0,0 +1,18 @@ ++++++ +++++ +[ + > +++++ +++++ ++ + > +++++ +++++ + + > +++++ + <<< - +] +>. +----------. +---------. +--. +--. +>+++++. +-. +>--. +$>! +. +@ \ No newline at end of file diff --git a/2BIT/winter-semester/INP1/login.png b/2BIT/winter-semester/INP1/login.png new file mode 100644 index 0000000..c1aff57 Binary files /dev/null and b/2BIT/winter-semester/INP1/login.png differ diff --git a/2BIT/winter-semester/INP2/xnecasr00.s b/2BIT/winter-semester/INP2/xnecasr00.s new file mode 100644 index 0000000..05a60ae --- /dev/null +++ b/2BIT/winter-semester/INP2/xnecasr00.s @@ -0,0 +1,81 @@ +; Autor reseni: roman necas xnecasr00 + +; Projekt 2 - INP 2024 +; Vigenerova sifra na architekture MIPS64 + +; DATA SEGMENT + .data +msg: .asciiz "romannecas" ; sem doplnte vase "jmenoprijmeni" +cipher: .space 31 ; misto pro zapis zasifrovaneho textu +; zde si muzete nadefinovat vlastni promenne ci konstanty, +; napr. hodnoty posuvu pro jednotlive znaky sifrovacho klice + +key: .asciiz "nec" + +params_sys5: .space 8 ; misto pro ulozeni adresy pocatku + ; retezce pro vypis pomoci syscall 5 + ; (viz nize "funkce" print_string) + +; CODE SEGMENT + .text + +main: ; ZDE NAHRATE KOD VASIM RESENIM + daddi r4, r0, msg ;nacitanie msg do r4 + daddi r5, r0, cipher ;nacitanie adr. cipher do r5 + daddi r6, r0, key ;adr. kluca do r6 + daddi r7, r0, 1 ;init priz. smeru(1 vpred, -1 vzad) +encrpt_loop: + lb r8, 0(r4) ;nacitanie znaku z msg + beqz r8, end_encrpt ; ak 0, tak konec siforvania + + lb r9, 0(r6) ;nacitanie znaku z key + beqz r9, reset_key ;ak 0, reset an zacaitok key + j continue_encrpt +reset_key: + daddi r6, r0, key ;reset adresy kluca na zaciatok + lb r9, 0(r6) ;nacitanie prveho kluca +continue_encrpt: + daddi r9, r9, -96 ; prevod znaku kluce na cislo (a=0, b=1, ...) + mult r9, r7 ; smeru posuvu + mflo r9 ; ziskani vysledku nasobeni + dadd r10, r8, r9 ; posuvu na znak zpravy + + slti r11, r10, 97 ; kontrola, ci je vysledek mensi nez 'a' + bnez r11, wrap_forward + + slti r11, r10, 123 ; kontrola, ci je vysl. vetsi nez 'z' + beqz r11, wrap_backward + + j store_char + +wrap_forward: + daddi r10, r10, 26 ; wrap zpet do rozsahu + j store_char + +wrap_backward: + daddi r10, r10, -26 ; wrap zpet do rozsahu + +store_char: + sb r10, 0(r5) ; ulozeni zasifrovaneho znaku + + daddi r4, r4, 1 ; posun na dalsi znak zpravy + daddi r5, r5, 1 ; posun na dalsiu poziciu v encrpt zprave + daddi r6, r6, 1 ; posun na dalsi znak kluca + dsub r7, r0, r7 ; zmena smeru z 1 na -1 nebo z -1 na 1 + j encrpt_loop + +end_encrpt: + sb r0, 0(r5) ;ukonc, 0 do cipher + daddi r4, r0, cipher ;priprava pre vypis encprt + jal print_string ;vypis encrpt textu + + +; NASLEDUJICI KOD NEMODIFIKUJTE! + + syscall 0 ; halt + +print_string: ; adresa retezce se ocekava v r4 + sw r4, params_sys5(r0) + daddi r14, r0, params_sys5 ; adr pro syscall 5 musi do r14 + syscall 5 ; systemova procedura - vypis retezce na terminal + jr r31 ; return - r31 je urcen na return address diff --git a/2BIT/winter-semester/ISS/Program.txt b/2BIT/winter-semester/ISS/Program.txt new file mode 100644 index 0000000..d8e21f7 --- /dev/null +++ b/2BIT/winter-semester/ISS/Program.txt @@ -0,0 +1 @@ +https://colab.research.google.com/drive/1ucmnN-E_KfQK3A9aCGL45RchSeYJuZl8?usp=sharing \ No newline at end of file diff --git a/2BIT/winter-semester/ISS/xnecasr00.ipynb b/2BIT/winter-semester/ISS/xnecasr00.ipynb new file mode 100644 index 0000000..221df3d --- /dev/null +++ b/2BIT/winter-semester/ISS/xnecasr00.ipynb @@ -0,0 +1,1110 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Protokol k projektu ISS 2024/25\n", + "### Rozpoznávanie zvukov automobilových motorov\n", + "#### **Autor**: Roman Nečas\n", + "#### **Login**: xnecasr00\n", + "#### **Dátum**: 7.12.2024\n", + "### 1. Úvod a cieľ projektu\n", + "Projekt sa zaoberá automatickým rozpoznávaním a klasifikáciou zvukov automobilových motorov. Hlavným cieľom je vyvinúť metodiku, ktorá dokáže priradiť neznáme zvukové nahrávky k referenčným nahrávkam rovnakého automobilu, aj keď motor beží na iných otáčkach.\n", + "\n", + "### 2. Teoretický rozbor\n", + "#### 2.1 Charakteristika zvuku motora\n", + "Zvuk motora je komplexný signál obsahujúci niekoľko kľúčových charakteristík:\n", + "\n", + "\n", + "* Základná frekvencia závislá od otáčok motora\n", + "* Harmonické frekvencie (násobky základnej frekvencie)\n", + "* Špecifické spektrálne charakteristiky dané konštrukciou motora\n", + "\n", + "#### 2.2 Metódy analýzy\n", + "Pre analýzu som zvolil nasledujúce metódy:\n", + "\n", + "\n", + "1. Časová analýza\n", + " * Zobrazenie priebehu signálu\n", + " * Výpočet základných štatistických parametrov\n", + " \n", + "2. Frekvenčná analýza\n", + " * Fourierova transformácia (FFT)\n", + " * Analýza spektra\n", + " * Identifikácia základnej frekvencie\n", + "\n", + "3. Normalizovaná spektrálna analýza\n", + " * Normalizácia spektra vzhľadom na základnú frekvenciu\n", + " * Normalizácia amplitúd\n", + " * Analýza harmonických komponentov\n", + "\n", + "Dôvod zvolenia týchto metód bol, aby som sa dostal k charakteristike zvukových nahrávok motorov, v ktorej by boli otáčky motora, teda základná frekvencia \"odfiltrované\" a mohol som porovnavať zvukové nahrávky nezávisle na otáčkach motora.\n", + "\n", + "\n", + "### 3. Implementácia" + ], + "metadata": { + "id": "43AksbDpPsRF" + } + }, + { + "cell_type": "markdown", + "source": [ + "#### Knižnice a stiahnutie signálu" + ], + "metadata": { + "id": "PmPbaKgw3SSB" + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "rt9zooK4PoOg" + }, + "outputs": [], + "source": [ + "import os\n", + "import re\n", + "import glob\n", + "import soundfile as sf\n", + "from IPython.display import Audio\n", + "from IPython.display import display\n", + "from scipy import signal\n", + "from scipy.io import wavfile\n", + "from scipy.fft import fft, ifft, fftfreq\n", + "import scipy.io\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n" + ] + }, + { + "cell_type": "code", + "source": [ + "login = \"xnecasr00\"\n", + "zip_file = login + \".zip\"\n", + "assignment_file = \"https://www.fit.vut.cz/study/course/ISS/public/proj2024-25/personal/\" + zip_file\n", + "!wget $assignment_file\n", + "!unzip -o $zip_file\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "6dVSj2mxtuOw", + "outputId": "d87199a8-5684-494c-8cab-d3e2c2900e43" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "--2024-12-07 15:43:24-- https://www.fit.vut.cz/study/course/ISS/public/proj2024-25/personal/xnecasr00.zip\n", + "Resolving www.fit.vut.cz (www.fit.vut.cz)... 147.229.9.65, 2001:67c:1220:809::93e5:941\n", + "Connecting to www.fit.vut.cz (www.fit.vut.cz)|147.229.9.65|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 227217 (222K) [application/zip]\n", + "Saving to: ‘xnecasr00.zip’\n", + "\n", + "xnecasr00.zip 100%[===================>] 221.89K 340KB/s in 0.7s \n", + "\n", + "2024-12-07 15:43:25 (340 KB/s) - ‘xnecasr00.zip’ saved [227217/227217]\n", + "\n", + "Archive: xnecasr00.zip\n", + " creating: xnecasr00/\n", + " inflating: xnecasr00/BMW_318i_Drive.wav \n", + " inflating: xnecasr00/test_f.wav \n", + " inflating: xnecasr00/Fiat_Panda_Drive.wav \n", + " inflating: xnecasr00/test_t.wav \n", + " inflating: xnecasr00/Audi_A3_Drive.wav \n", + " inflating: xnecasr00/test_s.wav \n", + " inflating: xnecasr00/Peugeot_307_Drive.wav \n", + " inflating: xnecasr00/test_i.wav \n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "# load the data\n", + "# references will be in ref_signals, reference labels in ref_labels, reference count in N_ref.\n", + "# tests will be in test_signals, test labels in test_labels, test count in N_test.\n", + "def get_signals(labs):\n", + " signals = []\n", + " N = len(labs)\n", + " for car in labs:\n", + " filename = login + \"/\" + car + \".wav\"\n", + " s, Fs = sf.read(filename)\n", + " signals.append(s)\n", + " return signals, N, Fs\n", + "\n", + "def play_signals(signals, Fs):\n", + " for signal in signals:\n", + " display(Audio(signal, rate=Fs))\n", + "\n", + "files = glob.glob(login + \"/*.wav\")\n", + "names = [re.sub(login + \"/\", \"\", s) for s in files]\n", + "labels = [re.sub(\".wav\", \"\",s) for s in names]\n", + "print (\"----- test signals ---------\")\n", + "r = re.compile(\"^test_\"); test_labels = list(filter(r.match, labels))\n", + "print (test_labels); test_signals, N_test, Fs = get_signals(test_labels); play_signals (test_signals, Fs)\n", + "print (\"----- reference signals ---------\")\n", + "r = re.compile(\"(?!^test_)\"); ref_labels = list(filter(r.match, labels))\n", + "print (ref_labels); ref_signals, N_ref, Fs = get_signals(ref_labels); play_signals (ref_signals, Fs)\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 457 + }, + "id": "BYYQvmDzyT5W", + "outputId": "1fdd67da-8222-41d8-f02d-10365cd6fdae" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "----- test signals ---------\n", + "['test_t', 'test_s', 'test_f', 'test_i']\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "----- reference signals ---------\n", + "['Fiat_Panda_Drive', 'BMW_318i_Drive', 'Peugeot_307_Drive', 'Audi_A3_Drive']\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "\n", + " \n", + " " + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "### Analýza signálu v čase\n", + "Najskôr si vykreslím časový priebeh signálov, spolu s ich základnými štatistickými parametrami, ktoré mi ale aj tak veľmi nepomohli." + ], + "metadata": { + "id": "b3jOXClCDBSu" + } + }, + { + "cell_type": "code", + "source": [ + "def analyze_signals(signals, Fs, labels, title):\n", + " \"\"\"\n", + " Analyzuje a vizualizuje základné vlastnosti zvukových signálov\n", + "\n", + " Parametre:\n", + " signals: list zvukových signálov\n", + " Fs: vzorkovacia frekvencia\n", + " labels: názvy signálov\n", + " title: názov pre graf\n", + " \"\"\"\n", + " n_signals = len(signals)\n", + " time = np.arange(len(signals[0])) / Fs\n", + "\n", + " plt.figure(figsize=(15, 10))\n", + "\n", + " # Časové priebehy\n", + " for i, (sig, label) in enumerate(zip(signals, labels)):\n", + " plt.subplot(n_signals, 1, i+1)\n", + " plt.plot(time, sig)\n", + " plt.title(f'{label} - Časový priebeh')\n", + " plt.xlabel('Čas [s]')\n", + " plt.ylabel('Amplitúda')\n", + "\n", + " # Výpis základných štatistík\n", + " print(f\"\\nŠtatistiky pre {label}:\")\n", + " print(f\"Maximum: {np.max(sig):.3f}\")\n", + " print(f\"Minimum: {np.min(sig):.3f}\")\n", + " print(f\"Stredná hodnota: {np.mean(sig):.3f}\")\n", + " print(f\"Smerodajná odchýlka: {np.std(sig):.3f}\")\n", + "\n", + " plt.suptitle(title)\n", + " plt.tight_layout()\n", + " plt.show()\n", + "\n", + "# Analýza referenčných signálov\n", + "analyze_signals(ref_signals, Fs, ref_labels, \"Referenčné signály\")\n", + "\n", + "# Analýza testovacích signálov\n", + "analyze_signals(test_signals, Fs, test_labels, \"Testovacie signály\")" + ], + "metadata": { + "id": "S1tLZITSE0Sh", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 2838 + }, + "outputId": "5129b1b1-1c5c-48d3-ed29-c1fc46a36f7f" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "Štatistiky pre Fiat_Panda_Drive:\n", + "Maximum: 0.669\n", + "Minimum: -0.635\n", + "Stredná hodnota: -0.001\n", + "Smerodajná odchýlka: 0.291\n", + "\n", + "Štatistiky pre BMW_318i_Drive:\n", + "Maximum: 0.020\n", + "Minimum: -0.020\n", + "Stredná hodnota: 0.000\n", + "Smerodajná odchýlka: 0.006\n", + "\n", + "Štatistiky pre Peugeot_307_Drive:\n", + "Maximum: 0.277\n", + "Minimum: -0.301\n", + "Stredná hodnota: -0.000\n", + "Smerodajná odchýlka: 0.079\n", + "\n", + "Štatistiky pre Audi_A3_Drive:\n", + "Maximum: 0.480\n", + "Minimum: -0.482\n", + "Stredná hodnota: 0.000\n", + "Smerodajná odchýlka: 0.147\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "Štatistiky pre test_t:\n", + "Maximum: 0.100\n", + "Minimum: -0.096\n", + "Stredná hodnota: -0.000\n", + "Smerodajná odchýlka: 0.027\n", + "\n", + "Štatistiky pre test_s:\n", + "Maximum: 0.125\n", + "Minimum: -0.135\n", + "Stredná hodnota: 0.000\n", + "Smerodajná odchýlka: 0.034\n", + "\n", + "Štatistiky pre test_f:\n", + "Maximum: 0.322\n", + "Minimum: -0.365\n", + "Stredná hodnota: -0.000\n", + "Smerodajná odchýlka: 0.111\n", + "\n", + "Štatistiky pre test_i:\n", + "Maximum: 0.061\n", + "Minimum: -0.059\n", + "Stredná hodnota: 0.000\n", + "Smerodajná odchýlka: 0.020\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "### Spektrálna analýza\n", + "Z časového priebehu sa dá pozorovať periodicita signálov. Je pomerne ľahko viditeľná základná frekvencia, teda rýchlost otáčok motora.Pomocou spektrálnej analýzi si teda zobrazíme frekvenčné spektrum." + ], + "metadata": { + "id": "_v9CuGVsD4T9" + } + }, + { + "cell_type": "code", + "source": [ + "# Spektrálna analýza\n", + "def spectral_analysis(signals, Fs, labels, title):\n", + " \"\"\"\n", + " Vykoná spektrálnu analýzu signálov\n", + "\n", + " Parametre:\n", + " signals: list zvukových signálov\n", + " Fs: vzorkovacia frekvencia\n", + " labels: názvy signálov\n", + " title: názov pre graf\n", + " \"\"\"\n", + " n_signals = len(signals)\n", + " plt.figure(figsize=(15, 10))\n", + "\n", + " for i, (sig, label) in enumerate(zip(signals, labels)):\n", + " # Výpočet FFT\n", + " freq = np.fft.fftfreq(len(sig), 1/Fs)\n", + " fft_sig = np.fft.fft(sig)\n", + "\n", + " # Zobrazenie len pozitívnych frekvencií\n", + " positive_freq_idx = freq >= 0\n", + "\n", + " plt.subplot(n_signals, 1, i+1)\n", + " plt.plot(freq[positive_freq_idx], np.abs(fft_sig)[positive_freq_idx])\n", + " plt.title(f'{label} - Frekvenčné spektrum')\n", + " plt.xlabel('Frekvencia [Hz]')\n", + " plt.ylabel('Magnitúda')\n", + "\n", + " plt.suptitle(title)\n", + " plt.tight_layout()\n", + " plt.show()\n", + "\n", + "# Spektrálna analýza referenčných signálov\n", + "spectral_analysis(ref_signals, Fs, ref_labels, \"Spektrálna analýza - Referenčné signály\")\n", + "\n", + "# Spektrálna analýza testovacích signálov\n", + "spectral_analysis(test_signals, Fs, test_labels, \"Spektrálna analýza - Testovacie signály\")\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1986 + }, + "id": "GD9rdOFgYjpn", + "outputId": "1de969b0-0145-48ca-dac8-1618095aab90" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "### Hľadanie základných frekvencií\n", + "Nájdem a označím si základnú frekvenciu, je dominantná a zo všetkých grafou ju je ľahko vidieť. Vypíšem jej hodnotu. Podľa tejto hodnoty by sa v podstate dali zistiť konkrétne otáčky všetkých motorov." + ], + "metadata": { + "id": "LAGKncYiFI-R" + } + }, + { + "cell_type": "code", + "source": [ + "def analyze_fundamental_frequency(signal, fs, freq_range=(20, 500)):\n", + " \"\"\"\n", + " Analyzuje frekvenčné spektrum a nájde základnú frekvenciu\n", + "\n", + " Parametre:\n", + " signal: vstupný signál\n", + " fs: vzorkovacia frekvencia\n", + " freq_range: rozsah frekvencií pre hľadanie základnej frekvencie (min, max)\n", + "\n", + " Návratové hodnoty:\n", + " freqs: všetky frekvencie\n", + " magnitude: magnitudy frekvencií\n", + " fund_freq: základná frekvencia\n", + " \"\"\"\n", + " # Výpočet FFT\n", + " fft_sig = np.fft.fft(signal)\n", + " freqs = np.fft.fftfreq(len(signal), 1/fs)\n", + " magnitude = np.abs(fft_sig)\n", + "\n", + " # Obmedzenie na pozitívne frekvencie\n", + " positive_freq_mask = freqs >= 0\n", + " freqs = freqs[positive_freq_mask]\n", + " magnitude = magnitude[positive_freq_mask]\n", + "\n", + " # Nájdenie základnej frekvencie v danom rozsahu\n", + " freq_mask = (freqs >= freq_range[0]) & (freqs <= freq_range[1])\n", + " fund_freq = freqs[freq_mask][np.argmax(magnitude[freq_mask])]\n", + "\n", + " return freqs, magnitude, fund_freq\n", + "\n", + "def plot_frequency_spectra(signals, labels, fs, title):\n", + " \"\"\"\n", + " Vykreslí frekvenčné spektrá so zvýraznenou základnou frekvenciou\n", + " \"\"\"\n", + " n_signals = len(signals)\n", + " plt.figure(figsize=(15, 3*n_signals))\n", + "\n", + " for i, (signal, label) in enumerate(zip(signals, labels)):\n", + " # Analýza frekvenčného spektra\n", + " freqs, magnitude, fund_freq = analyze_fundamental_frequency(signal, fs)\n", + "\n", + " # Vykreslenie spektra\n", + " plt.subplot(n_signals, 1, i+1)\n", + " plt.plot(freqs, magnitude)\n", + "\n", + " # Zvýraznenie základnej frekvencie\n", + " fund_idx = np.argmin(np.abs(freqs - fund_freq))\n", + " plt.plot(fund_freq, magnitude[fund_idx], 'r*',\n", + " markersize=15, label=f'Základná frekvencia: {fund_freq:.1f} Hz')\n", + "\n", + " plt.title(f'{label} - Frekvenčné spektrum')\n", + " plt.xlabel('Frekvencia [Hz]')\n", + " plt.ylabel('Magnitúda')\n", + " plt.grid(True)\n", + " plt.legend()\n", + "\n", + " # Obmedzenie zobrazenia na relevantný rozsah frekvencií\n", + " plt.xlim(0, 1000) # zobrazíme len prvých 1000 Hz\n", + "\n", + " plt.suptitle(title)\n", + " plt.tight_layout()\n", + " plt.show()\n", + "\n", + "# Analýza referenčných signálov\n", + "plot_frequency_spectra(ref_signals, ref_labels, Fs, \"Frekvenčné spektrá - Referenčné signály\")\n", + "\n", + "# Analýza testovacích signálov\n", + "plot_frequency_spectra(test_signals, test_labels, Fs, \"Frekvenčné spektrá - Testovacie signály\")\n", + "\n", + "# Výpis základných frekvencií\n", + "print(\"\\nZákladné frekvencie referenčných signálov:\")\n", + "for signal, label in zip(ref_signals, ref_labels):\n", + " _, _, fund_freq = analyze_fundamental_frequency(signal, Fs)\n", + " print(f\"{label}: {fund_freq:.1f} Hz\")\n", + "\n", + "print(\"\\nZákladné frekvencie testovacích signálov:\")\n", + "for signal, label in zip(test_signals, test_labels):\n", + " _, _, fund_freq = analyze_fundamental_frequency(signal, Fs)\n", + " print(f\"{label}: {fund_freq:.1f} Hz\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 2584 + }, + "id": "JWkRY8EsMthR", + "outputId": "c60896c0-6823-4f0a-989f-0742ac20023c" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" 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\n" + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "Základné frekvencie referenčných signálov:\n", + "Fiat_Panda_Drive: 216.0 Hz\n", + "BMW_318i_Drive: 38.0 Hz\n", + "Peugeot_307_Drive: 123.0 Hz\n", + "Audi_A3_Drive: 127.0 Hz\n", + "\n", + "Základné frekvencie testovacích signálov:\n", + "test_t: 25.0 Hz\n", + "test_s: 59.0 Hz\n", + "test_f: 166.0 Hz\n", + "test_i: 42.0 Hz\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "### Normalizácia frekvenčnej osi\n", + "Znormalizujem si frekvenčnú os na násobky základnej frekvencie. Frekvenčné spektrum sa bude dať porovnávať medzi nahrávkami." + ], + "metadata": { + "id": "2hAheJQkGD8v" + } + }, + { + "cell_type": "code", + "source": [ + "def get_normalized_spectrum(signal, fs):\n", + " \"\"\"\n", + " Vypočíta a posunie frekvenčné spektrum tak, aby základná frekvencia bola na fixnej pozícii\n", + " \"\"\"\n", + "\n", + " # Výpočet FFT\n", + " fft_sig = np.fft.fft(signal)\n", + " freqs = np.fft.fftfreq(len(signal), 1/fs)\n", + " magnitude = np.abs(fft_sig)\n", + "\n", + " # Nájdenie základnej frekvencie (v rozsahu 20-500 Hz)\n", + " positive_mask = freqs >= 0\n", + " freq_range_mask = (freqs >= 20) & (freqs <= 500)\n", + " valid_mask = positive_mask & freq_range_mask\n", + "\n", + " fund_freq = freqs[valid_mask][np.argmax(magnitude[valid_mask])]\n", + "\n", + " # Vytvorenie normalizovanej frekvenčnej osi\n", + " # Posunieme frekvencie tak, aby základná frekvencia bola na 1\n", + " normalized_freqs = freqs / fund_freq\n", + "\n", + " return normalized_freqs[positive_mask], magnitude[positive_mask], fund_freq\n", + "\n", + "def plot_normalized_spectra(signals, labels, fs, title):\n", + " \"\"\"\n", + " Vykreslí normalizované frekvenčné spektrá\n", + " \"\"\"\n", + " plt.figure(figsize=(15, 10))\n", + "\n", + " for i, (signal, label) in enumerate(zip(signals, labels)):\n", + " # Získanie normalizovaného spektra\n", + " norm_freqs, magnitude, fund_freq = get_normalized_spectrum(signal, fs)\n", + "\n", + " plt.subplot(len(signals), 1, i+1)\n", + " plt.plot(norm_freqs, magnitude)\n", + " plt.axvline(x=1, color='r', linestyle='--', label='Základná frekvencia')\n", + "\n", + " # Zvýraznenie harmonických\n", + " for n in range(2, 6):\n", + " plt.axvline(x=n, color='g', linestyle=':', alpha=0.5)\n", + "\n", + " plt.title(f'{label} (Základná frekvencia: {fund_freq:.1f} Hz)')\n", + " plt.xlabel('Normalizovaná frekvencia (f/f0)')\n", + " plt.ylabel('Magnitúda')\n", + " plt.xlim(0, 5) # Zobrazíme prvých 5 harmonických\n", + " plt.grid(True)\n", + " plt.legend()\n", + "\n", + " plt.suptitle(title)\n", + " plt.tight_layout()\n", + " plt.show()\n", + "\n", + "# Analýza referenčných signálov\n", + "print(\"Referenčné signály:\")\n", + "plot_normalized_spectra(ref_signals, ref_labels, Fs, \"Normalizované frekvenčné spektrá - Referenčné signály\")\n", + "\n", + "# Analýza testovacích signálov\n", + "print(\"\\nTestovacie signály:\")\n", + "plot_normalized_spectra(test_signals, test_labels, Fs, \"Normalizované frekvenčné spektrá - Testovacie signály\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 2037 + }, + "id": "52xXcPH4PG6m", + "outputId": "89a0b144-868b-4b7a-99de-2d2485ab27b3" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Referenčné signály:\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "Testovacie signály:\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "Teraz už z grafov je možné badať podobnosti, prípadne rozdiely medzi jednotlivými signálmi.\n", + "### Výsledná analýza spektra a výpočet vzdialeností medzi nahrávkami\n", + "Ďalej normalizujem amplitúdu, a vypočítam pomer medzi základnou frekvenciou a jej harmonickými násobkami. Avšak hodnotu frekvencií hramonických násobkov budem brať ako maximálnu hodnotu z malého okolia harmonického násobku aby som obmedzil nepresnosti, napríklad pri nahrávke Audi_A3_Drive sú vrcholy frekvencií v harmonických násobkoch mierne posunuté, čo by mohlo spôsobovať nepresné výsledky.\n", + "Vypočítam vzdialenosti medzi pomermi, pričom do výpočtu budem brať len prvých 6 harmonických frekvencií okrem základnej, je to z dôvodu toho že aj keď som zobral viac, tak sa už výsledok zásadne nezmenil." + ], + "metadata": { + "id": "X8RGq27yGkFP" + } + }, + { + "cell_type": "code", + "source": [ + "def get_normalized_spectrum_with_peak_ratios(signal, fs, window_width=0.05):\n", + " \"\"\"\n", + " Vykonáva spektrálnu analýzu zvukových signálov založenú na pomeroch\n", + " maximálnych amplitúd v okolí harmonických frekvencií.\n", + "\n", + " Parametre:\n", + " signal: Časový priebeh zvukového signálu\n", + " fs: Vzorkovacia frekvencia\n", + " window_width: Šírka okna okolo harmonických pre analýzu (ako zlomok harmonickej frekvencie)\n", + "\n", + " Vracia:\n", + " norm_freqs: Normalizované frekvencie (relatívne k základnej)\n", + " magnitude: Normalizované magnitudové spektrum\n", + " fund_freq: Základná frekvencia\n", + " peak_ratios: Normalizované pomery maximálnych amplitúd harmonických komponentov\n", + " highlight_masks: Boolovské masky pre vizualizáciu\n", + " \"\"\"\n", + " # Aplikujeme Hanningovo okno pre zníženie spektrálneho presakovania\n", + " window = np.hanning(len(signal))\n", + " signal = signal * window\n", + "\n", + " # Vypočítame FFT a získame frekvenčnú os\n", + " fft_sig = np.fft.fft(signal)\n", + " freqs = np.fft.fftfreq(len(signal), 1/fs)\n", + " magnitude = np.abs(fft_sig)\n", + "\n", + " # Vytvoríme masky pre platné frekvenčné rozsahy\n", + " positive_mask = freqs >= 0\n", + " # Zameriame sa na typický rozsah frekvencií motora (20-500 Hz)\n", + " freq_range_mask = (freqs >= 20) & (freqs <= 500)\n", + " valid_mask = positive_mask & freq_range_mask\n", + "\n", + " # Odhadneme úroveň šumu pre lepšiu detekciu špičiek\n", + " noise_floor = np.median(magnitude[valid_mask])\n", + " signal_threshold = noise_floor * 3\n", + "\n", + " # Nájdeme významné špičky nad úrovňou šumu\n", + " peaks = magnitude[valid_mask] > signal_threshold\n", + " potential_freqs = freqs[valid_mask][peaks]\n", + " potential_mags = magnitude[valid_mask][peaks]\n", + "\n", + " # Identifikujeme základnú frekvenciu z najsilnejšej špičky\n", + " if len(potential_mags) > 0:\n", + " fund_freq_idx = np.argmax(potential_mags)\n", + " fund_freq = potential_freqs[fund_freq_idx]\n", + " fund_magnitude = potential_mags[fund_freq_idx]\n", + " else:\n", + " max_idx = np.argmax(magnitude[valid_mask])\n", + " fund_freq = freqs[valid_mask][max_idx]\n", + " fund_magnitude = magnitude[valid_mask][max_idx]\n", + "\n", + " # Normalizujeme amplitúdy vzhľadom na amplitúdu základnej frekvencie\n", + " magnitude = magnitude / fund_magnitude\n", + "\n", + " # Normalizujeme frekvencie relatívne k základnej\n", + " norm_freqs = freqs[positive_mask] / fund_freq\n", + " magnitude = magnitude[positive_mask]\n", + "\n", + " # Analyzujeme harmonické komponenty pomocou maximálnych amplitúd\n", + " peak_ratios = []\n", + " n_harmonics = 6\n", + " highlight_masks = []\n", + "\n", + " for n in range(1, n_harmonics + 1):\n", + " # Vytvoríme úzke okno okolo každej harmonickej frekvencie\n", + " window_mask = (norm_freqs >= n - window_width) & \\\n", + " (norm_freqs <= n + window_width)\n", + " highlight_masks.append(window_mask)\n", + "\n", + " # Použijeme maximálnu hodnotu v okne\n", + " if np.any(window_mask):\n", + " peak_value = np.max(magnitude[window_mask])\n", + " peak_ratios.append(peak_value)\n", + " else:\n", + " peak_ratios.append(noise_floor / fund_magnitude) # Normalizovaná hodnota šumu\n", + "\n", + " return norm_freqs, magnitude, fund_freq, np.array(peak_ratios), highlight_masks\n", + "\n", + "def plot_normalized_spectra(signals, labels, fs, title, window_width=0.05):\n", + " \"\"\"\n", + " Vytvára vizualizáciu normalizovaných spektier so zvýraznenými harmonickými frekvenciami.\n", + " \"\"\"\n", + " plt.figure(figsize=(15, 10))\n", + "\n", + " for i, (signal, label) in enumerate(zip(signals, labels)):\n", + " norm_freqs, magnitude, fund_freq, peak_ratios, highlight_masks = \\\n", + " get_normalized_spectrum_with_peak_ratios(signal, fs, window_width)\n", + "\n", + " plt.subplot(len(signals), 1, i+1)\n", + " plt.plot(norm_freqs, magnitude)\n", + "\n", + " # Zvýrazníme oblasti harmonických frekvencií a pridáme označenie pomerov\n", + " colors = ['blue', 'green', 'pink', 'yellow', 'gray', 'orange']\n", + " for n, (mask, ratio, color) in enumerate(zip(highlight_masks, peak_ratios, colors)):\n", + " plt.fill_between(norm_freqs[mask], magnitude[mask], alpha=0.3, color=color)\n", + " center_freq = n + 1\n", + " max_mag = np.max(magnitude[mask]) if np.any(mask) else 0\n", + " plt.text(center_freq, max_mag, f'P{n+1}: {ratio:.2f}',\n", + " horizontalalignment='center', verticalalignment='bottom')\n", + "\n", + " plt.axvline(x=1, color='r', linestyle='--', label='Základná f')\n", + " plt.axhline(y=1, color='g', linestyle='--', label='Základná A')\n", + "\n", + " plt.title(f'{label} (f0: {fund_freq:.1f} Hz)')\n", + " plt.xlabel('Normalizovaná frekvencia (f/f0)')\n", + " plt.ylabel('Norm. amplitúda (A/A0)')\n", + " plt.xlim(0, 7)\n", + " plt.grid(True)\n", + " plt.legend()\n", + "\n", + " plt.suptitle(f'{title}\\nPomery maximálnych amplitúd (±{window_width * 100}% okno)')\n", + " plt.tight_layout()\n", + " plt.show()\n", + "\n", + "def match_test_to_reference(ref_signals, test_signals, ref_labels, test_labels, fs, window_width=0.05):\n", + " \"\"\"\n", + " Priraďuje testovacie signály k referenčným na základe porovnania\n", + " pomerov maximálnych amplitúd harmonických frekvencií.\n", + " Pre každý referenčný signál nájde testovací signál s najmenšou vzdialenosťou.\n", + " \"\"\"\n", + " # Získame pomery špičiek pre všetky signály\n", + " ref_ratios = []\n", + " test_ratios = []\n", + "\n", + " for signal in ref_signals:\n", + " _, _, _, ratios, _ = get_normalized_spectrum_with_peak_ratios(signal, fs, window_width)\n", + " ref_ratios.append(ratios)\n", + "\n", + " for signal in test_signals:\n", + " _, _, _, ratios, _ = get_normalized_spectrum_with_peak_ratios(signal, fs, window_width)\n", + " test_ratios.append(ratios)\n", + "\n", + " ref_ratios = np.array(ref_ratios)\n", + " test_ratios = np.array(test_ratios)\n", + "\n", + " # Vypočítame euklidovskú vzdialenosť medzi pomermi\n", + " all_distances = np.zeros((len(test_signals), len(ref_signals)))\n", + " for i, test_ratio in enumerate(test_ratios):\n", + " for j, ref_ratio in enumerate(ref_ratios):\n", + " distance = np.sqrt(np.sum((test_ratio - ref_ratio) ** 2))\n", + " all_distances[i, j] = distance\n", + "\n", + " # Výpis matice vzdialeností\n", + " print(\"\\nVzdialenosti medzi pomermi maximálnych amplitúd:\")\n", + " print(\"-\" * 50)\n", + " print(f\"{'':15}\", end=\"\")\n", + " for ref_label in ref_labels:\n", + " print(f\"{ref_label:15} \", end=\"\")\n", + " print()\n", + "\n", + " for i, test_label in enumerate(test_labels):\n", + " print(f\"{test_label:15}\", end=\"\")\n", + " for j in range(len(ref_labels)):\n", + " print(f\"{all_distances[i,j]:15.3f}\", end=\"\")\n", + " print()\n", + "\n", + " # Pre každý referenčný signál nájdeme najbližší testovací signál\n", + " final_matches = {}\n", + "\n", + " for ref_idx, ref_label in enumerate(ref_labels):\n", + " # Nájdeme najbližší testovací signál pre tento referenčný signál\n", + " distances_to_ref = all_distances[:, ref_idx]\n", + " closest_test_idx = np.argmin(distances_to_ref)\n", + " test_label = test_labels[closest_test_idx]\n", + " min_distance = distances_to_ref[closest_test_idx]\n", + "\n", + " final_matches[test_label] = (ref_label, min_distance)\n", + "\n", + " # Výpis výsledkov\n", + " print(\"\\nNájdené zhody:\")\n", + " print(\"-\" * 50)\n", + " for test_label, (ref_label, distance) in final_matches.items():\n", + " print(f\"{test_label} -> {ref_label} (vzdialenosť: {distance:.3f})\")\n", + "\n", + " # Nájdeme nepriradené testovacie signály\n", + " matched_test_labels = set(final_matches.keys())\n", + " unmatched_test_labels = set(test_labels) - matched_test_labels\n", + "\n", + " if unmatched_test_labels:\n", + " print(\"\\nNepriradené testovacie signály:\")\n", + " for test_label in unmatched_test_labels:\n", + " print(f\"- {test_label}\")\n", + "\n", + " return final_matches\n", + "\n", + "def analyze_car_sounds(ref_signals, test_signals, ref_labels, test_labels, fs):\n", + " \"\"\"\n", + " Vykonáva kompletnú analýzu zvukov automobilových motorov.\n", + " \"\"\"\n", + " plot_normalized_spectra(ref_signals, ref_labels, fs,\n", + " \"Analýza referenčných signálov\")\n", + "\n", + " plot_normalized_spectra(test_signals, test_labels, fs,\n", + " \"Analýza testovacích signálov\")\n", + "\n", + " matches = match_test_to_reference(\n", + " ref_signals, test_signals, ref_labels, test_labels, fs)\n", + "\n", + " return matches\n", + "# Spustíme analýzu\n", + "matches = analyze_car_sounds(ref_signals, test_signals, ref_labels, test_labels, Fs)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 2239 + }, + "id": "QIQjrYFN52DE", + "outputId": "64bd1de8-cf81-4e73-8dcc-44bc7ae4e4a9" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" 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\n" + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "Vzdialenosti medzi pomermi maximálnych amplitúd:\n", + "--------------------------------------------------\n", + " Fiat_Panda_Drive BMW_318i_Drive Peugeot_307_Drive Audi_A3_Drive \n", + "test_t 0.400 0.356 0.295 0.263\n", + "test_s 0.153 0.146 0.244 0.414\n", + "test_f 0.036 0.080 0.329 0.513\n", + "test_i 0.098 0.054 0.253 0.468\n", + "\n", + "Nájdené zhody:\n", + "--------------------------------------------------\n", + "test_f -> Fiat_Panda_Drive (vzdialenosť: 0.036)\n", + "test_i -> BMW_318i_Drive (vzdialenosť: 0.054)\n", + "test_s -> Peugeot_307_Drive (vzdialenosť: 0.244)\n", + "test_t -> Audi_A3_Drive (vzdialenosť: 0.263)\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "###4. Výsledky\n", + "Ku každému autu som dokázal násť neznámu nahrávku s najmenšou vzdialenosťou. Pri Peugeote sú výsledky najmenej jednoznačné. Ale všetky nahrávky zrejme patria k daným autám. Ďalej môžeme vidieť, že Fiat aj BMW maju veľmi malú vzdialenosť k svojim priradeným nahrávkam, pričom Peugeot a Audi majú výrazne vyššiu túto vzdialenosť. To môže byť spôsobené výraznejším rozdielom medzi otáčkami motorov oboch párov nahrávok Peugeotu a Audi, prípadne rôznym šumom v pozadí. Hoci za ideálnych okolností by mali byť tieto vplivy odfiltrované.\n", + "\n", + "###5. Záver\n", + "Implementovaný systém by mal demonštrovať schopnosť rozpoznávať a priraďovať zvuky automobilových motorov na základe ich spektrálnych charakteristík, konkrétne porovnávaním pomerov základnej frekvencie k jej harmonickým frekvenciám." + ], + "metadata": { + "id": "bWeBNWGKJZRi" + } + } + ] +} \ No newline at end of file diff --git a/2BIT/winter-semester/ISS/xnecasr00.pdf b/2BIT/winter-semester/ISS/xnecasr00.pdf new file mode 100644 index 0000000..aafc563 Binary files /dev/null and b/2BIT/winter-semester/ISS/xnecasr00.pdf differ diff --git a/2BIT/winter-semester/ITU/01_xnecasr00_source.zip b/2BIT/winter-semester/ITU/01_xnecasr00_source.zip new file mode 100644 index 0000000..8e08720 Binary files /dev/null and b/2BIT/winter-semester/ITU/01_xnecasr00_source.zip differ diff --git a/2BIT/winter-semester/ITU/02_xnecasr00_final.pdf b/2BIT/winter-semester/ITU/02_xnecasr00_final.pdf new file mode 100644 index 0000000..851fed1 Binary files /dev/null and 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b/3BIT/summer-semester/ITS/2/xnecasr00.zip new file mode 100644 index 0000000..b93db3a Binary files /dev/null and b/3BIT/summer-semester/ITS/2/xnecasr00.zip differ diff --git a/3BIT/winter-semester/IIS/xnecasr00.zip b/3BIT/winter-semester/IIS/xnecasr00.zip new file mode 100644 index 0000000..dcc6344 Binary files /dev/null and b/3BIT/winter-semester/IIS/xnecasr00.zip differ diff --git a/3BIT/winter-semester/IIS/xnecasr00/.env.example b/3BIT/winter-semester/IIS/xnecasr00/.env.example new file mode 100644 index 0000000..84c08af --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/.env.example @@ -0,0 +1,71 @@ +# NOTE: If you see "vendor/autoload.php" missing, run `composer install` in the project root to create the vendor directory. +# If Composer is not installed: +# - On Windows: install from https://getcomposer.org/download/ +# - On WSL/Ubuntu: sudo apt update && sudo apt install composer +# After composer install run: php artisan key:generate && php artisan config:clear && php artisan config:cache + +APP_NAME=Laravel +APP_ENV=local +APP_KEY= +APP_DEBUG=true +APP_URL=http://localhost + +APP_LOCALE=en +APP_FALLBACK_LOCALE=en +APP_FAKER_LOCALE=en_US + +APP_MAINTENANCE_DRIVER=file +# APP_MAINTENANCE_STORE=database + +PHP_CLI_SERVER_WORKERS=4 + +BCRYPT_ROUNDS=12 + +LOG_CHANNEL=stack +LOG_STACK=single +LOG_DEPRECATIONS_CHANNEL=null +LOG_LEVEL=debug + +DB_CONNECTION=mysql +DB_HOST=127.0.0.1 +DB_PORT=3306 +DB_DATABASE=laravel_winary +DB_USERNAME=winary_user +DB_PASSWORD=winary_password + +SESSION_DRIVER=database +SESSION_LIFETIME=120 +SESSION_ENCRYPT=false +SESSION_PATH=/ +SESSION_DOMAIN=null + +BROADCAST_CONNECTION=log +FILESYSTEM_DISK=local +QUEUE_CONNECTION=database + +CACHE_STORE=database +# CACHE_PREFIX= + +MEMCACHED_HOST=127.0.0.1 + +REDIS_CLIENT=phpredis +REDIS_HOST=127.0.0.1 +REDIS_PASSWORD=null +REDIS_PORT=6379 + +MAIL_MAILER=log +MAIL_SCHEME=null +MAIL_HOST=127.0.0.1 +MAIL_PORT=2525 +MAIL_USERNAME=null +MAIL_PASSWORD=null +MAIL_FROM_ADDRESS="hello@example.com" +MAIL_FROM_NAME="${APP_NAME}" + +AWS_ACCESS_KEY_ID= +AWS_SECRET_ACCESS_KEY= +AWS_DEFAULT_REGION=us-east-1 +AWS_BUCKET= +AWS_USE_PATH_STYLE_ENDPOINT=false + +VITE_APP_NAME="${APP_NAME}" diff --git a/3BIT/winter-semester/IIS/xnecasr00/Dockerfile.app b/3BIT/winter-semester/IIS/xnecasr00/Dockerfile.app new file mode 100644 index 0000000..48efee7 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/Dockerfile.app @@ -0,0 +1,42 @@ +FROM php:8.2-fpm + +# Install system dependencies + Node.js (for asset builds) +RUN apt-get update && apt-get install -y \ + git \ + curl \ + ca-certificates \ + gnupg \ + libpng-dev \ + libonig-dev \ + libxml2-dev \ + zip \ + unzip \ + && curl -fsSL https://deb.nodesource.com/setup_20.x | bash - \ + && apt-get install -y nodejs \ + && apt-get clean && rm -rf /var/lib/apt/lists/* + +# Install PHP extensions +RUN docker-php-ext-install pdo_mysql mbstring exif pcntl bcmath gd + +# Get latest Composer +COPY --from=composer:latest /usr/bin/composer /usr/bin/composer + +# Set working directory +WORKDIR /var/www + +# Add entrypoint +COPY docker/app-entrypoint.sh /usr/local/bin/app-entrypoint.sh +RUN chmod +x /usr/local/bin/app-entrypoint.sh + +# Copy existing application directory +COPY . /var/www + +# Set permissions +RUN chown -R www-data:www-data /var/www + +# Expose port 9000 for PHP-FPM and 8741 for artisan serve +EXPOSE 9000 +EXPOSE 8741 + +ENTRYPOINT ["app-entrypoint.sh"] +CMD ["php", "artisan", "serve"] diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Enums/UserRole.php b/3BIT/winter-semester/IIS/xnecasr00/app/Enums/UserRole.php new file mode 100644 index 0000000..f7590fa --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Enums/UserRole.php @@ -0,0 +1,11 @@ +filled('search')) { + $search = $request->search; + $query->where(function ($q) use ($search) { + $q->where('name', 'like', "%{$search}%") + ->orWhere('description', 'like', "%{$search}%") + ->orWhere('location', 'like', "%{$search}%"); + }); + } + + // Filter by type + if ($request->filled('type') && $request->type !== 'all') { + $query->where('type', $request->type); + } + + // Filter by status + if ($request->filled('status') && $request->status !== 'all') { + $query->where('status', $request->status); + } + + $events = $query->orderBy('event_date', 'desc')->paginate(15); + + return view('admin.events.index', compact('events')); + } + + /** + * Show the form for creating a new event. + */ + public function create() + { + return view('admin.events.create'); + } + + /** + * Store a newly created event in storage. + */ + public function store(Request $request) + { + $validated = $request->validate([ + 'name' => ['required', 'string', 'max:255'], + 'description' => ['required', 'string'], + 'type' => ['required', 'in:tasting,harvest_festival,vineyard_tour'], + 'event_date' => ['required', 'date', 'after_or_equal:today'], + 'event_time' => ['required', 'date_format:H:i'], + 'capacity' => ['required', 'integer', 'min:1'], + 'price_per_person' => ['required', 'numeric', 'min:0'], + 'location' => ['nullable', 'string', 'max:255'], + 'status' => ['required', 'in:upcoming,cancelled,completed'], + ]); + + Event::create($validated); + + return redirect()->route('admin.events.index') + ->with('success', 'Event created successfully.'); + } + + /** + * Show the form for editing the specified event. + */ + public function edit(Event $event) + { + // Load event with reservations and user data + $event->load(['reservations' => function($query) { + $query->wherePivot('status', 'confirmed') + ->withPivot('number_of_guests', 'status', 'created_at') + ->orderBy('event_reservations.created_at', 'desc'); + }]); + + return view('admin.events.edit', compact('event')); + } + + /** + * Update the specified event in storage. + */ + public function update(Request $request, Event $event) + { + $validated = $request->validate([ + 'name' => ['required', 'string', 'max:255'], + 'description' => ['required', 'string'], + 'type' => ['required', 'in:tasting,harvest_festival,vineyard_tour'], + 'event_date' => ['required', 'date'], + 'event_time' => ['required', 'date_format:H:i'], + 'capacity' => ['required', 'integer', 'min:1'], + 'price_per_person' => ['required', 'numeric', 'min:0'], + 'location' => ['nullable', 'string', 'max:255'], + 'status' => ['required', 'in:upcoming,cancelled,completed'], + ]); + + $event->update($validated); + + return redirect()->route('admin.events.index') + ->with('success', 'Event updated successfully.'); + } + + /** + * Delete an event. + */ + public function destroy(Event $event) + { + // Check if event has reservations + if ($event->reservations()->wherePivot('status', 'confirmed')->count() > 0) { + return back()->with('error', 'Cannot delete event with confirmed reservations.'); + } + + $event->delete(); + + return back()->with('success', 'Event deleted successfully.'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Admin/UserController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Admin/UserController.php new file mode 100644 index 0000000..0d325d5 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Admin/UserController.php @@ -0,0 +1,113 @@ +filled('search')) { + $search = $request->search; + $query->where(function ($q) use ($search) { + $q->where('name', 'like', "%{$search}%") + ->orWhere('username', 'like', "%{$search}%") + ->orWhere('email', 'like', "%{$search}%"); + }); + } + + // Filter by role + if ($request->filled('role') && $request->role !== 'all') { + $query->where('role', $request->role); + } + + // Order by ID descending (newest first) + $users = $query->orderBy('id', 'desc')->paginate(15); + + return view('admin.users.index', compact('users')); + } + + /** + * Show the form for creating a new user. + */ + public function create() + { + return view('admin.users.create'); + } + + /** + * Store a newly created user in storage. + */ + public function store(Request $request) + { + $validated = $request->validate([ + 'name' => ['required', 'string', 'max:255'], + 'username' => ['required', 'string', 'max:255', 'unique:users'], + 'email' => ['required', 'string', 'email', 'max:255', 'unique:users'], + 'password' => ['required', 'string', 'min:8', 'confirmed'], + 'role' => ['required', 'in:admin,winemaker,employee,customer'], + ]); + + User::create($validated); + + return redirect()->route('admin.users.index') + ->with('success', 'User created successfully.'); + } + + /** + * Show the form for editing the specified user. + */ + public function edit(User $user) + { + return view('admin.users.edit', compact('user')); + } + + /** + * Update the specified user in storage. + */ + public function update(Request $request, User $user) + { + $validated = $request->validate([ + 'name' => ['required', 'string', 'max:255'], + 'username' => ['required', 'string', 'max:255', 'unique:users,username,' . $user->id], + 'email' => ['required', 'string', 'email', 'max:255', 'unique:users,email,' . $user->id], + 'password' => ['nullable', 'string', 'min:8', 'confirmed'], + 'role' => ['required', 'in:admin,winemaker,employee,customer'], + ]); + + // Only update password if provided + if (empty($validated['password'])) { + unset($validated['password']); + } + + $user->update($validated); + + return redirect()->route('admin.users.index') + ->with('success', 'User updated successfully.'); + } + + /** + * Delete a user. + */ + public function destroy(User $user) + { + // Prevent deleting yourself + if ($user->id === auth()->id()) { + return back()->with('error', 'You cannot delete your own account.'); + } + + $user->delete(); + + return back()->with('success', 'User deleted successfully.'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Api/VarietyController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Api/VarietyController.php new file mode 100644 index 0000000..28ec89b --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Api/VarietyController.php @@ -0,0 +1,104 @@ +string('q')->toString(); + + $variations = VarietyVariation::with('grapeVariety') + ->when($query !== '', function ($builder) use ($query) { + $builder->where(function ($inner) use ($query) { + $inner->whereHas('grapeVariety', function ($sub) use ($query) { + $sub->where('variety_name', 'like', '%' . $query . '%'); + })->orWhere('color', 'like', '%' . $query . '%'); + }); + }) + ->orderBy('grape_variety_id') + ->orderBy('color') + ->limit(15) + ->get() + ->map(fn (VarietyVariation $variation) => $this->formatVariation($variation)); + + return response()->json([ + 'data' => $variations, + ]); + } + + public function createIfMissing(Request $request) + { + $validated = $request->validate([ + 'grape_variety_id' => ['nullable', 'integer', 'exists:grape_varieties,id'], + 'grape_variety_name' => ['nullable', 'string', 'max:255'], + 'color' => ['required', 'string', 'max:50'], + 'description' => ['nullable', 'string'], + 'typical_sugar_content' => ['nullable', 'numeric', 'min:0'], + 'typical_alcohol' => ['nullable', 'numeric', 'min:0'], + 'ripening_period' => ['nullable', 'string', 'max:255'], + ], [ + 'grape_variety_id.required_without' => 'Provide an existing variety or a name for a new variety.', + 'grape_variety_name.required_without' => 'Provide an existing variety or a name for a new variety.', + ]); + + $variety = null; + + if (! empty($validated['grape_variety_id'])) { + $variety = GrapeVariety::find($validated['grape_variety_id']); + } + + if (! $variety && ! empty($validated['grape_variety_name'])) { + $variety = GrapeVariety::firstOrCreate([ + 'variety_name' => $validated['grape_variety_name'], + ]); + } + + if (! $variety) { + return response()->json([ + 'message' => 'Unable to determine grape variety for variation creation.', + ], 422); + } + + $variation = VarietyVariation::firstOrCreate( + [ + 'grape_variety_id' => $variety->getKey(), + 'color' => $validated['color'], + ], + [ + 'description' => $validated['description'] ?? null, + 'typical_sugar_content' => $validated['typical_sugar_content'] ?? null, + 'typical_alcohol' => $validated['typical_alcohol'] ?? null, + 'ripening_period' => $validated['ripening_period'] ?? null, + 'status' => 'active', + ] + ); + + return response()->json([ + 'created' => $variation->wasRecentlyCreated, + 'variation' => $this->formatVariation($variation->loadMissing('grapeVariety')), + ], $variation->wasRecentlyCreated ? 201 : 200); + } + + protected function formatVariation(VarietyVariation $variation): array + { + $grape = $variation->grapeVariety; + + return [ + 'id' => $variation->getKey(), + 'label' => sprintf('%s — %s', $grape?->variety_name ?? 'Unknown', Str::title($variation->color)), + 'color' => $variation->color, + 'grape_variety' => $grape ? [ + 'id' => $grape->getKey(), + 'name' => $grape->variety_name, + ] : null, + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Api/VineyardRowController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Api/VineyardRowController.php new file mode 100644 index 0000000..d265e89 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Api/VineyardRowController.php @@ -0,0 +1,46 @@ +when($request->filled('status'), fn ($query) => $query->where('status', $request->string('status'))) + ->when($request->filled('variety_variation_id'), fn ($query) => $query->where('variety_variation_id', $request->integer('variety_variation_id'))) + ->when($request->filled('search'), function ($query) use ($request) { + $term = $request->string('search'); + $query->where(function ($inner) use ($term) { + $inner->where('location', 'like', '%' . $term . '%') + ->orWhereHas('varietyVariation.grapeVariety', function ($sub) use ($term) { + $sub->where('variety_name', 'like', '%' . $term . '%'); + }); + }); + }) + ->orderBy('id') + ->limit(100) + ->get() + ->map(function (VineyardRow $row) { + $variation = $row->varietyVariation; + $grape = $variation?->grapeVariety; + + return [ + 'id' => $row->getKey(), + 'location' => $row->location, + 'vine_count' => $row->vine_count, + 'status' => $row->status, + 'variety' => $variation ? [ + 'id' => $variation->getKey(), + 'label' => $grape ? sprintf('%s — %s', $grape->variety_name, ucfirst($variation->color)) : ucfirst($variation->color), + ] : null, + ]; + }); + + return response()->json(['data' => $rows]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Auth/LoginController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Auth/LoginController.php new file mode 100644 index 0000000..9da1db6 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Auth/LoginController.php @@ -0,0 +1,65 @@ +validate([ + 'username' => ['required', 'string'], + 'password' => ['required', 'string'], + ]); + + $remember = $request->boolean('remember'); + + if (Auth::attempt(['username' => $credentials['username'], 'password' => $credentials['password']], $remember)) { + // Regenerate session to prevent fixation + $request->session()->regenerate(); + + // If the user asked to be remembered, set a cookie with the username so we can + // pre-fill the username field next time. We deliberately DO NOT store the password + // in a cookie for security reasons. The Laravel "remember" feature keeps the + // user logged in across sessions using a secure remember_token. + if ($remember) { + // Cookie duration is in minutes (30 days) + Cookie::queue('remember_username', $credentials['username'], 60 * 24 * 30); + } else { + Cookie::queue(Cookie::forget('remember_username')); + } + + // Redirect based on user role + $user = Auth::user(); + if ($user->role === UserRole::CUSTOMER) { + return redirect()->intended('/catalog'); + } + if ($user->role === UserRole::WINEMAKER) { + return redirect()->intended('/winemaker/dashboard'); + } + if ($user->role === UserRole::EMPLOYEE) { + return redirect()->intended('/employee/tasks'); + } + if ($user->role === UserRole::ADMIN) { + return redirect()->intended('/admin/users'); + } + + return redirect()->intended('/dashboard'); + } + + return back()->withErrors(['username' => 'The provided credentials do not match our records.'])->onlyInput('username'); + } + + public function destroy(Request $request) + { + Auth::logout(); + $request->session()->invalidate(); + $request->session()->regenerateToken(); + return redirect()->route('login'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Auth/RegisterController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Auth/RegisterController.php new file mode 100644 index 0000000..506b3c5 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Auth/RegisterController.php @@ -0,0 +1,39 @@ +validate([ + 'name' => ['required', 'string', 'max:255'], + 'username' => ['required', 'string', 'max:255', 'unique:users,username'], + 'email' => ['required', 'string', 'email', 'max:255', 'unique:users,email'], + 'password' => ['required', 'string', 'min:8', 'confirmed'], + ]); + + // Create the user. The User model casts 'password' => 'hashed', so assigning + // the password will be hashed automatically. + $user = User::create([ + 'name' => $data['name'], + 'username' => $data['username'], + 'email' => $data['email'], + 'password' => $data['password'], + 'role' => UserRole::CUSTOMER, + ]); + + // Optionally: log the user in automatically. For now redirect to login with success. + return redirect()->route('login')->with('status', 'Account created successfully. You may now sign in.'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/CartController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/CartController.php new file mode 100644 index 0000000..2574bc0 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/CartController.php @@ -0,0 +1,140 @@ +getCart(); + $cartItems = []; + $total = 0; + + foreach ($cart as $wineId => $item) { + $wine = Wine::with('grapeVariety')->find($wineId); + if ($wine) { + $itemTotal = $wine->price_per_bottle * $item['quantity']; + $cartItems[] = [ + 'wine' => $wine, + 'quantity' => $item['quantity'], + 'item_total' => $itemTotal, + ]; + $total += $itemTotal; + } + } + + return view('cart.index', compact('cartItems', 'total')); + } + + /** + * Add item to cart + */ + public function add(Request $request, $wineId) + { + $wine = Wine::findOrFail($wineId); + + $quantity = $request->input('quantity', 1); + + // Check stock availability + if ($wine->bottles_in_stock < $quantity) { + return redirect()->back()->with('error', 'Nedostatočné množstvo na sklade.'); + } + + $cart = $this->getCart(); + + if (isset($cart[$wineId])) { + $cart[$wineId]['quantity'] += $quantity; + } else { + $cart[$wineId] = [ + 'quantity' => $quantity, + 'price' => $wine->price_per_bottle, + ]; + } + + Session::put('cart', $cart); + + return redirect()->back()->with('success', 'Víno pridané do košíka.'); + } + + /** + * Update cart item quantity + */ + public function update(Request $request, $wineId) + { + $quantity = $request->input('quantity', 1); + + if ($quantity < 1) { + return $this->remove($wineId); + } + + $wine = Wine::findOrFail($wineId); + + // Check stock availability + if ($wine->bottles_in_stock < $quantity) { + return redirect()->back()->with('error', 'Nedostatočné množstvo na sklade.'); + } + + $cart = $this->getCart(); + + if (isset($cart[$wineId])) { + $cart[$wineId]['quantity'] = $quantity; + Session::put('cart', $cart); + } + + return redirect()->back()->with('success', 'Košík aktualizovaný.'); + } + + /** + * Remove item from cart + */ + public function remove($wineId) + { + $cart = $this->getCart(); + + if (isset($cart[$wineId])) { + unset($cart[$wineId]); + Session::put('cart', $cart); + } + + return redirect()->back()->with('success', 'Položka odstránená z košíka.'); + } + + /** + * Clear entire cart + */ + public function clear() + { + Session::forget('cart'); + return redirect()->route('cart.index')->with('success', 'Košík vyprázdnený.'); + } + + /** + * Get cart from session + */ + private function getCart() + { + return Session::get('cart', []); + } + + /** + * Get cart item count + */ + public function count() + { + $cart = $this->getCart(); + $count = 0; + + foreach ($cart as $item) { + $count += $item['quantity']; + } + + return response()->json(['count' => $count]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Controller.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Controller.php new file mode 100644 index 0000000..8677cd5 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Controller.php @@ -0,0 +1,8 @@ +file($path); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Employee/TaskController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Employee/TaskController.php new file mode 100644 index 0000000..9136315 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/Employee/TaskController.php @@ -0,0 +1,96 @@ +whereNull('execution_date') + ->orderBy('planned_date', 'asc') + ->get(); + + // Load the parent Treatment records with vineyard row data + foreach ($treatments as $task) { + if ($task->taskable) { + $task->treatment = Treatment::with(['vineyardRow.varietyVariation.grapeVariety']) + ->find($task->taskable->treatment_id); + } + } + + // Get planned harvests + $harvests = PlannedTask::where('taskable_type', 'App\Models\Harvest') + ->with(['taskable', 'taskable.vineyardRow', 'taskable.vineyardRow.varietyVariation', 'taskable.vineyardRow.varietyVariation.grapeVariety']) + ->whereNull('execution_date') + ->orderBy('planned_date', 'asc') + ->get(); + + return view('employee.tasks.index', compact('treatments', 'harvests')); + } + + /** + * Mark treatment as done. + */ + public function completeTreatment(PlannedTask $task) + { + if (!in_array($task->taskable_type, [ + 'App\Models\Watering', + 'App\Models\Fertilization', + 'App\Models\Spraying', + 'App\Models\Pruning', + ])) { + return back()->with('error', 'Invalid task type.'); + } + + $task->update(['execution_date' => now()]); + + return back()->with('success', 'Treatment marked as done.'); + } + + /** + * Mark harvest as complete. + */ + public function completeHarvest(Request $request, PlannedTask $task) + { + if ($task->taskable_type !== 'App\Models\Harvest') { + return back()->with('error', 'Invalid task type.'); + } + + // Validate harvest completion data + $validated = $request->validate([ + 'sugar' => 'required|numeric|min:0', + 'weight' => 'required|numeric|min:0', + 'user_id' => 'required|exists:users,id', + 'quality' => 'required|in:excellent,good,fair,poor', + ]); + + // Update the harvest record with additional data + $task->taskable->update([ + 'sugar_content' => $validated['sugar'], + 'weight' => $validated['weight'], + 'user_id' => $validated['user_id'], + 'quality' => $validated['quality'], + ]); + + // Mark task as executed + $task->update(['execution_date' => now()]); + + return back()->with('success', 'Harvest completed successfully with all details.'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/EventController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/EventController.php new file mode 100644 index 0000000..ccee985 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/EventController.php @@ -0,0 +1,134 @@ +where('event_date', '>=', now()); + + // Search functionality + if ($request->filled('search')) { + $search = $request->search; + $query->where(function ($q) use ($search) { + $q->where('name', 'like', "%{$search}%") + ->orWhere('description', 'like', "%{$search}%"); + }); + } + + // Filter by type + if ($request->filled('type') && $request->type !== 'all') { + $query->where('type', $request->type); + } + + $events = $query->orderBy('event_date', 'asc')->paginate(12); + + return view('events.index', compact('events')); + } + + /** + * Display the specified event. + */ + public function show(Event $event) + { + $event->load('reservations'); + return view('events.show', compact('event')); + } + + /** + * Make a reservation for an event. + */ + public function reserve(Request $request, Event $event) + { + // Check if user is authenticated + if (!auth()->check()) { + return redirect()->route('login') + ->with('error', 'Please login to make a reservation.'); + } + + // Check if event is upcoming + if ($event->status !== 'upcoming') { + return back()->with('error', 'This event is not available for reservation.'); + } + + // Check if event date has passed + if ($event->event_date < now()->toDateString()) { + return back()->with('error', 'This event has already passed.'); + } + + // Validate number of guests + $validated = $request->validate([ + 'number_of_guests' => ['required', 'integer', 'min:1'], + ]); + + $numberOfGuests = $validated['number_of_guests']; + + // Check if user already has a reservation + $existingReservation = $event->reservations() + ->where('user_id', auth()->id()) + ->wherePivot('status', 'confirmed') + ->first(); + + if ($existingReservation) { + return back()->with('error', 'You already have a reservation for this event.'); + } + + // Check if enough spots available + if ($event->availableSpots() < $numberOfGuests) { + return back()->with('error', 'Not enough available spots for ' . $numberOfGuests . ' guests.'); + } + + // Create reservation + $event->reservations()->attach(auth()->id(), [ + 'number_of_guests' => $numberOfGuests, + 'status' => 'confirmed', + ]); + + return back()->with('success', 'Reservation confirmed! We look forward to seeing you.'); + } + + /** + * Cancel a reservation. + */ + public function cancelReservation(Event $event) + { + $reservation = $event->reservations() + ->where('user_id', auth()->id()) + ->wherePivot('status', 'confirmed') + ->first(); + + if (!$reservation) { + return back()->with('error', 'No active reservation found.'); + } + + // Update reservation status + $event->reservations()->updateExistingPivot(auth()->id(), [ + 'status' => 'cancelled', + ]); + + return back()->with('success', 'Reservation cancelled successfully.'); + } + + /** + * Display user's reservations. + */ + public function myReservations() + { + $reservations = EventReservation::with('event') + ->where('user_id', auth()->id()) + ->where('status', 'confirmed') + ->orderBy('created_at', 'desc') + ->paginate(10); + + return view('events.my-reservations', compact('reservations')); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/FertilizationController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/FertilizationController.php new file mode 100644 index 0000000..d5298c2 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/FertilizationController.php @@ -0,0 +1,66 @@ +paginate(15); + + return view('grape-varieties.index', compact('varieties')); + } + + /** + * Show the form for creating a new grape variety. + */ + public function create() + { + return view('grape-varieties.create'); + } + + /** + * Store a newly created grape variety in storage. + */ + public function store(Request $request) + { + $validated = $request->validate([ + 'variety_name' => 'required|string|max:255', + 'description' => 'nullable|string', + 'origin' => 'nullable|string|max:255', + 'wine_type' => 'nullable|in:red,white,rose', + 'characteristics' => 'nullable|string', + 'image_url' => 'nullable|url', + ]); + + $variety = GrapeVariety::create($validated); + + return redirect()->route('grape-varieties.show', $variety) + ->with('success', 'Grape variety created successfully.'); + } + + /** + * Display the specified grape variety. + */ + public function show(GrapeVariety $grapeVariety) + { + $grapeVariety->load('variations', 'wines'); + + return view('grape-varieties.show', compact('grapeVariety')); + } + + /** + * Show the form for editing the specified grape variety. + */ + public function edit(GrapeVariety $grapeVariety) + { + return view('grape-varieties.edit', compact('grapeVariety')); + } + + /** + * Update the specified grape variety in storage. + */ + public function update(Request $request, GrapeVariety $grapeVariety) + { + $validated = $request->validate([ + 'variety_name' => 'required|string|max:255', + 'description' => 'nullable|string', + 'origin' => 'nullable|string|max:255', + 'wine_type' => 'nullable|in:red,white,rose', + 'characteristics' => 'nullable|string', + 'image_url' => 'nullable|url', + ]); + + $grapeVariety->update($validated); + + return redirect()->route('grape-varieties.show', $grapeVariety) + ->with('success', 'Grape variety updated successfully.'); + } + + /** + * Remove the specified grape variety from storage. + */ + public function destroy(GrapeVariety $grapeVariety) + { + $grapeVariety->delete(); + + return redirect()->route('grape-varieties.index') + ->with('success', 'Grape variety deleted successfully.'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/HarvestController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/HarvestController.php new file mode 100644 index 0000000..5ffd691 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/HarvestController.php @@ -0,0 +1,251 @@ +orderBy('date', 'desc') + ->paginate(15); + + return view('harvests.index', compact('harvests')); + } + + /** + * Show the form for creating a new harvest. + */ + public function create() + { + $vineyardRows = VineyardRow::with('varietyVariation.grapeVariety')->get(); + $varietyVariations = VarietyVariation::with('grapeVariety')->get(); + + return view('harvests.create', compact('vineyardRows', 'varietyVariations')); + } + + /** + * Store a newly created harvest in storage. + */ + public function store(Request $request) + { + $validated = $request->validate([ + 'vineyard_row_id' => 'required|exists:vineyard_rows,id', + 'variety_variation_id' => 'required|exists:variety_variations,id', + 'weight' => 'required|numeric|min:0', + 'sugar_content' => 'nullable|numeric|min:0|max:50', + 'date' => 'required|date', + 'quality' => 'nullable|in:excellent,good,fair,poor', + 'grape_condition' => 'nullable|string|max:255', + 'notes' => 'nullable|string', + 'weather_conditions' => 'nullable|string', + 'harvest_time' => 'nullable|date_format:H:i', + ]); + + $validated['user_id'] = Auth::id(); + + $harvest = Harvest::create($validated); + + return redirect()->route('harvests.show', $harvest) + ->with('success', 'Harvest recorded successfully.'); + } + + /** + * Display the specified harvest. + */ + public function show(Harvest $harvest) + { + $harvest->load('vineyardRow.varietyVariation.grapeVariety', 'varietyVariation.grapeVariety', 'user', 'wines', 'plannedTask'); + + return view('harvests.show', compact('harvest')); + } + + /** + * Show the form for editing the specified harvest. + */ + public function edit(Harvest $harvest) + { + $vineyardRows = VineyardRow::with('varietyVariation.grapeVariety')->get(); + $varietyVariations = VarietyVariation::with('grapeVariety')->get(); + + return view('harvests.edit', compact('harvest', 'vineyardRows', 'varietyVariations')); + } + + /** + * Update the specified harvest in storage. + */ + public function update(Request $request, Harvest $harvest) + { + $validated = $request->validate([ + 'vineyard_row_id' => 'required|exists:vineyard_rows,id', + 'variety_variation_id' => 'required|exists:variety_variations,id', + 'weight' => 'required|numeric|min:0', + 'sugar_content' => 'nullable|numeric|min:0|max:50', + 'date' => 'required|date', + 'quality' => 'nullable|in:excellent,good,fair,poor', + 'grape_condition' => 'nullable|string|max:255', + 'notes' => 'nullable|string', + 'weather_conditions' => 'nullable|string', + 'harvest_time' => 'nullable|date_format:H:i', + ]); + + $harvest->update($validated); + + return redirect()->route('harvests.show', $harvest) + ->with('success', 'Harvest updated successfully.'); + } + + /** + * Remove the specified harvest from storage. + */ + public function destroy(Harvest $harvest) + { + // Check if there are wines in the cellar made from this harvest + if ($harvest->hasWinesInCellar()) { + return redirect()->route('winemaker.harvests.index') + ->with('error', 'Cannot delete harvest: There are still wines in the cellar made from this harvest. Wait until all wines are sold out.'); + } + + $harvest->delete(); + + return redirect()->route('winemaker.harvests.index') + ->with('success', 'Harvest record deleted successfully.'); + } + + /** + * Display harvests for winemaker (with wine production status). + * Only shows completed harvests (with actual harvest data). + */ + public function winemakerIndex() + { + $harvests = Harvest::with(['vineyardRow', 'varietyVariation.grapeVariety', 'user', 'wines', 'plannedTask']) + ->where('weight', '>', 0) // Only show harvests with actual weight (completed harvests) + ->where(function ($query) { + $query->whereHas('plannedTask', function ($sub) { + $sub->whereNotNull('execution_date'); + })->orWhereDoesntHave('plannedTask'); + }) + ->orderByRaw( + 'COALESCE((select execution_date from planned_tasks where planned_tasks.taskable_type = ? and planned_tasks.taskable_id = harvests.id limit 1), harvests.date) desc', + [Harvest::class] + ) + ->paginate(15); + + return view('winemaker.harvests.index', compact('harvests')); + } + + /** + * Show the form for bottling wine from a harvest. + */ + public function bottleForm($id) + { + $harvest = Harvest::with(['vineyardRow', 'varietyVariation.grapeVariety', 'user', 'plannedTask']) + ->findOrFail($id); + + return view('winemaker.harvests.bottle', compact('harvest')); + } + + /** + * Store a new wine from harvest (bottling process). + */ + public function bottleStore(Request $request) + { + $validated = $request->validate([ + 'harvest_id' => 'required|exists:harvests,id', + 'weight_to_use' => 'required|numeric|min:0.01', + 'wine_name' => 'required|string|max:255', + 'vintage' => 'required|integer|min:1900|max:' . (date('Y') + 1), + 'wine_type' => 'required|in:red,white,rose', + 'sweetness' => 'required|in:dry,semi_dry,semi_sweet,sweet', + 'alcohol_percentage' => 'required|numeric|min:0|max:20', + 'bottles_produced' => 'required|integer|min:1', + 'bottle_volume' => 'nullable|numeric|min:0.1|max:10', + 'production_date' => 'required|date', + 'bottling_date' => 'nullable|date', + 'status' => 'required|in:in_production,aging,ready,sold_out', + 'price_per_bottle' => 'nullable|numeric|min:0', + 'description' => 'nullable|string', + 'image' => 'nullable|image|mimes:jpeg,jpg,png,webp|max:2048', + ]); + + try { + DB::beginTransaction(); + + // Get the harvest + $harvest = Harvest::with('varietyVariation.grapeVariety')->findOrFail($validated['harvest_id']); + + // Validate weight to use doesn't exceed available weight + if ($validated['weight_to_use'] > $harvest->remaining_weight) { + return back() + ->withInput() + ->with('error', 'Cannot use ' . $validated['weight_to_use'] . ' kg. Only ' . number_format($harvest->remaining_weight, 2) . ' kg available.'); + } + + // Get or find the grape variety + $grapeVariety = $harvest->varietyVariation->grapeVariety; + + // Handle image upload + $imagePath = null; + if ($request->hasFile('image')) { + $imagePath = $request->file('image')->store('wines', 'public'); + + } + + // Create the wine + $wine = Wine::create([ + 'wine_name' => $validated['wine_name'], + 'vintage' => $validated['vintage'], + 'grape_variety_id' => $grapeVariety->id, + 'wine_type' => $validated['wine_type'], + 'sweetness' => $validated['sweetness'], + 'alcohol_percentage' => $validated['alcohol_percentage'], + 'bottles_produced' => $validated['bottles_produced'], + 'bottles_in_stock' => $validated['bottles_produced'], // Initially all bottles are in stock + 'bottle_volume' => $validated['bottle_volume'] ?? 0.75, + 'production_date' => $validated['production_date'], + 'bottling_date' => $validated['bottling_date'], + 'status' => $validated['status'], + 'price_per_bottle' => $validated['price_per_bottle'], + 'description' => $validated['description'], + 'image_url' => $imagePath, + ]); + + // Create wine production record (link harvest to wine with specified weight) + WineProduction::create([ + 'wine_id' => $wine->id, + 'harvest_id' => $harvest->id, + 'consumed_weight' => $validated['weight_to_use'], // Use specified weight + 'blend_percentage' => 100.00, // 100% from this harvest + ]); + + DB::commit(); + + $message = 'Wine bottled successfully from harvest #' . $harvest->id . ' using ' . number_format($validated['weight_to_use'], 2) . ' kg'; + if ($harvest->remaining_weight - $validated['weight_to_use'] > 0.01) { + $message .= '. Remaining: ' . number_format($harvest->remaining_weight - $validated['weight_to_use'], 2) . ' kg'; + } + + return redirect()->route('winemaker.cellar.index') + ->with('success', $message); + + } catch (\Exception $e) { + DB::rollBack(); + return back() + ->withInput() + ->with('error', 'Failed to bottle wine: ' . $e->getMessage()); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/PlannedTaskController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/PlannedTaskController.php new file mode 100644 index 0000000..3450f43 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/PlannedTaskController.php @@ -0,0 +1,269 @@ +query('date')) { + return redirect()->route('vineyard.map') + ->with('error', 'Please choose a date on the vineyard map before planning watering.'); + } + + return $this->renderForm('watering', 'planned-tasks.watering', $request); + } + + public function showPruningForm(Request $request) + { + if (! $request->query('date')) { + return redirect()->route('vineyard.map') + ->with('error', 'Please choose a date on the vineyard map before planning pruning.'); + } + + return $this->renderForm('pruning', 'planned-tasks.pruning', $request); + } + + public function showFertilisationForm(Request $request) + { + if (! $request->query('date')) { + return redirect()->route('vineyard.map') + ->with('error', 'Please choose a date on the vineyard map before planning fertilisation.'); + } + + return $this->renderForm('fertilization', 'planned-tasks.fertilisation', $request, 'fertilisation'); + } + + public function showPesticideForm(Request $request) + { + if (! $request->query('date')) { + return redirect()->route('vineyard.map') + ->with('error', 'Please choose a date on the vineyard map before planning pesticide treatment.'); + } + + return $this->renderForm('spraying', 'planned-tasks.pesticide', $request, 'pesticide'); + } + + public function showHarvestForm(Request $request) + { + if (! $request->query('date')) { + return redirect()->route('vineyard.map') + ->with('error', 'Please choose a date on the vineyard map before planning harvest.'); + } + + return $this->renderForm('harvest', 'planned-tasks.harvest', $request); + } + + public function storeBulk(StoreBulkPlannedTasksRequest $request) + { + $result = $this->bulkService->handle($request->validated()); + + $status = $result['success'] ? 201 : 422; + + return response()->json($result, $status); + } + + protected function renderForm(string $actionKey, string $view, Request $request, ?string $displayAction = null) + { + $selectedRowIds = $this->parseRowIds($request->input('rows', [])); + + $plannedDate = $request->query('date'); + + $rows = VineyardRow::with('varietyVariation.grapeVariety') + ->when($selectedRowIds->isNotEmpty(), fn ($query) => $query->whereIn('id', $selectedRowIds)) + ->orderBy('id') + ->get(); + + return view($view, [ + 'action' => $displayAction ?? $actionKey, + 'actionKey' => $actionKey, + 'rows' => $rows, + 'selectedRowIds' => $selectedRowIds, + 'plannedDate' => $plannedDate, + ]); + } + + protected function parseRowIds(array|string $value): Collection + { + if (is_string($value)) { + $value = explode(',', $value); + } + + return collect($value) + ->map(fn ($id) => (int) $id) + ->filter(fn ($id) => $id > 0) + ->values(); + } + + public function edit(PlannedTask $task) + { + $task->load('taskable'); + + // Find all tasks in the same group (same type, date, note) + $groupTasks = PlannedTask::with('taskable') + ->where('type', $task->type) + ->where('planned_date', $task->planned_date) + ->where(function($query) use ($task) { + if ($task->note) { + $query->where('note', $task->note); + } else { + $query->whereNull('note'); + } + }) + ->whereNull('execution_date') + ->get(); + + // Build task_rows array with task IDs and vineyard row info + $taskRows = $groupTasks->map(function($t) { + $row = null; + + if (!$t->taskable) { + return null; + } + + // Check taskable type to determine how to get vineyard row + $taskableType = $t->taskable_type; + + // For Harvest, vineyard_row_id is directly on the taskable + if (str_contains($taskableType, 'Harvest') && $t->taskable->vineyard_row_id) { + $row = VineyardRow::with('varietyVariation.grapeVariety') + ->find($t->taskable->vineyard_row_id); + } + // For treatment types (Watering, Spraying, Fertilization, Pruning), get it through parent Treatment + elseif ($t->taskable->treatment_id) { + $treatment = Treatment::with('vineyardRow.varietyVariation.grapeVariety') + ->find($t->taskable->treatment_id); + if ($treatment && $treatment->vineyardRow) { + $row = $treatment->vineyardRow; + } + } + + return $row ? [ + 'task_id' => $t->planned_task_id, + 'row_id' => $row->id, + 'row' => $row, + ] : null; + })->filter()->sortBy('row_id')->values(); + + // Get the vineyard row for the main task (for display) + $vineyardRow = null; + if ($task->taskable) { + $taskableType = $task->taskable_type; + + // For Harvest + if (str_contains($taskableType, 'Harvest') && $task->taskable->vineyard_row_id) { + $vineyardRow = VineyardRow::with('varietyVariation.grapeVariety') + ->find($task->taskable->vineyard_row_id); + } + // For treatment types + elseif ($task->taskable->treatment_id) { + $treatment = Treatment::with('vineyardRow.varietyVariation.grapeVariety') + ->find($task->taskable->treatment_id); + if ($treatment) { + $vineyardRow = $treatment->vineyardRow; + } + } + } + + return view('planned-tasks.edit', [ + 'task' => $task, + 'vineyardRow' => $vineyardRow, + 'taskRows' => $taskRows, + ]); + } + + public function update(UpdatePlannedTaskRequest $request, PlannedTask $task) + { + $validated = $request->validated(); + + // Get selected task IDs (if provided, otherwise just update the single task) + $taskIds = $request->input('task_ids', [$task->planned_task_id]); + + // Get all selected tasks + $tasksToUpdate = PlannedTask::with('taskable') + ->whereIn('planned_task_id', $taskIds) + ->whereNull('execution_date') + ->get(); + + foreach ($tasksToUpdate as $taskToUpdate) { + // Update PlannedTask + $updateData = [ + 'note' => $validated['note'] ?? null, + ]; + + // For spraying and harvest tasks, don't update the date (it's readonly) + if (!str_contains($taskToUpdate->taskable_type, 'Spraying') && !str_contains($taskToUpdate->taskable_type, 'Harvest') && isset($validated['planned_date'])) { + $updateData['planned_date'] = $validated['planned_date']; + } + + $taskToUpdate->update($updateData); + + // Update taskable (Treatment/Harvest) specific fields + if ($taskToUpdate->taskable) { + $taskableData = []; + $taskableType = $taskToUpdate->taskable_type; + + if (str_contains($taskableType, 'Watering')) { + $taskableData = [ + 'time_interval' => $validated['time_interval'] ?? null, + 'amount' => $validated['amount'], + ]; + } elseif (str_contains($taskableType, 'Fertilization')) { + $taskableData = [ + 'substance' => $validated['substance'], + 'concentration' => $validated['concentration'] ?? null, + ]; + } elseif (str_contains($taskableType, 'Spraying')) { + $taskableData = [ + 'pesticide' => $validated['pesticide'], + 'concentration' => $validated['concentration'] ?? null, + ]; + } elseif (str_contains($taskableType, 'Pruning')) { + $taskableData = [ + 'method' => $validated['method'], + 'percentage_removed' => $validated['percentage_removed'] ?? null, + ]; + } + + if (!empty($taskableData)) { + $taskToUpdate->taskable->update($taskableData); + } + } + } + + $count = $tasksToUpdate->count(); + $message = $count === 1 + ? 'Planned task updated successfully.' + : "{$count} planned tasks updated successfully."; + + return redirect()->route('winemaker.planned-tasks') + ->with('success', $message); + } + + public function destroy(PlannedTask $task) + { + // Delete the taskable first (Treatment/Harvest) + if ($task->taskable) { + $task->taskable->delete(); + } + + // Delete the planned task + $task->delete(); + + return redirect()->route('winemaker.planned-tasks') + ->with('success', 'Planned task deleted successfully.'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/PlantController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/PlantController.php new file mode 100644 index 0000000..73d757a --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/PlantController.php @@ -0,0 +1,129 @@ +input('rows', []); + + if (is_string($rowsInput)) { + $rowsInput = array_filter(array_map('trim', explode(',', $rowsInput))); + } + + $selectedRowIds = collect($rowsInput) + ->map(fn ($value) => (int) $value) + ->filter() + ->values(); + + $rows = VineyardRow::with('varietyVariation.grapeVariety') + ->when($selectedRowIds->isNotEmpty(), fn ($query) => $query->whereIn('id', $selectedRowIds)) + ->orderBy('id') + ->get(); + + $variations = VarietyVariation::with('grapeVariety') + ->orderBy('grape_variety_id') + ->get() + ->map(fn (VarietyVariation $variation) => [ + 'id' => $variation->getKey(), + 'label' => sprintf('%s — %s', $variation->grapeVariety->variety_name, ucfirst($variation->color)), + ]); + + return view('vineyard.plants.add', [ + 'rows' => $rows, + 'variationOptions' => $variations, + 'selectedRowIds' => $selectedRowIds, + ]); + } + + /** + * Assign a variation to selected rows, creating plants in bulk. + */ + public function assignToRows(AssignPlantsRequest $request) + { + $rows = VineyardRow::whereIn('id', $request->validated('rows'))->get(); + + if ($rows->isEmpty()) { + return response()->json([ + 'success' => false, + 'message' => 'No matching rows were found for assignment.', + ], 422); + } + + $variationId = $this->resolveVariationId($request); + + DB::transaction(function () use ($rows, $variationId) { + foreach ($rows as $row) { + $row->update([ + 'variety_variation_id' => $variationId, + 'planting_year' => now()->year, + 'status' => 'active', + ]); + } + }); + + return response()->json([ + 'success' => true, + 'updated_rows' => $rows->pluck('id'), + ]); + } + + protected function resolveVariationId(AssignPlantsRequest $request): int + { + $variationId = $request->validated('variety_variation_id'); + + if ($variationId) { + return (int) $variationId; + } + + $payload = $request->validated('create_variation'); + + if (! $payload) { + throw new RuntimeException('A variety variation must be provided or created for assignment.'); + } + + $variety = null; + + if (! empty($payload['grape_variety_id'])) { + $variety = GrapeVariety::find($payload['grape_variety_id']); + } + + if (! $variety && ! empty($payload['grape_variety_name'])) { + $variety = GrapeVariety::firstOrCreate([ + 'variety_name' => $payload['grape_variety_name'], + ]); + } + + if (! $variety) { + throw new RuntimeException('Unable to resolve grape variety for the new variation.'); + } + + $variation = VarietyVariation::firstOrCreate( + [ + 'grape_variety_id' => $variety->getKey(), + 'color' => $payload['color'], + ], + [ + 'description' => $payload['description'] ?? null, + 'typical_sugar_content' => $payload['typical_sugar_content'] ?? null, + 'typical_alcohol' => $payload['typical_alcohol'] ?? null, + 'ripening_period' => $payload['ripening_period'] ?? null, + 'status' => 'active', + ] + ); + + return $variation->getKey(); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/PruningController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/PruningController.php new file mode 100644 index 0000000..96c7186 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/PruningController.php @@ -0,0 +1,67 @@ +latest()->paginate(20); + return response()->json($purchases); + } + + /** + * Store a new purchase with items. + * + * Expected payload: + * { + * user_id: int, + * status: string, + * items: [ { wine_id: int, quantity: int, unit_price?: decimal }, ... ] + * } + */ + public function store(Request $request) + { + $data = $request->validate([ + 'user_id' => 'required|integer|exists:users,id', + 'status' => 'nullable|string', + 'items' => 'required|array|min:1', + 'items.*.wine_id' => 'required|integer|exists:wines,wine_id', + 'items.*.quantity' => 'required|integer|min:1', + 'items.*.unit_price' => 'nullable|numeric|min:0', + ]); + + try { + $purchase = Purchase::createWithItems([ + 'user_id' => $data['user_id'], + 'status' => $data['status'] ?? 'pending', + ], $data['items']); + + return response()->json(['success' => true, 'purchase' => $purchase->load(['items.wine','user'])], 201); + } catch (\Exception $e) { + return response()->json(['success' => false, 'message' => $e->getMessage()], 422); + } + } + + /** + * Process checkout from shopping cart + */ + public function checkout(Request $request) + { + $validated = $request->validate([ + 'full_name' => 'required|string|max:255', + 'phone' => ['required', 'string', 'max:20', 'regex:/^[\+]?[(]?[0-9]{1,4}[)]?[-\s\.]?[(]?[0-9]{1,4}[)]?[-\s\.]?[0-9]{1,9}$/'], + 'country' => 'required|string|max:100', + 'street' => 'required|string|max:255', + 'city' => 'required|string|max:255', + 'postal_code' => ['required', 'string', 'max:20', 'regex:/^[0-9]{3}\s?[0-9]{2}$/'], + ], [ + 'phone.regex' => 'The phone number format is invalid. Please use format: +420 123 456 789', + 'postal_code.regex' => 'The postal code format is invalid. Please use format: 123 45', + ]); + + $cart = Session::get('cart', []); + + if (empty($cart)) { + return redirect()->route('cart.index')->with('error', 'Košík je prázdny.'); + } + + // Prepare items for purchase creation + $items = []; + foreach ($cart as $wineId => $cartItem) { + $wine = Wine::find($wineId); + if (!$wine) { + continue; + } + + // Check stock + if ($wine->bottles_in_stock < $cartItem['quantity']) { + return redirect()->route('cart.index') + ->with('error', "Nedostatočné množstvo na sklade pre {$wine->wine_name}."); + } + + $items[] = [ + 'wine_id' => $wineId, + 'quantity' => $cartItem['quantity'], + 'unit_price' => $wine->price_per_bottle, + ]; + } + + try { + // Create purchase with invoice details in note + $invoiceNote = "Name: {$validated['full_name']}\n" . + "Phone: {$validated['phone']}\n" . + "Street: {$validated['street']}\n" . + "City: {$validated['city']}\n" . + "Postal Code: {$validated['postal_code']}\n" . + "Country: {$validated['country']}"; + + $purchase = Purchase::createWithItems([ + 'user_id' => Auth::id(), + 'status' => 'completed', + 'note' => $invoiceNote, + 'purchased_at' => now(), + ], $items); + + // Clear cart after successful purchase + Session::forget('cart'); + + return redirect()->route('purchases.my') + ->with('success', 'Objednávka bola úspešne vytvorená!'); + } catch (\Exception $e) { + return redirect()->route('cart.index') + ->with('error', 'Chyba pri vytváraní objednávky: ' . $e->getMessage()); + } + } + + /** + * Display customer's purchase history + */ + public function myPurchases() + { + $purchases = Purchase::with(['items.wine.grapeVariety']) + ->where('user_id', Auth::id()) + ->orderBy('purchased_at', 'desc') + ->orderBy('created_at', 'desc') + ->get(); + + return view('purchases.my', compact('purchases')); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/TreatmentController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/TreatmentController.php new file mode 100644 index 0000000..b0fd47c --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/TreatmentController.php @@ -0,0 +1,66 @@ +paginate(15); + + return view('variety-variations.index', compact('variations')); + } + + /** + * Show the form for creating a new variety variation. + */ + public function create() + { + $grapeVarieties = GrapeVariety::all(); + + return view('variety-variations.create', compact('grapeVarieties')); + } + + /** + * Store a newly created variety variation in storage. + */ + public function store(Request $request) + { + $validated = $request->validate([ + 'grape_variety_id' => 'required|exists:grape_varieties,id', + 'color' => 'required|in:green,blue,yellow,red', + 'description' => 'nullable|string', + 'typical_sugar_content' => 'nullable|numeric|min:0|max:50', + 'typical_alcohol' => 'nullable|numeric|min:0|max:20', + 'ripening_period' => 'nullable|string|max:255', + 'status' => 'required|in:active,inactive', + ]); + + $variation = VarietyVariation::create($validated); + + return redirect()->route('variety-variations.show', $variation) + ->with('success', 'Variety variation created successfully.'); + } + + /** + * Display the specified variety variation. + */ + public function show(VarietyVariation $varietyVariation) + { + $varietyVariation->load('grapeVariety', 'vineyardRows', 'harvests'); + + return view('variety-variations.show', compact('varietyVariation')); + } + + /** + * Show the form for editing the specified variety variation. + */ + public function edit(VarietyVariation $varietyVariation) + { + $grapeVarieties = GrapeVariety::all(); + + return view('variety-variations.edit', compact('varietyVariation', 'grapeVarieties')); + } + + /** + * Update the specified variety variation in storage. + */ + public function update(Request $request, VarietyVariation $varietyVariation) + { + $validated = $request->validate([ + 'grape_variety_id' => 'required|exists:grape_varieties,id', + 'color' => 'required|in:green,blue,yellow,red', + 'description' => 'nullable|string', + 'typical_sugar_content' => 'nullable|numeric|min:0|max:50', + 'typical_alcohol' => 'nullable|numeric|min:0|max:20', + 'ripening_period' => 'nullable|string|max:255', + 'status' => 'required|in:active,inactive', + ]); + + $varietyVariation->update($validated); + + return redirect()->route('variety-variations.show', $varietyVariation) + ->with('success', 'Variety variation updated successfully.'); + } + + /** + * Remove the specified variety variation from storage. + */ + public function destroy(VarietyVariation $varietyVariation) + { + $varietyVariation->delete(); + + return redirect()->route('variety-variations.index') + ->with('success', 'Variety variation deleted successfully.'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/VineyardMapController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/VineyardMapController.php new file mode 100644 index 0000000..fd8f145 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/VineyardMapController.php @@ -0,0 +1,182 @@ + function ($query) { + $query->latest('created_at'); + }, + 'sprayings' => function ($query) { + $query->with('plannedTask')->orderByDesc('created_at'); + }, + 'harvests' => function ($query) { + $query->with('plannedTask')->orderByDesc('date'); + }, + ])->get(); + + $actionGroups = [ + 'Treatment' => [ + 'watering', + 'pruning', + 'fertilisation', + 'pesticide', + ], + 'Manage Crops' => [ + 'harvest', + 'add-plants', + 'discard-plants', + ], + ]; + + return view('vineyard.map.index', [ + 'rows' => $this->formatRows($rows), + 'actions' => array_merge(...array_values($actionGroups)), + 'actionGroups' => $actionGroups, + ]); + } + + /** + * Display the editable vineyard map. + */ + public function edit() + { + $rows = VineyardRow::with(['varietyVariation.grapeVariety'])->get(); + $variations = VarietyVariation::with('grapeVariety') + ->orderBy('grape_variety_id') + ->get() + ->map(function (VarietyVariation $variation) { + $grape = $variation->grapeVariety; + $label = $grape + ? sprintf('%s — %s', $grape->variety_name, ucfirst($variation->color)) + : ucfirst($variation->color); + + return [ + 'id' => $variation->getKey(), + 'label' => $label, + ]; + }); + + return view('vineyard.map.edit', [ + 'rows' => $this->formatRows($rows), + 'statuses' => ['active', 'inactive', 'replanting', 'discarded'], + 'variationOptions' => $variations, + ]); + } + + /** + * Transform rows into a structure suitable for the front-end map. + */ + protected function formatRows(Collection $rows): Collection + { + return $rows->map(function (VineyardRow $row) { + [$x, $y] = $this->parseLocation($row->location); + + $variation = $row->varietyVariation; + $grapeVariety = $variation?->grapeVariety; + + $lastTreatmentDate = optional($row->treatments->first())->created_at; + + $pesticideCompleted = $row->sprayings->map(function ($spraying) { + $executionDate = optional($spraying->plannedTask)->execution_date; + if ($executionDate) { + return Carbon::parse($executionDate)->toDateString(); + } + + return optional($spraying->created_at)?->toDateString(); + })->filter()->unique()->sort()->values()->all(); + + $pesticidePlanned = $row->sprayings->map(function ($spraying) { + $plannedDate = optional($spraying->plannedTask)->planned_date; + if ($plannedDate) { + return Carbon::parse($plannedDate)->toDateString(); + } + + return null; + })->filter()->unique()->sort()->values()->all(); + + $harvestCompleted = $row->harvests->map(function ($harvest) { + $executionDate = optional($harvest->plannedTask)->execution_date; + if ($executionDate) { + return Carbon::parse($executionDate)->toDateString(); + } + + $harvestDate = $harvest->date; + return $harvestDate ? Carbon::parse($harvestDate)->toDateString() : null; + })->filter()->unique()->sort()->values()->all(); + + $harvestPlanned = $row->harvests->map(function ($harvest) { + $plannedDate = optional($harvest->plannedTask)->planned_date; + if ($plannedDate) { + return Carbon::parse($plannedDate)->toDateString(); + } + + return null; + })->filter()->unique()->sort()->values()->all(); + + return [ + 'id' => $row->getKey(), + 'location' => [ + 'x' => $x, + 'y' => $y, + ], + 'dimensions' => [ + 'width' => 1, + 'height' => 1, + ], + 'vine_count' => $row->vine_count, + 'status' => $row->status, + 'notes' => $row->notes, + 'planting_year' => $row->planting_year, + 'variety' => $variation ? [ + 'id' => $variation->getKey(), + 'color' => $variation->color, + 'label' => $grapeVariety + ? sprintf('%s — %s', $grapeVariety->variety_name, ucfirst($variation->color)) + : ucfirst($variation->color), + ] : null, + 'last_treatment_at' => $lastTreatmentDate, + 'timeline' => [ + 'pesticide' => [ + 'completed' => $pesticideCompleted, + 'planned' => $pesticidePlanned, + ], + 'harvest' => [ + 'completed' => $harvestCompleted, + 'planned' => $harvestPlanned, + ], + ], + ]; + }); + } + + /** + * Parse the "x,y" string stored on vineyard rows. + */ + protected function parseLocation(?string $location): array + { + if (blank($location)) { + return [0, 0]; + } + + $parts = Str::of($location)->explode(',')->map(fn ($fragment) => (int) trim($fragment)); + + return [ + $parts->get(0, 0), + $parts->get(1, 0), + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/VineyardOverviewController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/VineyardOverviewController.php new file mode 100644 index 0000000..727602c --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/VineyardOverviewController.php @@ -0,0 +1,141 @@ +with(['varietyVariation.grapeVariety']) + ->withMax('treatments as last_treatment_at', 'created_at'); + + $query = $this->applyFilters($query, $request); + + $rows = $query + ->orderBy('id') + ->paginate(15) + ->withQueryString(); + + $rowIds = $rows->pluck('id'); + $upcomingCounts = $this->upcomingPlannedCounts($rowIds); + + $rows->transform(function (VineyardRow $row) use ($upcomingCounts) { + if ($row->last_treatment_at) { + $row->last_treatment_at = Carbon::parse($row->last_treatment_at); + } + $row->upcoming_planned_count = $upcomingCounts[$row->getKey()] ?? 0; + return $row; + }); + + $variationOptions = VarietyVariation::with('grapeVariety') + ->orderBy('grape_variety_id') + ->get() + ->map(fn (VarietyVariation $variation) => [ + 'id' => $variation->getKey(), + 'label' => sprintf( + '%s — %s', + $variation->grapeVariety->variety_name, + ucfirst($variation->color) + ), + ]); + + return view('vineyard.overview.index', [ + 'rows' => $rows, + 'variationOptions' => $variationOptions, + 'statusOptions' => ['active', 'inactive', 'replanting', 'discarded'], + 'filters' => Arr::only($request->all(), [ + 'status', + 'variety_variation_id', + 'planting_year_from', + 'planting_year_to', + 'vine_count_min', + 'vine_count_max', + ]), + ]); + } + + protected function applyFilters($query, Request $request) + { + if ($request->filled('status')) { + $query->where('status', $request->string('status')); + } + + if ($request->filled('variety_variation_id')) { + $query->where('variety_variation_id', $request->integer('variety_variation_id')); + } + + if ($request->filled('planting_year_from')) { + $query->where('planting_year', '>=', $request->integer('planting_year_from')); + } + + if ($request->filled('planting_year_to')) { + $query->where('planting_year', '<=', $request->integer('planting_year_to')); + } + + if ($request->filled('vine_count_min')) { + $query->where('vine_count', '>=', $request->integer('vine_count_min')); + } + + if ($request->filled('vine_count_max')) { + $query->where('vine_count', '<=', $request->integer('vine_count_max')); + } + + return $query; + } + + protected function upcomingPlannedCounts(Collection $rowIds): array + { + if ($rowIds->isEmpty()) { + return []; + } + + $today = Carbon::now()->toDateString(); + + $treatmentCounts = PlannedTask::query() + ->selectRaw('treatments.row_id as row_id, COUNT(*) as aggregate') + ->join('treatments', function ($join) { + $join->on('planned_tasks.taskable_id', '=', 'treatments.treatment_id') + ->where('planned_tasks.taskable_type', '=', Treatment::class); + }) + ->whereIn('treatments.row_id', $rowIds) + ->whereNull('planned_tasks.execution_date') + ->whereDate('planned_tasks.planned_date', '>=', $today) + ->groupBy('treatments.row_id') + ->pluck('aggregate', 'row_id'); + + $harvestCounts = PlannedTask::query() + ->selectRaw('harvests.vineyard_row_id as row_id, COUNT(*) as aggregate') + ->join('harvests', function ($join) { + $join->on('planned_tasks.taskable_id', '=', 'harvests.id') + ->where('planned_tasks.taskable_type', '=', Harvest::class); + }) + ->whereIn('harvests.vineyard_row_id', $rowIds) + ->whereNull('planned_tasks.execution_date') + ->whereDate('planned_tasks.planned_date', '>=', $today) + ->groupBy('harvests.vineyard_row_id') + ->pluck('aggregate', 'row_id'); + + $combined = []; + + foreach ($treatmentCounts as $rowId => $count) { + $combined[$rowId] = ($combined[$rowId] ?? 0) + $count; + } + + foreach ($harvestCounts as $rowId => $count) { + $combined[$rowId] = ($combined[$rowId] ?? 0) + $count; + } + + return $combined; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/VineyardRowController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/VineyardRowController.php new file mode 100644 index 0000000..1cee047 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/VineyardRowController.php @@ -0,0 +1,215 @@ +paginate(15); + + return view('vineyard-rows.index', compact('rows')); + } + + /** + * Show the form for creating a new vineyard row. + */ + public function create() + { + $varietyVariations = VarietyVariation::with('grapeVariety')->get(); + + return view('vineyard-rows.create', compact('varietyVariations')); + } + + /** + * Store a newly created vineyard row in storage. + */ + public function store(Request $request) + { + $validated = $request->validate([ + 'variety_variation_id' => 'nullable|integer|exists:variety_variations,id', + 'vine_count' => 'required|integer|min:1', + 'planting_year' => 'required|integer|min:1900|max:' . date('Y'), + 'area' => 'nullable|numeric|min:0', + 'location' => ['nullable', 'string', 'max:255', new LocationCoordinates()], + 'status' => 'required|in:active,inactive,replanting,discarded', + 'notes' => 'nullable|string', + ]); + + $row = VineyardRow::create($validated); + + return redirect()->route('vineyard-rows.show', $row) + ->with('success', 'Vineyard row created successfully.'); + } + + /** + * Display the specified vineyard row. + */ + public function show(VineyardRow $vineyardRow) + { + $vineyardRow->load('varietyVariation.grapeVariety', 'harvests'); + + return view('vineyard-rows.show', compact('vineyardRow')); + } + + /** + * Show the form for editing the specified vineyard row. + */ + public function edit(VineyardRow $vineyardRow) + { + $varietyVariations = VarietyVariation::with('grapeVariety')->get(); + + return view('vineyard-rows.edit', compact('vineyardRow', 'varietyVariations')); + } + + /** + * Update the specified vineyard row in storage. + */ + public function update(Request $request, VineyardRow $vineyardRow) + { + $validated = $request->validate([ + 'variety_variation_id' => 'nullable|integer|exists:variety_variations,id', + 'vine_count' => 'required|integer|min:1', + 'planting_year' => 'required|integer|min:1900|max:' . date('Y'), + 'area' => 'nullable|numeric|min:0', + 'location' => ['nullable', 'string', 'max:255', new LocationCoordinates()], + 'status' => 'required|in:active,inactive,replanting,discarded', + 'notes' => 'nullable|string', + ]); + + $vineyardRow->update($validated); + + return redirect()->route('vineyard-rows.show', $vineyardRow) + ->with('success', 'Vineyard row updated successfully.'); + } + + /** + * Remove the specified vineyard row from storage. + */ + public function destroy(Request $request, VineyardRow $vineyardRow) + { + $vineyardRow->delete(); + + if ($request->expectsJson()) { + return response()->json([ + 'success' => true, + 'deleted' => $vineyardRow->id, + ]); + } + + return redirect()->route('vineyard-rows.index') + ->with('success', 'Vineyard row deleted successfully.'); + } + + /** + * Bulk delete rows from the vineyard map. + */ + public function destroyMany(Request $request) + { + $validated = $request->validate([ + 'rows' => 'required|array|min:1', + 'rows.*' => 'required|exists:vineyard_rows,id', + ]); + + DB::transaction(function () use ($validated) { + VineyardRow::whereIn('id', $validated['rows'])->delete(); + }); + + return response()->json([ + 'success' => true, + 'deleted' => $validated['rows'], + ]); + } + + /** + * Bulk update vine counts for one or more rows. + */ + public function updateHeadCount(Request $request) + { + $validated = $request->validate([ + 'rows' => 'required|array|min:1', + 'rows.*.id' => 'required|exists:vineyard_rows,id', + 'rows.*.vine_count' => 'required|integer|min:0', + 'rows.*.location' => ['nullable', 'string', 'max:255', new LocationCoordinates()], + ]); + + DB::transaction(function () use ($validated) { + foreach ($validated['rows'] as $payload) { + $updates = ['vine_count' => $payload['vine_count']]; + + if (array_key_exists('location', $payload) && ! blank($payload['location'])) { + $updates['location'] = $payload['location']; + } + + VineyardRow::whereKey($payload['id'])->update($updates); + } + }); + + return response()->json([ + 'success' => true, + 'updated' => collect($validated['rows'])->pluck('id'), + ]); + } + + /** + * Add new rows to the vineyard map. + */ + public function addRows(Request $request) + { + $validated = $request->validate([ + 'rows' => 'required|array|min:1', + 'rows.*.location' => ['required', 'string', 'max:255', new LocationCoordinates()], + 'rows.*.vine_count' => 'nullable|integer|min:0', + ]); + + $created = DB::transaction(function () use ($validated) { + return collect($validated['rows'])->map(function ($payload) { + return VineyardRow::create([ + 'location' => $payload['location'], + 'vine_count' => $payload['vine_count'] ?? 0, + 'status' => 'inactive', + 'variety_variation_id' => null, + 'planting_year' => $payload['planting_year'] ?? now()->year, + ])->getKey(); + }); + }); + + return response()->json([ + 'success' => true, + 'created' => $created, + ], 201); + } + + /** + * Discard plants for provided rows. + */ + public function discard(Request $request) + { + $validated = $request->validate([ + 'rows' => 'required|array|min:1', + 'rows.*' => 'required|exists:vineyard_rows,id', + ]); + + DB::transaction(function () use ($validated) { + VineyardRow::whereIn('id', $validated['rows'])->update([ + // Mark as inactive and decouple from any assigned variation + 'status' => 'inactive', + 'variety_variation_id' => null, + ]); + }); + + return response()->json([ + 'success' => true, + 'discarded' => $validated['rows'], + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/WateringController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/WateringController.php new file mode 100644 index 0000000..90a5586 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/WateringController.php @@ -0,0 +1,66 @@ +orderBy('vintage', 'desc') + ->paginate(15); + + return view('wines.index', compact('wines')); + } + + /** + * Display wine catalog for e-shop (with search and filters) + */ + public function catalog(Request $request) + { + $query = Wine::with('grapeVariety') + ->where('status', 'ready') // Only show wines marked as available for sale + ->where('bottles_in_stock', '>', 0); // Only show wines in stock + + // Search by wine name + if ($request->filled('search')) { + $query->where('wine_name', 'like', '%' . $request->search . '%'); + } + + // Filter by grape variety + if ($request->filled('variety') && $request->variety !== 'all') { + $query->where('grape_variety_id', $request->variety); + } + + // Filter by vintage + if ($request->filled('vintage') && $request->vintage !== 'all') { + $query->where('vintage', $request->vintage); + } + + // Filter by wine type + if ($request->filled('wine_type') && $request->wine_type !== 'all') { + $query->where('wine_type', $request->wine_type); + } + + // Filter by sweetness + if ($request->filled('sweetness') && $request->sweetness !== 'all') { + $query->where('sweetness', $request->sweetness); + } + + $wines = $query->orderBy('vintage', 'desc')->paginate(12); + + // Get all grape varieties for filter dropdown (distinct by name to avoid duplicates) + $grapeVarieties = GrapeVariety::all() + ->unique('variety_name') + ->sortBy('variety_name') + ->values(); + + // Get all unique vintages for filter dropdown + $vintages = Wine::where('status', 'ready') + ->where('bottles_in_stock', '>', 0) + ->distinct() + ->pluck('vintage') + ->sort() + ->values(); + + // Get all unique wine types for filter dropdown + $wineTypes = Wine::where('status', 'ready') + ->where('bottles_in_stock', '>', 0) + ->whereNotNull('wine_type') + ->distinct() + ->pluck('wine_type') + ->values(); + + // Get all unique sweetness levels for filter dropdown + $sweetnessLevels = Wine::where('status', 'ready') + ->where('bottles_in_stock', '>', 0) + ->whereNotNull('sweetness') + ->distinct() + ->pluck('sweetness') + ->values(); + + return view('catalog.index', compact('wines', 'grapeVarieties', 'vintages', 'wineTypes', 'sweetnessLevels')); + } + + /** + * Show the form for creating a new wine. + */ + public function create() + { + $grapeVarieties = GrapeVariety::all(); + + return view('wines.create', compact('grapeVarieties')); + } + + /** + * Store a newly created wine in storage. + */ + public function store(StoreWineRequest $request) + { + $validated = $request->validated(); + + $wine = Wine::create($validated); + + return redirect()->route('wines.show', $wine) + ->with('success', 'Wine created successfully.'); + } + + /** + * Display the specified wine. + */ + public function show($id) + { + $wine = Wine::with('grapeVariety', 'harvests.plannedTask')->findOrFail($id); + + // Check if this is a catalog request (from the route) + if (request()->route()->getName() === 'catalog.show') { + return view('catalog.show', compact('wine')); + } + + return view('wines.show', compact('wine')); + } + + /** + * Show the form for editing the specified wine. + */ + public function edit(Wine $wine) + { + $grapeVarieties = GrapeVariety::all(); + + return view('wines.edit', compact('wine', 'grapeVarieties')); + } + + /** + * Update the specified wine in storage. + */ + public function update(UpdateWineRequest $request, Wine $wine) + { + $validated = $request->validated(); + + // Handle image upload + if ($request->hasFile('image')) { + // Delete old image if exists + if ($wine->image_url) { + \Storage::disk('public')->delete($wine->image_url); + } + $validated['image_url'] = $request->file('image')->store('wines', 'public'); + } + + // Remove the 'image' key from validated data (we only want 'image_url') + unset($validated['image']); + + $wine->update($validated); + + return redirect()->route('wines.show', $wine) + ->with('success', 'Wine updated successfully.'); + } + + /** + * Remove the specified wine from storage. + */ + public function destroy(Wine $wine) + { + $wineName = $wine->wine_name; + $wine->delete(); + + return redirect()->route('winemaker.cellar.index') + ->with('success', "Wine '{$wineName}' has been permanently removed from the cellar."); + } + + /** + * Display cellar wine inventory (for winemaker) + */ + public function cellarIndex() + { + $wines = Wine::with('grapeVariety') + ->orderBy('vintage', 'desc') + ->orderBy('wine_name') + ->get(); + + return view('winemaker.cellar.index', compact('wines')); + } + + /** + * Display wines available for sales management (for winemaker) + */ + public function salesIndex() + { + $wines = Wine::with('grapeVariety') + ->where('bottles_in_stock', '>', 0) + ->orderBy('vintage', 'desc') + ->orderBy('wine_name') + ->paginate(15); + + return view('winemaker.sales.index', compact('wines')); + } + + /** + * Add wine to sales (mark as available) + */ + public function addToSales($id) + { + $wine = Wine::findOrFail($id); + + if ($wine->status === 'in_production') { + return redirect()->back()->with('error', 'Cannot add wine that is still in production to catalog.'); + } + + if ($wine->bottles_in_stock <= 0) { + return redirect()->back()->with('error', 'Cannot add wine without stock to catalog.'); + } + + if (!$wine->price_per_bottle) { + return redirect()->back()->with('error', 'Please set a price before adding wine to catalog.'); + } + + $wine->update(['status' => 'ready']); + + return redirect()->back()->with('success', 'Wine has been added to the catalog.'); + } + + /** + * Remove wine from sales (mark as not available) + */ + public function removeFromSales($id) + { + $wine = Wine::findOrFail($id); + + $wine->update(['status' => 'aging']); + + return redirect()->back()->with('success', 'Wine has been removed from the catalog.'); + } + + /** + * Show form to create blended wine from multiple harvests + */ + public function createBlendForm() + { + $availableHarvests = Harvest::with(['varietyVariation.grapeVariety', 'wineProductions', 'plannedTask']) + ->where(function ($query) { + $query->whereHas('plannedTask', function ($sub) { + $sub->whereNotNull('execution_date'); + })->orWhereDoesntHave('plannedTask'); + }) + ->get() + ->filter(function ($harvest) { + return $harvest->remaining_weight > 0.01; + }) + ->sortByDesc(function ($harvest) { + return $harvest->plannedTask?->execution_date ?? $harvest->date; + }); + + return view('winemaker.cellar.create-blend', compact('availableHarvests')); + } + + /** + * Store a new blended wine from multiple harvests + */ + public function storeBlend(Request $request) + { + $validated = $request->validate([ + 'harvests' => 'required|array|min:1', + 'harvests.*.selected' => 'sometimes', + 'harvests.*.weight' => 'required_with:harvests.*.selected|numeric|min:0.01', + 'wine_name' => 'required|string|max:255', + 'vintage' => 'required|integer|min:1900|max:' . (date('Y') + 1), + 'wine_type' => 'required|in:red,white,rose', + 'sweetness' => 'required|in:dry,semi_dry,semi_sweet,sweet', + 'alcohol_percentage' => 'required|numeric|min:0|max:20', + 'bottles_produced' => 'required|integer|min:1', + 'bottle_volume' => 'nullable|numeric|min:0.1|max:10', + 'production_date' => 'required|date', + 'bottling_date' => 'nullable|date', + 'status' => 'required|in:in_production,aging,ready,sold_out', + 'price_per_bottle' => 'nullable|numeric|min:0', + 'description' => 'nullable|string', + 'image' => 'nullable|image|mimes:jpeg,jpg,png,webp|max:2048', + ]); + + try { + DB::beginTransaction(); + + // Filter selected harvests and calculate total weight + $selectedHarvests = []; + $totalWeight = 0; + + foreach ($validated['harvests'] as $harvestId => $data) { + if (isset($data['selected']) && isset($data['weight']) && $data['weight'] > 0) { + $harvest = Harvest::with('varietyVariation.grapeVariety')->findOrFail($harvestId); + + // Validate weight + if ($data['weight'] > $harvest->remaining_weight) { + return back() + ->withInput() + ->with('error', 'Harvest #' . $harvestId . ': Cannot use ' . $data['weight'] . ' kg. Only ' . number_format($harvest->remaining_weight, 2) . ' kg available.'); + } + + $selectedHarvests[] = [ + 'harvest' => $harvest, + 'weight' => $data['weight'] + ]; + $totalWeight += $data['weight']; + } + } + + if (count($selectedHarvests) === 0) { + return back() + ->withInput() + ->with('error', 'Please select at least one harvest with a weight.'); + } + + // Determine primary grape variety (from harvest with highest weight) + $primaryHarvest = collect($selectedHarvests)->sortByDesc('weight')->first(); + $grapeVariety = $primaryHarvest['harvest']->varietyVariation->grapeVariety; + + // Handle image upload + $imagePath = null; + if ($request->hasFile('image')) { + $imagePath = $request->file('image')->store('wines', 'public'); + } + + // Create the wine + $wine = Wine::create([ + 'wine_name' => $validated['wine_name'], + 'vintage' => $validated['vintage'], + 'grape_variety_id' => $grapeVariety->id, + 'wine_type' => $validated['wine_type'], + 'sweetness' => $validated['sweetness'], + 'alcohol_percentage' => $validated['alcohol_percentage'], + 'bottles_produced' => $validated['bottles_produced'], + 'bottles_in_stock' => $validated['bottles_produced'], + 'bottle_volume' => $validated['bottle_volume'] ?? 0.75, + 'production_date' => $validated['production_date'], + 'bottling_date' => $validated['bottling_date'], + 'status' => $validated['status'], + 'price_per_bottle' => $validated['price_per_bottle'], + 'description' => $validated['description'], + 'image_url' => $imagePath, + ]); + + // Create wine production records for each harvest + $harvestIds = []; + foreach ($selectedHarvests as $item) { + $blendPercentage = ($item['weight'] / $totalWeight) * 100; + + WineProduction::create([ + 'wine_id' => $wine->id, + 'harvest_id' => $item['harvest']->id, + 'consumed_weight' => $item['weight'], + 'blend_percentage' => $blendPercentage, + ]); + + $harvestIds[] = '#' . $item['harvest']->id; + } + + DB::commit(); + + $message = 'Blended wine created successfully from ' . count($selectedHarvests) . ' harvest(s): ' . implode(', ', $harvestIds); + $message .= '. Total blend: ' . number_format($totalWeight, 2) . ' kg'; + + return redirect()->route('winemaker.cellar.index') + ->with('success', $message); + + } catch (\Exception $e) { + DB::rollBack(); + return back() + ->withInput() + ->with('error', 'Failed to create blended wine: ' . $e->getMessage()); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/WineProductionController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/WineProductionController.php new file mode 100644 index 0000000..391e8ba --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/WineProductionController.php @@ -0,0 +1,100 @@ +paginate(15); + + return view('wine-productions.index', compact('productions')); + } + + /** + * Show the form for creating a new wine production record. + */ + public function create() + { + $wines = Wine::all(); + $harvests = Harvest::with('varietyVariation.grapeVariety')->get(); + + return view('wine-productions.create', compact('wines', 'harvests')); + } + + /** + * Store a newly created wine production record in storage. + */ + public function store(Request $request) + { + $validated = $request->validate([ + 'wine_id' => 'required|exists:wines,id', + 'harvest_id' => 'required|exists:harvests,id', + 'consumed_weight' => 'required|numeric|min:0', + 'blend_percentage' => 'nullable|numeric|min:0|max:100', + ]); + + $production = WineProduction::create($validated); + + return redirect()->route('wine-productions.show', $production) + ->with('success', 'Wine production record created successfully.'); + } + + /** + * Display the specified wine production record. + */ + public function show(WineProduction $wineProduction) + { + $wineProduction->load('wine.grapeVariety', 'harvest.varietyVariation'); + + return view('wine-productions.show', compact('wineProduction')); + } + + /** + * Show the form for editing the specified wine production record. + */ + public function edit(WineProduction $wineProduction) + { + $wines = Wine::all(); + $harvests = Harvest::with('varietyVariation.grapeVariety')->get(); + + return view('wine-productions.edit', compact('wineProduction', 'wines', 'harvests')); + } + + /** + * Update the specified wine production record in storage. + */ + public function update(Request $request, WineProduction $wineProduction) + { + $validated = $request->validate([ + 'wine_id' => 'required|exists:wines,id', + 'harvest_id' => 'required|exists:harvests,id', + 'consumed_weight' => 'required|numeric|min:0', + 'blend_percentage' => 'nullable|numeric|min:0|max:100', + ]); + + $wineProduction->update($validated); + + return redirect()->route('wine-productions.show', $wineProduction) + ->with('success', 'Wine production record updated successfully.'); + } + + /** + * Remove the specified wine production record from storage. + */ + public function destroy(WineProduction $wineProduction) + { + $wineProduction->delete(); + + return redirect()->route('wine-productions.index') + ->with('success', 'Wine production record deleted successfully.'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/WinemakerController.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/WinemakerController.php new file mode 100644 index 0000000..4a0cf74 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Controllers/WinemakerController.php @@ -0,0 +1,422 @@ +whereNull('execution_date') + ->where('planned_date', '>=', now()->subDays(7)) + ->where('planned_date', '<=', now()->addDays(7)) + ->orderBy('planned_date') + ->get(); + + // Load parent Treatment records for treatment types (to access vineyard row data) + foreach ($plannedTasksRaw as $task) { + if (in_array($task->taskable_type, [ + 'App\Models\Spraying', + 'App\Models\Watering', + 'App\Models\Fertilization', + 'App\Models\Pruning' + ]) && $task->taskable) { + $task->treatment = Treatment::with('vineyardRow')->find($task->taskable->treatment_id); + } + } + + // Group planned tasks by type, date, and note + $plannedTasks = $plannedTasksRaw->groupBy(function($task) { + return $task->type . '|' . $task->planned_date->format('Y-m-d') . '|' . ($task->note ?? ''); + })->map(function($group) { + $first = $group->first(); + $first->vineyard_rows = $group->map(function($task) { + if ($task->taskable_type === VineyardRow::class) { + return $task->taskable; + } + // For Treatment types, use the parent Treatment record + if (isset($task->treatment) && $task->treatment) { + return $task->treatment->vineyardRow; + } + // For Harvest, load the vineyardRow if it exists + if ($task->taskable && method_exists($task->taskable, 'vineyardRow')) { + return $task->taskable->vineyardRow; + } + return null; + })->filter()->values(); + // Map task IDs to their vineyard rows + $first->task_rows = $group->map(function($task) { + $row = null; + if ($task->taskable_type === VineyardRow::class) { + $row = $task->taskable; + } elseif (isset($task->treatment) && $task->treatment) { + $row = $task->treatment->vineyardRow; + } elseif ($task->taskable && method_exists($task->taskable, 'vineyardRow')) { + $row = $task->taskable->vineyardRow; + } + return $row ? [ + 'task_id' => $task->planned_task_id, + 'row_id' => $row->id, + 'row' => $row, + ] : null; + })->filter()->values(); + $first->task_count = $group->count(); + return $first; + })->values(); + + // Sort all planned tasks chronologically + $allPlannedTasks = $plannedTasks->sortBy('planned_date')->values(); + + // ======================================== + // COMPLETED ACTIONS + // ======================================== + + $completedActivities = collect(); + + // 1. Completed treatments and tasks (including completed Harvests) + $completedTasksRaw = PlannedTask::with(['taskable']) + ->whereNotNull('execution_date') + ->where('execution_date', '>=', now()->subDays(30)) + ->orderBy('execution_date', 'desc') + ->get(); + + // Load parent Treatment records for treatment types + foreach ($completedTasksRaw as $task) { + if (in_array($task->taskable_type, [ + 'App\Models\Spraying', + 'App\Models\Watering', + 'App\Models\Fertilization', + 'App\Models\Pruning' + ]) && $task->taskable) { + $task->treatment = Treatment::with('vineyardRow')->find($task->taskable->treatment_id); + } + } + + // Group completed tasks by type, execution date, and note + $completedTasks = $completedTasksRaw->groupBy(function($task) { + return $task->type . '|' . $task->execution_date->format('Y-m-d') . '|' . ($task->note ?? ''); + })->map(function($group) { + $first = $group->first(); + $first->vineyard_rows = $group->map(function($task) { + if ($task->taskable_type === VineyardRow::class) { + return $task->taskable; + } + // For Treatment types, use the parent Treatment record + if (isset($task->treatment) && $task->treatment) { + return $task->treatment->vineyardRow; + } + // For Harvest, load the vineyardRow if it exists + if ($task->taskable && method_exists($task->taskable, 'vineyardRow')) { + return $task->taskable->vineyardRow; + } + return null; + })->filter()->values(); + $first->task_count = $group->count(); + $first->activity_type = 'task'; + $first->activity_date = $first->execution_date; + return $first; + })->values(); + + $completedActivities = $completedActivities->concat($completedTasks); + + // 2. Recent wine productions (bottling/blending) - DISABLED FOR RECENT ACTIVITY + // Note: Bottling and blending activities are only shown in "All Completed Activities" + // They are excluded from the recent activity timeline on the dashboard + /* + $recentProductions = WineProduction::with(['wine.grapeVariety', 'harvest.vineyardRow.varietyVariation']) + ->where('created_at', '>=', now()->subDays(30)) + ->orderBy('created_at', 'desc') + ->get(); + + // Group by wine to detect blends + $productionsByWine = $recentProductions->groupBy('wine_id'); + + foreach ($productionsByWine as $wineId => $productions) { + $wine = $productions->first()->wine; + if (!$wine) continue; + + $activity = (object)[ + 'activity_type' => 'production', + 'activity_date' => $productions->first()->created_at, + 'wine' => $wine, + 'productions' => $productions, + 'is_blend' => $productions->count() > 1, + 'total_weight' => $productions->sum('consumed_weight'), + ]; + + $completedActivities->push($activity); + } + */ + + // 3. Recent harvests (not from planned tasks) - DISABLED + // Note: Only showing "Harvest completed" from PlannedTask, not "Harvest Recorded" + // Harvest recorded activities are excluded from recent activity timeline + /* + $recentHarvests = Harvest::with(['vineyardRow.varietyVariation.grapeVariety']) + ->where('date', '>=', now()->subDays(30)) + ->orderBy('date', 'desc') + ->get() + ->map(function($harvest) { + // Check if this harvest is already represented in completed tasks + $existingTask = PlannedTask::where('taskable_type', Harvest::class) + ->where('taskable_id', $harvest->id) + ->whereNotNull('execution_date') + ->exists(); + + if ($existingTask) { + return null; // Skip to avoid duplicates + } + + return (object)[ + 'activity_type' => 'harvest', + 'activity_date' => $harvest->date, + 'harvest' => $harvest, + ]; + }) + ->filter(); + + $completedActivities = $completedActivities->concat($recentHarvests); + */ + + // Sort all completed activities by date (most recent first) + $completedActivities = $completedActivities + ->sortByDesc('activity_date') + ->take(20) + ->values(); + + // ======================================== + // STATISTICS + // ======================================== + + // Wine statistics + $wineStats = [ + 'total_bottles' => Wine::sum('bottles_in_stock') ?? 0, + 'by_status' => Wine::select('status', DB::raw('count(*) as count')) + ->groupBy('status') + ->pluck('count', 'status') + ->toArray(), + ]; + + // Harvest statistics + $totalHarvestWeight = Harvest::sum('weight') ?? 0; + $totalConsumedWeight = WineProduction::sum('consumed_weight') ?? 0; + $harvestStats = [ + 'total_harvest' => $totalHarvestWeight, + 'consumed' => $totalConsumedWeight, + 'available_weight' => max(0, $totalHarvestWeight - $totalConsumedWeight), + ]; + + // Vineyard statistics + $vineyardStats = [ + 'total_rows' => VineyardRow::count(), + 'active_rows' => VineyardRow::where('status', 'active')->count(), + 'total_area' => VineyardRow::sum('area') ?? 0, + ]; + + return view('winemaker.dashboard.index', compact( + 'allPlannedTasks', + 'completedActivities', + 'wineStats', + 'harvestStats', + 'vineyardStats' + )); + } + + /** + * Display all planned tasks. + */ + public function allPlannedTasks() + { + // Get all planned tasks (not yet executed) - including overdue tasks + $plannedTasksRaw = PlannedTask::with(['taskable']) + ->whereNull('execution_date') + ->orderBy('planned_date') + ->get(); + + // Load parent Treatment records for treatment types + foreach ($plannedTasksRaw as $task) { + if (in_array($task->taskable_type, [ + 'App\Models\Spraying', + 'App\Models\Watering', + 'App\Models\Fertilization', + 'App\Models\Pruning' + ]) && $task->taskable) { + $task->treatment = Treatment::with('vineyardRow')->find($task->taskable->treatment_id); + } + } + + // Group planned tasks by type, date, and note + $plannedTasks = $plannedTasksRaw->groupBy(function($task) { + return $task->type . '|' . $task->planned_date->format('Y-m-d') . '|' . ($task->note ?? ''); + })->map(function($group) { + $first = $group->first(); + $first->vineyard_rows = $group->map(function($task) { + if ($task->taskable_type === VineyardRow::class) { + return $task->taskable; + } + // For Treatment types, use the parent Treatment record + if (isset($task->treatment) && $task->treatment) { + return $task->treatment->vineyardRow; + } + // For Harvest, load the vineyardRow if it exists + if ($task->taskable && method_exists($task->taskable, 'vineyardRow')) { + return $task->taskable->vineyardRow; + } + return null; + })->filter()->values(); + // Map task IDs to their vineyard rows + $first->task_rows = $group->map(function($task) { + $row = null; + if ($task->taskable_type === VineyardRow::class) { + $row = $task->taskable; + } elseif (isset($task->treatment) && $task->treatment) { + $row = $task->treatment->vineyardRow; + } elseif ($task->taskable && method_exists($task->taskable, 'vineyardRow')) { + $row = $task->taskable->vineyardRow; + } + return $row ? [ + 'task_id' => $task->planned_task_id, + 'row_id' => $row->id, + 'row' => $row, + ] : null; + })->filter()->values(); + $first->task_count = $group->count(); + return $first; + })->values(); + + // Sort all planned tasks chronologically + $allPlannedTasks = $plannedTasks->sortBy('planned_date')->values(); + + return view('winemaker.dashboard.planned-tasks', compact('allPlannedTasks')); + } + + /** + * Display all completed activities. + */ + public function allCompletedActivities() + { + $completedActivities = collect(); + + // 1. Completed treatments and tasks + $completedTasksRaw = PlannedTask::with(['taskable']) + ->whereNotNull('execution_date') + ->orderBy('execution_date', 'desc') + ->get(); + + // Load parent Treatment records for treatment types + foreach ($completedTasksRaw as $task) { + if (in_array($task->taskable_type, [ + 'App\Models\Spraying', + 'App\Models\Watering', + 'App\Models\Fertilization', + 'App\Models\Pruning' + ]) && $task->taskable) { + $task->treatment = Treatment::with('vineyardRow')->find($task->taskable->treatment_id); + } + } + + // Group completed tasks by type, execution date, and note + $completedTasks = $completedTasksRaw->groupBy(function($task) { + return $task->type . '|' . $task->execution_date->format('Y-m-d') . '|' . ($task->note ?? ''); + })->map(function($group) { + $first = $group->first(); + $first->vineyard_rows = $group->map(function($task) { + if ($task->taskable_type === VineyardRow::class) { + return $task->taskable; + } + // For Treatment types, use the parent Treatment record + if (isset($task->treatment) && $task->treatment) { + return $task->treatment->vineyardRow; + } + // For Harvest, load the vineyardRow if it exists + if ($task->taskable && method_exists($task->taskable, 'vineyardRow')) { + return $task->taskable->vineyardRow; + } + return null; + })->filter()->values(); + $first->task_count = $group->count(); + $first->activity_type = 'task'; + $first->activity_date = $first->execution_date; + return $first; + })->values(); + + $completedActivities = $completedActivities->concat($completedTasks); + + // 2. All wine productions (bottling/blending) + $allProductions = WineProduction::with(['wine.grapeVariety', 'harvest.vineyardRow.varietyVariation']) + ->orderBy('created_at', 'desc') + ->get(); + + // Group by wine to detect blends + $productionsByWine = $allProductions->groupBy('wine_id'); + + foreach ($productionsByWine as $wineId => $productions) { + $wine = $productions->first()->wine; + if (!$wine) continue; + + $activity = (object)[ + 'activity_type' => 'production', + 'activity_date' => $productions->first()->created_at, + 'wine' => $wine, + 'productions' => $productions, + 'is_blend' => $productions->count() > 1, + 'total_weight' => $productions->sum('consumed_weight'), + ]; + + $completedActivities->push($activity); + } + + // 3. All harvests (not from planned tasks) + $allHarvests = Harvest::with(['vineyardRow.varietyVariation.grapeVariety', 'plannedTask']) + ->orderBy('date', 'desc') + ->get() + ->map(function($harvest) { + $existingTask = PlannedTask::where('taskable_type', Harvest::class) + ->where('taskable_id', $harvest->id) + ->whereNotNull('execution_date') + ->exists(); + + if ($existingTask) { + return null; + } + + // Use execution_date from plannedTask if available, otherwise use harvest date + $activityDate = ($harvest->plannedTask && $harvest->plannedTask->execution_date) + ? $harvest->plannedTask->execution_date + : $harvest->date; + + return (object)[ + 'activity_type' => 'harvest', + 'activity_date' => $activityDate, + 'harvest' => $harvest, + ]; + }) + ->filter(); + + $completedActivities = $completedActivities->concat($allHarvests); + + // Sort all completed activities by date (most recent first) + $completedActivities = $completedActivities + ->sortByDesc('activity_date') + ->values(); + + return view('winemaker.dashboard.completed-activities', compact('completedActivities')); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Middleware/AdminMiddleware.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Middleware/AdminMiddleware.php new file mode 100644 index 0000000..2713549 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Middleware/AdminMiddleware.php @@ -0,0 +1,25 @@ +check() || auth()->user()->role !== UserRole::ADMIN) { + abort(403, 'Unauthorized access. Admin only.'); + } + + return $next($request); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Middleware/EmployeeMiddleware.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Middleware/EmployeeMiddleware.php new file mode 100644 index 0000000..d01a112 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Middleware/EmployeeMiddleware.php @@ -0,0 +1,25 @@ +check() || (auth()->user()->role !== UserRole::EMPLOYEE && auth()->user()->role !== UserRole::ADMIN)) { + abort(403, 'Unauthorized access. Employee role required.'); + } + + return $next($request); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Middleware/EnsureUserHasRole.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Middleware/EnsureUserHasRole.php new file mode 100644 index 0000000..3ce29cc --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Middleware/EnsureUserHasRole.php @@ -0,0 +1,37 @@ +user()) { + abort(403, 'Unauthorized action.'); + } + + $userRole = $request->user()->role; + + // Convert string roles to UserRole enum cases for comparison + $allowedRoles = array_map(function ($role) { + return UserRole::from($role); + }, $roles); + + if (!in_array($userRole, $allowedRoles)) { + abort(403, 'You do not have permission to access this page.'); + } + + return $next($request); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/AssignPlantsRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/AssignPlantsRequest.php new file mode 100644 index 0000000..9001513 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/AssignPlantsRequest.php @@ -0,0 +1,61 @@ +input('rows'); + if (is_string($rows)) { + $rows = array_filter(array_map('trim', explode(',', $rows))); + } + + $createVariation = $this->input('create_variation'); + if (is_string($createVariation)) { + $decoded = json_decode($createVariation, true); + $createVariation = is_array($decoded) ? $decoded : null; + } + + $this->merge([ + 'rows' => $rows, + 'create_variation' => $createVariation, + ]); + } + + /** + * Get the validation rules that apply to the request. + * + * @return array + */ + public function rules(): array + { + return [ + 'rows' => ['required', 'array', 'min:1'], + 'rows.*' => ['integer', 'exists:vineyard_rows,id'], + 'variety_variation_id' => ['nullable', 'integer', 'exists:variety_variations,id', 'required_without:create_variation'], + 'create_variation' => ['nullable', 'array', 'required_without:variety_variation_id'], + 'create_variation.grape_variety_id' => ['nullable', 'integer', 'exists:grape_varieties,id'], + 'create_variation.grape_variety_name' => ['nullable', 'string', 'max:255'], + 'create_variation.color' => ['required_without:variety_variation_id', 'string', 'max:50'], + 'create_variation.description' => ['nullable', 'string'], + 'create_variation.typical_sugar_content' => ['nullable', 'numeric', 'min:0'], + 'create_variation.typical_alcohol' => ['nullable', 'numeric', 'min:0'], + 'create_variation.ripening_period' => ['nullable', 'string', 'max:255'], + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreBulkPlannedTasksRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreBulkPlannedTasksRequest.php new file mode 100644 index 0000000..9c5f17e --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreBulkPlannedTasksRequest.php @@ -0,0 +1,87 @@ +input('rows'); + if (is_string($rows)) { + $rows = array_filter(array_map('trim', explode(',', $rows))); + } + + $details = $this->input('details'); + if (is_string($details)) { + $decoded = json_decode($details, true); + $details = is_array($decoded) ? $decoded : []; + } + + $plannedDate = $this->input('planned_date'); + if (! $plannedDate && $this->query('date')) { + $plannedDate = $this->query('date'); + } + + $this->merge([ + 'rows' => $rows, + 'details' => $details ?? [], + 'planned_date' => $plannedDate, + ]); + } + + /** + * Get the validation rules that apply to the request. + * + * @return array + */ + public function rules(): array + { + $action = $this->input('action'); + + $rules = [ + 'action' => ['required', 'string', Rule::in(['watering', 'fertilization', 'spraying', 'pruning', 'harvest'])], + 'planned_date' => ['required', 'date'], + 'execution_date' => ['nullable', 'date', 'after_or_equal:planned_date'], + 'rows' => ['required', 'array', 'min:1'], + 'rows.*' => ['integer', 'exists:vineyard_rows,id'], + 'note' => ['nullable', 'string', 'max:1000'], + 'details' => ['nullable', 'array'], + 'details.time_interval' => ['nullable', 'integer', 'min:1'], + 'details.amount' => ['required_if:action,watering', 'numeric', 'min:0.01'], + 'details.substance' => ['required_if:action,fertilization', 'string', 'max:255'], + 'details.concentration' => ['nullable', 'numeric', 'min:0'], + 'details.pesticide' => ['required_if:action,spraying', 'string', 'max:255'], + 'details.method' => ['required_if:action,pruning', 'string', 'max:255'], + 'details.percentage_removed' => ['nullable', 'integer', 'min:0', 'max:100'], + 'details.weight' => ['nullable', 'numeric', 'min:0'], + 'details.sugar_content' => ['nullable', 'numeric', 'min:0'], + 'details.date' => ['nullable', 'date'], + 'details.quality' => ['nullable', 'string', 'max:255'], + 'details.condition' => ['nullable', 'string', 'max:255'], + 'details.weather' => ['nullable', 'string', 'max:255'], + 'details.time' => ['nullable', 'date_format:H:i'], + 'details.user_id' => ['nullable', 'integer', 'exists:users,id'], + 'details.variety_variation_id' => ['nullable', 'integer', 'exists:variety_variations,id'], + ]; + + if (in_array($action, ['watering', 'fertilization', 'spraying', 'pruning'], true)) { + $rules['details'] = ['required', 'array']; + } + + return $rules; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreFertilizationRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreFertilizationRequest.php new file mode 100644 index 0000000..ec42e27 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreFertilizationRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreGrapeVarietyRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreGrapeVarietyRequest.php new file mode 100644 index 0000000..b9fac72 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreGrapeVarietyRequest.php @@ -0,0 +1,48 @@ +|string> + */ + public function rules(): array + { + return [ + 'variety_name' => ['required', 'string', 'max:255', 'unique:grape_varieties,variety_name'], + 'description' => ['nullable', 'string'], + 'origin' => ['nullable', 'string', 'max:255'], + 'wine_type' => ['nullable', 'in:red,white,rose'], + 'characteristics' => ['nullable', 'string'], + 'image_url' => ['nullable', 'url', 'max:500'], + ]; + } + + /** + * Get custom attribute names for validator errors. + * + * @return array + */ + public function attributes(): array + { + return [ + 'variety_name' => 'variety name', + 'wine_type' => 'wine type', + 'image_url' => 'image URL', + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreHarvestRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreHarvestRequest.php new file mode 100644 index 0000000..41e238f --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreHarvestRequest.php @@ -0,0 +1,66 @@ +|string> + */ + public function rules(): array + { + return [ + 'vineyard_row_id' => ['required', 'exists:vineyard_rows,id'], + 'variety_variation_id' => ['required', 'exists:variety_variations,id'], + 'weight' => ['required', 'numeric', 'min:0', 'max:99999.99'], + 'sugar_content' => ['nullable', 'numeric', 'min:0', 'max:50'], + 'date' => ['required', 'date', 'before_or_equal:today'], + 'quality' => ['nullable', 'in:excellent,good,fair,poor'], + 'grape_condition' => ['nullable', 'string', 'max:255'], + 'notes' => ['nullable', 'string', 'max:1000'], + 'weather_conditions' => ['nullable', 'string', 'max:500'], + 'harvest_time' => ['nullable', 'date_format:H:i'], + ]; + } + + /** + * Get custom messages for validator errors. + * + * @return array + */ + public function messages(): array + { + return [ + 'date.before_or_equal' => 'The harvest date cannot be in the future.', + 'harvest_time.date_format' => 'The harvest time must be in HH:MM format.', + ]; + } + + /** + * Get custom attribute names for validator errors. + * + * @return array + */ + public function attributes(): array + { + return [ + 'vineyard_row_id' => 'vineyard row', + 'variety_variation_id' => 'variety variation', + 'sugar_content' => 'sugar content (°NM)', + 'harvest_time' => 'harvest time', + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StorePlannedTaskRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StorePlannedTaskRequest.php new file mode 100644 index 0000000..f3561ed --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StorePlannedTaskRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StorePruningRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StorePruningRequest.php new file mode 100644 index 0000000..e5f66d1 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StorePruningRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StorePsprayingRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StorePsprayingRequest.php new file mode 100644 index 0000000..413e8cc --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StorePsprayingRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreTreatmentRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreTreatmentRequest.php new file mode 100644 index 0000000..370a5b7 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreTreatmentRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreVineyardRowRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreVineyardRowRequest.php new file mode 100644 index 0000000..92a406b --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreVineyardRowRequest.php @@ -0,0 +1,53 @@ +|string> + */ + public function rules(): array + { + $currentYear = date('Y'); + + return [ + 'variety_variation_id' => ['nullable', 'integer', 'exists:variety_variations,id'], + 'vine_count' => ['required', 'integer', 'min:1', 'max:10000'], + 'planting_year' => ['required', 'integer', 'min:1900', 'max:' . $currentYear], + 'area' => ['nullable', 'numeric', 'min:0', 'max:99999.99'], + 'location' => ['nullable', 'string', 'max:255', new LocationCoordinates()], + 'status' => ['required', 'in:active,inactive,replanting,discarded'], + 'notes' => ['nullable', 'string', 'max:1000'], + ]; + } + + /** + * Get custom attribute names for validator errors. + * + * @return array + */ + public function attributes(): array + { + return [ + 'variety_variation_id' => 'variety variation', + 'vine_count' => 'vine count', + 'planting_year' => 'planting year', + 'area' => 'area (m²)', + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreWateringRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreWateringRequest.php new file mode 100644 index 0000000..9932310 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreWateringRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreWineRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreWineRequest.php new file mode 100644 index 0000000..3e1e8f6 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/StoreWineRequest.php @@ -0,0 +1,79 @@ +|string> + */ + public function rules(): array + { + $currentYear = date('Y'); + + return [ + 'vintage' => ['required', 'integer', 'min:1900', 'max:' . ($currentYear + 1)], + 'grape_variety_id' => ['required', 'exists:grape_varieties,id'], + 'wine_name' => ['required', 'string', 'max:255'], + 'wine_type' => ['nullable', 'in:red,white,rose'], + 'description' => ['nullable', 'string'], + 'alcohol_percentage' => ['nullable', 'numeric', 'min:0', 'max:20'], + 'bottles_produced' => ['required', 'integer', 'min:0'], + 'bottles_in_stock' => ['required', 'integer', 'min:0', 'lte:bottles_produced'], + 'price_per_bottle' => ['nullable', 'numeric', 'min:0'], + 'bottle_volume' => ['nullable', 'numeric', 'min:0', 'max:10'], + 'production_date' => ['nullable', 'date', 'before_or_equal:today'], + 'bottling_date' => ['nullable', 'date', 'before_or_equal:today', 'after_or_equal:production_date'], + 'status' => ['required', 'in:in_production,aging,ready,sold_out'], + 'image_url' => ['nullable', 'url', 'max:500'], + ]; + } + + /** + * Get custom messages for validator errors. + * + * @return array + */ + public function messages(): array + { + return [ + 'bottles_in_stock.lte' => 'Bottles in stock cannot exceed bottles produced.', + 'bottling_date.after_or_equal' => 'Bottling date must be after or equal to production date.', + ]; + } + + /** + * Get custom attribute names for validator errors. + * + * @return array + */ + public function attributes(): array + { + return [ + 'grape_variety_id' => 'grape variety', + 'wine_name' => 'wine name', + 'wine_type' => 'wine type', + 'alcohol_percentage' => 'alcohol percentage', + 'bottles_produced' => 'bottles produced', + 'bottles_in_stock' => 'bottles in stock', + 'price_per_bottle' => 'price per bottle', + 'bottle_volume' => 'bottle volume', + 'production_date' => 'production date', + 'bottling_date' => 'bottling date', + 'image_url' => 'image URL', + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateFertilizationRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateFertilizationRequest.php new file mode 100644 index 0000000..ce837a6 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateFertilizationRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateGrapeVarietyRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateGrapeVarietyRequest.php new file mode 100644 index 0000000..6ee89e5 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateGrapeVarietyRequest.php @@ -0,0 +1,49 @@ +|string> + */ + public function rules(): array + { + return [ + 'variety_name' => ['required', 'string', 'max:255', Rule::unique('grape_varieties', 'variety_name')->ignore($this->grapeVariety)], + 'description' => ['nullable', 'string'], + 'origin' => ['nullable', 'string', 'max:255'], + 'wine_type' => ['nullable', 'in:red,white,rose'], + 'characteristics' => ['nullable', 'string'], + 'image_url' => ['nullable', 'url', 'max:500'], + ]; + } + + /** + * Get custom attribute names for validator errors. + * + * @return array + */ + public function attributes(): array + { + return [ + 'variety_name' => 'variety name', + 'wine_type' => 'wine type', + 'image_url' => 'image URL', + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateHarvestRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateHarvestRequest.php new file mode 100644 index 0000000..b38b9eb --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateHarvestRequest.php @@ -0,0 +1,66 @@ +|string> + */ + public function rules(): array + { + return [ + 'vineyard_row_id' => ['required', 'exists:vineyard_rows,id'], + 'variety_variation_id' => ['required', 'exists:variety_variations,id'], + 'weight' => ['required', 'numeric', 'min:0', 'max:99999.99'], + 'sugar_content' => ['nullable', 'numeric', 'min:0', 'max:50'], + 'date' => ['required', 'date', 'before_or_equal:today'], + 'quality' => ['nullable', 'in:excellent,good,fair,poor'], + 'grape_condition' => ['nullable', 'string', 'max:255'], + 'notes' => ['nullable', 'string', 'max:1000'], + 'weather_conditions' => ['nullable', 'string', 'max:500'], + 'harvest_time' => ['nullable', 'date_format:H:i'], + ]; + } + + /** + * Get custom messages for validator errors. + * + * @return array + */ + public function messages(): array + { + return [ + 'date.before_or_equal' => 'The harvest date cannot be in the future.', + 'harvest_time.date_format' => 'The harvest time must be in HH:MM format.', + ]; + } + + /** + * Get custom attribute names for validator errors. + * + * @return array + */ + public function attributes(): array + { + return [ + 'vineyard_row_id' => 'vineyard row', + 'variety_variation_id' => 'variety variation', + 'sugar_content' => 'sugar content (°NM)', + 'harvest_time' => 'harvest time', + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdatePlannedTaskRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdatePlannedTaskRequest.php new file mode 100644 index 0000000..b5ba30b --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdatePlannedTaskRequest.php @@ -0,0 +1,57 @@ +|string> + */ + public function rules(): array + { + $task = $this->route('task'); + $taskableType = $task->taskable_type; + + // For spraying and harvest tasks, date cannot be changed + $dateRules = (str_contains($taskableType, 'Spraying') || str_contains($taskableType, 'Harvest')) + ? ['nullable', 'date'] + : ['required', 'date', 'after_or_equal:today']; + + $rules = [ + 'planned_date' => $dateRules, + 'note' => ['nullable', 'string', 'max:1000'], + 'task_ids' => ['nullable', 'array', 'min:1'], + 'task_ids.*' => ['integer', 'exists:planned_tasks,planned_task_id'], + ]; + + // Add type-specific validation rules based on taskable type + if (str_contains($taskableType, 'Watering')) { + $rules['time_interval'] = ['nullable', 'integer', 'min:1']; + $rules['amount'] = ['required', 'numeric', 'min:0.01']; + } elseif (str_contains($taskableType, 'Fertilization')) { + $rules['substance'] = ['required', 'string', 'max:255']; + $rules['concentration'] = ['nullable', 'numeric', 'min:0']; + } elseif (str_contains($taskableType, 'Spraying')) { + $rules['pesticide'] = ['required', 'string', 'max:255']; + $rules['concentration'] = ['nullable', 'numeric', 'min:0']; + } elseif (str_contains($taskableType, 'Pruning')) { + $rules['method'] = ['required', 'string', 'max:255']; + $rules['percentage_removed'] = ['nullable', 'integer', 'min:0', 'max:100']; + } + // Harvest doesn't have editable details fields (they're filled when completed) + + return $rules; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdatePruningRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdatePruningRequest.php new file mode 100644 index 0000000..da4c3cb --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdatePruningRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdatePsprayingRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdatePsprayingRequest.php new file mode 100644 index 0000000..22e2903 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdatePsprayingRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateTreatmentRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateTreatmentRequest.php new file mode 100644 index 0000000..e5300c0 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateTreatmentRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateVineyardRowRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateVineyardRowRequest.php new file mode 100644 index 0000000..2c5515e --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateVineyardRowRequest.php @@ -0,0 +1,54 @@ +|string> + */ + public function rules(): array + { + $currentYear = date('Y'); + + return [ + 'variety_variation_id' => ['nullable', 'integer', 'exists:variety_variations,id'], + 'vine_count' => ['required', 'integer', 'min:1', 'max:10000'], + 'planting_year' => ['required', 'integer', 'min:1900', 'max:' . $currentYear], + 'area' => ['nullable', 'numeric', 'min:0', 'max:99999.99'], + 'location' => ['nullable', 'string', 'max:255', new LocationCoordinates()], + 'status' => ['required', 'in:active,inactive,replanting,discarded'], + 'notes' => ['nullable', 'string', 'max:1000'], + ]; + } + + /** + * Get custom attribute names for validator errors. + * + * @return array + */ + public function attributes(): array + { + return [ + 'variety_variation_id' => 'variety variation', + 'vine_count' => 'vine count', + 'planting_year' => 'planting year', + 'area' => 'area (m²)', + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateWateringRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateWateringRequest.php new file mode 100644 index 0000000..f11eb54 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateWateringRequest.php @@ -0,0 +1,28 @@ +|string> + */ + public function rules(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateWineRequest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateWineRequest.php new file mode 100644 index 0000000..fdb06b6 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Http/Requests/UpdateWineRequest.php @@ -0,0 +1,81 @@ +|string> + */ + public function rules(): array + { + $currentYear = date('Y'); + + return [ + 'vintage' => ['required', 'integer', 'min:1900', 'max:' . ($currentYear + 1)], + 'grape_variety_id' => ['required', 'exists:grape_varieties,id'], + 'wine_name' => ['required', 'string', 'max:255'], + 'wine_type' => ['nullable', 'in:red,white,rose'], + 'sweetness' => ['nullable', 'in:dry,semi_dry,semi_sweet,sweet'], + 'description' => ['nullable', 'string'], + 'alcohol_percentage' => ['nullable', 'numeric', 'min:0', 'max:20'], + 'bottles_produced' => ['required', 'integer', 'min:0'], + 'bottles_in_stock' => ['required', 'integer', 'min:0', 'lte:bottles_produced'], + 'price_per_bottle' => ['nullable', 'numeric', 'min:0'], + 'bottle_volume' => ['nullable', 'numeric', 'min:0', 'max:10'], + 'production_date' => ['nullable', 'date', 'before_or_equal:today'], + 'bottling_date' => ['nullable', 'date', 'before_or_equal:today', 'after_or_equal:production_date'], + 'status' => ['required', 'in:in_production,aging,ready,sold_out'], + 'image_url' => ['nullable', 'url', 'max:500'], + 'image' => ['nullable', 'image', 'mimes:jpeg,jpg,png,webp', 'max:2048'], + ]; + } + + /** + * Get custom messages for validator errors. + * + * @return array + */ + public function messages(): array + { + return [ + 'bottles_in_stock.lte' => 'Bottles in stock cannot exceed bottles produced.', + 'bottling_date.after_or_equal' => 'Bottling date must be after or equal to production date.', + ]; + } + + /** + * Get custom attribute names for validator errors. + * + * @return array + */ + public function attributes(): array + { + return [ + 'grape_variety_id' => 'grape variety', + 'wine_name' => 'wine name', + 'wine_type' => 'wine type', + 'alcohol_percentage' => 'alcohol percentage', + 'bottles_produced' => 'bottles produced', + 'bottles_in_stock' => 'bottles in stock', + 'price_per_bottle' => 'price per bottle', + 'bottle_volume' => 'bottle volume', + 'production_date' => 'production date', + 'bottling_date' => 'bottling date', + 'image_url' => 'image URL', + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/Event.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Event.php new file mode 100644 index 0000000..0ec9a9e --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Event.php @@ -0,0 +1,63 @@ + 'date', + 'event_time' => 'datetime:H:i', + 'price_per_person' => 'decimal:2', + ]; + + /** + * Get all reservations for this event. + */ + public function reservations(): BelongsToMany + { + return $this->belongsToMany(User::class, 'event_reservations') + ->withPivot('number_of_guests', 'status', 'created_at') + ->withTimestamps(); + } + + /** + * Get the number of confirmed reservations. + */ + public function confirmedReservationsCount(): int + { + return $this->reservations() + ->wherePivot('status', 'confirmed') + ->sum('event_reservations.number_of_guests'); + } + + /** + * Get the number of available spots. + */ + public function availableSpots(): int + { + return $this->capacity - $this->confirmedReservationsCount(); + } + + /** + * Check if the event is full. + */ + public function isFull(): bool + { + return $this->availableSpots() <= 0; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/EventReservation.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/EventReservation.php new file mode 100644 index 0000000..bf51346 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/EventReservation.php @@ -0,0 +1,32 @@ +belongsTo(Event::class); + } + + /** + * Get the user who made this reservation. + */ + public function user(): BelongsTo + { + return $this->belongsTo(User::class); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/Fertilization.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Fertilization.php new file mode 100644 index 0000000..4864ac5 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Fertilization.php @@ -0,0 +1,30 @@ + */ + use HasFactory; + + protected $table = 'fertilizations'; + + protected $primaryKey = 'treatment_id'; + + public $incrementing = false; + + protected $keyType = 'int'; + + protected $fillable = [ + 'treatment_id', + 'substance', + 'concentration', + 'note', + ]; + + protected $casts = [ + 'concentration' => 'float', + ]; +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/GrapeVariety.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/GrapeVariety.php new file mode 100644 index 0000000..e2fcc3e --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/GrapeVariety.php @@ -0,0 +1,39 @@ +hasMany(VarietyVariation::class, 'grape_variety_id'); + } + + /** + * Get the wines for this grape variety. + */ + public function wines(): HasMany + { + return $this->hasMany(Wine::class, 'grape_variety_id'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/GrapeVarietyVariant.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/GrapeVarietyVariant.php new file mode 100644 index 0000000..cc5e815 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/GrapeVarietyVariant.php @@ -0,0 +1,24 @@ + */ + use HasFactory; + // The migrations create the default `id` primary key for grape_variety_variants. + // Do not override $primaryKey so Eloquent uses the database `id` column. + + protected $fillable = [ + 'grape_variety_id', + 'color', + ]; + + public function grapeVariety() + { + return $this->belongsTo(GrapeVariety::class, 'grape_variety_id'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/Harvest.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Harvest.php new file mode 100644 index 0000000..3998adf --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Harvest.php @@ -0,0 +1,158 @@ + 'date', + 'weight' => 'decimal:2', + 'sugar_content' => 'decimal:2', + ]; + + /** + * Get the vineyard row for this harvest. + */ + public function vineyardRow(): BelongsTo + { + return $this->belongsTo(VineyardRow::class, 'vineyard_row_id'); + } + + /** + * Get the planned task associated with this treatment. + */ + public function plannedTask(): MorphOne + { + return $this->morphOne(PlannedTask::class, 'taskable'); + } + + /** + * Get the variety variation for this harvest. + */ + public function varietyVariation(): BelongsTo + { + return $this->belongsTo(VarietyVariation::class, 'variety_variation_id'); + } + + /** + * Get the user who performed this harvest. + */ + public function user(): BelongsTo + { + return $this->belongsTo(User::class, 'user_id'); + } + + /** + * Get the wine production records for this harvest. + */ + public function wineProductions(): HasMany + { + return $this->hasMany(WineProduction::class, 'harvest_id'); + } + + /** + * Get the wines produced from this harvest (many-to-many through wine_productions). + */ + public function wines(): BelongsToMany + { + return $this->belongsToMany(Wine::class, 'wine_productions', 'harvest_id', 'wine_id') + ->withPivot('consumed_weight', 'blend_percentage') + ->withTimestamps(); + } + + /** + * Get the total consumed weight from all wine productions. + */ + public function getConsumedWeightAttribute(): float + { + return $this->wineProductions()->sum('consumed_weight') ?? 0; + } + + /** + * Get the remaining available weight. + */ + public function getRemainingWeightAttribute(): float + { + return max(0, $this->weight - $this->consumed_weight); + } + + /** + * Get the usage percentage. + */ + public function getUsagePercentageAttribute(): float + { + if ($this->weight <= 0) { + return 0; + } + return min(100, ($this->consumed_weight / $this->weight) * 100); + } + + /** + * Check if harvest is fully used. + */ + public function isFullyUsed(): bool + { + return $this->remaining_weight <= 0.01; // Allow small floating point difference + } + + /** + * Check if harvest is partially used. + */ + public function isPartiallyUsed(): bool + { + return $this->consumed_weight > 0 && !$this->isFullyUsed(); + } + + /** + * Check if harvest is available (not used at all). + */ + public function isAvailable(): bool + { + return $this->consumed_weight < 0.01; // Allow small floating point difference + } + + /** + * Check if there are any wines still in the cellar that were made from this harvest. + * Returns true if any connected wine has bottles in stock. + */ + public function hasWinesInCellar(): bool + { + return $this->wines()->where('bottles_in_stock', '>', 0)->exists(); + } + + /** + * Check if harvest can be safely deleted. + * A harvest can only be deleted when: + * 1. It has been fully used in wine production + * 2. All wines made from it have been sold out (no bottles in cellar) + */ + public function canBeDeleted(): bool + { + return $this->isFullyUsed() && !$this->hasWinesInCellar(); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/PlannedTask.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/PlannedTask.php new file mode 100644 index 0000000..ddfc53a --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/PlannedTask.php @@ -0,0 +1,36 @@ + 'date', + 'execution_date' => 'date', + ]; + + /** + * Get the taskable model (Treatment or Harvest). + */ + public function taskable(): MorphTo + { + return $this->morphTo(); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/Pruning.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Pruning.php new file mode 100644 index 0000000..73ac327 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Pruning.php @@ -0,0 +1,30 @@ + */ + use HasFactory; + + protected $table = 'prunings'; + + protected $primaryKey = 'treatment_id'; + + public $incrementing = false; + + protected $keyType = 'int'; + + protected $fillable = [ + 'treatment_id', + 'method', + 'percentage_removed', + 'note', + ]; + + protected $casts = [ + 'percentage_removed' => 'integer', + ]; +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/Purchase.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Purchase.php new file mode 100644 index 0000000..2a7966a --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Purchase.php @@ -0,0 +1,96 @@ + */ + use HasFactory; + protected $fillable = [ + 'user_id', + 'wine_id', + 'amount', + 'price', + 'status', + 'purchased_at', + 'note', + ]; + + /** + * Casts for attributes + * + * @var array + */ + protected $casts = [ + 'amount' => 'integer', + 'price' => 'decimal:2', + 'purchased_at' => 'datetime', + 'status' => 'string', + 'note' => 'string', + ]; + + public function user() + { + return $this->belongsTo(User::class, 'user_id'); + } + + public function wine() + { + return $this->belongsTo(Wine::class, 'wine_id'); + } + + /** + * Purchase has many items (weak entity) + */ + public function items(): HasMany + { + return $this->hasMany(PurchaseItem::class, 'purchase_id'); + } + + /** + * Create a purchase with items and decrement wine stock atomically. + * + * $items = [ ['wine_id'=>1,'quantity'=>2,'unit_price'=>12.5], ... ] + */ + public static function createWithItems(array $data, array $items): self + { + return DB::transaction(function () use ($data, $items) { + $purchase = self::create($data); + + foreach ($items as $it) { + $wine = Wine::findOrFail($it['wine_id']); + + $qty = (int) ($it['quantity'] ?? 1); + if ($wine->bottles_in_stock !== null && $wine->bottles_in_stock < $qty) { + throw new \Exception("Insufficient stock for wine id {$wine->id}"); + } + + $unit = $it['unit_price'] ?? $wine->price_per_bottle ?? 0; + $lineTotal = round($qty * $unit, 2); + + $purchase->items()->create([ + 'wine_id' => $wine->getKey(), + 'quantity' => $qty, + 'unit_price' => $unit, + 'line_total' => $lineTotal, + ]); + + // decrement stock if tracked + if ($wine->bottles_in_stock !== null) { + $wine->decrement('bottles_in_stock', $qty); + } + } + + return $purchase; + }); + } + +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/PurchaseItem.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/PurchaseItem.php new file mode 100644 index 0000000..700d2e1 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/PurchaseItem.php @@ -0,0 +1,36 @@ + 'integer', + 'unit_price' => 'decimal:2', + 'line_total' => 'decimal:2', + ]; + + public function purchase(): BelongsTo + { + return $this->belongsTo(Purchase::class, 'purchase_id'); + } + + public function wine(): BelongsTo + { + return $this->belongsTo(Wine::class, 'wine_id'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/Spraying.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Spraying.php new file mode 100644 index 0000000..9a16ba6 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Spraying.php @@ -0,0 +1,30 @@ + */ + use HasFactory; + + protected $table = 'sprayings'; + + protected $primaryKey = 'treatment_id'; + + public $incrementing = false; + + protected $keyType = 'int'; + + protected $fillable = [ + 'treatment_id', + 'pesticide', + 'concentration', + 'note', + ]; + + protected $casts = [ + 'concentration' => 'float', + ]; +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/Treatment.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Treatment.php new file mode 100644 index 0000000..4fa5394 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Treatment.php @@ -0,0 +1,37 @@ + */ + use HasFactory; + + protected $primaryKey = 'treatment_id'; + + protected $fillable = [ + 'row_id', + 'note', + ]; + + /** + * Get the vineyard row that has this treatment. + */ + public function vineyardRow(): BelongsTo + { + return $this->belongsTo(VineyardRow::class, 'row_id'); + } + + /** + * Get the planned task associated with this treatment. + */ + public function plannedTask(): MorphOne + { + return $this->morphOne(PlannedTask::class, 'taskable'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/User.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/User.php new file mode 100644 index 0000000..3955105 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/User.php @@ -0,0 +1,110 @@ + */ + use HasFactory, Notifiable; + + /** + * The attributes that are mass assignable. + * + * @var list + */ + protected $fillable = [ + 'name', + 'username', + 'email', + 'password', + 'role', + + ]; + + /** + * The attributes that should be hidden for serialization. + * + * @var list + */ + protected $hidden = [ + 'password', + 'remember_token', + ]; + + /** + * The attributes that should be cast. + * + * @var array + */ + protected $casts = [ + 'email_verified_at' => 'datetime', + 'password' => 'hashed', + 'role' => UserRole::class, + ]; + + /** + * Get purchases for the user (one-to-many) + */ + public function purchases(): HasMany + { + return $this->hasMany(Purchase::class, 'user_id'); + } + + /** + * Get event reservations for the user. + */ + public function eventReservations() + { + return $this->belongsToMany(Event::class, 'event_reservations') + ->withPivot('number_of_guests', 'status') + ->withTimestamps(); + } + + /** + * Check if the user has a specific role + */ + public function hasRole(UserRole $role): bool + { + return $this->role === $role; + } + + /** + * Check if the user is a winemaker + */ + public function isWinemaker(): bool + { + return $this->role === UserRole::WINEMAKER; + } + + /** + * Check if the user is a customer + */ + public function isCustomer(): bool + { + return $this->role === UserRole::CUSTOMER; + } + + /** + * Check if the user is an admin + */ + public function isAdmin(): bool + { + return $this->role === UserRole::ADMIN; + } + + /** + * Check if the user is an employee + */ + public function isEmployee(): bool + { + return $this->role === UserRole::EMPLOYEE; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/VarietyVariation.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/VarietyVariation.php new file mode 100644 index 0000000..cd9fe52 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/VarietyVariation.php @@ -0,0 +1,54 @@ + 'decimal:2', + 'typical_alcohol' => 'decimal:2', + ]; + + /** + * Get the grape variety that owns this variation. + */ + public function grapeVariety(): BelongsTo + { + return $this->belongsTo(GrapeVariety::class, 'grape_variety_id'); + } + + /** + * Get the vineyard rows for this variety variation. + */ + public function vineyardRows(): HasMany + { + return $this->hasMany(VineyardRow::class, 'variety_variation_id'); + } + + /** + * Get the harvests for this variety variation. + */ + public function harvests(): HasMany + { + return $this->hasMany(Harvest::class, 'variety_variation_id'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/VineyardRow.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/VineyardRow.php new file mode 100644 index 0000000..0ecc116 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/VineyardRow.php @@ -0,0 +1,69 @@ + 'decimal:2', + ]; + + /** + * Get the variety variation for this vineyard row. + */ + public function varietyVariation(): BelongsTo + { + return $this->belongsTo(VarietyVariation::class, 'variety_variation_id'); + } + + /** + * Get the harvests for this vineyard row. + */ + public function harvests(): HasMany + { + return $this->hasMany(Harvest::class, 'vineyard_row_id'); + } + + /** + * Get the treatments assigned to this vineyard row. + */ + public function treatments(): HasMany + { + return $this->hasMany(Treatment::class, 'row_id'); + } + + /** + * Get pesticide sprayings associated with the vineyard row. + */ + public function sprayings(): HasManyThrough + { + return $this->hasManyThrough( + Spraying::class, + Treatment::class, + 'row_id', + 'treatment_id', + 'id', + 'treatment_id' + ); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/Watering.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Watering.php new file mode 100644 index 0000000..b2425af --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Watering.php @@ -0,0 +1,26 @@ + */ + use HasFactory; + + protected $table = 'waterings'; + + protected $primaryKey = 'treatment_id'; + + public $incrementing = false; + + protected $keyType = 'int'; + + protected $fillable = [ + 'treatment_id', + 'time_interval', + 'amount', + 'note', + ]; +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/Wine.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Wine.php new file mode 100644 index 0000000..88674a4 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/Wine.php @@ -0,0 +1,84 @@ + 'date', + 'production_date' => 'date', + 'alcohol_percentage' => 'decimal:2', + 'price_per_bottle' => 'decimal:2', + 'bottle_volume' => 'decimal:3', + ]; + + /** + * Bootstrap the model and its traits. + */ + protected static function boot() + { + parent::boot(); + + // Automatically delete the wine image when the wine is deleted + static::deleting(function ($wine) { + if ($wine->image_url && Storage::disk('public')->exists($wine->image_url)) { + Storage::disk('public')->delete($wine->image_url); + } + }); + } + + /** + * Get the grape variety for this wine. + */ + public function grapeVariety(): BelongsTo + { + return $this->belongsTo(GrapeVariety::class, 'grape_variety_id'); + } + + /** + * Get the wine production records for this wine. + */ + public function wineProductions(): HasMany + { + return $this->hasMany(WineProduction::class, 'wine_id'); + } + + /** + * Get the harvests used in this wine production (many-to-many through wine_productions). + */ + public function harvests(): BelongsToMany + { + return $this->belongsToMany(Harvest::class, 'wine_productions', 'wine_id', 'harvest_id') + ->withPivot('consumed_weight', 'blend_percentage') + ->withTimestamps(); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Models/WineProduction.php b/3BIT/winter-semester/IIS/xnecasr00/app/Models/WineProduction.php new file mode 100644 index 0000000..b069c42 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Models/WineProduction.php @@ -0,0 +1,42 @@ + 'decimal:2', + 'blend_percentage' => 'decimal:2', + ]; + + /** + * Get the wine that this production record belongs to. + */ + public function wine(): BelongsTo + { + return $this->belongsTo(Wine::class, 'wine_id'); + } + + /** + * Get the harvest used in this wine production. + */ + public function harvest(): BelongsTo + { + return $this->belongsTo(Harvest::class, 'harvest_id'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Policies/FertilizationPolicy.php b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/FertilizationPolicy.php new file mode 100644 index 0000000..3b12b6d --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/FertilizationPolicy.php @@ -0,0 +1,66 @@ +hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can update the grape variety. + */ + public function update(User $user, GrapeVariety $grapeVariety): bool + { + // TODO: Implement role-based authorization + // Only administrators and winemakers should be able to update grape varieties + // Example: return $user->hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can delete the grape variety. + */ + public function delete(User $user, GrapeVariety $grapeVariety): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to delete grape varieties + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can restore the grape variety. + */ + public function restore(User $user, GrapeVariety $grapeVariety): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to restore grape varieties + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can permanently delete the grape variety. + */ + public function forceDelete(User $user, GrapeVariety $grapeVariety): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to force delete grape varieties + // Example: return $user->hasRole('admin'); + return true; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Policies/HarvestPolicy.php b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/HarvestPolicy.php new file mode 100644 index 0000000..e5d79af --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/HarvestPolicy.php @@ -0,0 +1,82 @@ +hasRole(['admin', 'winemaker', 'worker']); + return true; + } + + /** + * Determine whether the user can update the harvest. + */ + public function update(User $user, Harvest $harvest): bool + { + // TODO: Implement role-based authorization + // Users can update their own harvests, or admins/winemakers can update any + // Example: return $user->id === $harvest->user_id || $user->hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can delete the harvest. + */ + public function delete(User $user, Harvest $harvest): bool + { + // TODO: Implement role-based authorization + // Only administrators and winemakers should be able to delete harvests + // Example: return $user->hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can restore the harvest. + */ + public function restore(User $user, Harvest $harvest): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to restore harvests + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can permanently delete the harvest. + */ + public function forceDelete(User $user, Harvest $harvest): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to force delete harvests + // Example: return $user->hasRole('admin'); + return true; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Policies/PlannedTaskPolicy.php b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/PlannedTaskPolicy.php new file mode 100644 index 0000000..8907883 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/PlannedTaskPolicy.php @@ -0,0 +1,66 @@ +role === 'winemaker' && $plannedTask->execution_date === null; + } + + /** + * Determine whether the user can delete the model. + */ + public function delete(User $user, PlannedTask $plannedTask): bool + { + return $user->role === 'winemaker' && $plannedTask->execution_date === null; + } + + /** + * Determine whether the user can restore the model. + */ + public function restore(User $user, PlannedTask $plannedTask): bool + { + return false; + } + + /** + * Determine whether the user can permanently delete the model. + */ + public function forceDelete(User $user, PlannedTask $plannedTask): bool + { + return false; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Policies/PruningPolicy.php b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/PruningPolicy.php new file mode 100644 index 0000000..cde5ade --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/PruningPolicy.php @@ -0,0 +1,66 @@ +hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can update the variety variation. + */ + public function update(User $user, VarietyVariation $varietyVariation): bool + { + // TODO: Implement role-based authorization + // Only administrators and winemakers should be able to update variety variations + // Example: return $user->hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can delete the variety variation. + */ + public function delete(User $user, VarietyVariation $varietyVariation): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to delete variety variations + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can restore the variety variation. + */ + public function restore(User $user, VarietyVariation $varietyVariation): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to restore variety variations + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can permanently delete the variety variation. + */ + public function forceDelete(User $user, VarietyVariation $varietyVariation): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to force delete variety variations + // Example: return $user->hasRole('admin'); + return true; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Policies/VineyardRowPolicy.php b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/VineyardRowPolicy.php new file mode 100644 index 0000000..ccaed9c --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/VineyardRowPolicy.php @@ -0,0 +1,82 @@ +hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can update the vineyard row. + */ + public function update(User $user, VineyardRow $vineyardRow): bool + { + // TODO: Implement role-based authorization + // Only administrators and winemakers should be able to update vineyard rows + // Example: return $user->hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can delete the vineyard row. + */ + public function delete(User $user, VineyardRow $vineyardRow): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to delete vineyard rows + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can restore the vineyard row. + */ + public function restore(User $user, VineyardRow $vineyardRow): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to restore vineyard rows + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can permanently delete the vineyard row. + */ + public function forceDelete(User $user, VineyardRow $vineyardRow): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to force delete vineyard rows + // Example: return $user->hasRole('admin'); + return true; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Policies/WateringPolicy.php b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/WateringPolicy.php new file mode 100644 index 0000000..48e9c3f --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/WateringPolicy.php @@ -0,0 +1,66 @@ +hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can update the wine. + */ + public function update(User $user, Wine $wine): bool + { + // TODO: Implement role-based authorization + // Only administrators and winemakers should be able to update wines + // Example: return $user->hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can delete the wine. + */ + public function delete(User $user, Wine $wine): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to delete wines + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can restore the wine. + */ + public function restore(User $user, Wine $wine): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to restore wines + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can permanently delete the wine. + */ + public function forceDelete(User $user, Wine $wine): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to force delete wines + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can purchase the wine. + */ + public function purchase(?User $user, Wine $wine): bool + { + // TODO: Implement purchase authorization logic + // Customers and authenticated users should be able to purchase wines + // Check if wine is available (status = ready and bottles_in_stock > 0) + // Example: return $wine->status === 'ready' && $wine->bottles_in_stock > 0; + return $wine->status === 'ready' && $wine->bottles_in_stock > 0; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Policies/WineProductionPolicy.php b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/WineProductionPolicy.php new file mode 100644 index 0000000..4699a03 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Policies/WineProductionPolicy.php @@ -0,0 +1,82 @@ +hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can update the wine production record. + */ + public function update(User $user, WineProduction $wineProduction): bool + { + // TODO: Implement role-based authorization + // Only administrators and winemakers should be able to update wine production records + // Example: return $user->hasRole(['admin', 'winemaker']); + return true; + } + + /** + * Determine whether the user can delete the wine production record. + */ + public function delete(User $user, WineProduction $wineProduction): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to delete wine production records + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can restore the wine production record. + */ + public function restore(User $user, WineProduction $wineProduction): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to restore wine production records + // Example: return $user->hasRole('admin'); + return true; + } + + /** + * Determine whether the user can permanently delete the wine production record. + */ + public function forceDelete(User $user, WineProduction $wineProduction): bool + { + // TODO: Implement role-based authorization + // Only administrators should be able to force delete wine production records + // Example: return $user->hasRole('admin'); + return true; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Providers/AppServiceProvider.php b/3BIT/winter-semester/IIS/xnecasr00/app/Providers/AppServiceProvider.php new file mode 100644 index 0000000..8721284 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Providers/AppServiceProvider.php @@ -0,0 +1,33 @@ +," format using integers.'; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/app/Services/BulkPlannedTaskService.php b/3BIT/winter-semester/IIS/xnecasr00/app/Services/BulkPlannedTaskService.php new file mode 100644 index 0000000..83943e5 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/app/Services/BulkPlannedTaskService.php @@ -0,0 +1,209 @@ +whereIn('id', $payload['rows']) + ->get(); + + if ($rows->isEmpty()) { + return [ + 'success' => false, + 'message' => 'No vineyard rows matched the provided selection.', + 'created' => 0, + 'task_ids' => [], + 'errors' => [], + ]; + } + + $plannedDate = Carbon::parse($payload['planned_date'])->startOfDay(); + $executionDate = isset($payload['execution_date']) ? Carbon::parse($payload['execution_date'])->startOfDay() : null; + $note = $payload['note'] ?? null; + $details = $payload['details'] ?? []; + $action = $payload['action']; + + $createdTasks = collect(); + $errors = []; + + DB::transaction(function () use ($rows, $action, $details, $plannedDate, $executionDate, $note, &$createdTasks, &$errors) { + foreach ($rows as $row) { + try { + $taskable = $this->createTaskable($action, $row, $details, $note, $plannedDate); + + $plannedTask = $taskable->plannedTask()->create([ + 'planned_date' => $plannedDate->toDateString(), + 'execution_date' => $executionDate?->toDateString(), + 'type' => ucfirst($action), + 'note' => $note, + ]); + + $createdTasks->push($plannedTask); + } catch (RuntimeException $exception) { + $errors[] = [ + 'row_id' => $row->getKey(), + 'message' => $exception->getMessage(), + ]; + } + } + }); + + $success = $createdTasks->isNotEmpty() && empty($errors); + + return [ + 'success' => $success, + 'message' => $this->buildMessage($createdTasks, $errors, $rows->count()), + 'created_tasks_count' => $createdTasks->count(), + 'task_ids' => $createdTasks->map(fn (PlannedTask $task) => $task->getKey()), + 'errors' => $errors, + ]; + } + + /** + * Create the appropriate taskable model for the action. + */ + protected function createTaskable(string $action, VineyardRow $row, array $details, ?string $note, Carbon $plannedDate) + { + return match ($action) { + 'watering' => $this->createWatering($row, $details, $note), + 'fertilization' => $this->createFertilization($row, $details, $note), + 'spraying' => $this->createSpraying($row, $details, $note), + 'pruning' => $this->createPruning($row, $details, $note), + 'harvest' => $this->createHarvest($row, $details, $note, $plannedDate), + default => throw new RuntimeException("Unsupported planned task action: {$action}"), + }; + } + + protected function createWatering(VineyardRow $row, array $details, ?string $note): Watering + { + $treatment = Treatment::create([ + 'row_id' => $row->getKey(), + 'note' => $note, + ]); + + return Watering::create([ + 'treatment_id' => $treatment->getKey(), + 'time_interval' => $details['time_interval'] ?? null, + 'amount' => $details['amount'] ?? null, + 'note' => $note, + ]); + } + + protected function createFertilization(VineyardRow $row, array $details, ?string $note): Fertilization + { + if (empty($details['substance'])) { + throw new RuntimeException('Fertilization requires a substance name.'); + } + + $treatment = Treatment::create([ + 'row_id' => $row->getKey(), + 'note' => $note, + ]); + + return Fertilization::create([ + 'treatment_id' => $treatment->getKey(), + 'substance' => $details['substance'], + 'concentration' => $details['concentration'] ?? null, + 'note' => $note, + ]); + } + + protected function createSpraying(VineyardRow $row, array $details, ?string $note): Spraying + { + if (empty($details['pesticide'])) { + throw new RuntimeException('Spraying requires a pesticide value.'); + } + + $treatment = Treatment::create([ + 'row_id' => $row->getKey(), + 'note' => $note, + ]); + + return Spraying::create([ + 'treatment_id' => $treatment->getKey(), + 'pesticide' => $details['pesticide'], + 'concentration' => $details['concentration'] ?? null, + 'note' => $note, + ]); + } + + protected function createPruning(VineyardRow $row, array $details, ?string $note): Pruning + { + if (empty($details['method'])) { + throw new RuntimeException('Pruning requires a pruning method.'); + } + + $treatment = Treatment::create([ + 'row_id' => $row->getKey(), + 'note' => $note, + ]); + + return Pruning::create([ + 'treatment_id' => $treatment->getKey(), + 'method' => $details['method'], + 'percentage_removed' => $details['percentage_removed'] ?? null, + 'note' => $note, + ]); + } + + protected function createHarvest(VineyardRow $row, array $details, ?string $note, Carbon $plannedDate): Harvest + { + $variationId = $details['variety_variation_id'] ?? $row->variety_variation_id; + + if (! $variationId) { + throw new RuntimeException('A variety variation must be defined for harvest planning.'); + } + + return Harvest::create([ + 'vineyard_row_id' => $row->getKey(), + 'variety_variation_id' => $variationId, + 'user_id' => $details['user_id'] ?? null, + 'weight' => $details['weight'] ?? 0, + 'sugar_content' => $details['sugar_content'] ?? null, + 'date' => $details['date'] ?? $plannedDate->toDateString(), + 'quality' => $details['quality'] ?? null, + 'grape_condition' => $details['condition'] ?? null, + 'notes' => $note, + 'weather_conditions' => $details['weather'] ?? null, + 'harvest_time' => $details['time'] ?? null, + ]); + } + + protected function buildMessage(Collection $createdTasks, array $errors, int $requestedCount): string + { + if ($createdTasks->isEmpty()) { + return $errors ? 'No tasks were created.' : 'Unable to create planned tasks.'; + } + + if (empty($errors) && $createdTasks->count() === $requestedCount) { + return 'All planned tasks were created successfully.'; + } + + $failed = count($errors); + + return sprintf( + 'Created %d planned tasks%s.', + $createdTasks->count(), + $failed > 0 ? sprintf(' (%d rows could not be processed)', $failed) : '' + ); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/artisan b/3BIT/winter-semester/IIS/xnecasr00/artisan new file mode 100644 index 0000000..c35e31d --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/artisan @@ -0,0 +1,18 @@ +#!/usr/bin/env php +handleCommand(new ArgvInput); + +exit($status); diff --git a/3BIT/winter-semester/IIS/xnecasr00/bootstrap/app.php b/3BIT/winter-semester/IIS/xnecasr00/bootstrap/app.php new file mode 100644 index 0000000..80174d3 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/bootstrap/app.php @@ -0,0 +1,23 @@ +withRouting( + web: __DIR__.'/../routes/web.php', + api: __DIR__.'/../routes/api.php', + commands: __DIR__.'/../routes/console.php', + health: '/up', + ) + ->withMiddleware(function (Middleware $middleware): void { + $middleware->alias([ + 'role' => \App\Http\Middleware\EnsureUserHasRole::class, + 'admin' => \App\Http\Middleware\AdminMiddleware::class, + 'employee' => \App\Http\Middleware\EmployeeMiddleware::class, + ]); + }) + ->withExceptions(function (Exceptions $exceptions): void { + // + })->create(); diff --git a/3BIT/winter-semester/IIS/xnecasr00/bootstrap/cache/.gitignore b/3BIT/winter-semester/IIS/xnecasr00/bootstrap/cache/.gitignore new file mode 100644 index 0000000..d6b7ef3 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/bootstrap/cache/.gitignore @@ -0,0 +1,2 @@ +* +!.gitignore diff --git a/3BIT/winter-semester/IIS/xnecasr00/bootstrap/providers.php b/3BIT/winter-semester/IIS/xnecasr00/bootstrap/providers.php new file mode 100644 index 0000000..38b258d --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/bootstrap/providers.php @@ -0,0 +1,5 @@ + env('APP_NAME', 'Laravel'), + + /* + |-------------------------------------------------------------------------- + | Application Environment + |-------------------------------------------------------------------------- + | + | This value determines the "environment" your application is currently + | running in. This may determine how you prefer to configure various + | services the application utilizes. Set this in your ".env" file. + | + */ + + 'env' => env('APP_ENV', 'production'), + + /* + |-------------------------------------------------------------------------- + | Application Debug Mode + |-------------------------------------------------------------------------- + | + | When your application is in debug mode, detailed error messages with + | stack traces will be shown on every error that occurs within your + | application. If disabled, a simple generic error page is shown. + | + */ + + 'debug' => (bool) env('APP_DEBUG', false), + + /* + |-------------------------------------------------------------------------- + | Application URL + |-------------------------------------------------------------------------- + | + | This URL is used by the console to properly generate URLs when using + | the Artisan command line tool. You should set this to the root of + | the application so that it's available within Artisan commands. + | + */ + + 'url' => env('APP_URL', 'http://localhost'), + + /* + |-------------------------------------------------------------------------- + | Application Timezone + |-------------------------------------------------------------------------- + | + | Here you may specify the default timezone for your application, which + | will be used by the PHP date and date-time functions. The timezone + | is set to "UTC" by default as it is suitable for most use cases. + | + */ + + 'timezone' => 'Europe/Bratislava', + + /* + |-------------------------------------------------------------------------- + | Application Locale Configuration + |-------------------------------------------------------------------------- + | + | The application locale determines the default locale that will be used + | by Laravel's translation / localization methods. This option can be + | set to any locale for which you plan to have translation strings. + | + */ + + 'locale' => env('APP_LOCALE', 'en'), + + 'fallback_locale' => env('APP_FALLBACK_LOCALE', 'en'), + + 'faker_locale' => env('APP_FAKER_LOCALE', 'en_US'), + + /* + |-------------------------------------------------------------------------- + | Encryption Key + |-------------------------------------------------------------------------- + | + | This key is utilized by Laravel's encryption services and should be set + | to a random, 32 character string to ensure that all encrypted values + | are secure. You should do this prior to deploying the application. + | + */ + + 'cipher' => 'AES-256-CBC', + + 'key' => env('APP_KEY'), + + 'previous_keys' => [ + ...array_filter( + explode(',', (string) env('APP_PREVIOUS_KEYS', '')) + ), + ], + + /* + |-------------------------------------------------------------------------- + | Maintenance Mode Driver + |-------------------------------------------------------------------------- + | + | These configuration options determine the driver used to determine and + | manage Laravel's "maintenance mode" status. The "cache" driver will + | allow maintenance mode to be controlled across multiple machines. + | + | Supported drivers: "file", "cache" + | + */ + + 'maintenance' => [ + 'driver' => env('APP_MAINTENANCE_DRIVER', 'file'), + 'store' => env('APP_MAINTENANCE_STORE', 'database'), + ], + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/config/auth.php b/3BIT/winter-semester/IIS/xnecasr00/config/auth.php new file mode 100644 index 0000000..7d1eb0d --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/config/auth.php @@ -0,0 +1,115 @@ + [ + 'guard' => env('AUTH_GUARD', 'web'), + 'passwords' => env('AUTH_PASSWORD_BROKER', 'users'), + ], + + /* + |-------------------------------------------------------------------------- + | Authentication Guards + |-------------------------------------------------------------------------- + | + | Next, you may define every authentication guard for your application. + | Of course, a great default configuration has been defined for you + | which utilizes session storage plus the Eloquent user provider. + | + | All authentication guards have a user provider, which defines how the + | users are actually retrieved out of your database or other storage + | system used by the application. Typically, Eloquent is utilized. + | + | Supported: "session" + | + */ + + 'guards' => [ + 'web' => [ + 'driver' => 'session', + 'provider' => 'users', + ], + ], + + /* + |-------------------------------------------------------------------------- + | User Providers + |-------------------------------------------------------------------------- + | + | All authentication guards have a user provider, which defines how the + | users are actually retrieved out of your database or other storage + | system used by the application. Typically, Eloquent is utilized. + | + | If you have multiple user tables or models you may configure multiple + | providers to represent the model / table. These providers may then + | be assigned to any extra authentication guards you have defined. + | + | Supported: "database", "eloquent" + | + */ + + 'providers' => [ + 'users' => [ + 'driver' => 'eloquent', + 'model' => env('AUTH_MODEL', App\Models\User::class), + ], + + // 'users' => [ + // 'driver' => 'database', + // 'table' => 'users', + // ], + ], + + /* + |-------------------------------------------------------------------------- + | Resetting Passwords + |-------------------------------------------------------------------------- + | + | These configuration options specify the behavior of Laravel's password + | reset functionality, including the table utilized for token storage + | and the user provider that is invoked to actually retrieve users. + | + | The expiry time is the number of minutes that each reset token will be + | considered valid. This security feature keeps tokens short-lived so + | they have less time to be guessed. You may change this as needed. + | + | The throttle setting is the number of seconds a user must wait before + | generating more password reset tokens. This prevents the user from + | quickly generating a very large amount of password reset tokens. + | + */ + + 'passwords' => [ + 'users' => [ + 'provider' => 'users', + 'table' => env('AUTH_PASSWORD_RESET_TOKEN_TABLE', 'password_reset_tokens'), + 'expire' => 60, + 'throttle' => 60, + ], + ], + + /* + |-------------------------------------------------------------------------- + | Password Confirmation Timeout + |-------------------------------------------------------------------------- + | + | Here you may define the number of seconds before a password confirmation + | window expires and users are asked to re-enter their password via the + | confirmation screen. By default, the timeout lasts for three hours. + | + */ + + 'password_timeout' => env('AUTH_PASSWORD_TIMEOUT', 10800), + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/config/cache.php b/3BIT/winter-semester/IIS/xnecasr00/config/cache.php new file mode 100644 index 0000000..c2d927d --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/config/cache.php @@ -0,0 +1,108 @@ + env('CACHE_STORE', 'database'), + + /* + |-------------------------------------------------------------------------- + | Cache Stores + |-------------------------------------------------------------------------- + | + | Here you may define all of the cache "stores" for your application as + | well as their drivers. You may even define multiple stores for the + | same cache driver to group types of items stored in your caches. + | + | Supported drivers: "array", "database", "file", "memcached", + | "redis", "dynamodb", "octane", "null" + | + */ + + 'stores' => [ + + 'array' => [ + 'driver' => 'array', + 'serialize' => false, + ], + + 'database' => [ + 'driver' => 'database', + 'connection' => env('DB_CACHE_CONNECTION'), + 'table' => env('DB_CACHE_TABLE', 'cache'), + 'lock_connection' => env('DB_CACHE_LOCK_CONNECTION'), + 'lock_table' => env('DB_CACHE_LOCK_TABLE'), + ], + + 'file' => [ + 'driver' => 'file', + 'path' => storage_path('framework/cache/data'), + 'lock_path' => storage_path('framework/cache/data'), + ], + + 'memcached' => [ + 'driver' => 'memcached', + 'persistent_id' => env('MEMCACHED_PERSISTENT_ID'), + 'sasl' => [ + env('MEMCACHED_USERNAME'), + env('MEMCACHED_PASSWORD'), + ], + 'options' => [ + // Memcached::OPT_CONNECT_TIMEOUT => 2000, + ], + 'servers' => [ + [ + 'host' => env('MEMCACHED_HOST', '127.0.0.1'), + 'port' => env('MEMCACHED_PORT', 11211), + 'weight' => 100, + ], + ], + ], + + 'redis' => [ + 'driver' => 'redis', + 'connection' => env('REDIS_CACHE_CONNECTION', 'cache'), + 'lock_connection' => env('REDIS_CACHE_LOCK_CONNECTION', 'default'), + ], + + 'dynamodb' => [ + 'driver' => 'dynamodb', + 'key' => env('AWS_ACCESS_KEY_ID'), + 'secret' => env('AWS_SECRET_ACCESS_KEY'), + 'region' => env('AWS_DEFAULT_REGION', 'us-east-1'), + 'table' => env('DYNAMODB_CACHE_TABLE', 'cache'), + 'endpoint' => env('DYNAMODB_ENDPOINT'), + ], + + 'octane' => [ + 'driver' => 'octane', + ], + + ], + + /* + |-------------------------------------------------------------------------- + | Cache Key Prefix + |-------------------------------------------------------------------------- + | + | When utilizing the APC, database, memcached, Redis, and DynamoDB cache + | stores, there might be other applications using the same cache. For + | that reason, you may prefix every cache key to avoid collisions. + | + */ + + 'prefix' => env('CACHE_PREFIX', Str::slug((string) env('APP_NAME', 'laravel')).'-cache-'), + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/config/database.php b/3BIT/winter-semester/IIS/xnecasr00/config/database.php new file mode 100644 index 0000000..83e97da --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/config/database.php @@ -0,0 +1,185 @@ + env('DB_CONNECTION', 'mysql'), + + /* + |-------------------------------------------------------------------------- + | Database Connections + |-------------------------------------------------------------------------- + | + | Below are all of the database connections defined for your application. + | An example configuration is provided for each database system which + | is supported by Laravel. You're free to add / remove connections. + | + */ + + 'connections' => [ + + 'sqlite' => [ + 'driver' => 'sqlite', + 'url' => env('DB_URL'), + 'database' => env('DB_DATABASE', database_path('database.sqlite')), + 'prefix' => '', + 'foreign_key_constraints' => env('DB_FOREIGN_KEYS', true), + 'busy_timeout' => null, + 'journal_mode' => null, + 'synchronous' => null, + 'transaction_mode' => 'DEFERRED', + ], + + 'mysql' => [ + 'driver' => 'mysql', + 'url' => env('DB_URL'), + 'host' => env('DB_HOST', '127.0.0.1'), + 'port' => env('DB_PORT', '3306'), + 'database' => env('DB_DATABASE', 'laravel'), + 'username' => env('DB_USERNAME', 'root'), + 'password' => env('DB_PASSWORD', ''), + 'unix_socket' => env('DB_SOCKET', ''), + 'charset' => env('DB_CHARSET', 'utf8mb4'), + 'collation' => env('DB_COLLATION', 'utf8mb4_unicode_ci'), + 'prefix' => '', + 'prefix_indexes' => true, + 'strict' => true, + 'engine' => null, + 'options' => extension_loaded('pdo_mysql') ? array_filter([ + PDO::MYSQL_ATTR_SSL_CA => env('MYSQL_ATTR_SSL_CA'), + ]) : [], + ], + + 'mariadb' => [ + 'driver' => 'mariadb', + 'url' => env('DB_URL'), + 'host' => env('DB_HOST', '127.0.0.1'), + 'port' => env('DB_PORT', '3306'), + 'database' => env('DB_DATABASE', 'laravel'), + 'username' => env('DB_USERNAME', 'root'), + 'password' => env('DB_PASSWORD', ''), + 'unix_socket' => env('DB_SOCKET', ''), + 'charset' => env('DB_CHARSET', 'utf8mb4'), + 'collation' => env('DB_COLLATION', 'utf8mb4_unicode_ci'), + 'prefix' => '', + 'prefix_indexes' => true, + 'strict' => true, + 'engine' => null, + 'options' => extension_loaded('pdo_mysql') ? array_filter([ + PDO::MYSQL_ATTR_SSL_CA => env('MYSQL_ATTR_SSL_CA'), + ]) : [], + ], + + 'pgsql' => [ + 'driver' => 'pgsql', + 'url' => env('DB_URL'), + 'host' => env('DB_HOST', '127.0.0.1'), + 'port' => env('DB_PORT', '5432'), + 'database' => env('DB_DATABASE', 'laravel'), + 'username' => env('DB_USERNAME', 'root'), + 'password' => env('DB_PASSWORD', ''), + 'charset' => env('DB_CHARSET', 'utf8'), + 'prefix' => '', + 'prefix_indexes' => true, + 'search_path' => 'public', + 'sslmode' => 'prefer', + ], + + 'sqlsrv' => [ + 'driver' => 'sqlsrv', + 'url' => env('DB_URL'), + 'host' => env('DB_HOST', 'localhost'), + 'port' => env('DB_PORT', '1433'), + 'database' => env('DB_DATABASE', 'laravel'), + 'username' => env('DB_USERNAME', 'root'), + 'password' => env('DB_PASSWORD', ''), + 'charset' => env('DB_CHARSET', 'utf8'), + 'prefix' => '', + 'prefix_indexes' => true, + // 'encrypt' => env('DB_ENCRYPT', 'yes'), + // 'trust_server_certificate' => env('DB_TRUST_SERVER_CERTIFICATE', 'false'), + ], + + ], + + /* + |-------------------------------------------------------------------------- + | Migration Repository Table + |-------------------------------------------------------------------------- + | + | This table keeps track of all the migrations that have already run for + | your application. Using this information, we can determine which of + | the migrations on disk haven't actually been run on the database. + | + */ + + 'migrations' => [ + 'table' => 'migrations', + 'update_date_on_publish' => true, + ], + + /* + |-------------------------------------------------------------------------- + | Redis Databases + |-------------------------------------------------------------------------- + | + | Redis is an open source, fast, and advanced key-value store that also + | provides a richer body of commands than a typical key-value system + | such as Memcached. You may define your connection settings here. + | + */ + + 'redis' => [ + + 'client' => env('REDIS_CLIENT', 'phpredis'), + + 'options' => [ + 'cluster' => env('REDIS_CLUSTER', 'redis'), + 'prefix' => env('REDIS_PREFIX', Str::slug((string) env('APP_NAME', 'laravel')).'-database-'), + 'persistent' => env('REDIS_PERSISTENT', false), + ], + + 'default' => [ + 'url' => env('REDIS_URL'), + 'host' => env('REDIS_HOST', '127.0.0.1'), + 'username' => env('REDIS_USERNAME'), + 'password' => env('REDIS_PASSWORD'), + 'port' => env('REDIS_PORT', '6379'), + 'database' => env('REDIS_DB', '0'), + 'max_retries' => env('REDIS_MAX_RETRIES', 3), + 'backoff_algorithm' => env('REDIS_BACKOFF_ALGORITHM', 'decorrelated_jitter'), + 'backoff_base' => env('REDIS_BACKOFF_BASE', 100), + 'backoff_cap' => env('REDIS_BACKOFF_CAP', 1000), + ], + + 'cache' => [ + 'url' => env('REDIS_URL'), + 'host' => env('REDIS_HOST', '127.0.0.1'), + 'username' => env('REDIS_USERNAME'), + 'password' => env('REDIS_PASSWORD'), + 'port' => env('REDIS_PORT', '6379'), + 'database' => env('REDIS_CACHE_DB', '1'), + 'max_retries' => env('REDIS_MAX_RETRIES', 3), + 'backoff_algorithm' => env('REDIS_BACKOFF_ALGORITHM', 'decorrelated_jitter'), + 'backoff_base' => env('REDIS_BACKOFF_BASE', 100), + 'backoff_cap' => env('REDIS_BACKOFF_CAP', 1000), + ], + + ], + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/config/filesystems.php b/3BIT/winter-semester/IIS/xnecasr00/config/filesystems.php new file mode 100644 index 0000000..3d671bd --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/config/filesystems.php @@ -0,0 +1,80 @@ + env('FILESYSTEM_DISK', 'local'), + + /* + |-------------------------------------------------------------------------- + | Filesystem Disks + |-------------------------------------------------------------------------- + | + | Below you may configure as many filesystem disks as necessary, and you + | may even configure multiple disks for the same driver. Examples for + | most supported storage drivers are configured here for reference. + | + | Supported drivers: "local", "ftp", "sftp", "s3" + | + */ + + 'disks' => [ + + 'local' => [ + 'driver' => 'local', + 'root' => storage_path('app/private'), + 'serve' => true, + 'throw' => false, + 'report' => false, + ], + + 'public' => [ + 'driver' => 'local', + 'root' => storage_path('app/public'), + 'url' => env('APP_URL').'/storage', + 'visibility' => 'public', + 'throw' => false, + 'report' => false, + ], + + 's3' => [ + 'driver' => 's3', + 'key' => env('AWS_ACCESS_KEY_ID'), + 'secret' => env('AWS_SECRET_ACCESS_KEY'), + 'region' => env('AWS_DEFAULT_REGION'), + 'bucket' => env('AWS_BUCKET'), + 'url' => env('AWS_URL'), + 'endpoint' => env('AWS_ENDPOINT'), + 'use_path_style_endpoint' => env('AWS_USE_PATH_STYLE_ENDPOINT', false), + 'throw' => false, + 'report' => false, + ], + + ], + + /* + |-------------------------------------------------------------------------- + | Symbolic Links + |-------------------------------------------------------------------------- + | + | Here you may configure the symbolic links that will be created when the + | `storage:link` Artisan command is executed. The array keys should be + | the locations of the links and the values should be their targets. + | + */ + + 'links' => [ + public_path('storage') => storage_path('app/public'), + ], + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/config/logging.php b/3BIT/winter-semester/IIS/xnecasr00/config/logging.php new file mode 100644 index 0000000..9e998a4 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/config/logging.php @@ -0,0 +1,132 @@ + env('LOG_CHANNEL', 'stack'), + + /* + |-------------------------------------------------------------------------- + | Deprecations Log Channel + |-------------------------------------------------------------------------- + | + | This option controls the log channel that should be used to log warnings + | regarding deprecated PHP and library features. This allows you to get + | your application ready for upcoming major versions of dependencies. + | + */ + + 'deprecations' => [ + 'channel' => env('LOG_DEPRECATIONS_CHANNEL', 'null'), + 'trace' => env('LOG_DEPRECATIONS_TRACE', false), + ], + + /* + |-------------------------------------------------------------------------- + | Log Channels + |-------------------------------------------------------------------------- + | + | Here you may configure the log channels for your application. Laravel + | utilizes the Monolog PHP logging library, which includes a variety + | of powerful log handlers and formatters that you're free to use. + | + | Available drivers: "single", "daily", "slack", "syslog", + | "errorlog", "monolog", "custom", "stack" + | + */ + + 'channels' => [ + + 'stack' => [ + 'driver' => 'stack', + 'channels' => explode(',', (string) env('LOG_STACK', 'single')), + 'ignore_exceptions' => false, + ], + + 'single' => [ + 'driver' => 'single', + 'path' => storage_path('logs/laravel.log'), + 'level' => env('LOG_LEVEL', 'debug'), + 'replace_placeholders' => true, + ], + + 'daily' => [ + 'driver' => 'daily', + 'path' => storage_path('logs/laravel.log'), + 'level' => env('LOG_LEVEL', 'debug'), + 'days' => env('LOG_DAILY_DAYS', 14), + 'replace_placeholders' => true, + ], + + 'slack' => [ + 'driver' => 'slack', + 'url' => env('LOG_SLACK_WEBHOOK_URL'), + 'username' => env('LOG_SLACK_USERNAME', 'Laravel Log'), + 'emoji' => env('LOG_SLACK_EMOJI', ':boom:'), + 'level' => env('LOG_LEVEL', 'critical'), + 'replace_placeholders' => true, + ], + + 'papertrail' => [ + 'driver' => 'monolog', + 'level' => env('LOG_LEVEL', 'debug'), + 'handler' => env('LOG_PAPERTRAIL_HANDLER', SyslogUdpHandler::class), + 'handler_with' => [ + 'host' => env('PAPERTRAIL_URL'), + 'port' => env('PAPERTRAIL_PORT'), + 'connectionString' => 'tls://'.env('PAPERTRAIL_URL').':'.env('PAPERTRAIL_PORT'), + ], + 'processors' => [PsrLogMessageProcessor::class], + ], + + 'stderr' => [ + 'driver' => 'monolog', + 'level' => env('LOG_LEVEL', 'debug'), + 'handler' => StreamHandler::class, + 'handler_with' => [ + 'stream' => 'php://stderr', + ], + 'formatter' => env('LOG_STDERR_FORMATTER'), + 'processors' => [PsrLogMessageProcessor::class], + ], + + 'syslog' => [ + 'driver' => 'syslog', + 'level' => env('LOG_LEVEL', 'debug'), + 'facility' => env('LOG_SYSLOG_FACILITY', LOG_USER), + 'replace_placeholders' => true, + ], + + 'errorlog' => [ + 'driver' => 'errorlog', + 'level' => env('LOG_LEVEL', 'debug'), + 'replace_placeholders' => true, + ], + + 'null' => [ + 'driver' => 'monolog', + 'handler' => NullHandler::class, + ], + + 'emergency' => [ + 'path' => storage_path('logs/laravel.log'), + ], + + ], + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/config/mail.php b/3BIT/winter-semester/IIS/xnecasr00/config/mail.php new file mode 100644 index 0000000..522b284 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/config/mail.php @@ -0,0 +1,118 @@ + env('MAIL_MAILER', 'log'), + + /* + |-------------------------------------------------------------------------- + | Mailer Configurations + |-------------------------------------------------------------------------- + | + | Here you may configure all of the mailers used by your application plus + | their respective settings. Several examples have been configured for + | you and you are free to add your own as your application requires. + | + | Laravel supports a variety of mail "transport" drivers that can be used + | when delivering an email. You may specify which one you're using for + | your mailers below. You may also add additional mailers if needed. + | + | Supported: "smtp", "sendmail", "mailgun", "ses", "ses-v2", + | "postmark", "resend", "log", "array", + | "failover", "roundrobin" + | + */ + + 'mailers' => [ + + 'smtp' => [ + 'transport' => 'smtp', + 'scheme' => env('MAIL_SCHEME'), + 'url' => env('MAIL_URL'), + 'host' => env('MAIL_HOST', '127.0.0.1'), + 'port' => env('MAIL_PORT', 2525), + 'username' => env('MAIL_USERNAME'), + 'password' => env('MAIL_PASSWORD'), + 'timeout' => null, + 'local_domain' => env('MAIL_EHLO_DOMAIN', parse_url((string) env('APP_URL', 'http://localhost'), PHP_URL_HOST)), + ], + + 'ses' => [ + 'transport' => 'ses', + ], + + 'postmark' => [ + 'transport' => 'postmark', + // 'message_stream_id' => env('POSTMARK_MESSAGE_STREAM_ID'), + // 'client' => [ + // 'timeout' => 5, + // ], + ], + + 'resend' => [ + 'transport' => 'resend', + ], + + 'sendmail' => [ + 'transport' => 'sendmail', + 'path' => env('MAIL_SENDMAIL_PATH', '/usr/sbin/sendmail -bs -i'), + ], + + 'log' => [ + 'transport' => 'log', + 'channel' => env('MAIL_LOG_CHANNEL'), + ], + + 'array' => [ + 'transport' => 'array', + ], + + 'failover' => [ + 'transport' => 'failover', + 'mailers' => [ + 'smtp', + 'log', + ], + 'retry_after' => 60, + ], + + 'roundrobin' => [ + 'transport' => 'roundrobin', + 'mailers' => [ + 'ses', + 'postmark', + ], + 'retry_after' => 60, + ], + + ], + + /* + |-------------------------------------------------------------------------- + | Global "From" Address + |-------------------------------------------------------------------------- + | + | You may wish for all emails sent by your application to be sent from + | the same address. Here you may specify a name and address that is + | used globally for all emails that are sent by your application. + | + */ + + 'from' => [ + 'address' => env('MAIL_FROM_ADDRESS', 'hello@example.com'), + 'name' => env('MAIL_FROM_NAME', 'Example'), + ], + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/config/queue.php b/3BIT/winter-semester/IIS/xnecasr00/config/queue.php new file mode 100644 index 0000000..df9a1ab --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/config/queue.php @@ -0,0 +1,120 @@ + env('QUEUE_CONNECTION', 'database'), + + /* + |-------------------------------------------------------------------------- + | Queue Connections + |-------------------------------------------------------------------------- + | + | Here you may configure the connection options for every queue backend + | used by your application. An example configuration is provided for + | each backend supported by Laravel. You're also free to add more. + | + | Drivers: "sync", "database", "beanstalkd", "sqs", "redis", "failover", "null" + | + */ + + 'connections' => [ + + 'sync' => [ + 'driver' => 'sync', + ], + + 'database' => [ + 'driver' => 'database', + 'connection' => env('DB_QUEUE_CONNECTION'), + 'table' => env('DB_QUEUE_TABLE', 'jobs'), + 'queue' => env('DB_QUEUE', 'default'), + 'retry_after' => (int) env('DB_QUEUE_RETRY_AFTER', 90), + 'after_commit' => false, + ], + + 'beanstalkd' => [ + 'driver' => 'beanstalkd', + 'host' => env('BEANSTALKD_QUEUE_HOST', 'localhost'), + 'queue' => env('BEANSTALKD_QUEUE', 'default'), + 'retry_after' => (int) env('BEANSTALKD_QUEUE_RETRY_AFTER', 90), + 'block_for' => 0, + 'after_commit' => false, + ], + + 'sqs' => [ + 'driver' => 'sqs', + 'key' => env('AWS_ACCESS_KEY_ID'), + 'secret' => env('AWS_SECRET_ACCESS_KEY'), + 'prefix' => env('SQS_PREFIX', 'https://sqs.us-east-1.amazonaws.com/your-account-id'), + 'queue' => env('SQS_QUEUE', 'default'), + 'suffix' => env('SQS_SUFFIX'), + 'region' => env('AWS_DEFAULT_REGION', 'us-east-1'), + 'after_commit' => false, + ], + + 'redis' => [ + 'driver' => 'redis', + 'connection' => env('REDIS_QUEUE_CONNECTION', 'default'), + 'queue' => env('REDIS_QUEUE', 'default'), + 'retry_after' => (int) env('REDIS_QUEUE_RETRY_AFTER', 90), + 'block_for' => null, + 'after_commit' => false, + ], + + 'failover' => [ + 'driver' => 'failover', + 'connections' => [ + 'database', + 'sync', + ], + ], + + ], + + /* + |-------------------------------------------------------------------------- + | Job Batching + |-------------------------------------------------------------------------- + | + | The following options configure the database and table that store job + | batching information. These options can be updated to any database + | connection and table which has been defined by your application. + | + */ + + 'batching' => [ + 'database' => env('DB_CONNECTION', 'sqlite'), + 'table' => 'job_batches', + ], + + /* + |-------------------------------------------------------------------------- + | Failed Queue Jobs + |-------------------------------------------------------------------------- + | + | These options configure the behavior of failed queue job logging so you + | can control how and where failed jobs are stored. Laravel ships with + | support for storing failed jobs in a simple file or in a database. + | + | Supported drivers: "database-uuids", "dynamodb", "file", "null" + | + */ + + 'failed' => [ + 'driver' => env('QUEUE_FAILED_DRIVER', 'database-uuids'), + 'database' => env('DB_CONNECTION', 'sqlite'), + 'table' => 'failed_jobs', + ], + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/config/services.php b/3BIT/winter-semester/IIS/xnecasr00/config/services.php new file mode 100644 index 0000000..6182e4b --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/config/services.php @@ -0,0 +1,38 @@ + [ + 'token' => env('POSTMARK_TOKEN'), + ], + + 'resend' => [ + 'key' => env('RESEND_KEY'), + ], + + 'ses' => [ + 'key' => env('AWS_ACCESS_KEY_ID'), + 'secret' => env('AWS_SECRET_ACCESS_KEY'), + 'region' => env('AWS_DEFAULT_REGION', 'us-east-1'), + ], + + 'slack' => [ + 'notifications' => [ + 'bot_user_oauth_token' => env('SLACK_BOT_USER_OAUTH_TOKEN'), + 'channel' => env('SLACK_BOT_USER_DEFAULT_CHANNEL'), + ], + ], + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/config/session.php b/3BIT/winter-semester/IIS/xnecasr00/config/session.php new file mode 100644 index 0000000..bc45901 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/config/session.php @@ -0,0 +1,217 @@ + env('SESSION_DRIVER', 'database'), + + /* + |-------------------------------------------------------------------------- + | Session Lifetime + |-------------------------------------------------------------------------- + | + | Here you may specify the number of minutes that you wish the session + | to be allowed to remain idle before it expires. If you want them + | to expire immediately when the browser is closed then you may + | indicate that via the expire_on_close configuration option. + | + */ + + 'lifetime' => (int) env('SESSION_LIFETIME', 120), + + 'expire_on_close' => env('SESSION_EXPIRE_ON_CLOSE', false), + + /* + |-------------------------------------------------------------------------- + | Session Encryption + |-------------------------------------------------------------------------- + | + | This option allows you to easily specify that all of your session data + | should be encrypted before it's stored. All encryption is performed + | automatically by Laravel and you may use the session like normal. + | + */ + + 'encrypt' => env('SESSION_ENCRYPT', false), + + /* + |-------------------------------------------------------------------------- + | Session File Location + |-------------------------------------------------------------------------- + | + | When utilizing the "file" session driver, the session files are placed + | on disk. The default storage location is defined here; however, you + | are free to provide another location where they should be stored. + | + */ + + 'files' => storage_path('framework/sessions'), + + /* + |-------------------------------------------------------------------------- + | Session Database Connection + |-------------------------------------------------------------------------- + | + | When using the "database" or "redis" session drivers, you may specify a + | connection that should be used to manage these sessions. This should + | correspond to a connection in your database configuration options. + | + */ + + 'connection' => env('SESSION_CONNECTION'), + + /* + |-------------------------------------------------------------------------- + | Session Database Table + |-------------------------------------------------------------------------- + | + | When using the "database" session driver, you may specify the table to + | be used to store sessions. Of course, a sensible default is defined + | for you; however, you're welcome to change this to another table. + | + */ + + 'table' => env('SESSION_TABLE', 'sessions'), + + /* + |-------------------------------------------------------------------------- + | Session Cache Store + |-------------------------------------------------------------------------- + | + | When using one of the framework's cache driven session backends, you may + | define the cache store which should be used to store the session data + | between requests. This must match one of your defined cache stores. + | + | Affects: "dynamodb", "memcached", "redis" + | + */ + + 'store' => env('SESSION_STORE'), + + /* + |-------------------------------------------------------------------------- + | Session Sweeping Lottery + |-------------------------------------------------------------------------- + | + | Some session drivers must manually sweep their storage location to get + | rid of old sessions from storage. Here are the chances that it will + | happen on a given request. By default, the odds are 2 out of 100. + | + */ + + 'lottery' => [2, 100], + + /* + |-------------------------------------------------------------------------- + | Session Cookie Name + |-------------------------------------------------------------------------- + | + | Here you may change the name of the session cookie that is created by + | the framework. Typically, you should not need to change this value + | since doing so does not grant a meaningful security improvement. + | + */ + + 'cookie' => env( + 'SESSION_COOKIE', + Str::slug((string) env('APP_NAME', 'laravel')).'-session' + ), + + /* + |-------------------------------------------------------------------------- + | Session Cookie Path + |-------------------------------------------------------------------------- + | + | The session cookie path determines the path for which the cookie will + | be regarded as available. Typically, this will be the root path of + | your application, but you're free to change this when necessary. + | + */ + + 'path' => env('SESSION_PATH', '/'), + + /* + |-------------------------------------------------------------------------- + | Session Cookie Domain + |-------------------------------------------------------------------------- + | + | This value determines the domain and subdomains the session cookie is + | available to. By default, the cookie will be available to the root + | domain and all subdomains. Typically, this shouldn't be changed. + | + */ + + 'domain' => env('SESSION_DOMAIN'), + + /* + |-------------------------------------------------------------------------- + | HTTPS Only Cookies + |-------------------------------------------------------------------------- + | + | By setting this option to true, session cookies will only be sent back + | to the server if the browser has a HTTPS connection. This will keep + | the cookie from being sent to you when it can't be done securely. + | + */ + + 'secure' => env('SESSION_SECURE_COOKIE'), + + /* + |-------------------------------------------------------------------------- + | HTTP Access Only + |-------------------------------------------------------------------------- + | + | Setting this value to true will prevent JavaScript from accessing the + | value of the cookie and the cookie will only be accessible through + | the HTTP protocol. It's unlikely you should disable this option. + | + */ + + 'http_only' => env('SESSION_HTTP_ONLY', true), + + /* + |-------------------------------------------------------------------------- + | Same-Site Cookies + |-------------------------------------------------------------------------- + | + | This option determines how your cookies behave when cross-site requests + | take place, and can be used to mitigate CSRF attacks. By default, we + | will set this value to "lax" to permit secure cross-site requests. + | + | See: https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/Set-Cookie#samesitesamesite-value + | + | Supported: "lax", "strict", "none", null + | + */ + + 'same_site' => env('SESSION_SAME_SITE', 'lax'), + + /* + |-------------------------------------------------------------------------- + | Partitioned Cookies + |-------------------------------------------------------------------------- + | + | Setting this value to true will tie the cookie to the top-level site for + | a cross-site context. Partitioned cookies are accepted by the browser + | when flagged "secure" and the Same-Site attribute is set to "none". + | + */ + + 'partitioned' => env('SESSION_PARTITIONED_COOKIE', false), + +]; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/.gitignore b/3BIT/winter-semester/IIS/xnecasr00/database/.gitignore new file mode 100644 index 0000000..9b19b93 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/.gitignore @@ -0,0 +1 @@ +*.sqlite* diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/FertilizationFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/FertilizationFactory.php new file mode 100644 index 0000000..e8fc670 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/FertilizationFactory.php @@ -0,0 +1,23 @@ + + */ +class FertilizationFactory extends Factory +{ + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/GrapeVarietyFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/GrapeVarietyFactory.php new file mode 100644 index 0000000..64209de --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/GrapeVarietyFactory.php @@ -0,0 +1,70 @@ + + */ +class GrapeVarietyFactory extends Factory +{ + protected $model = GrapeVariety::class; + + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + $varieties = [ + 'Chardonnay', 'Sauvignon Blanc', 'Riesling', 'Pinot Grigio', 'Gewürztraminer', + 'Cabernet Sauvignon', 'Merlot', 'Pinot Noir', 'Syrah', 'Malbec', + 'Grüner Veltliner', 'Blaufränkisch', 'St. Laurent', 'Müller Thurgau' + ]; + + $wineTypes = ['white', 'red', 'rose']; + $selectedType = fake()->randomElement($wineTypes); + + return [ + 'variety_name' => fake()->randomElement($varieties) . ' ' . fake()->unique()->word(), + 'description' => fake()->paragraph(3), + 'origin' => fake()->country(), + 'wine_type' => $selectedType, + 'characteristics' => fake()->sentence(6), + 'image_url' => fake()->optional()->imageUrl(640, 480, 'wine', true), + ]; + } + + /** + * Indicate that the variety is for white wine. + */ + public function white(): static + { + return $this->state(fn (array $attributes) => [ + 'wine_type' => 'white', + ]); + } + + /** + * Indicate that the variety is for red wine. + */ + public function red(): static + { + return $this->state(fn (array $attributes) => [ + 'wine_type' => 'red', + ]); + } + + /** + * Indicate that the variety is for rosé wine. + */ + public function rose(): static + { + return $this->state(fn (array $attributes) => [ + 'wine_type' => 'rose', + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/HarvestFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/HarvestFactory.php new file mode 100644 index 0000000..45717d9 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/HarvestFactory.php @@ -0,0 +1,120 @@ + + */ +class HarvestFactory extends Factory +{ + protected $model = Harvest::class; + + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + $qualities = ['excellent', 'good', 'fair', 'poor']; + $conditions = ['healthy', 'slightly damaged', 'botrytis', 'overripe']; + + $weatherConditions = [ + 'Sunny, 20°C', + 'Sunny, 22°C', + 'Partly cloudy, 18°C', + 'Overcast, 16°C', + 'Clear sky, 24°C', + 'Light rain, 14°C' + ]; + + return [ + 'vineyard_row_id' => VineyardRow::factory(), + 'variety_variation_id' => VarietyVariation::factory(), + 'user_id' => User::factory(), + 'weight' => fake()->randomFloat(2, 300.0, 1200.0), + 'sugar_content' => fake()->randomFloat(2, 16.0, 26.0), + 'date' => fake()->dateTimeBetween('-1 year', 'now'), + 'quality' => fake()->randomElement($qualities), + 'grape_condition' => fake()->randomElement($conditions), + 'notes' => fake()->optional()->sentence(12), + 'weather_conditions' => fake()->randomElement($weatherConditions), + 'harvest_time' => fake()->time('H:i:s'), + ]; + } + + /** + * Indicate that the harvest is of excellent quality. + */ + public function excellent(): static + { + return $this->state(fn (array $attributes) => [ + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + ]); + } + + /** + * Indicate that the harvest is recent. + */ + public function recent(): static + { + return $this->state(fn (array $attributes) => [ + 'date' => fake()->dateTimeBetween('-3 months', 'now'), + ]); + } + + /** + * Keep the harvest aligned with its vineyard row's variation. + */ + public function configure(): static + { + return $this->afterMaking(function (Harvest $harvest) { + $row = $harvest->relationLoaded('vineyardRow') ? $harvest->vineyardRow : null; + + if (! $row && $harvest->vineyard_row_id) { + $row = VineyardRow::find($harvest->vineyard_row_id); + if ($row) { + $harvest->setRelation('vineyardRow', $row); + } + } + + if ($row) { + $harvest->variety_variation_id = $row->variety_variation_id; + return; + } + + $variationId = $this->normalizeVarietyVariationId($harvest->variety_variation_id); + + if (! $variationId) { + $variation = VarietyVariation::factory()->create(); + $variationId = $variation->getKey(); + $harvest->variety_variation_id = $variationId; + } else { + $harvest->variety_variation_id = $variationId; + } + + $row = VineyardRow::factory()->create([ + 'variety_variation_id' => $harvest->variety_variation_id, + ]); + + $harvest->vineyard_row_id = $row->getKey(); + $harvest->setRelation('vineyardRow', $row); + }); + } + + private function normalizeVarietyVariationId(mixed $value): ?int + { + if ($value instanceof VarietyVariation) { + return $value->getKey(); + } + + return $value !== null ? (int) $value : null; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/PlannedTaskFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PlannedTaskFactory.php new file mode 100644 index 0000000..7af9706 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PlannedTaskFactory.php @@ -0,0 +1,56 @@ + + */ +class PlannedTaskFactory extends Factory +{ + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + $plannedDate = fake()->dateTimeBetween('-1 week', '+3 weeks'); + + return [ + 'planned_date' => $plannedDate, + 'execution_date' => fake()->optional()->dateTimeBetween($plannedDate, '+2 months'), + 'type' => 'treatment', + 'note' => fake()->optional()->sentence(10), + 'taskable_type' => Treatment::class, + 'taskable_id' => Treatment::factory(), + ]; + } + + /** + * Target a specific treatment. + */ + public function forTreatment(Treatment $treatment): static + { + return $this->state(fn (array $attributes) => [ + 'type' => 'treatment', + 'taskable_type' => Treatment::class, + 'taskable_id' => $treatment->getKey(), + ]); + } + + /** + * Target a specific harvest. + */ + public function forHarvest(Harvest $harvest): static + { + return $this->state(fn (array $attributes) => [ + 'type' => 'harvest', + 'taskable_type' => Harvest::class, + 'taskable_id' => $harvest->getKey(), + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/PruningFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PruningFactory.php new file mode 100644 index 0000000..e4fad4b --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PruningFactory.php @@ -0,0 +1,23 @@ + + */ +class PruningFactory extends Factory +{ + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/PsprayingFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PsprayingFactory.php new file mode 100644 index 0000000..a7bdbc5 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PsprayingFactory.php @@ -0,0 +1,23 @@ + + */ +class PsprayingFactory extends Factory +{ + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/PurchaseFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PurchaseFactory.php new file mode 100644 index 0000000..1e54a2a --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PurchaseFactory.php @@ -0,0 +1,36 @@ + + */ +class PurchaseFactory extends Factory +{ + protected $model = Purchase::class; + + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + $statuses = ['pending', 'completed', 'cancelled']; + + return [ + 'user_id' => User::factory(), + 'wine_id' => Wine::factory(), + 'amount' => fake()->numberBetween(1, 12), + 'price' => fake()->randomFloat(2, 20.0, 500.0), + 'status' => fake()->randomElement($statuses), + 'purchased_at' => fake()->optional()->dateTimeBetween('-1 month', 'now'), + 'note' => fake()->optional()->sentence(8), + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/PurchaseItemFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PurchaseItemFactory.php new file mode 100644 index 0000000..c76d1dd --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/PurchaseItemFactory.php @@ -0,0 +1,30 @@ + + */ +class PurchaseItemFactory extends Factory +{ + protected $model = PurchaseItem::class; + + public function definition(): array + { + $quantity = fake()->numberBetween(1, 6); + $unitPrice = fake()->randomFloat(2, 5, 120); + + return [ + 'purchase_id' => Purchase::factory(), + 'wine_id' => Wine::factory(), + 'quantity' => $quantity, + 'unit_price' => $unitPrice, + 'line_total' => round($quantity * $unitPrice, 2), + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/TreatmentFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/TreatmentFactory.php new file mode 100644 index 0000000..78bf019 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/TreatmentFactory.php @@ -0,0 +1,38 @@ + + */ +class TreatmentFactory extends Factory +{ + protected $model = Treatment::class; + + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + return [ + 'row_id' => VineyardRow::factory(), + 'note' => fake()->optional()->sentence(8), + ]; + } + + /** + * Associate the treatment with a specific vineyard row. + */ + public function forVineyardRow(VineyardRow $row): static + { + return $this->state(fn (array $attributes) => [ + 'row_id' => $row->getKey(), + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/UserFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/UserFactory.php new file mode 100644 index 0000000..ced783a --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/UserFactory.php @@ -0,0 +1,47 @@ + + */ +class UserFactory extends Factory +{ + /** + * The current password being used by the factory. + */ + protected static ?string $password; + + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + return [ + 'name' => fake()->name(), + 'username' => fake()->unique()->userName(), + 'email' => fake()->unique()->safeEmail(), + 'email_verified_at' => now(), + 'password' => static::$password ??= Hash::make('password'), + 'remember_token' => Str::random(10), + 'role' => UserRole::WINEMAKER, + ]; + } + + /** + * Indicate that the model's email address should be unverified. + */ + public function unverified(): static + { + return $this->state(fn (array $attributes) => [ + 'email_verified_at' => null, + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/VarietyVariationFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/VarietyVariationFactory.php new file mode 100644 index 0000000..9ee310e --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/VarietyVariationFactory.php @@ -0,0 +1,67 @@ + + */ +class VarietyVariationFactory extends Factory +{ + protected $model = VarietyVariation::class; + + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + $colors = ['green', 'blue', 'yellow', 'red']; + $statuses = ['active', 'inactive']; + + $ripeningPeriods = [ + 'Early September', + 'Mid-September', + 'Late September', + 'Early October', + 'Mid-October', + 'Late October', + 'September - early October', + 'Late September - mid-October' + ]; + + return [ + 'grape_variety_id' => GrapeVariety::factory(), + 'color' => fake()->randomElement($colors), + 'description' => fake()->sentence(8), + 'typical_sugar_content' => fake()->randomFloat(2, 16.0, 25.0), + 'typical_alcohol' => fake()->randomFloat(2, 10.0, 14.5), + 'ripening_period' => fake()->randomElement($ripeningPeriods), + 'status' => fake()->randomElement($statuses), + ]; + } + + /** + * Indicate that the variation is active. + */ + public function active(): static + { + return $this->state(fn (array $attributes) => [ + 'status' => 'active', + ]); + } + + /** + * Indicate that the variation is inactive. + */ + public function inactive(): static + { + return $this->state(fn (array $attributes) => [ + 'status' => 'inactive', + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/VineyardRowFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/VineyardRowFactory.php new file mode 100644 index 0000000..c2c05d7 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/VineyardRowFactory.php @@ -0,0 +1,78 @@ + + */ +class VineyardRowFactory extends Factory +{ + protected $model = VineyardRow::class; + + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + $locations = [ + 'North slope', + 'South slope', + 'East slope', + 'West slope', + 'Northeast slope', + 'Southeast slope', + 'Southwest slope', + 'Northwest slope', + 'Valley floor', + 'Hilltop' + ]; + + $statuses = ['active', 'inactive', 'replanting']; + + return [ + 'variety_variation_id' => VarietyVariation::factory(), + 'vine_count' => fake()->numberBetween(50, 200), + 'planting_year' => fake()->numberBetween(2000, 2023), + 'area' => fake()->randomFloat(2, 100.0, 800.0), + 'location' => fake()->randomElement($locations), + 'status' => fake()->randomElement($statuses), + 'notes' => fake()->optional()->sentence(10), + ]; + } + + /** + * Indicate that the vineyard row is active. + */ + public function active(): static + { + return $this->state(fn (array $attributes) => [ + 'status' => 'active', + ]); + } + + /** + * Indicate that the vineyard row is being replanted. + */ + public function replanting(): static + { + return $this->state(fn (array $attributes) => [ + 'status' => 'replanting', + ]); + } + + /** + * Assign the vineyard row to a specific variety variation. + */ + public function forVarietyVariation(VarietyVariation $variation): static + { + return $this->state(fn (array $attributes) => [ + 'variety_variation_id' => $variation->getKey(), + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/WateringFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/WateringFactory.php new file mode 100644 index 0000000..aa1a338 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/WateringFactory.php @@ -0,0 +1,23 @@ + + */ +class WateringFactory extends Factory +{ + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + return [ + // + ]; + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/WineFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/WineFactory.php new file mode 100644 index 0000000..074f527 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/WineFactory.php @@ -0,0 +1,87 @@ + + */ +class WineFactory extends Factory +{ + protected $model = Wine::class; + + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + $wineTypes = ['white', 'red', 'rose']; + $statuses = ['in_production', 'aging', 'ready', 'sold_out']; + $bottlesProduced = fake()->numberBetween(300, 3000); + $bottlesSold = fake()->numberBetween(0, $bottlesProduced / 2); + + $wineNames = [ + 'Reserve Selection', + 'Estate Classic', + 'Late Harvest', + 'Premium Vintage', + 'Grand Cru', + 'Special Edition', + 'Limited Release', + 'Heritage Collection' + ]; + + return [ + 'vintage' => fake()->numberBetween(2018, 2024), + 'grape_variety_id' => GrapeVariety::factory(), + 'wine_name' => fake()->randomElement($wineNames) . ' ' . fake()->year(), + 'wine_type' => fake()->randomElement($wineTypes), + 'description' => fake()->paragraph(2), + 'alcohol_percentage' => fake()->randomFloat(2, 10.0, 14.5), + 'bottles_produced' => $bottlesProduced, + 'bottles_in_stock' => $bottlesProduced - $bottlesSold, + 'price_per_bottle' => fake()->randomFloat(2, 150.0, 500.0), + 'bottle_volume' => fake()->randomElement([0.375, 0.75, 1.5]), + 'production_date' => fake()->dateTimeBetween('-2 years', '-6 months'), + 'bottling_date' => fake()->dateTimeBetween('-6 months', 'now'), + 'status' => fake()->randomElement($statuses), + 'image_url' => fake()->optional()->imageUrl(640, 480, 'wine', true), + ]; + } + + /** + * Indicate that the wine is ready for sale. + */ + public function ready(): static + { + return $this->state(fn (array $attributes) => [ + 'status' => 'ready', + ]); + } + + /** + * Indicate that the wine is sold out. + */ + public function soldOut(): static + { + return $this->state(fn (array $attributes) => [ + 'status' => 'sold_out', + 'bottles_in_stock' => 0, + ]); + } + + /** + * Indicate that the wine is aging. + */ + public function aging(): static + { + return $this->state(fn (array $attributes) => [ + 'status' => 'aging', + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/factories/WineProductionFactory.php b/3BIT/winter-semester/IIS/xnecasr00/database/factories/WineProductionFactory.php new file mode 100644 index 0000000..2412ed7 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/factories/WineProductionFactory.php @@ -0,0 +1,41 @@ + + */ +class WineProductionFactory extends Factory +{ + protected $model = WineProduction::class; + + /** + * Define the model's default state. + * + * @return array + */ + public function definition(): array + { + return [ + 'wine_id' => Wine::factory(), + 'harvest_id' => Harvest::factory(), + 'consumed_weight' => fake()->randomFloat(2, 100.0, 1000.0), + 'blend_percentage' => fake()->randomFloat(2, 10.0, 100.0), + ]; + } + + /** + * Indicate that this is a single-variety wine (100% blend). + */ + public function singleVariety(): static + { + return $this->state(fn (array $attributes) => [ + 'blend_percentage' => 100.00, + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/0001_01_01_000000_create_users_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/0001_01_01_000000_create_users_table.php new file mode 100644 index 0000000..05fb5d9 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/0001_01_01_000000_create_users_table.php @@ -0,0 +1,49 @@ +id(); + $table->string('name'); + $table->string('email')->unique(); + $table->timestamp('email_verified_at')->nullable(); + $table->string('password'); + $table->rememberToken(); + $table->timestamps(); + }); + + Schema::create('password_reset_tokens', function (Blueprint $table) { + $table->string('email')->primary(); + $table->string('token'); + $table->timestamp('created_at')->nullable(); + }); + + Schema::create('sessions', function (Blueprint $table) { + $table->string('id')->primary(); + $table->foreignId('user_id')->nullable()->index(); + $table->string('ip_address', 45)->nullable(); + $table->text('user_agent')->nullable(); + $table->longText('payload'); + $table->integer('last_activity')->index(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('users'); + Schema::dropIfExists('password_reset_tokens'); + Schema::dropIfExists('sessions'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/0001_01_01_000001_create_cache_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/0001_01_01_000001_create_cache_table.php new file mode 100644 index 0000000..b9c106b --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/0001_01_01_000001_create_cache_table.php @@ -0,0 +1,35 @@ +string('key')->primary(); + $table->mediumText('value'); + $table->integer('expiration'); + }); + + Schema::create('cache_locks', function (Blueprint $table) { + $table->string('key')->primary(); + $table->string('owner'); + $table->integer('expiration'); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('cache'); + Schema::dropIfExists('cache_locks'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/0001_01_01_000002_create_jobs_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/0001_01_01_000002_create_jobs_table.php new file mode 100644 index 0000000..425e705 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/0001_01_01_000002_create_jobs_table.php @@ -0,0 +1,57 @@ +id(); + $table->string('queue')->index(); + $table->longText('payload'); + $table->unsignedTinyInteger('attempts'); + $table->unsignedInteger('reserved_at')->nullable(); + $table->unsignedInteger('available_at'); + $table->unsignedInteger('created_at'); + }); + + Schema::create('job_batches', function (Blueprint $table) { + $table->string('id')->primary(); + $table->string('name'); + $table->integer('total_jobs'); + $table->integer('pending_jobs'); + $table->integer('failed_jobs'); + $table->longText('failed_job_ids'); + $table->mediumText('options')->nullable(); + $table->integer('cancelled_at')->nullable(); + $table->integer('created_at'); + $table->integer('finished_at')->nullable(); + }); + + Schema::create('failed_jobs', function (Blueprint $table) { + $table->id(); + $table->string('uuid')->unique(); + $table->text('connection'); + $table->text('queue'); + $table->longText('payload'); + $table->longText('exception'); + $table->timestamp('failed_at')->useCurrent(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('jobs'); + Schema::dropIfExists('job_batches'); + Schema::dropIfExists('failed_jobs'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2023_10_25_000008_create_planned_tasks_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2023_10_25_000008_create_planned_tasks_table.php new file mode 100644 index 0000000..ab05582 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2023_10_25_000008_create_planned_tasks_table.php @@ -0,0 +1,32 @@ +id('planned_task_id'); + $table->date('planned_date'); + $table->date('execution_date')->nullable(); + $table->string('type'); + $table->string('note')->nullable(); + $table->morphs('taskable'); // Creates taskable_id and taskable_type columns + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('planned_tasks'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000001_create_grape_varieties_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000001_create_grape_varieties_table.php new file mode 100644 index 0000000..e10a951 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000001_create_grape_varieties_table.php @@ -0,0 +1,33 @@ +id(); + $table->string('variety_name')->comment('Name of the grape variety'); + $table->text('description')->nullable()->comment('Detailed description of the grape variety'); + $table->string('origin')->nullable()->comment('Origin/region of the variety'); + $table->enum('wine_type', ['red', 'white', 'rose'])->nullable()->comment('Wine type classification'); + $table->text('characteristics')->nullable()->comment('General characteristics and properties'); + $table->string('image_url')->nullable()->comment('Image URL for catalog display'); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('grape_varieties'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000002_create_variety_variations_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000002_create_variety_variations_table.php new file mode 100644 index 0000000..2ffc495 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000002_create_variety_variations_table.php @@ -0,0 +1,34 @@ +id(); + $table->foreignId('grape_variety_id')->constrained('grape_varieties')->onDelete('cascade')->comment('Reference to grape variety'); + $table->enum('color', ['green', 'blue', 'yellow', 'red'])->comment('Color variation of the grape'); + $table->text('description')->nullable()->comment('Description of this specific variation'); + $table->decimal('typical_sugar_content', 5, 2)->nullable()->comment('Typical sugar content in NM (°NM)'); + $table->decimal('typical_alcohol', 5, 2)->nullable()->comment('Typical alcohol content percentage'); + $table->string('ripening_period')->nullable()->comment('Ripening period (e.g., September - early October)'); + $table->enum('status', ['active', 'inactive'])->default('active')->comment('Variation status'); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('variety_variations'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000003_create_vineyard_rows_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000003_create_vineyard_rows_table.php new file mode 100644 index 0000000..262c531 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000003_create_vineyard_rows_table.php @@ -0,0 +1,34 @@ +id(); + $table->foreignId('variety_variation_id')->nullable()->constrained('variety_variations')->onDelete('cascade')->comment('Reference to variety variation'); + $table->integer('vine_count')->comment('Number of vine plants/heads in this row'); + $table->integer('planting_year')->comment('Year when the row was planted'); + $table->decimal('area', 8, 2)->nullable()->comment('Area size in hectares'); + $table->string('location')->nullable()->comment('Physical location description'); + $table->enum('status', ['active', 'inactive', 'replanting'])->default('active')->comment('Row status'); + $table->text('notes')->nullable()->comment('Additional notes and observations'); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('vineyard_rows'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000004_create_harvests_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000004_create_harvests_table.php new file mode 100644 index 0000000..7d58c95 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000004_create_harvests_table.php @@ -0,0 +1,38 @@ +id(); + $table->foreignId('vineyard_row_id')->constrained('vineyard_rows')->onDelete('cascade')->comment('Reference to vineyard row'); + $table->foreignId('variety_variation_id')->constrained('variety_variations')->onDelete('cascade')->comment('Reference to variety variation'); + $table->foreignId('user_id')->nullable()->constrained('users')->onDelete('set null')->comment('User who performed the harvest'); + $table->decimal('weight', 8, 2)->comment('Weight of harvested grapes in kg'); + $table->decimal('sugar_content', 5, 2)->nullable()->comment('Sugar content in NM (°NM)'); + $table->date('date')->comment('Harvest date'); + $table->enum('quality', ['excellent', 'good', 'fair', 'poor'])->nullable()->comment('Quality grade of the harvest'); + $table->string('grape_condition')->nullable()->comment('Condition of grapes at harvest'); + $table->text('notes')->nullable()->comment('Harvest notes and observations'); + $table->text('weather_conditions')->nullable()->comment('Weather conditions during harvest'); + $table->time('harvest_time')->nullable()->comment('Time of day when harvest occurred'); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('harvests'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000005_create_wines_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000005_create_wines_table.php new file mode 100644 index 0000000..5daa4d5 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000005_create_wines_table.php @@ -0,0 +1,41 @@ +id(); + $table->integer('vintage')->comment('Wine vintage year'); + $table->foreignId('grape_variety_id')->constrained('grape_varieties')->onDelete('cascade')->comment('Primary grape variety'); + $table->string('wine_name')->comment('Name of the wine product'); + $table->enum('wine_type', ['red', 'white', 'rose'])->nullable()->comment('Wine type'); + $table->text('description')->nullable()->comment('Wine description and tasting notes'); + $table->decimal('alcohol_percentage', 5, 2)->nullable()->comment('Alcohol content percentage'); + $table->integer('bottles_produced')->nullable()->comment('Total number of bottles produced'); + $table->integer('bottles_in_stock')->default(0)->comment('Current bottles in stock'); + $table->decimal('price_per_bottle', 8, 2)->nullable()->comment('Price per bottle'); + $table->decimal('bottle_volume', 5, 3)->default(0.75)->comment('Bottle volume in liters'); + $table->date('production_date')->nullable()->comment('Wine production date'); + $table->date('bottling_date')->nullable()->comment('Bottling date'); + $table->enum('status', ['in_production', 'aging', 'ready', 'sold_out'])->default('in_production')->comment('Wine status'); + $table->string('image_url')->nullable()->comment('Image URL for catalog display'); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('wines'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000006_create_wine_productions_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000006_create_wine_productions_table.php new file mode 100644 index 0000000..f881cf4 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_21_000006_create_wine_productions_table.php @@ -0,0 +1,34 @@ +id(); + $table->foreignId('wine_id')->constrained('wines')->onDelete('cascade')->comment('Reference to wine product'); + $table->foreignId('harvest_id')->constrained('harvests')->onDelete('cascade')->comment('Reference to harvest used'); + $table->decimal('consumed_weight', 8, 2)->comment('Weight of grapes consumed from this harvest'); + $table->decimal('blend_percentage', 5, 2)->nullable()->comment('Percentage in blend composition'); + $table->timestamps(); + + // Ensure unique combination of wine and harvest + $table->unique(['wine_id', 'harvest_id']); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('wine_productions'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_24_160143_create_grape_variety_variants_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_24_160143_create_grape_variety_variants_table.php new file mode 100644 index 0000000..166e801 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_24_160143_create_grape_variety_variants_table.php @@ -0,0 +1,29 @@ +id(); + $table->foreignId('grape_variety_id')->constrained('grape_varieties')->onDelete('cascade'); + $table->string('color'); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('grape_variety_variants'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_28_230000_remove_legacy_variety_version_columns.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_28_230000_remove_legacy_variety_version_columns.php new file mode 100644 index 0000000..53af2c3 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_28_230000_remove_legacy_variety_version_columns.php @@ -0,0 +1,60 @@ +dropColumn('grape_variety_version'); + }); + } + + // Drop legacy variety version columns from harvests if present + if (Schema::hasColumn('harvests', 'variety_version')) { + Schema::table('harvests', function (Blueprint $table) { + $table->dropColumn('variety_version'); + }); + } + + if (Schema::hasColumn('harvests', 'grape_variety_version')) { + Schema::table('harvests', function (Blueprint $table) { + $table->dropColumn('grape_variety_version'); + }); + } + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + // Restore columns as nullable integers if rolling back (safe default) + if (! Schema::hasColumn('vineyard_rows', 'grape_variety_version')) { + Schema::table('vineyard_rows', function (Blueprint $table) { + $table->integer('grape_variety_version')->nullable()->after('grape_variety_variant_id'); + }); + } + + if (! Schema::hasColumn('harvests', 'variety_version')) { + Schema::table('harvests', function (Blueprint $table) { + $table->integer('variety_version')->nullable()->after('grape_variety_variant_id'); + }); + } + + if (! Schema::hasColumn('harvests', 'grape_variety_version')) { + Schema::table('harvests', function (Blueprint $table) { + $table->integer('grape_variety_version')->nullable()->after('grape_variety_variant_id'); + }); + } + } +} + diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_31_000001_add_role_to_users_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_31_000001_add_role_to_users_table.php new file mode 100644 index 0000000..e72d6a9 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_31_000001_add_role_to_users_table.php @@ -0,0 +1,32 @@ +enum('role', ['winemaker','admin','employee','customer'])->default('customer')->after('password'); + }); + } + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + if (Schema::hasColumn('users', 'role')) { + Schema::table('users', function (Blueprint $table) { + $table->dropColumn('role'); + }); + } + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_31_222446_create_purchases_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_31_222446_create_purchases_table.php new file mode 100644 index 0000000..30c2f72 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_10_31_222446_create_purchases_table.php @@ -0,0 +1,34 @@ +id(); + $table->foreignId('user_id')->nullable()->constrained('users')->nullOnDelete(); + $table->foreignId('wine_id')->nullable()->constrained('wines')->nullOnDelete(); + $table->unsignedInteger('amount')->default(1); + $table->decimal('price', 10, 2)->default(0); + $table->string('status', 50)->default('pending'); + $table->timestamp('purchased_at')->nullable(); + $table->text('note')->nullable(); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('purchases'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_01_000001_create_purchase_items_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_01_000001_create_purchase_items_table.php new file mode 100644 index 0000000..689478a --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_01_000001_create_purchase_items_table.php @@ -0,0 +1,32 @@ +id(); + $table->foreignId('purchase_id')->constrained('purchases')->onDelete('cascade'); + $table->foreignId('wine_id')->constrained('wines')->onDelete('cascade'); + $table->integer('quantity')->unsigned(); + $table->decimal('unit_price', 10, 2); + $table->decimal('line_total', 12, 2); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('purchase_items'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_02_000000_add_username_to_users_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_02_000000_add_username_to_users_table.php new file mode 100644 index 0000000..70077e7 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_02_000000_add_username_to_users_table.php @@ -0,0 +1,47 @@ +string('username')->nullable()->unique()->after('name'); + } + }); + } + + /** + * Reverse the migrations. + * + * @return void + */ + public function down(): void + { + if (!Schema::hasTable('users')) { + return; + } + + Schema::table('users', function (Blueprint $table) { + if (Schema::hasColumn('users', 'username')) { + $table->dropUnique(['username']); + $table->dropColumn('username'); + } + }); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_09_000100_create_treatment_tables.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_09_000100_create_treatment_tables.php new file mode 100644 index 0000000..8312427 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_09_000100_create_treatment_tables.php @@ -0,0 +1,85 @@ +id('treatment_id'); + $table->foreignId('row_id')->constrained('vineyard_rows')->cascadeOnDelete(); + $table->text('note')->nullable(); + $table->timestamps(); + }); + + Schema::create('waterings', function (Blueprint $table) { + $table->unsignedBigInteger('treatment_id')->primary(); + $table->unsignedInteger('time_interval')->nullable(); + $table->decimal('amount', 8, 2)->nullable(); + $table->text('note')->nullable(); + $table->timestamps(); + + $table->foreign('treatment_id') + ->references('treatment_id') + ->on('treatments') + ->cascadeOnDelete(); + }); + + Schema::create('fertilizations', function (Blueprint $table) { + $table->unsignedBigInteger('treatment_id')->primary(); + $table->string('substance'); + $table->decimal('concentration', 8, 2)->nullable(); + $table->text('note')->nullable(); + $table->timestamps(); + + $table->foreign('treatment_id') + ->references('treatment_id') + ->on('treatments') + ->cascadeOnDelete(); + }); + + Schema::create('sprayings', function (Blueprint $table) { + $table->unsignedBigInteger('treatment_id')->primary(); + $table->string('pesticide'); + $table->decimal('concentration', 8, 2)->nullable(); + $table->text('note')->nullable(); + $table->timestamps(); + + $table->foreign('treatment_id') + ->references('treatment_id') + ->on('treatments') + ->cascadeOnDelete(); + }); + + Schema::create('prunings', function (Blueprint $table) { + $table->unsignedBigInteger('treatment_id')->primary(); + $table->string('method'); + $table->unsignedInteger('percentage_removed')->nullable(); + $table->text('note')->nullable(); + $table->timestamps(); + + $table->foreign('treatment_id') + ->references('treatment_id') + ->on('treatments') + ->cascadeOnDelete(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('prunings'); + Schema::dropIfExists('sprayings'); + Schema::dropIfExists('fertilizations'); + Schema::dropIfExists('waterings'); + Schema::dropIfExists('treatments'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_10_000210_drop_row_number_from_vineyard_rows.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_10_000210_drop_row_number_from_vineyard_rows.php new file mode 100644 index 0000000..8d90b13 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_10_000210_drop_row_number_from_vineyard_rows.php @@ -0,0 +1,34 @@ +dropColumn('row_number'); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::table('vineyard_rows', function (Blueprint $table) { + if (! Schema::hasColumn('vineyard_rows', 'row_number')) { + $table->string('row_number')->nullable()->comment('Legacy row identifier'); + } + }); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_11_090902_add_sweetness_to_wines_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_11_090902_add_sweetness_to_wines_table.php new file mode 100644 index 0000000..1aa3390 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_11_090902_add_sweetness_to_wines_table.php @@ -0,0 +1,28 @@ +enum('sweetness', ['dry', 'semi_dry', 'semi_sweet', 'sweet'])->nullable()->after('wine_type'); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::table('wines', function (Blueprint $table) { + $table->dropColumn('sweetness'); + }); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_12_164218_modify_wine_productions_preserve_on_wine_delete.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_12_164218_modify_wine_productions_preserve_on_wine_delete.php new file mode 100644 index 0000000..93bc742 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_12_164218_modify_wine_productions_preserve_on_wine_delete.php @@ -0,0 +1,48 @@ +dropForeign(['wine_id']); + + // Make wine_id nullable + $table->foreignId('wine_id')->nullable()->change(); + + // Re-add the foreign key with onDelete('set null') + $table->foreign('wine_id') + ->references('id') + ->on('wines') + ->onDelete('set null'); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::table('wine_productions', function (Blueprint $table) { + // Drop the modified foreign key + $table->dropForeign(['wine_id']); + + // Make wine_id non-nullable again + $table->foreignId('wine_id')->nullable(false)->change(); + + // Re-add the original foreign key with cascade + $table->foreign('wine_id') + ->references('id') + ->on('wines') + ->onDelete('cascade'); + }); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_13_120000_update_vineyard_rows_variety_variation_nullable.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_13_120000_update_vineyard_rows_variety_variation_nullable.php new file mode 100644 index 0000000..0ad98e1 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_13_120000_update_vineyard_rows_variety_variation_nullable.php @@ -0,0 +1,92 @@ +getDriverName(); + + if ($driver === 'sqlite') { + // SQLite requires full table rebuilds for altering nullability; skip and rely on fresh migrations. + return; + } + + Schema::table('vineyard_rows', function (Blueprint $table) { + $table->dropForeign(['variety_variation_id']); + }); + + switch ($driver) { + case 'mysql': + DB::statement('ALTER TABLE `vineyard_rows` MODIFY `variety_variation_id` BIGINT UNSIGNED NULL'); + break; + case 'pgsql': + DB::statement('ALTER TABLE vineyard_rows ALTER COLUMN variety_variation_id DROP NOT NULL'); + break; + case 'sqlsrv': + DB::statement('ALTER TABLE vineyard_rows ALTER COLUMN variety_variation_id BIGINT NULL'); + break; + default: + return; + } + + Schema::table('vineyard_rows', function (Blueprint $table) { + $table->foreign('variety_variation_id') + ->references('id') + ->on('variety_variations') + ->onDelete('cascade'); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + if (! Schema::hasTable('vineyard_rows')) { + return; + } + + $driver = Schema::getConnection()->getDriverName(); + + if ($driver === 'sqlite') { + return; + } + + Schema::table('vineyard_rows', function (Blueprint $table) { + $table->dropForeign(['variety_variation_id']); + }); + + switch ($driver) { + case 'mysql': + DB::statement('ALTER TABLE `vineyard_rows` MODIFY `variety_variation_id` BIGINT UNSIGNED NOT NULL'); + break; + case 'pgsql': + DB::statement('ALTER TABLE vineyard_rows ALTER COLUMN variety_variation_id SET NOT NULL'); + break; + case 'sqlsrv': + DB::statement('ALTER TABLE vineyard_rows ALTER COLUMN variety_variation_id BIGINT NOT NULL'); + break; + default: + return; + } + + Schema::table('vineyard_rows', function (Blueprint $table) { + $table->foreign('variety_variation_id') + ->references('id') + ->on('variety_variations') + ->onDelete('cascade'); + }); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_18_191059_create_events_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_18_191059_create_events_table.php new file mode 100644 index 0000000..76bc684 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_18_191059_create_events_table.php @@ -0,0 +1,36 @@ +id(); + $table->string('name'); + $table->text('description'); + $table->enum('type', ['tasting', 'harvest_festival', 'vineyard_tour']); + $table->date('event_date'); + $table->time('event_time'); + $table->integer('capacity'); + $table->decimal('price_per_person', 8, 2); + $table->enum('status', ['upcoming', 'cancelled', 'completed'])->default('upcoming'); + $table->string('location')->nullable(); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('events'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_18_191221_create_event_reservations_table.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_18_191221_create_event_reservations_table.php new file mode 100644 index 0000000..0184a97 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_18_191221_create_event_reservations_table.php @@ -0,0 +1,31 @@ +id(); + $table->foreignId('event_id')->constrained('events')->onDelete('cascade'); + $table->foreignId('user_id')->constrained('users')->onDelete('cascade'); + $table->integer('number_of_guests')->default(1); + $table->enum('status', ['confirmed', 'cancelled'])->default('confirmed'); + $table->timestamps(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::dropIfExists('event_reservations'); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_18_200626_alter_color_on_variety_variations.php b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_18_200626_alter_color_on_variety_variations.php new file mode 100644 index 0000000..276168c --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/migrations/2025_11_18_200626_alter_color_on_variety_variations.php @@ -0,0 +1,30 @@ +string('color', 50)->change(); + }); + } + + /** + * Reverse the migrations. + */ + public function down(): void + { + Schema::table('variety_variations', function (Blueprint $table) { + // Optional: revert to original definition if needed + // $table->enum('color', ['green', 'blue', 'yellow', 'red'])->change(); + }); + } +}; diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/AdminUserSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/AdminUserSeeder.php new file mode 100644 index 0000000..bc01195 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/AdminUserSeeder.php @@ -0,0 +1,34 @@ +exists(); + + if (!$adminExists) { + User::create([ + 'name' => 'Administrator', + 'username' => 'admin', + 'email' => 'admin@winery.local', + 'password' => Hash::make('Admin@1234'), + 'role' => UserRole::ADMIN, + ]); + + $this->command->info('✓ Admin user created (username: admin, password: Admin@1234)'); + } else { + $this->command->info('Admin user already exists'); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/DatabaseSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/DatabaseSeeder.php new file mode 100644 index 0000000..74ed1d2 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/DatabaseSeeder.php @@ -0,0 +1,64 @@ +create(); + + // create a default test user + // User::updateOrCreate( + // ['email' => 'test@example.com'], + // [ + // 'name' => 'Test User', + // 'username' => 'test', + // // model casts password => hashed, so plain text will be auto-hashed + // 'password' => 'password123', + // 'role' => UserRole::CUSTOMER, + // ] + // ); + + // // create an admin user (idempotent) + // User::updateOrCreate( + // ['email' => 'admin@local'], + // [ + // 'name' => 'Administrator', + // 'username' => 'admin', + // 'password' => 'Admin@1234', + // 'role' => UserRole::ADMIN, + // ] + // ); + + // Seed grape varieties and their variants first so other seeders can reference them + $this->call([ + UserSeeder::class, + WinerySeeder::class, + GrapeVarietySeeder::class, + VarietyVariationSeeder::class, + VineyardRowSeeder::class, + HarvestSeeder::class, + WineSeeder::class, + WineProductionSeeder::class, + WateringSeeder::class, + FertilizationSeeder::class, + SprayingSeeder::class, + PruningSeeder::class, + PlannedTaskSeeder::class, + PurchaseSeeder::class, + EventSeeder::class, + ]); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/EventSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/EventSeeder.php new file mode 100644 index 0000000..2e7ca10 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/EventSeeder.php @@ -0,0 +1,135 @@ + 'Premium Wine Tasting Experience', + 'description' => 'Join us for an exclusive evening of premium wine tasting. Sample our finest selections including Grüner Veltliner Cabinet, Riesling Berry Selection, and Blaufränkisch Reserve. Our sommelier will guide you through the tasting notes and wine-making process.', + 'type' => 'tasting', + 'event_date' => now()->addDays(14), + 'event_time' => '18:00:00', + 'capacity' => 25, + 'price_per_person' => 35.00, + 'status' => 'upcoming', + 'location' => 'Main Tasting Room', + ], + [ + 'name' => 'White Wine Masterclass', + 'description' => 'Discover the secrets of our white wine collection. This masterclass focuses on Grüner Veltliner, Riesling, and Chardonnay varieties. Learn about fermentation, aging, and pairing suggestions from our expert winemakers.', + 'type' => 'tasting', + 'event_date' => now()->addDays(21), + 'event_time' => '17:00:00', + 'capacity' => 20, + 'price_per_person' => 40.00, + 'status' => 'upcoming', + 'location' => 'Barrel Room', + ], + [ + 'name' => 'Red Wine & Cheese Pairing', + 'description' => 'Experience the perfect harmony of red wines and artisanal cheeses. Taste our Blaufränkisch and St. Laurent wines paired with carefully selected cheeses from local producers.', + 'type' => 'tasting', + 'event_date' => now()->addDays(28), + 'event_time' => '19:00:00', + 'capacity' => 30, + 'price_per_person' => 45.00, + 'status' => 'upcoming', + 'location' => 'Main Tasting Room', + ], + + // Harvest Festivals + [ + 'name' => 'Autumn Harvest Festival', + 'description' => 'Celebrate the harvest season with us! Join our traditional grape harvest festival featuring live music, local cuisine, wine tasting, and vineyard tours. Experience the joy of grape picking and learn about traditional wine-making methods.', + 'type' => 'harvest_festival', + 'event_date' => now()->addDays(45), + 'event_time' => '11:00:00', + 'capacity' => 100, + 'price_per_person' => 25.00, + 'status' => 'upcoming', + 'location' => 'Main Vineyard', + ], + [ + 'name' => 'Grape Stomping Experience', + 'description' => 'Join us for a fun-filled afternoon of traditional grape stomping! Get your feet purple while making wine the old-fashioned way. Includes wine tasting, live folk music, and traditional refreshments.', + 'type' => 'harvest_festival', + 'event_date' => now()->addDays(52), + 'event_time' => '14:00:00', + 'capacity' => 50, + 'price_per_person' => 20.00, + 'status' => 'upcoming', + 'location' => 'Fermentation Pavilion', + ], + + // Vineyard Tours + [ + 'name' => 'Guided Vineyard Tour & Tasting', + 'description' => 'Explore our beautiful vineyard with a guided tour. Walk through rows of Grüner Veltliner, Riesling, and Blaufränkisch vines. Learn about viticulture, terroir, and sustainable farming practices. Tour concludes with a wine tasting session.', + 'type' => 'vineyard_tour', + 'event_date' => now()->addDays(7), + 'event_time' => '10:00:00', + 'capacity' => 15, + 'price_per_person' => 30.00, + 'status' => 'upcoming', + 'location' => 'Vineyard Starting Point', + ], + [ + 'name' => 'Sunrise Vineyard Walk', + 'description' => 'Experience the vineyard at its most beautiful moment. This early morning tour includes a peaceful walk through the vines as the sun rises, followed by a light breakfast and wine tasting in our garden.', + 'type' => 'vineyard_tour', + 'event_date' => now()->addDays(10), + 'event_time' => '06:30:00', + 'capacity' => 12, + 'price_per_person' => 35.00, + 'status' => 'upcoming', + 'location' => 'East Vineyard', + ], + [ + 'name' => 'Behind the Scenes: Cellar Tour', + 'description' => 'Go behind the scenes and explore our wine cellar and production facility. See where the magic happens - from fermentation tanks to aging barrels. Includes exclusive barrel tasting and a bottle of wine to take home.', + 'type' => 'vineyard_tour', + 'event_date' => now()->addDays(35), + 'event_time' => '15:00:00', + 'capacity' => 20, + 'price_per_person' => 50.00, + 'status' => 'upcoming', + 'location' => 'Wine Cellar', + ], + + // Past Events (for testing) + [ + 'name' => 'Spring Wine Festival', + 'description' => 'Our annual spring wine festival featuring new vintage releases.', + 'type' => 'harvest_festival', + 'event_date' => now()->subDays(30), + 'event_time' => '12:00:00', + 'capacity' => 80, + 'price_per_person' => 20.00, + 'status' => 'completed', + 'location' => 'Main Vineyard', + ], + ]; + + foreach ($events as $eventData) { + Event::create($eventData); + } + + if ($this->command) { + $this->command->info('✓ Created ' . count($events) . ' events'); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/FertilizationSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/FertilizationSeeder.php new file mode 100644 index 0000000..5adf8e4 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/FertilizationSeeder.php @@ -0,0 +1,96 @@ +get() + ->keyBy(fn (VineyardRow $row) => $row->varietyVariation->grapeVariety->variety_name ?? $row->id); + + $applications = [ + [ + 'variety' => 'Riesling', + 'treatment_note' => 'Spring nitrogen fertilization', + 'substance' => 'Nitrogen mix 12-6-6', + 'concentration' => 0.75, + 'note' => 'Applied pre-budbreak to boost growth', + 'planned_for' => now()->addDays(7)->format('Y-m-d'), + ], + [ + 'variety' => 'Chardonnay', + 'treatment_note' => 'Potassium boost application', + 'substance' => 'Potassium sulfate', + 'concentration' => 0.60, + 'note' => 'Pre-flowering nutrient supplement', + 'planned_for' => now()->addWeeks(2)->format('Y-m-d'), + ], + [ + 'variety' => 'Grüner Veltliner', + 'treatment_note' => 'Autumn potassium fertilization', + 'substance' => 'Potassium sulfate', + 'concentration' => 0.60, + 'note' => 'Supports winter hardiness', + 'completed_at' => now()->subWeeks(2)->format('Y-m-d'), + ], + ]; + + foreach ($applications as $application) { + $row = $rows[$application['variety']] ?? null; + + if (! $row) { + continue; + } + + $treatment = Treatment::updateOrCreate( + [ + 'row_id' => $row->id, + 'note' => $application['treatment_note'], + ], + [] + ); + + $fertilization = Fertilization::updateOrCreate( + ['treatment_id' => $treatment->treatment_id], + [ + 'substance' => $application['substance'], + 'concentration' => $application['concentration'], + 'note' => $application['note'], + ] + ); + + $plannedDate = $application['planned_for'] ?? null; + $completedDate = $application['completed_at'] ?? null; + $defaultDate = $plannedDate ?? $completedDate; + + if ($plannedDate || $completedDate || $defaultDate) { + PlannedTask::updateOrCreate( + [ + 'type' => 'Fertilization', + 'taskable_id' => $fertilization->getKey(), + 'taskable_type' => Fertilization::class, + ], + [ + 'planned_date' => $plannedDate ?? $defaultDate, + 'execution_date' => $completedDate, + 'note' => $application['treatment_note'], + ] + ); + } + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/GrapeVarietySeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/GrapeVarietySeeder.php new file mode 100644 index 0000000..03eece0 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/GrapeVarietySeeder.php @@ -0,0 +1,80 @@ + 'Grüner Veltliner', + 'description' => 'The most widespread white wine variety in the Czech Republic, producing fresh wines with light acidity.', + 'origin' => 'Austria', + 'wine_type' => 'white', + 'characteristics' => 'Fresh, fruity aromas, light acidity, piquant taste', + 'image_url' => 'https://example.com/images/gruner-veltliner.jpg', + ], + [ + 'variety_name' => 'Riesling', + 'description' => 'Premium white wine variety with a distinctive bouquet and mineral tones.', + 'origin' => 'Rhine, Germany', + 'wine_type' => 'white', + 'characteristics' => 'Mineral, acidic, elegant, long-aging potential', + 'image_url' => 'https://example.com/images/riesling.jpg', + ], + [ + 'variety_name' => 'Blaufränkisch', + 'description' => 'Classic red wine variety typical for Moravia.', + 'origin' => 'France', + 'wine_type' => 'red', + 'characteristics' => 'Distinctive, spicy, tannic, long-aging potential', + 'image_url' => 'https://example.com/images/blaufrankisch.jpg', + ], + [ + 'variety_name' => 'St. Laurent', + 'description' => 'Quality red wine with soft taste and delicate tannins.', + 'origin' => 'Austria', + 'wine_type' => 'red', + 'characteristics' => 'Delicate, fruity, soft tannins, velvety taste', + 'image_url' => 'https://example.com/images/st-laurent.jpg', + ], + [ + 'variety_name' => 'Müller Thurgau', + 'description' => 'Popular white wine with a subtle muscat aroma.', + 'origin' => 'Switzerland', + 'wine_type' => 'white', + 'characteristics' => 'Muscat, fresh, young wines', + 'image_url' => 'https://example.com/images/muller-thurgau.jpg', + ], + [ + 'variety_name' => 'Chardonnay', + 'description' => 'World-renowned variety producing complex white wines with aging potential.', + 'origin' => 'Burgundy, France', + 'wine_type' => 'white', + 'characteristics' => 'Complex, buttery, vanilla (after oak barrel), full-bodied', + 'image_url' => 'https://example.com/images/chardonnay.jpg', + ], + ]; + + foreach ($varieties as $variety) { + GrapeVariety::updateOrCreate( + ['variety_name' => $variety['variety_name']], + $variety + ); + } + + if ($this->command) { + $this->command->info('✓ Created ' . count($varieties) . ' grape varieties'); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/GrapeVarietyVariantSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/GrapeVarietyVariantSeeder.php new file mode 100644 index 0000000..58db577 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/GrapeVarietyVariantSeeder.php @@ -0,0 +1,48 @@ + 'Grüner Veltliner', 'color' => 'green'], + ['variety' => 'Grüner Veltliner', 'color' => 'yellow'], + ['variety' => 'Riesling', 'color' => 'green'], + ['variety' => 'Riesling', 'color' => 'yellow'], + ['variety' => 'Blaufränkisch', 'color' => 'blue'], + ['variety' => 'St. Laurent', 'color' => 'red'], + ['variety' => 'Müller Thurgau', 'color' => 'green'], + ['variety' => 'Chardonnay', 'color' => 'yellow'], + ]; + + foreach ($variants as $variant) { + $varietyName = $variant['variety']; + + if (! isset($varietyIds[$varietyName])) { + continue; + } + + GrapeVarietyVariant::updateOrCreate( + [ + 'grape_variety_id' => $varietyIds[$varietyName], + 'color' => $variant['color'], + ], + [] + ); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/HarvestSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/HarvestSeeder.php new file mode 100644 index 0000000..52ce148 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/HarvestSeeder.php @@ -0,0 +1,603 @@ +get() + ->groupBy(fn (VineyardRow $row) => $row->varietyVariation->grapeVariety->variety_name ?? $row->id); + + $variations = VarietyVariation::with('grapeVariety') + ->get() + ->keyBy(fn (VarietyVariation $variation) => ($variation->grapeVariety->variety_name ?? $variation->id) . ':' . $variation->color); + + $harvests = [ + // Historical harvests from 2024 + [ + 'variety' => 'Grüner Veltliner', + 'color' => 'green', + 'weight' => 850.50, + 'sugar_content' => 19.5, + 'date' => '2024-09-15', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Excellent harvest, optimal ripeness', + 'weather_conditions' => 'Sunny, 22°C', + 'harvest_time' => '08:00:00', + 'executed_at' => '2024-09-15', + ], + [ + 'variety' => 'Riesling', + 'color' => 'green', + 'weight' => 720.30, + 'sugar_content' => 21.2, + 'date' => '2024-09-20', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Premium quality, high sugar content', + 'weather_conditions' => 'Partly cloudy, 20°C', + 'harvest_time' => '07:30:00', + 'executed_at' => '2024-09-20', + ], + [ + 'variety' => 'Blaufränkisch', + 'color' => 'blue', + 'weight' => 950.00, + 'sugar_content' => 22.8, + 'date' => '2024-10-05', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Best harvest of the season, ideal conditions', + 'weather_conditions' => 'Sunny, 18°C', + 'harvest_time' => '09:00:00', + 'executed_at' => '2024-10-05', + ], + [ + 'variety' => 'St. Laurent', + 'color' => 'blue', + 'weight' => 600.75, + 'sugar_content' => 20.5, + 'date' => '2024-10-01', + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Good quality, smaller yield', + 'weather_conditions' => 'Overcast, 16°C', + 'harvest_time' => '10:00:00', + 'planned_for' => '2025-09-22', + ], + [ + 'variety' => 'Müller Thurgau', + 'color' => 'green', + 'weight' => 780.20, + 'sugar_content' => 18.3, + 'date' => '2024-09-10', + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Early harvest, lighter wine', + 'weather_conditions' => 'Sunny, 24°C', + 'harvest_time' => '08:30:00', + 'planned_for' => '2025-09-12', + ], + + // ========== HISTORICAL HARVESTS 2023 ========== + [ + 'variety' => 'Grüner Veltliner', + 'color' => 'green', + 'weight' => 920.00, + 'sugar_content' => 19.2, + 'date' => '2023-09-18', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Main harvest for Cabinet wine, excellent quality', + 'weather_conditions' => 'Sunny, 21°C', + 'harvest_time' => '08:00:00', + 'executed_at' => '2023-09-18', + ], + [ + 'variety' => 'Grüner Veltliner', + 'color' => 'green', + 'weight' => 650.50, + 'sugar_content' => 21.8, + 'date' => '2023-10-12', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Late harvest, higher sugar for semi-dry wine', + 'weather_conditions' => 'Partly cloudy, 18°C', + 'harvest_time' => '09:00:00', + 'executed_at' => '2023-10-12', + ], + [ + 'variety' => 'Müller Thurgau', + 'color' => 'green', + 'weight' => 890.75, + 'sugar_content' => 17.8, + 'date' => '2023-09-08', + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Early harvest, aromatic profile', + 'weather_conditions' => 'Sunny, 23°C', + 'harvest_time' => '07:30:00', + 'executed_at' => '2023-09-08', + ], + [ + 'variety' => 'Chardonnay', + 'color' => 'green', + 'weight' => 580.30, + 'sugar_content' => 20.5, + 'date' => '2023-09-22', + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Balanced harvest for unfiltered wine', + 'weather_conditions' => 'Sunny, 20°C', + 'harvest_time' => '08:00:00', + 'executed_at' => '2023-09-22', + ], + [ + 'variety' => 'Blaufränkisch', + 'color' => 'blue', + 'weight' => 1050.00, + 'sugar_content' => 22.0, + 'date' => '2023-10-08', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Premium quality for classic red wine', + 'weather_conditions' => 'Sunny, 17°C', + 'harvest_time' => '09:30:00', + 'executed_at' => '2023-10-08', + ], + [ + 'variety' => 'St. Laurent', + 'color' => 'blue', + 'weight' => 720.50, + 'sugar_content' => 20.8, + 'date' => '2023-10-02', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Main harvest for Moravian style', + 'weather_conditions' => 'Partly cloudy, 16°C', + 'harvest_time' => '08:30:00', + 'executed_at' => '2023-10-02', + ], + [ + 'variety' => 'St. Laurent', + 'color' => 'blue', + 'weight' => 480.25, + 'sugar_content' => 19.5, + 'date' => '2023-09-28', + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Early harvest for lighter rosé style', + 'weather_conditions' => 'Sunny, 19°C', + 'harvest_time' => '07:00:00', + 'executed_at' => '2023-09-28', + ], + + // ========== HISTORICAL HARVESTS 2022 ========== + [ + 'variety' => 'Grüner Veltliner', + 'color' => 'green', + 'weight' => 580.80, + 'sugar_content' => 22.5, + 'date' => '2022-10-20', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Selection harvest, hand-picked clusters for premium wine', + 'weather_conditions' => 'Cool, 14°C', + 'harvest_time' => '10:00:00', + 'executed_at' => '2022-10-20', + ], + [ + 'variety' => 'Riesling', + 'color' => 'green', + 'weight' => 640.60, + 'sugar_content' => 20.8, + 'date' => '2022-10-05', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Classic dry Riesling harvest, perfect acidity', + 'weather_conditions' => 'Sunny, 18°C', + 'harvest_time' => '08:00:00', + 'executed_at' => '2022-10-05', + ], + [ + 'variety' => 'Chardonnay', + 'color' => 'green', + 'weight' => 510.40, + 'sugar_content' => 21.5, + 'date' => '2022-09-25', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Premium grapes for barrel aging', + 'weather_conditions' => 'Sunny, 21°C', + 'harvest_time' => '08:30:00', + 'executed_at' => '2022-09-25', + ], + [ + 'variety' => 'Blaufränkisch', + 'color' => 'blue', + 'weight' => 680.75, + 'sugar_content' => 23.2, + 'date' => '2022-10-12', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Reserve selection, concentrated flavors', + 'weather_conditions' => 'Sunny, 16°C', + 'harvest_time' => '09:00:00', + 'executed_at' => '2022-10-12', + ], + [ + 'variety' => 'St. Laurent', + 'color' => 'blue', + 'weight' => 620.90, + 'sugar_content' => 21.8, + 'date' => '2022-10-05', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Premium harvest for barrel aging', + 'weather_conditions' => 'Partly cloudy, 17°C', + 'harvest_time' => '08:00:00', + 'executed_at' => '2022-10-05', + ], + + // ========== HISTORICAL HARVESTS 2021 ========== + [ + 'variety' => 'Riesling', + 'color' => 'green', + 'weight' => 420.50, + 'sugar_content' => 28.5, + 'date' => '2021-11-08', + 'quality' => 'excellent', + 'grape_condition' => 'botrytis-affected', + 'notes' => 'Noble rot berries, individual selection for sweet wine', + 'weather_conditions' => 'Foggy morning, 10°C', + 'harvest_time' => '10:00:00', + 'executed_at' => '2021-11-08', + ], + + // ========== HISTORICAL HARVESTS 2020 ========== + [ + 'variety' => 'Blaufränkisch', + 'color' => 'blue', + 'weight' => 550.00, + 'sugar_content' => 23.8, + 'date' => '2020-10-18', + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Exceptional vintage, archive quality', + 'weather_conditions' => 'Perfect harvest weather, 15°C', + 'harvest_time' => '09:00:00', + 'executed_at' => '2020-10-18', + ], + + // Recent harvests (within last 30 days) - dynamic dates + [ + 'variety' => 'Chardonnay', + 'color' => 'green', + 'weight' => 420.50, + 'sugar_content' => 20.8, + 'date' => now()->subDays(5)->format('Y-m-d'), + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'First Chardonnay harvest - excellent for sparkling wine', + 'weather_conditions' => 'Sunny, 19°C', + 'harvest_time' => '07:00:00', + ], + [ + 'variety' => 'Grüner Veltliner', + 'color' => 'green', + 'weight' => 320.75, + 'sugar_content' => 19.2, + 'date' => now()->subDays(12)->format('Y-m-d'), + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Partial harvest from north section', + 'weather_conditions' => 'Partly cloudy, 17°C', + 'harvest_time' => '08:30:00', + ], + [ + 'variety' => 'Riesling', + 'color' => 'green', + 'weight' => 280.40, + 'sugar_content' => 22.5, + 'date' => now()->subDays(18)->format('Y-m-d'), + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Late harvest - high sugar content for dessert wine', + 'weather_conditions' => 'Cool, 12°C', + 'harvest_time' => '09:00:00', + ], + [ + 'variety' => 'Blaufränkisch', + 'color' => 'blue', + 'weight' => 450.00, + 'sugar_content' => 21.5, + 'date' => now()->subDays(8)->format('Y-m-d'), + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Premium selection for reserve wine', + 'weather_conditions' => 'Sunny, 16°C', + 'harvest_time' => '08:00:00', + ], + + // ========== FULLY AVAILABLE HARVESTS (Not yet used in production) ========== + [ + 'variety' => 'Grüner Veltliner', + 'color' => 'green', + 'weight' => 780.40, + 'sugar_content' => 19.8, + 'date' => now()->subDays(3)->format('Y-m-d'), + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Fresh harvest, excellent for young wine production', + 'weather_conditions' => 'Sunny, 20°C', + 'harvest_time' => '07:30:00', + ], + [ + 'variety' => 'Müller Thurgau', + 'color' => 'green', + 'weight' => 650.25, + 'sugar_content' => 18.0, + 'date' => now()->subDays(6)->format('Y-m-d'), + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Aromatic harvest, ready for processing', + 'weather_conditions' => 'Partly cloudy, 19°C', + 'harvest_time' => '08:00:00', + ], + [ + 'variety' => 'Chardonnay', + 'color' => 'green', + 'weight' => 540.80, + 'sugar_content' => 21.0, + 'date' => now()->subDays(2)->format('Y-m-d'), + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Premium quality, suitable for barrel aging', + 'weather_conditions' => 'Sunny, 21°C', + 'harvest_time' => '07:00:00', + ], + [ + 'variety' => 'Riesling', + 'color' => 'green', + 'weight' => 470.60, + 'sugar_content' => 20.5, + 'date' => now()->subDays(10)->format('Y-m-d'), + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Balanced acidity, perfect for classic dry style', + 'weather_conditions' => 'Cool, 15°C', + 'harvest_time' => '08:30:00', + ], + [ + 'variety' => 'St. Laurent', + 'color' => 'blue', + 'weight' => 690.50, + 'sugar_content' => 20.2, + 'date' => now()->subDays(4)->format('Y-m-d'), + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Excellent color and tannins, available for production', + 'weather_conditions' => 'Partly cloudy, 17°C', + 'harvest_time' => '09:00:00', + ], + [ + 'variety' => 'Blaufränkisch', + 'color' => 'blue', + 'weight' => 820.00, + 'sugar_content' => 22.5, + 'date' => now()->subDays(7)->format('Y-m-d'), + 'quality' => 'excellent', + 'grape_condition' => 'healthy', + 'notes' => 'Rich concentration, ideal for reserve wine', + 'weather_conditions' => 'Sunny, 18°C', + 'harvest_time' => '08:30:00', + ], + [ + 'variety' => 'Grüner Veltliner', + 'color' => 'green', + 'weight' => 560.30, + 'sugar_content' => 18.5, + 'date' => '2023-09-25', + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Secondary harvest from 2023, still available', + 'weather_conditions' => 'Overcast, 18°C', + 'harvest_time' => '09:30:00', + 'executed_at' => '2023-09-25', + ], + [ + 'variety' => 'Chardonnay', + 'color' => 'green', + 'weight' => 390.75, + 'sugar_content' => 19.8, + 'date' => '2023-10-05', + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Late 2023 harvest, clean and fresh', + 'weather_conditions' => 'Sunny, 16°C', + 'harvest_time' => '08:00:00', + 'executed_at' => '2023-10-05', + ], + [ + 'variety' => 'St. Laurent', + 'color' => 'blue', + 'weight' => 410.20, + 'sugar_content' => 19.0, + 'date' => '2022-09-28', + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => 'Older harvest from 2022, still usable for blending', + 'weather_conditions' => 'Partly cloudy, 19°C', + 'harvest_time' => '10:00:00', + 'executed_at' => '2022-09-28', + ], + [ + 'variety' => 'Müller Thurgau', + 'color' => 'green', + 'weight' => 720.50, + 'sugar_content' => 17.5, + 'date' => '2022-09-15', + 'quality' => 'good', + 'grape_condition' => 'healthy', + 'notes' => '2022 reserve harvest, light and aromatic', + 'weather_conditions' => 'Sunny, 22°C', + 'harvest_time' => '07:30:00', + 'executed_at' => '2022-09-15', + ], + + // ========== PLANNED HARVESTS (Future - No completion data) ========== + // Note: These have minimal data since they're planned, not yet executed + [ + 'variety' => 'Grüner Veltliner', + 'color' => 'green', + 'weight' => 0, // Placeholder - actual weight unknown until harvest + 'date' => now()->addYear()->addMonths(8)->format('Y-m-d'), // ~Sept 2026 + 'notes' => 'Planned harvest for premium wine production', + 'planned_for' => now()->addYear()->addMonths(8)->format('Y-m-d'), + ], + [ + 'variety' => 'Riesling', + 'color' => 'green', + 'weight' => 0, + 'date' => now()->addYear()->addMonths(8)->addDays(10)->format('Y-m-d'), // ~Sept 2026 + 'notes' => 'Expected high sugar content for late harvest wine', + 'planned_for' => now()->addYear()->addMonths(8)->addDays(10)->format('Y-m-d'), + ], + [ + 'variety' => 'Chardonnay', + 'color' => 'green', + 'weight' => 0, + 'date' => now()->addYear()->addMonths(9)->format('Y-m-d'), // ~Oct 2026 + 'notes' => 'Planned harvest for reserve Chardonnay', + 'planned_for' => now()->addYear()->addMonths(9)->format('Y-m-d'), + ], + [ + 'variety' => 'Blaufränkisch', + 'color' => 'blue', + 'weight' => 0, + 'date' => now()->addYear()->addMonths(9)->addDays(5)->format('Y-m-d'), // ~Oct 2026 + 'notes' => 'Planned red grape harvest for full-bodied wine', + 'planned_for' => now()->addYear()->addMonths(9)->addDays(5)->format('Y-m-d'), + ], + [ + 'variety' => 'St. Laurent', + 'color' => 'blue', + 'weight' => 0, + 'date' => now()->addYear()->addMonths(9)->addWeeks(1)->format('Y-m-d'), // ~Oct 2026 + 'notes' => 'Planned harvest for elegant red wine', + 'planned_for' => now()->addYear()->addMonths(9)->addWeeks(1)->format('Y-m-d'), + ], + ]; + + // Track which rows have been used for which years + $rowYearUsage = []; + + foreach ($harvests as $harvest) { + $varietyRows = $rows[$harvest['variety']] ?? collect(); + $variationKey = $harvest['variety'] . ':' . $harvest['color']; + $variation = $variations[$variationKey] ?? null; + + // Resolve a usable variety variation id; fall back to row assignment or any variation for the variety + $variationId = $variation?->id; + if (! $variationId && $varietyRows->isNotEmpty()) { + $variationId = $varietyRows->first()->variety_variation_id; + } + if (! $variationId) { + $variationId = \App\Models\VarietyVariation::whereHas( + 'grapeVariety', + fn ($q) => $q->where('variety_name', $harvest['variety']) + )->value('id'); + } + + if ($varietyRows->isEmpty() || ! $variationId) { + continue; + } + + // Get the year from the PLANNED date (not harvest date) + // Planned date is: planned_for > executed_at > date + $plannedDateField = $harvest['planned_for'] ?? $harvest['executed_at'] ?? $harvest['date']; + $plannedYear = is_string($plannedDateField) + ? \Carbon\Carbon::parse($plannedDateField)->year + : now()->subDays((int)$plannedDateField)->year; + + // Find a row that hasn't been used for this planned year + $row = null; + foreach ($varietyRows as $candidateRow) { + $rowYearKey = $candidateRow->id . '_' . $plannedYear; + if (!isset($rowYearUsage[$rowYearKey])) { + $row = $candidateRow; + $rowYearUsage[$rowYearKey] = true; + break; + } + } + + // If all rows for this variety already have a harvest this planned year, skip + if (!$row) { + continue; + } + + $harvestModel = Harvest::updateOrCreate( + [ + 'vineyard_row_id' => $row->id, + 'date' => $harvest['date'], + ], + [ + 'variety_variation_id' => $variationId, + 'weight' => $harvest['weight'] ?? null, + 'sugar_content' => $harvest['sugar_content'] ?? null, + 'quality' => $harvest['quality'] ?? null, + 'grape_condition' => $harvest['grape_condition'] ?? null, + 'notes' => $harvest['notes'] ?? null, + 'weather_conditions' => $harvest['weather_conditions'] ?? null, + 'harvest_time' => $harvest['harvest_time'] ?? null, + ] + ); + + $plannedDate = $harvest['planned_for'] ?? null; + $executionDate = $harvest['executed_at'] ?? null; + + // If harvest has completion data (sugar, weather, etc.), it's completed + // Set execution_date to the harvest date, regardless of 'planned_for' + $hasCompletionData = $harvestModel->sugar_content || $harvestModel->weather_conditions || $harvestModel->quality_rating; + if ($hasCompletionData && !$executionDate) { + $executionDate = $harvestModel->date?->format('Y-m-d'); + } + + $defaultDate = $executionDate ?? $harvestModel->date?->format('Y-m-d'); + + if ($plannedDate || $executionDate || $defaultDate) { + PlannedTask::updateOrCreate( + [ + 'type' => 'Harvest', + 'taskable_id' => $harvestModel->getKey(), + 'taskable_type' => Harvest::class, + ], + [ + 'planned_date' => $plannedDate ?? $defaultDate, + 'execution_date' => $executionDate, + 'note' => $harvest['notes'], + ] + ); + } + } + + if ($this->command) { + $this->command->info('✓ Created ' . count($harvests) . ' harvests'); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/PlannedTaskSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/PlannedTaskSeeder.php new file mode 100644 index 0000000..1e10922 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/PlannedTaskSeeder.php @@ -0,0 +1,506 @@ +get(); + + if ($vineyardRows->isEmpty()) { + if ($this->command) { + $this->command->warn('No vineyard rows found. Skipping PlannedTaskSeeder.'); + } + return; + } + + // ========================================== + // PLANNED TREATMENTS (Not yet executed) + // ========================================== + + // Spraying - planned for this week and next week + $sprayingTasks = [ + [ + 'type' => 'Spraying', + 'planned_date' => now()->addDays(2), + 'note' => 'Fungicide application for mildew prevention', + 'rows' => [1, 2, 4, 5, 13], // Grüner Veltliner, Riesling, Müller Thurgau rows + ], + [ + 'type' => 'Spraying', + 'planned_date' => now()->addDays(5), + 'note' => 'Copper sulfate treatment', + 'rows' => [7, 8, 11], // Blaufränkisch and St. Laurent rows + ], + [ + 'type' => 'Spraying', + 'planned_date' => now()->addDays(9), + 'note' => 'Organic pest control spray', + 'rows' => [16, 17], // Chardonnay rows + ], + [ + 'type' => 'Spraying', + 'planned_date' => now()->addDays(11), + 'note' => 'Sulfur spray for powdery mildew', + 'rows' => [3, 6, 14, 15], // Selected white variety rows + ], + [ + 'type' => 'Spraying', + 'planned_date' => now()->addDays(13), + 'note' => 'Insect protection spray', + 'rows' => [9, 10, 12], // Red variety rows + ], + [ + 'type' => 'Spraying', + 'planned_date' => now()->addDays(16), + 'note' => 'Botrytis prevention treatment', + 'rows' => [1, 4, 7, 8], // Mixed varieties + ], + [ + 'type' => 'Spraying', + 'planned_date' => now()->addDays(20), + 'note' => 'Final pre-harvest fungicide', + 'rows' => [13, 14, 16], // Selected rows for early harvest + ], + ]; + + // Fertilization - planned for upcoming weeks + $fertilizationTasks = [ + [ + 'type' => 'Fertilization', + 'planned_date' => now()->addDays(1), + 'note' => 'Spring nitrogen fertilization', + 'rows' => [1, 3, 4, 6], // Selected Grüner Veltliner and Riesling rows + ], + [ + 'type' => 'Fertilization', + 'planned_date' => now()->addDays(7), + 'note' => 'Potassium supplement application', + 'rows' => [7, 9, 10, 11, 12, 16, 18], // Blaufränkisch, St. Laurent, and Chardonnay rows + ], + [ + 'type' => 'Fertilization', + 'planned_date' => now()->addDays(12), + 'note' => 'Organic compost distribution', + 'rows' => [13, 14, 15], // All Müller Thurgau rows + ], + [ + 'type' => 'Fertilization', + 'planned_date' => now()->addDays(14), + 'note' => 'Magnesium foliar spray', + 'rows' => [2, 5, 17], // Selected white variety rows + ], + [ + 'type' => 'Fertilization', + 'planned_date' => now()->addDays(18), + 'note' => 'Calcium nitrate application', + 'rows' => [7, 8, 9, 11], // Red variety rows + ], + [ + 'type' => 'Fertilization', + 'planned_date' => now()->addDays(21), + 'note' => 'Phosphorus enrichment', + 'rows' => [1, 2, 3, 4, 5, 6], // Grüner Veltliner and Riesling rows + ], + [ + 'type' => 'Fertilization', + 'planned_date' => now()->addDays(25), + 'note' => 'Pre-harvest nutrient boost', + 'rows' => [13, 14, 16, 18], // Early harvest rows + ], + [ + 'type' => 'Fertilization', + 'planned_date' => now()->addDays(28), + 'note' => 'Micronutrient foliar feed', + 'rows' => [10, 12, 15], // Selected rows + ], + ]; + + // Watering - planned for this week + $wateringTasks = [ + [ + 'type' => 'Watering', + 'planned_date' => now()->addDays(3), + 'note' => 'Deep irrigation cycle', + 'rows' => [1, 2, 3, 4, 5, 13, 14, 16], // Multiple white variety rows + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->addDays(6), + 'note' => 'Evening drip irrigation', + 'rows' => [7, 8, 9, 11], // Red variety rows + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->addDays(8), + 'note' => 'Morning light watering', + 'rows' => [15, 17, 18], // Chardonnay and Müller Thurgau rows + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->addDays(10), + 'note' => 'Stress relief deep watering', + 'rows' => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], // Most rows + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->addDays(13), + 'note' => 'Targeted root zone irrigation', + 'rows' => [13, 14, 15], // All Müller Thurgau rows + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->addDays(15), + 'note' => 'Drip system maintenance watering', + 'rows' => [16, 17, 18], // All Chardonnay rows + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->addDays(17), + 'note' => 'Pre-harvest moisture regulation', + 'rows' => [1, 4, 5, 13, 14], // Early harvest rows + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->addDays(22), + 'note' => 'Post-treatment irrigation', + 'rows' => [7, 8, 9, 10, 11, 12], // Red variety rows + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->addDays(24), + 'note' => 'Controlled stress watering', + 'rows' => [2, 3, 6], // Selected white rows + ], + ]; + + // Pruning - planned for upcoming days + $pruningTasks = [ + [ + 'type' => 'Pruning', + 'planned_date' => now()->addDays(4), + 'note' => 'Summer green pruning - remove excess shoots', + 'rows' => [1, 2, 4, 5], // Specific Grüner Veltliner and Riesling rows + ], + [ + 'type' => 'Pruning', + 'planned_date' => now()->addDays(8), + 'note' => 'Canopy management - leaf thinning', + 'rows' => [7, 8, 9, 11, 12], // Blaufränkisch and St. Laurent rows + ], + [ + 'type' => 'Pruning', + 'planned_date' => now()->addDays(11), + 'note' => 'Lateral shoot removal', + 'rows' => [13, 14, 15], // Müller Thurgau rows + ], + [ + 'type' => 'Pruning', + 'planned_date' => now()->addDays(14), + 'note' => 'Cluster thinning for quality', + 'rows' => [3, 6, 16, 17], // Selected rows for premium wine + ], + [ + 'type' => 'Pruning', + 'planned_date' => now()->addDays(19), + 'note' => 'Leaf removal around clusters', + 'rows' => [1, 2, 3, 4, 5, 6], // White variety rows + ], + [ + 'type' => 'Pruning', + 'planned_date' => now()->addDays(23), + 'note' => 'Secondary shoot trimming', + 'rows' => [10, 11, 12], // Red variety rows + ], + [ + 'type' => 'Pruning', + 'planned_date' => now()->addDays(26), + 'note' => 'Pre-harvest canopy opening', + 'rows' => [13, 14, 16, 18], // Early harvest rows + ], + ]; + + // Create planned tasks (not executed) + $modelMap = [ + 'Spraying' => [Spraying::class, ['pesticide' => 'Standard pesticide', 'concentration' => 2.5]], + 'Fertilization' => [Fertilization::class, ['substance' => 'NPK fertilizer', 'concentration' => 5.0]], + 'Watering' => [Watering::class, ['time_interval' => 60, 'amount' => 100.0]], + 'Pruning' => [Pruning::class, ['method' => 'Manual pruning', 'percentage_removed' => 30]], + ]; + + foreach ([$sprayingTasks, $fertilizationTasks, $wateringTasks, $pruningTasks] as $taskGroup) { + foreach ($taskGroup as $taskData) { + foreach ($taskData['rows'] as $rowId) { + $row = $vineyardRows->firstWhere('id', $rowId); + + if ($row) { + // Create the base treatment + $treatment = Treatment::create([ + 'row_id' => $row->id, + 'note' => $taskData['note'], + ]); + + // Create the specific treatment type + [$modelClass, $specificData] = $modelMap[$taskData['type']]; + $specificTreatment = $modelClass::create(array_merge( + ['treatment_id' => $treatment->treatment_id], + $specificData, + ['note' => $taskData['note']] + )); + + // Create planned task linked to the specific treatment + PlannedTask::create([ + 'type' => $taskData['type'], + 'planned_date' => $taskData['planned_date'], + 'execution_date' => null, // Not yet executed + 'note' => $taskData['note'], + 'taskable_id' => $treatment->treatment_id, + 'taskable_type' => $modelClass, + ]); + } + } + } + } + + // ========================================== + // COMPLETED TREATMENTS (Recently executed) + // ========================================== + + $completedTreatments = [ + [ + 'type' => 'Spraying', + 'planned_date' => now()->subDays(10), + 'execution_date' => now()->subDays(10), + 'note' => 'Early season sulfur spray', + 'rows' => [1, 2, 3, 4, 6, 13, 15], // Multiple white variety rows + ], + [ + 'type' => 'Fertilization', + 'planned_date' => now()->subDays(7), + 'execution_date' => now()->subDays(7), + 'note' => 'Base fertilization with compost', + 'rows' => [7, 8, 11, 12], // Red variety rows + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->subDays(5), + 'execution_date' => now()->subDays(5), + 'note' => 'Post-planting irrigation', + 'rows' => [16, 17, 18], // All Chardonnay rows + ], + [ + 'type' => 'Pruning', + 'planned_date' => now()->subDays(3), + 'execution_date' => now()->subDays(3), + 'note' => 'Winter pruning final pass', + 'rows' => [1, 3, 4, 6], // Selected Grüner Veltliner and Riesling rows + ], + [ + 'type' => 'Spraying', + 'planned_date' => now()->subDays(14), + 'execution_date' => now()->subDays(15), + 'note' => 'Preventive copper treatment', + 'rows' => [7, 9, 10, 11, 16, 17], // Mix of red varieties and Chardonnay + ], + [ + 'type' => 'Watering', + 'planned_date' => now()->subDays(12), + 'execution_date' => now()->subDays(12), + 'note' => 'Emergency drought watering', + 'rows' => [1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15], // Most rows + ], + ]; + + foreach ($completedTreatments as $taskData) { + foreach ($taskData['rows'] as $rowId) { + $row = $vineyardRows->firstWhere('id', $rowId); + + if ($row) { + // Create the base treatment + $treatment = Treatment::create([ + 'row_id' => $row->id, + 'note' => $taskData['note'], + ]); + + // Create the specific treatment type + [$modelClass, $specificData] = $modelMap[$taskData['type']]; + $specificTreatment = $modelClass::create(array_merge( + ['treatment_id' => $treatment->treatment_id], + $specificData, + ['note' => $taskData['note']] + )); + + // Create planned task linked to the specific treatment (already executed) + PlannedTask::create([ + 'type' => $taskData['type'], + 'planned_date' => $taskData['planned_date'], + 'execution_date' => $taskData['execution_date'], + 'note' => $taskData['note'], + 'taskable_id' => $treatment->treatment_id, + 'taskable_type' => $modelClass, + ]); + } + } + } + + // ========================================== + // PLANNED HARVESTS (Near-term - within 2 weeks) + // ========================================== + + $nearTermHarvests = [ + [ + 'type' => 'Harvest', + 'planned_date' => now()->addDays(3), + 'note' => 'Test harvest - sugar content assessment', + 'rows' => [1], // Single Grüner Veltliner row + ], + [ + 'type' => 'Harvest', + 'planned_date' => now()->addDays(6), + 'note' => 'Early white grape harvest', + 'rows' => [13, 14, 4, 5], // Müller Thurgau and Riesling rows + ], + [ + 'type' => 'Harvest', + 'planned_date' => now()->addDays(10), + 'note' => 'Chardonnay harvest for reserve wine', + 'rows' => [16, 18], // Selected Chardonnay rows + ], + [ + 'type' => 'Harvest', + 'planned_date' => now()->addDays(12), + 'note' => 'Riesling harvest for late vintage', + 'rows' => [2, 3], // Selected Riesling rows + ], + [ + 'type' => 'Harvest', + 'planned_date' => now()->addDays(15), + 'note' => 'Grüner Veltliner main harvest', + 'rows' => [1, 2, 3], // Grüner Veltliner rows + ], + [ + 'type' => 'Harvest', + 'planned_date' => now()->addDays(18), + 'note' => 'Müller Thurgau harvest', + 'rows' => [15], // Single Müller Thurgau row + ], + [ + 'type' => 'Harvest', + 'planned_date' => now()->addDays(21), + 'note' => 'Chardonnay harvest continuation', + 'rows' => [17], // Remaining Chardonnay row + ], + ]; + + foreach ($nearTermHarvests as $taskData) { + foreach ($taskData['rows'] as $rowId) { + $row = $vineyardRows->firstWhere('id', $rowId); + + if ($row) { + // Create harvest model + $harvest = Harvest::create([ + 'vineyard_row_id' => $row->id, + 'variety_variation_id' => $row->variety_variation_id, + 'date' => $taskData['planned_date'], + 'sugar_content' => 0, + 'weight' => 0, + 'quality' => null, + 'user_id' => null, + 'notes' => $taskData['note'], + ]); + + // Create planned task linked to the harvest + PlannedTask::create([ + 'type' => $taskData['type'], + 'planned_date' => $taskData['planned_date'], + 'execution_date' => null, + 'note' => $taskData['note'], + 'taskable_id' => $harvest->id, + 'taskable_type' => Harvest::class, + ]); + } + } + } + + // ========================================== + // PLANNED HARVESTS (Future - beyond 2 weeks) + // ========================================== + + $futureHarvests = [ + [ + 'type' => 'Harvest', + 'planned_date' => now()->addMonths(2), + 'note' => 'Early harvest for sparkling wine production', + 'rows' => [17], // Single Chardonnay row + ], + [ + 'type' => 'Harvest', + 'planned_date' => now()->addMonths(3), + 'note' => 'Main white grape harvest', + 'rows' => [1, 2, 3, 4, 5, 6, 13, 14, 15], // All white variety rows + ], + [ + 'type' => 'Harvest', + 'planned_date' => now()->addMonths(3)->addDays(7), + 'note' => 'Red grape harvest', + 'rows' => [7, 8, 9, 10, 11, 12], // All red variety rows + ], + ]; + + foreach ($futureHarvests as $taskData) { + foreach ($taskData['rows'] as $rowId) { + $row = $vineyardRows->firstWhere('id', $rowId); + + if ($row) { + // Create harvest model + $harvest = Harvest::create([ + 'vineyard_row_id' => $row->id, + 'variety_variation_id' => $row->variety_variation_id, + 'date' => $taskData['planned_date'], + 'sugar_content' => 0, + 'weight' => 0, + 'quality' => null, + 'user_id' => null, + 'notes' => $taskData['note'], + ]); + + // Create planned task linked to the harvest + PlannedTask::create([ + 'type' => $taskData['type'], + 'planned_date' => $taskData['planned_date'], + 'execution_date' => null, + 'note' => $taskData['note'], + 'taskable_id' => $harvest->id, + 'taskable_type' => Harvest::class, + ]); + } + } + } + + // Count and report + $totalPlanned = PlannedTask::whereNull('execution_date')->count(); + $totalCompleted = PlannedTask::whereNotNull('execution_date')->count(); + + if ($this->command) { + $this->command->info("✓ Created {$totalPlanned} planned tasks and {$totalCompleted} completed tasks"); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/PruningSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/PruningSeeder.php new file mode 100644 index 0000000..3c90bf5 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/PruningSeeder.php @@ -0,0 +1,96 @@ +get() + ->keyBy(fn (VineyardRow $row) => $row->varietyVariation->grapeVariety->variety_name ?? $row->id); + + $sessions = [ + [ + 'variety' => 'Grüner Veltliner', + 'treatment_note' => 'Summer canopy thinning', + 'method' => 'Canopy thinning', + 'percentage_removed' => 20, + 'note' => 'Light thinning for air circulation', + 'planned_for' => now()->addDays(10)->format('Y-m-d'), + ], + [ + 'variety' => 'Riesling', + 'treatment_note' => 'Leaf removal around clusters', + 'method' => 'Leaf thinning', + 'percentage_removed' => 15, + 'note' => 'Improve sunlight exposure and air circulation', + 'planned_for' => now()->addWeeks(4)->format('Y-m-d'), + ], + [ + 'variety' => 'Blaufränkisch', + 'treatment_note' => 'Winter spur pruning', + 'method' => 'Spur pruning', + 'percentage_removed' => 35, + 'note' => 'Balanced spur pruning to manage yield', + 'completed_at' => now()->subMonths(1)->format('Y-m-d'), + ], + ]; + + foreach ($sessions as $session) { + $row = $vineyardRows[$session['variety']] ?? null; + + if (! $row) { + continue; + } + + $treatment = Treatment::updateOrCreate( + [ + 'row_id' => $row->id, + 'note' => $session['treatment_note'], + ], + [] + ); + + $pruning = Pruning::updateOrCreate( + ['treatment_id' => $treatment->treatment_id], + [ + 'method' => $session['method'], + 'percentage_removed' => $session['percentage_removed'], + 'note' => $session['note'], + ] + ); + + $plannedDate = $session['planned_for'] ?? null; + $completedDate = $session['completed_at'] ?? null; + $defaultDate = $plannedDate ?? $completedDate; + + if ($plannedDate || $completedDate || $defaultDate) { + PlannedTask::updateOrCreate( + [ + 'type' => 'Pruning', + 'taskable_id' => $pruning->getKey(), + 'taskable_type' => Pruning::class, + ], + [ + 'planned_date' => $plannedDate ?? $defaultDate, + 'execution_date' => $completedDate, + 'note' => $session['treatment_note'], + ] + ); + } + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/PurchaseSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/PurchaseSeeder.php new file mode 100644 index 0000000..5eac719 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/PurchaseSeeder.php @@ -0,0 +1,137 @@ +first() ?? User::first(); + + if (! $customer) { + if ($this->command) { + $this->command->warn('No users found. Skipping PurchaseSeeder.'); + } + return; + } + + $wines = Wine::where('status', 'ready')->get(); + + if ($wines->isEmpty()) { + if ($this->command) { + $this->command->warn('No wines available. Skipping PurchaseSeeder.'); + } + return; + } + + $winesByName = $wines->keyBy('wine_name'); + + $orders = [ + // Recent orders (within last 30 days) + [ + 'note' => "Name: John Doe\nPhone: +43 123 456 789\nStreet: 123 Wine Street\nCity: Vienna\nPostal Code: 1010\nCountry: Austria", + 'status' => 'shipped', + 'purchased_at' => now()->subDays(6), + 'items' => [ + ['wine' => $wines->random(), 'quantity' => 2], + ['wine' => $wines->random(), 'quantity' => 1], + ], + ], + [ + 'note' => "Name: John Doe\nPhone: +43 123 456 789\nStreet: 456 Grape Avenue\nCity: Salzburg\nPostal Code: 5020\nCountry: Austria", + 'status' => 'shipped', + 'purchased_at' => now()->subDays(5), + 'items' => [ + ['wine' => $wines->random(), 'quantity' => 3], + ], + ], + [ + 'note' => "Name: John Doe\nPhone: +43 123 456 789\nStreet: 789 Vineyard Road\nCity: Graz\nPostal Code: 8010\nCountry: Austria", + 'status' => 'shipped', + 'purchased_at' => now()->subDays(4), + 'items' => [ + ['wine' => $wines->random(), 'quantity' => 6], + ['wine' => $wines->random(), 'quantity' => 3], + ], + ], + [ + 'note' => "Name: John Doe\nPhone: +43 123 456 789\nStreet: 321 Cellar Lane\nCity: Linz\nPostal Code: 4020\nCountry: Austria", + 'status' => 'shipped', + 'purchased_at' => now()->subDays(3), + 'items' => [ + ['wine' => $wines->random(), 'quantity' => 1], + ], + ], + [ + 'note' => "Name: John Doe\nPhone: +43 123 456 789\nStreet: 654 Barrel Street\nCity: Innsbruck\nPostal Code: 6020\nCountry: Austria", + 'status' => 'shipped', + 'purchased_at' => now()->subDays(2), + 'items' => [ + ['wine' => $wines->random(), 'quantity' => 12], + ], + ], + [ + 'note' => "Name: John Doe\nPhone: +43 123 456 789\nStreet: 987 Cork Boulevard\nCity: Klagenfurt\nPostal Code: 9020\nCountry: Austria", + 'status' => 'completed', + 'purchased_at' => now()->subDays(1), + 'items' => [ + ['wine' => $wines->random(), 'quantity' => 2], + ['wine' => $wines->random(), 'quantity' => 2], + ['wine' => $wines->random(), 'quantity' => 2], + ], + ], + ]; + + foreach ($orders as $order) { + $items = $order['items']; + $primaryWine = $items[0]['wine'] ?? null; + + $totalAmount = collect($items)->sum('quantity'); + $totalPrice = collect($items)->sum(fn ($item) => $item['quantity'] * $item['wine']->price_per_bottle); + + $purchase = Purchase::create([ + 'user_id' => $customer->id, + 'wine_id' => $primaryWine?->id, + 'amount' => $totalAmount, + 'price' => $totalPrice, + 'status' => $order['status'], + 'purchased_at' => $order['purchased_at'], + 'note' => $order['note'], + ]); + + foreach ($items as $item) { + $wine = $item['wine']; + + if (! $wine) { + continue; + } + + PurchaseItem::create([ + 'purchase_id' => $purchase->id, + 'wine_id' => $wine->id, + 'quantity' => $item['quantity'], + 'unit_price' => $wine->price_per_bottle, + 'line_total' => round($item['quantity'] * $wine->price_per_bottle, 2), + ]); + } + } + + if ($this->command) { + $this->command->info('✓ Created ' . count($orders) . ' purchase orders'); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/SprayingSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/SprayingSeeder.php new file mode 100644 index 0000000..7d0ec51 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/SprayingSeeder.php @@ -0,0 +1,112 @@ +get() + ->keyBy(fn (VineyardRow $row) => $row->varietyVariation->grapeVariety->variety_name ?? $row->id); + + $applications = [ + [ + 'variety' => 'Blaufränkisch', + 'treatment_note' => 'Fungicide application for mildew prevention', + 'pesticide' => 'Copper sulfate', + 'concentration' => 0.20, + 'note' => 'Preventive treatment before rainy season', + 'planned_for' => now()->addDays(3)->format('Y-m-d'), + ], + [ + 'variety' => 'St. Laurent', + 'treatment_note' => 'Botrytis control spray', + 'pesticide' => 'Sulfur-lime mix', + 'concentration' => 0.15, + 'note' => 'Evening spray to avoid leaf burn', + 'planned_for' => now()->addWeeks(1)->format('Y-m-d'), + ], + [ + 'variety' => 'Riesling', + 'treatment_note' => 'Organic pest control application', + 'pesticide' => 'Dithane M-45', + 'concentration' => 0.18, + 'note' => 'Preventive spray for pest management', + 'planned_for' => now()->addWeeks(5)->format('Y-m-d'), + ], + [ + 'variety' => 'Chardonnay', + 'treatment_note' => 'Pre-flowering mildew protection', + 'pesticide' => 'Copper sulfate', + 'concentration' => 0.20, + 'note' => 'Applied to prevent downy mildew before flowering', + 'completed_at' => now()->subWeeks(3)->format('Y-m-d'), + ], + [ + 'variety' => 'Grüner Veltliner', + 'treatment_note' => 'Urgent aphid control treatment', + 'pesticide' => 'Neem oil solution', + 'concentration' => 0.12, + 'note' => 'Apply in early morning to avoid leaf damage', + 'planned_for' => now()->format('Y-m-d'), + ], + ]; + + foreach ($applications as $application) { + $row = $rows[$application['variety']] ?? null; + + if (! $row) { + continue; + } + + $treatment = Treatment::updateOrCreate( + [ + 'row_id' => $row->id, + 'note' => $application['treatment_note'], + ], + [] + ); + + $spraying = Spraying::updateOrCreate( + ['treatment_id' => $treatment->treatment_id], + [ + 'pesticide' => $application['pesticide'], + 'concentration' => $application['concentration'], + 'note' => $application['note'], + ] + ); + + $plannedDate = $application['planned_for'] ?? null; + $completedDate = $application['completed_at'] ?? null; + $defaultDate = $plannedDate ?? $completedDate; + + if ($plannedDate || $completedDate || $defaultDate) { + PlannedTask::updateOrCreate( + [ + 'type' => 'Spraying', + 'taskable_id' => $spraying->getKey(), + 'taskable_type' => Spraying::class, + ], + [ + 'planned_date' => $plannedDate ?? $defaultDate, + 'execution_date' => $completedDate, + 'note' => $application['treatment_note'], + ] + ); + } + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/UserSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/UserSeeder.php new file mode 100644 index 0000000..ec231bc --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/UserSeeder.php @@ -0,0 +1,30 @@ +value; + + User::updateOrCreate( + ['email' => sprintf('%s@winery.test', $username)], + [ + 'name' => ucfirst($username) . ' User', + 'username' => $username, + 'password' => 'password', + 'role' => $role, + ] + ); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/VarietyVariationSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/VarietyVariationSeeder.php new file mode 100644 index 0000000..904e93c --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/VarietyVariationSeeder.php @@ -0,0 +1,104 @@ + 'Grüner Veltliner', + 'color' => 'green', + 'description' => 'Classic green variation', + 'typical_sugar_content' => 19.5, + 'typical_alcohol' => 12.5, + 'ripening_period' => 'September - early October', + 'status' => 'active' + ], + [ + 'variety' => 'Riesling', + 'color' => 'green', + 'description' => 'Green variation with high acidity', + 'typical_sugar_content' => 21.0, + 'typical_alcohol' => 13.0, + 'ripening_period' => 'Late September - mid-October', + 'status' => 'active' + ], + [ + 'variety' => 'Blaufränkisch', + 'color' => 'blue', + 'description' => 'Blue variation with pronounced tannins', + 'typical_sugar_content' => 22.5, + 'typical_alcohol' => 12.0, + 'ripening_period' => 'Mid-October', + 'status' => 'active' + ], + [ + 'variety' => 'St. Laurent', + 'color' => 'blue', + 'description' => 'Blue variation with delicate tannins', + 'typical_sugar_content' => 20.0, + 'typical_alcohol' => 11.5, + 'ripening_period' => 'Early October', + 'status' => 'active' + ], + [ + 'variety' => 'Müller Thurgau', + 'color' => 'green', + 'description' => 'Early green variation', + 'typical_sugar_content' => 18.0, + 'typical_alcohol' => 11.0, + 'ripening_period' => 'Early September', + 'status' => 'active' + ], + [ + 'variety' => 'Chardonnay', + 'color' => 'green', + 'description' => 'Premium green variation', + 'typical_sugar_content' => 21.5, + 'typical_alcohol' => 13.5, + 'ripening_period' => 'Mid-October', + 'status' => 'active' + ], + ]; + + foreach ($variations as $variation) { + $varietyName = $variation['variety']; + + if (! isset($varietyIds[$varietyName])) { + continue; + } + + VarietyVariation::updateOrCreate( + [ + 'grape_variety_id' => $varietyIds[$varietyName], + 'color' => $variation['color'], + ], + [ + 'description' => $variation['description'], + 'typical_sugar_content' => $variation['typical_sugar_content'], + 'typical_alcohol' => $variation['typical_alcohol'], + 'ripening_period' => $variation['ripening_period'], + 'status' => $variation['status'], + ] + ); + } + + if ($this->command) { + $this->command->info('✓ Created ' . count($variations) . ' variety variations'); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/VineyardRowSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/VineyardRowSeeder.php new file mode 100644 index 0000000..b9072ae --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/VineyardRowSeeder.php @@ -0,0 +1,228 @@ +get() + ->keyBy(fn (VarietyVariation $variation) => $variation->grapeVariety->variety_name ?? $variation->id); + + $rows = [ + // Grüner Veltliner - 3 rows + [ + 'variety' => 'Grüner Veltliner', + 'vine_count' => 120, + 'planting_year' => 2015, + 'area' => 450.50, + 'location' => [2, 1], + 'status' => 'active', + 'notes' => 'Oldest vineyard row, excellent quality', + ], + [ + 'variety' => 'Grüner Veltliner', + 'vine_count' => 115, + 'planting_year' => 2016, + 'area' => 430.00, + 'location' => [2, 2], + 'status' => 'active', + 'notes' => 'North-facing slope, good drainage', + ], + [ + 'variety' => 'Grüner Veltliner', + 'vine_count' => 125, + 'planting_year' => 2015, + 'area' => 465.75, + 'location' => [2, 3], + 'status' => 'active', + 'notes' => 'Premium section with old vines', + ], + + // Riesling - 3 rows + [ + 'variety' => 'Riesling', + 'vine_count' => 100, + 'planting_year' => 2016, + 'area' => 380.00, + 'location' => [3, 1], + 'status' => 'active', + 'notes' => 'Optimal sun orientation', + ], + [ + 'variety' => 'Riesling', + 'vine_count' => 95, + 'planting_year' => 2017, + 'area' => 365.00, + 'location' => [3, 2], + 'status' => 'active', + 'notes' => 'Steep slope, excellent ripening', + ], + [ + 'variety' => 'Riesling', + 'vine_count' => 105, + 'planting_year' => 2016, + 'area' => 395.50, + 'location' => [3, 3], + 'status' => 'active', + 'notes' => 'Protected from wind', + ], + + // Blaufränkisch - 4 rows + [ + 'variety' => 'Blaufränkisch', + 'vine_count' => 150, + 'planting_year' => 2014, + 'area' => 520.75, + 'location' => [4, 2], + 'status' => 'active', + 'notes' => 'Oldest red variety', + ], + [ + 'variety' => 'Blaufränkisch', + 'vine_count' => 140, + 'planting_year' => 2015, + 'area' => 495.00, + 'location' => [4, 3], + 'status' => 'active', + 'notes' => 'South-facing, ideal for reds', + ], + [ + 'variety' => 'Blaufränkisch', + 'vine_count' => 145, + 'planting_year' => 2014, + 'area' => 510.25, + 'location' => [4, 4], + 'status' => 'active', + 'notes' => 'Clay-rich soil, intense flavor', + ], + [ + 'variety' => 'Blaufränkisch', + 'vine_count' => 135, + 'planting_year' => 2016, + 'area' => 480.00, + 'location' => [4, 5], + 'status' => 'active', + 'notes' => 'Younger vines, developing well', + ], + + // St. Laurent - 2 rows + [ + 'variety' => 'St. Laurent', + 'vine_count' => 80, + 'planting_year' => 2017, + 'area' => 290.30, + 'location' => [5, 2], + 'status' => 'active', + 'notes' => 'Younger planting, doing well', + ], + [ + 'variety' => 'St. Laurent', + 'vine_count' => 85, + 'planting_year' => 2018, + 'area' => 305.50, + 'location' => [5, 3], + 'status' => 'active', + 'notes' => 'Experimental clone, promising results', + ], + + // Müller Thurgau - 3 rows + [ + 'variety' => 'Müller Thurgau', + 'vine_count' => 110, + 'planting_year' => 2018, + 'area' => 410.20, + 'location' => [1, 3], + 'status' => 'active', + 'notes' => 'Test planting of new clone', + ], + [ + 'variety' => 'Müller Thurgau', + 'vine_count' => 105, + 'planting_year' => 2019, + 'area' => 395.00, + 'location' => [1, 4], + 'status' => 'active', + 'notes' => 'Cool microclimate, early harvest', + ], + [ + 'variety' => 'Müller Thurgau', + 'vine_count' => 115, + 'planting_year' => 2018, + 'area' => 425.75, + 'location' => [1, 5], + 'status' => 'active', + 'notes' => 'Higher elevation, good acidity', + ], + + // Chardonnay - 3 rows + [ + 'variety' => 'Chardonnay', + 'vine_count' => 95, + 'planting_year' => 2019, + 'area' => 350.00, + 'location' => [2, 4], + 'status' => 'active', + 'notes' => 'Premium variety, requires care', + ], + [ + 'variety' => 'Chardonnay', + 'vine_count' => 90, + 'planting_year' => 2020, + 'area' => 335.50, + 'location' => [2, 5], + 'status' => 'active', + 'notes' => 'Newest planting, organic certified', + ], + [ + 'variety' => 'Chardonnay', + 'vine_count' => 100, + 'planting_year' => 2019, + 'area' => 365.00, + 'location' => [2, 6], + 'status' => 'active', + 'notes' => 'Reserve quality potential', + ], + ]; + + foreach ($rows as $row) { + $variation = $variationByVariety->get($row['variety']); + + if (! $variation) { + continue; + } + + $location = $row['location']; + if (is_array($location) && count($location) === 2) { + $location = sprintf('%d,%d', $location[0], $location[1]); + } + + VineyardRow::updateOrCreate( + ['variety_variation_id' => $variation->id], + [ + 'vine_count' => $row['vine_count'], + 'planting_year' => $row['planting_year'], + 'area' => $row['area'], + 'location' => $location, + 'status' => $row['status'], + 'notes' => $row['notes'], + ] + ); + } + + if ($this->command) { + $this->command->info('✓ Created ' . count($rows) . ' vineyard rows'); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WateringSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WateringSeeder.php new file mode 100644 index 0000000..561ae07 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WateringSeeder.php @@ -0,0 +1,104 @@ +get() + ->keyBy(fn (VineyardRow $row) => $row->varietyVariation->grapeVariety->variety_name ?? $row->id); + + $schedules = [ + [ + 'variety' => 'Grüner Veltliner', + 'treatment_note' => 'Irrigation cycle before flowering', + 'watering_note' => 'Applied via drip system to maintain soil moisture', + 'time_interval' => 72, + 'amount' => 120.50, + 'planned_for' => now()->addDays(5)->format('Y-m-d'), + ], + [ + 'variety' => 'Müller Thurgau', + 'treatment_note' => 'Post-harvest irrigation', + 'watering_note' => 'Deep soak to support root recovery', + 'time_interval' => 96, + 'amount' => 150.00, + 'planned_for' => now()->addWeeks(3)->format('Y-m-d'), + ], + [ + 'variety' => 'Riesling', + 'treatment_note' => 'Summer watering cycle', + 'watering_note' => 'Regular irrigation during dry period', + 'time_interval' => 48, + 'amount' => 100.00, + 'completed_at' => now()->subDays(10)->format('Y-m-d'), + ], + [ + 'variety' => 'Blaufränkisch', + 'treatment_note' => 'Emergency drought response irrigation', + 'watering_note' => 'Deep root watering to prevent vine stress', + 'time_interval' => 24, + 'amount' => 200.00, + 'planned_for' => now()->subDays(3)->format('Y-m-d'), + ], + ]; + + foreach ($schedules as $schedule) { + $row = $rows[$schedule['variety']] ?? null; + + if (! $row) { + continue; + } + + $treatment = Treatment::updateOrCreate( + [ + 'row_id' => $row->id, + 'note' => $schedule['treatment_note'], + ], + [] + ); + + $watering = Watering::updateOrCreate( + ['treatment_id' => $treatment->treatment_id], + [ + 'time_interval' => $schedule['time_interval'], + 'amount' => $schedule['amount'], + 'note' => $schedule['watering_note'], + ] + ); + + $plannedDate = $schedule['planned_for'] ?? null; + $completedDate = $schedule['completed_at'] ?? null; + $defaultDate = $plannedDate ?? $completedDate; + + if ($plannedDate || $completedDate || $defaultDate) { + PlannedTask::updateOrCreate( + [ + 'type' => 'Watering', + 'taskable_id' => $watering->getKey(), + 'taskable_type' => Watering::class, + ], + [ + 'planned_date' => $plannedDate ?? $defaultDate, + 'execution_date' => $completedDate, + 'note' => $schedule['treatment_note'], + ] + ); + } + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WineProductionSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WineProductionSeeder.php new file mode 100644 index 0000000..2139770 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WineProductionSeeder.php @@ -0,0 +1,219 @@ +get() + ->keyBy(fn (Harvest $harvest) => ($harvest->vineyardRow?->varietyVariation->grapeVariety->variety_name ?? $harvest->vineyard_row_id) . ':' . $harvest->date->format('Y-m-d')); + + $productions = [ + // ========== 2024 VINTAGE WINES ========== + [ + 'wine_name' => 'Grüner Veltliner Young Wine', + 'variety' => 'Grüner Veltliner', + 'date' => '2024-09-15', + 'consumed_weight' => 850.50, + 'blend_percentage' => 100.00, + ], + // Riesling Classic 2024 - blended from two harvests + [ + 'wine_name' => 'Riesling Classic', + 'variety' => 'Riesling', + 'date' => '2024-09-20', + 'consumed_weight' => 500.00, + 'blend_percentage' => 64.00, + ], + [ + 'wine_name' => 'Riesling Classic', + 'variety' => 'Riesling', + 'date' => now()->subDays(18)->format('Y-m-d'), + 'consumed_weight' => 280.40, + 'blend_percentage' => 36.00, + ], + [ + 'wine_name' => 'Müller Thurgau Young', + 'variety' => 'Müller Thurgau', + 'date' => '2024-09-10', + 'consumed_weight' => 780.20, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'Chardonnay Classic', + 'variety' => 'Chardonnay', + 'date' => now()->subDays(5)->format('Y-m-d'), + 'consumed_weight' => 420.50, + 'blend_percentage' => 100.00, + ], + // Blaufränkisch Young 2024 - blended from two harvests + [ + 'wine_name' => 'Blaufränkisch Young', + 'variety' => 'Blaufränkisch', + 'date' => '2024-10-05', + 'consumed_weight' => 650.00, + 'blend_percentage' => 59.00, + ], + [ + 'wine_name' => 'Blaufränkisch Young', + 'variety' => 'Blaufränkisch', + 'date' => now()->subDays(8)->format('Y-m-d'), + 'consumed_weight' => 450.00, + 'blend_percentage' => 41.00, + ], + [ + 'wine_name' => 'St. Laurent New Wine', + 'variety' => 'St. Laurent', + 'date' => '2024-10-01', + 'consumed_weight' => 600.75, + 'blend_percentage' => 100.00, + ], + + // ========== 2023 VINTAGE WINES ========== + [ + 'wine_name' => 'Grüner Veltliner Cabinet', + 'variety' => 'Grüner Veltliner', + 'date' => '2023-09-18', + 'consumed_weight' => 750.00, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'Grüner Veltliner Late Harvest', + 'variety' => 'Grüner Veltliner', + 'date' => '2023-10-12', + 'consumed_weight' => 650.50, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'Müller Thurgau Cabinet', + 'variety' => 'Müller Thurgau', + 'date' => '2023-09-08', + 'consumed_weight' => 890.75, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'Chardonnay Unfiltered', + 'variety' => 'Chardonnay', + 'date' => '2023-09-22', + 'consumed_weight' => 580.30, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'Blaufränkisch Classic', + 'variety' => 'Blaufränkisch', + 'date' => '2023-10-08', + 'consumed_weight' => 900.00, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'St. Laurent Moravian', + 'variety' => 'St. Laurent', + 'date' => '2023-10-02', + 'consumed_weight' => 720.50, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'St. Laurent Rosé', + 'variety' => 'St. Laurent', + 'date' => '2023-09-28', + 'consumed_weight' => 480.25, + 'blend_percentage' => 100.00, + ], + + // ========== 2022 VINTAGE WINES ========== + [ + 'wine_name' => 'Grüner Veltliner Grape Selection', + 'variety' => 'Grüner Veltliner', + 'date' => '2022-10-20', + 'consumed_weight' => 580.80, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'Riesling Dry', + 'variety' => 'Riesling', + 'date' => '2022-10-05', + 'consumed_weight' => 640.60, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'Chardonnay Barrique', + 'variety' => 'Chardonnay', + 'date' => '2022-09-25', + 'consumed_weight' => 510.40, + 'blend_percentage' => 100.00, + ], + // Blaufränkisch Reserve 2022 - premium blend from single harvest + [ + 'wine_name' => 'Blaufränkisch Reserve', + 'variety' => 'Blaufränkisch', + 'date' => '2022-10-12', + 'consumed_weight' => 680.75, + 'blend_percentage' => 100.00, + ], + [ + 'wine_name' => 'St. Laurent Barrique', + 'variety' => 'St. Laurent', + 'date' => '2022-10-05', + 'consumed_weight' => 620.90, + 'blend_percentage' => 100.00, + ], + + // ========== 2021 VINTAGE WINES ========== + [ + 'wine_name' => 'Riesling Berry Selection', + 'variety' => 'Riesling', + 'date' => '2021-11-08', + 'consumed_weight' => 420.50, + 'blend_percentage' => 100.00, + ], + + // ========== 2020 VINTAGE WINES ========== + [ + 'wine_name' => 'Blaufränkisch Archive', + 'variety' => 'Blaufränkisch', + 'date' => '2020-10-18', + 'consumed_weight' => 550.00, + 'blend_percentage' => 100.00, + ], + ]; + + foreach ($productions as $production) { + $wineId = $wineIds[$production['wine_name']] ?? null; + $harvestKey = $production['variety'] . ':' . $production['date']; + $harvest = $harvests[$harvestKey] ?? null; + + if (! $wineId || ! $harvest) { + continue; + } + + WineProduction::updateOrCreate( + [ + 'wine_id' => $wineId, + 'harvest_id' => $harvest->id, + ], + [ + 'consumed_weight' => $production['consumed_weight'], + 'blend_percentage' => $production['blend_percentage'], + ] + ); + } + + if ($this->command) { + $this->command->info('✓ Created ' . count($productions) . ' wine production records'); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WineSeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WineSeeder.php new file mode 100644 index 0000000..481a65f --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WineSeeder.php @@ -0,0 +1,395 @@ + 'Grüner Veltliner', + 'vintage' => 2023, + 'wine_name' => 'Grüner Veltliner Cabinet', + 'wine_type' => 'white', + 'sweetness' => 'dry', + 'description' => 'Fresh, light-bodied white wine with citrus and green apple notes. Perfect aperitif with excellent acidity.', + 'alcohol_percentage' => 11.5, + 'bottles_produced' => 1500, + 'bottles_in_stock' => 1320, + 'price_per_bottle' => 19.00, + 'bottle_volume' => 0.75, + 'production_date' => '2023-10-05', + 'bottling_date' => '2024-02-20', + 'status' => 'ready', + 'image_url' => 'wines/Gruner-Veltliner-Cabinet.png', + ], + [ + 'variety' => 'Grüner Veltliner', + 'vintage' => 2023, + 'wine_name' => 'Grüner Veltliner Late Harvest', + 'wine_type' => 'white', + 'sweetness' => 'semi_dry', + 'description' => 'Late harvest wine with ripe stone fruit aromas, honey undertones, and balanced sweetness. Pairs beautifully with Asian cuisine.', + 'alcohol_percentage' => 12.5, + 'bottles_produced' => 1200, + 'bottles_in_stock' => 1150, + 'price_per_bottle' => 19.00, + 'bottle_volume' => 0.75, + 'production_date' => '2023-10-25', + 'bottling_date' => '2024-03-15', + 'status' => 'ready', + 'image_url' => 'wines/Gruner-Veltliner-Late-Harvest.png', + ], + [ + 'variety' => 'Grüner Veltliner', + 'vintage' => 2022, + 'wine_name' => 'Grüner Veltliner Grape Selection', + 'wine_type' => 'white', + 'sweetness' => 'semi_sweet', + 'description' => 'Selection of finest grape clusters. Rich, complex wine with tropical fruit, hints of white pepper, and elegant finish.', + 'alcohol_percentage' => 13.0, + 'bottles_produced' => 800, + 'bottles_in_stock' => 650, + 'price_per_bottle' => 24.90, + 'bottle_volume' => 0.75, + 'production_date' => '2022-11-10', + 'bottling_date' => '2023-04-20', + 'status' => 'ready', + 'image_url' => 'wines/Gruner-Veltliner-Grape-Selection.png', + ], + [ + 'variety' => 'Grüner Veltliner', + 'vintage' => 2024, + 'wine_name' => 'Grüner Veltliner Young Wine', + 'wine_type' => 'white', + 'sweetness' => 'dry', + 'description' => 'Young wine with vibrant freshness, grassy notes, and crisp minerality. Currently aging to develop full character.', + 'alcohol_percentage' => 11.0, + 'bottles_produced' => 1800, + 'bottles_in_stock' => 1800, + 'price_per_bottle' => 10.90, + 'bottle_volume' => 0.75, + 'production_date' => '2024-10-01', + 'bottling_date' => '2025-03-01', + 'status' => 'aging', + 'image_url' => 'wines/Grüner Veltliner Young Wine.png', + ], + + // ========== RIESLING (3 wines) ========== + [ + 'variety' => 'Riesling', + 'vintage' => 2022, + 'wine_name' => 'Riesling Dry', + 'wine_type' => 'white', + 'sweetness' => 'dry', + 'description' => 'Dry Riesling with classic petrol notes, citrus aromas, and mineral finish. Crisp acidity makes it ideal for seafood.', + 'alcohol_percentage' => 12.0, + 'bottles_produced' => 900, + 'bottles_in_stock' => 825, + 'price_per_bottle' => 17.90, + 'bottle_volume' => 0.75, + 'production_date' => '2022-10-15', + 'bottling_date' => '2023-03-10', + 'status' => 'ready', + 'image_url' => 'wines/Riesling-Dry.png', + ], + [ + 'variety' => 'Riesling', + 'vintage' => 2021, + 'wine_name' => 'Riesling Berry Selection', + 'wine_type' => 'white', + 'sweetness' => 'sweet', + 'description' => 'Noble sweet wine from individually selected berries. Luscious apricot, honey, and orange marmalade flavors. Perfect dessert wine.', + 'alcohol_percentage' => 11.5, + 'bottles_produced' => 500, + 'bottles_in_stock' => 380, + 'price_per_bottle' => 39.90, + 'bottle_volume' => 0.75, + 'production_date' => '2021-11-20', + 'bottling_date' => '2022-05-15', + 'status' => 'ready', + 'image_url' => 'wines/Riesling-Berry-Selection.png', + ], + [ + 'variety' => 'Riesling', + 'vintage' => 2024, + 'wine_name' => 'Riesling Classic', + 'wine_type' => 'white', + 'sweetness' => 'dry', + 'description' => 'Classic Riesling style with green apple, peach, and petrol notes. Still developing in the cellar.', + 'alcohol_percentage' => 12.0, + 'bottles_produced' => 1100, + 'bottles_in_stock' => 1100, + 'price_per_bottle' => 19.90, + 'bottle_volume' => 0.75, + 'production_date' => '2024-10-10', + 'bottling_date' => '2025-04-01', + 'status' => 'aging', + 'image_url' => 'wines/Riesling Classic.png', + ], + + // ========== MÜLLER THURGAU (2 wines) ========== + [ + 'variety' => 'Müller Thurgau', + 'vintage' => 2023, + 'wine_name' => 'Müller Thurgau Cabinet', + 'wine_type' => 'white', + 'sweetness' => 'semi_dry', + 'description' => 'Easy-drinking wine with delicate muscat aroma, elderflower notes, and refreshing character. Perfect for warm summer evenings.', + 'alcohol_percentage' => 11.0, + 'bottles_produced' => 1600, + 'bottles_in_stock' => 1450, + 'price_per_bottle' => 9.00, + 'bottle_volume' => 0.75, + 'production_date' => '2023-09-20', + 'bottling_date' => '2024-01-15', + 'status' => 'ready', + 'image_url' => 'wines/Muller-Thurgau-Cabinet.png', + ], + [ + 'variety' => 'Müller Thurgau', + 'vintage' => 2024, + 'wine_name' => 'Müller Thurgau Young', + 'wine_type' => 'white', + 'sweetness' => 'semi_dry', + 'description' => 'Young, fresh wine with aromatic profile. Floral and fruity character will develop beautifully. Currently in production.', + 'alcohol_percentage' => 10.5, + 'bottles_produced' => 2000, + 'bottles_in_stock' => 2000, + 'price_per_bottle' => 8.90, + 'bottle_volume' => 0.75, + 'production_date' => '2024-09-25', + 'bottling_date' => '2025-01-20', + 'status' => 'in_production', + 'image_url' => 'wines/Müller Thurgau Young.png', + ], + + // ========== CHARDONNAY (3 wines) ========== + [ + 'variety' => 'Chardonnay', + 'vintage' => 2022, + 'wine_name' => 'Chardonnay Barrique', + 'wine_type' => 'white', + 'sweetness' => 'dry', + 'description' => 'Premium Chardonnay aged in French oak barrels. Rich, buttery texture with vanilla, toasted nuts, and ripe apple. Complex and elegant.', + 'alcohol_percentage' => 13.5, + 'bottles_produced' => 700, + 'bottles_in_stock' => 580, + 'price_per_bottle' => 27.90, + 'bottle_volume' => 0.75, + 'production_date' => '2022-10-01', + 'bottling_date' => '2023-09-15', + 'status' => 'ready', + 'image_url' => 'wines/Chardonnay-Barrique.png', + ], + [ + 'variety' => 'Chardonnay', + 'vintage' => 2023, + 'wine_name' => 'Chardonnay Unfiltered', + 'wine_type' => 'white', + 'sweetness' => 'dry', + 'description' => 'Unfiltered Chardonnay with natural cloudiness. Full-bodied with citrus, pear, and mineral notes. Authentic, terroir-driven style.', + 'alcohol_percentage' => 12.5, + 'bottles_produced' => 900, + 'bottles_in_stock' => 820, + 'price_per_bottle' => 18.90, + 'bottle_volume' => 0.75, + 'production_date' => '2023-09-28', + 'bottling_date' => '2024-03-10', + 'status' => 'ready', + 'image_url' => 'wines/Chardonnay-Unfiltered.png', + ], + [ + 'variety' => 'Chardonnay', + 'vintage' => 2024, + 'wine_name' => 'Chardonnay Classic', + 'wine_type' => 'white', + 'sweetness' => 'dry', + 'description' => 'Classic style Chardonnay without oak aging. Clean, fresh, with green apple and white flowers. Currently maturing in tank.', + 'alcohol_percentage' => 12.0, + 'bottles_produced' => 1200, + 'bottles_in_stock' => 1200, + 'price_per_bottle' => 13.90, + 'bottle_volume' => 0.75, + 'production_date' => '2024-09-30', + 'bottling_date' => '2025-02-15', + 'status' => 'aging', + 'image_url' => 'wines/Chardonnay Classic.png', + ], + + // ========== BLAUFRÄNKISCH (4 wines) ========== + [ + 'variety' => 'Blaufränkisch', + 'vintage' => 2022, + 'wine_name' => 'Blaufränkisch Reserve', + 'wine_type' => 'red', + 'sweetness' => 'dry', + 'description' => 'Reserve quality red wine with deep ruby color. Intense blackberry, cherry, and spice. Firm tannins with excellent aging potential.', + 'alcohol_percentage' => 13.5, + 'bottles_produced' => 600, + 'bottles_in_stock' => 450, + 'price_per_bottle' => 25.90, + 'bottle_volume' => 0.75, + 'production_date' => '2022-10-20', + 'bottling_date' => '2024-03-15', + 'status' => 'ready', + 'image_url' => 'wines/Blaufrankisch-Reserve.png', + ], + [ + 'variety' => 'Blaufränkisch', + 'vintage' => 2023, + 'wine_name' => 'Blaufränkisch Classic', + 'wine_type' => 'red', + 'sweetness' => 'dry', + 'description' => 'Classic style with pronounced spicy character, dark fruit, and medium body. Excellent with grilled meats and hearty stews.', + 'alcohol_percentage' => 12.5, + 'bottles_produced' => 1400, + 'bottles_in_stock' => 1150, + 'price_per_bottle' => 14.90, + 'bottle_volume' => 0.75, + 'production_date' => '2023-10-18', + 'bottling_date' => '2024-09-01', + 'status' => 'ready', + 'image_url' => 'wines/Blaufrankisch-Classic.png', + ], + [ + 'variety' => 'Blaufränkisch', + 'vintage' => 2020, + 'wine_name' => 'Blaufränkisch Archive', + 'wine_type' => 'red', + 'sweetness' => 'dry', + 'description' => 'Mature archive wine from excellent vintage. Complex layers of dried fruit, leather, tobacco, and forest floor. Limited quantity.', + 'alcohol_percentage' => 13.0, + 'bottles_produced' => 400, + 'bottles_in_stock' => 0, + 'price_per_bottle' => 32.90, + 'bottle_volume' => 0.75, + 'production_date' => '2020-10-25', + 'bottling_date' => '2022-09-10', + 'status' => 'sold_out', + 'image_url' => 'wines/Blaufränkisch Archive.png', + ], + [ + 'variety' => 'Blaufränkisch', + 'vintage' => 2024, + 'wine_name' => 'Blaufränkisch Young', + 'wine_type' => 'red', + 'sweetness' => 'dry', + 'description' => 'Young red wine with bright fruit and fresh acidity. Currently developing tannin structure and complexity during barrel aging.', + 'alcohol_percentage' => 12.0, + 'bottles_produced' => 1500, + 'bottles_in_stock' => 1500, + 'price_per_bottle' => 12.90, + 'bottle_volume' => 0.75, + 'production_date' => '2024-10-15', + 'bottling_date' => '2025-09-01', + 'status' => 'aging', + 'image_url' => 'wines/Blaufränkisch Young.png', + ], + + // ========== ST. LAURENT (4 wines) ========== + [ + 'variety' => 'St. Laurent', + 'vintage' => 2022, + 'wine_name' => 'St. Laurent Barrique', + 'wine_type' => 'red', + 'sweetness' => 'dry', + 'description' => 'Oak-aged St. Laurent with velvety texture. Red cherry, vanilla, and subtle smoky notes. Elegant and sophisticated.', + 'alcohol_percentage' => 13.0, + 'bottles_produced' => 750, + 'bottles_in_stock' => 620, + 'price_per_bottle' => 22.90, + 'bottle_volume' => 0.75, + 'production_date' => '2022-10-12', + 'bottling_date' => '2024-02-28', + 'status' => 'ready', + 'image_url' => 'wines/St-Laurent-Barrique.png', + ], + [ + 'variety' => 'St. Laurent', + 'vintage' => 2023, + 'wine_name' => 'St. Laurent Moravian', + 'wine_type' => 'red', + 'sweetness' => 'dry', + 'description' => 'Traditional Moravian style with soft tannins, red fruit, and silky mouthfeel. Approachable and food-friendly.', + 'alcohol_percentage' => 12.0, + 'bottles_produced' => 1200, + 'bottles_in_stock' => 950, + 'price_per_bottle' => 13.90, + 'bottle_volume' => 0.75, + 'production_date' => '2023-10-10', + 'bottling_date' => '2024-08-15', + 'status' => 'ready', + 'image_url' => 'wines/St-Laurent-Moravian.png', + ], + [ + 'variety' => 'St. Laurent', + 'vintage' => 2023, + 'wine_name' => 'St. Laurent Rosé', + 'wine_type' => 'red', + 'sweetness' => 'semi_dry', + 'description' => 'Lighter style with emphasis on fresh fruit. Strawberry, raspberry, and floral notes. Versatile food pairing.', + 'alcohol_percentage' => 11.5, + 'bottles_produced' => 1000, + 'bottles_in_stock' => 870, + 'price_per_bottle' => 12.90, + 'bottle_volume' => 0.75, + 'production_date' => '2023-10-08', + 'bottling_date' => '2024-02-10', + 'status' => 'ready', + 'image_url' => 'wines/St-Laurent-Rose.png', + ], + [ + 'variety' => 'St. Laurent', + 'vintage' => 2024, + 'wine_name' => 'St. Laurent New Wine', + 'wine_type' => 'red', + 'sweetness' => 'dry', + 'description' => 'New wine with vibrant color and youthful energy. Fresh red fruit and gentle tannins. Currently being produced.', + 'alcohol_percentage' => 11.0, + 'bottles_produced' => 1600, + 'bottles_in_stock' => 1600, + 'price_per_bottle' => 10.90, + 'bottle_volume' => 0.75, + 'production_date' => '2024-10-12', + 'bottling_date' => '2025-08-01', + 'status' => 'in_production', + 'image_url' => 'wines/St. Laurent New Wine.png', + ], + ]; + + foreach ($wines as $wine) { + $varietyName = $wine['variety']; + + if (! isset($varieties[$varietyName])) { + continue; + } + + $payload = $wine; + unset($payload['variety']); + $payload['grape_variety_id'] = $varieties[$varietyName]; + + Wine::updateOrCreate( + ['wine_name' => $payload['wine_name']], + $payload + ); + } + + $this->command->info('✓ Created/updated ' . count($wines) . ' wines'); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WinerySeeder.php b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WinerySeeder.php new file mode 100644 index 0000000..76b382f --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/database/seeders/WinerySeeder.php @@ -0,0 +1,38 @@ +command) { + $this->command->info('🍇 Seeding Winery Data...'); + $this->command->newLine(); + } + + // Seed in correct order due to foreign key dependencies + $this->call([ + GrapeVarietySeeder::class, // 1. Base grape varieties + GrapeVarietyVariantSeeder::class, // 2. Variants depend on varieties + VarietyVariationSeeder::class, // 2. Variations depend on varieties + VineyardRowSeeder::class, // 3. Rows depend on variations + HarvestSeeder::class, // 4. Harvests depend on rows and variations + WineSeeder::class, // 5. Wines depend on varieties + WineProductionSeeder::class, // 6. Productions depend on wines and harvests + ]); + + if ($this->command) { + $this->command->newLine(); + $this->command->info('✅ Winery seeding completed successfully!'); + } + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/doc.html b/3BIT/winter-semester/IIS/xnecasr00/doc.html new file mode 100644 index 0000000..1457447 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/doc.html @@ -0,0 +1,176 @@ + + + + + Projekt IIS + + + + + + +

Vinastv

+ +
+
Autoi
+
Roman Neas + xnecasr00@stud.fit.vutbr.cz - +
    +
  • ERD: Tabuky pre sklize, variciu odrody, vinohradncky riadok, odrodu a vno
    • +
  • Implementcia prpadov pouitia: +
      +
    • Vinr - Kalendr, prava plnovanch loh a zberu, vedenie zznamov o zozbieranch hroznch, zaraovanie vna do predaja
      • +
    • Zkaznk - Nakupovanie vna, histria nkupov
      • +
    • Nvtevnk - Prezeranie katalgu vn, prezeranie zkladnch informci o vinrstve
      • +
    +
    • +
+
+
Tom Foltyn + xfolty21@stud.fit.vutbr.cz - +
    +
  • ERD: Tabuky pre plnovanie, oetrenie, zalievanie, hnojenie, rez, postrek
    • +
  • Implementcia prpadov pouitia: +
      +
    • Vinr - sprva vinohradnckych riadkov (mapa), plnovanie oetren, plnovanie zavlaovania, rezu vinice, sklizne
      • +
    +
  • Intalcia aplikcie na server
    • + +
+
+
Kristin Pribila + xpribik00@stud.fit.vutbr.cz - +
    +
  • ERD: Tabuky pre nkup, uvatea, vinra, pracovnka a zkaznka
    • +
  • Implementcia prpadov pouitia: +
      +
    • Administrtor - sprva uivateov a ich rol, sprva plnovanch akci
      • +
    • Pracovnk vinrstva - zaznamenvanie prevedench innost vo vinici, vykonanie zberu hrozna
      • +
    +
  • Prihlasovanie a registrcia
    • + +
+
+
URL aplikace
+
http://www.stud.fit.vutbr.cz/~xnecasr00/IIS
+
+ +

Uivatel systmu pro testovn

+ + + + + + + +
LoginHesloRole
adminpasswordAdministrtor
winemakerpasswordVina
employeepasswordPracovnk vinastv
customerpasswordZkaznk
Nvtevnk
+ +

Video

+ +https://nextcloud.fit.vutbr.cz/s/g3ycQrXQwwFmpPX + +

Implementace

+ +

Administrtor

+
    +
  • Sprva uvateov a ich rol - app/Http/Controllers/Admin/UserController.php +
    Views: resources/views/admin/users/ (index, create, edit)
    • +
  • Sprva plnovanch akci/udalost - app/Http/Controllers/Admin/EventController.php +
    Views: resources/views/admin/events/ (index, create, edit)
    • +
+ +

Vinr (Winemaker)

+
    +
  • Dashboard a kalendr - app/Http/Controllers/WinemakerController.php +
    Views: resources/views/winemaker/dashboard/ (index, planned-tasks, completed-activities)
    • +
  • Sprva vinohradnckych riadkov - app/Http/Controllers/VineyardRowController.php, app/Http/Controllers/VineyardMapController.php +
    Views: resources/views/vineyard-rows/, resources/views/vineyard/map/
    • +
  • Plnovanie oetren (postreky, hnojenie, zavlaovanie, rez) - app/Http/Controllers/PlannedTaskController.php +
    Views: resources/views/planned-tasks/ (watering, pruning, fertilisation, pesticide, harvest, edit)
    • +
  • Plnovanie a sprva zberu - app/Http/Controllers/HarvestController.php +
    Views: resources/views/winemaker/harvests/ (index, bottle)
    • +
  • Pivnica - vedenie zznamov o vne - app/Http/Controllers/WineController.php (metdy cellarIndex, createBlendForm, storeBlend) +
    Views: resources/views/winemaker/cellar/ (index, create-blend)
    • +
  • Zaraovanie vna do predaja - app/Http/Controllers/WineController.php (metdy salesIndex, addToSales, removeFromSales) +
    Views: resources/views/winemaker/sales/index.blade.php
    • +
+ +

Pracovnk vinrstva (Employee)

+
    +
  • Zaznamenvanie prevedench innost (oetrenia) - app/Http/Controllers/Employee/TaskController.php (metda completeTreatment) +
    Views: resources/views/employee/tasks/index.blade.php
    • +
  • Vykonanie zberu hrozna - app/Http/Controllers/Employee/TaskController.php (metda completeHarvest)
    • +
+ +

Zkaznk (Customer)

+
    +
  • Nakupovanie vna - app/Http/Controllers/CartController.php, app/Http/Controllers/PurchaseController.php +
    Views: resources/views/cart/index.blade.php, resources/views/catalog/
    • +
  • Histria nkupov - app/Http/Controllers/PurchaseController.php (metda myPurchases) +
    Views: resources/views/purchases/my.blade.php
    • +
  • Rezervcie udalost - app/Http/Controllers/EventController.php (metdy reserve, cancelReservation, myReservations) +
    Views: resources/views/events/my-reservations.blade.php
    • +
+ +

Nvtevnk (Guest)

+
    +
  • Prezeranie katalgu vn - app/Http/Controllers/WineController.php (metda catalog) +
    Views: resources/views/catalog/ (index, show)
    • +
  • Prezeranie udalost - app/Http/Controllers/EventController.php (metda index) +
    Views: resources/views/events/index.blade.php
    • +
  • Zkladn informcie o vinrstve - routes/web.php (closure routes) +
    Views: resources/views/about.blade.php, resources/views/contact.blade.php
    • +
  • Prihlsenie a registrcia - app/Http/Controllers/Auth/LoginController.php, app/Http/Controllers/Auth/RegisterController.php +
    Views: resources/views/auth/ (login, register)
    • +
+ +

Dtov modely

+

Vetky modely sa nachdzaj v app/Models/:

+
    +
  • Uvatelia - User.php (s rolami definovanmi v app/Enums/UserRole.php)
    • +
  • Vinica - VineyardRow.php, GrapeVariety.php, VarietyVariation.php
    • +
  • Oetrenia - Treatment.php (abstraktn), Spraying.php, Watering.php, Fertilization.php, Pruning.php
    • +
  • Zber a vroba - Harvest.php, Wine.php, WineProduction.php
    • +
  • Plnovanie - PlannedTask.php
    • +
  • Nkupy - Purchase.php, PurchaseItem.php
    • +
  • Udalosti - Event.php, EventReservation.php
    • +
+ +

Rozrenia

+
    +
  • Integrovan kalendr - WinemakerController::dashboard() - vinr vid vetky plnovan kony
    • +
  • Degustcie a akcie - EventController, Admin\EventController - organizcia akci s rezervciami
    • +

    Databze

    + +ERD diagram + +

    Instalace

    + +

    Lokln bh (bez Dockeru)

    +

    Postup pro lokln vvoj nebo instalaci na klasick server:

    +
      +
    1. Softwarov poadavky - PHP 8.2+ s rozenmi OpenSSL, PDO, Mbstring, Tokenizer, Ctype, JSON, BCMath a Fileinfo; Composer 2; Node.js 18+ (dop. 20 LTS) a npm; MySQL 8 / MariaDB 10.5+; webserver Apache nebo Nginx s PHP-FPM.
      2. +
    2. Staen a rozbalen - projekt umstte na server napklad pomoc git clone nebo rozbalenm archivu do /var/www/laravel-winary; sloky storage a bootstrap/cache mus mt zpis pro uivatele webserveru.
      3. +
    3. Konfigurace prosted - v koeni zkoprujte .env.example na .env; vyplte APP_URL, APP_ENV=production, DB pstupy, ppadn SMTP; vygenerujte kl php artisan key:generate.
      4. +
    4. Instalace zvislost - spuste composer install --no-dev --optimize-autoloader; pot npm install a npm run build pro sestaven statickch asset (Vite).
      5. +
    5. Inicializace databze - zalote przdnou databzi a uivatele; spuste php artisan migrate --force --seed pro vytvoen schmatu a naplnn zkladnmi daty/uivateli; pokud je teba prce se soubory, vytvote symlink php artisan storage:link.
      6. +
    6. Sputn aplikace - nasmrujte webserver na sloku public/; pro produkci doporueno php artisan config:cache a php artisan route:cache; ppadn spuste frontu php artisan queue:work (nap. jako systemd slubu).
      7. +
    + +

    Produkn bh (Docker Compose)

    +

    Pro nasazen pomoc Dockeru lze pout skript ./script/up.sh:

    +
      +
    1. Pprava konfigurace - upravte .env.prod (APP_URL, hesla DB, APP_KEY, port 8741 apod.); soubor se pipojuje do kontejneru jako .env.
      2. +
    2. Start kontejneru - spuste ./script/up.sh, co zavol docker compose -f docker-compose.prod.yml up --build -d pro aplikaci a MySQL (data v volume mysql_data).
      3. +
    3. Prvn inicializace - entrypoint kontejneru ek na databzi, instaluje Composer a NPM zvislosti, provd php artisan migrate:fresh --seed --force, vytvo symlink storage a pebuduje assety. Dal sputn pouije stvajc dependencies.
      4. +
    4. Pstup k aplikaci - webserver/reverse proxy smujte na port APP_PORT (default 8741) a clte na kontejner app; veejn soubory jsou ve sloce public/ uvnit kontejneru.
      5. +
    + + + diff --git a/3BIT/winter-semester/IIS/xnecasr00/docker-compose.prod.yml b/3BIT/winter-semester/IIS/xnecasr00/docker-compose.prod.yml new file mode 100644 index 0000000..bbf4aab --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/docker-compose.prod.yml @@ -0,0 +1,61 @@ +services: + # PHP & Laravel Application + app: + container_name: laravel_winary_app + restart: unless-stopped + working_dir: /var/www + volumes: + - ./:/var/www + - .env.prod:/var/www/.env + depends_on: + - mysql + networks: + - winary_network + - routing_net + env_file: + - .env.prod + build: + context: . + dockerfile: Dockerfile.app + + # MySQL Service + mysql: + image: mysql:8.0 + container_name: laravel_winary_mysql + restart: unless-stopped + env_file: + - .env.prod + environment: + SERVICE_NAME: mysql + volumes: + - mysql_data:/var/lib/mysql + networks: + - winary_network + + # phpMyAdmin Service + # phpmyadmin: + # image: phpmyadmin/phpmyadmin + # container_name: laravel_winary_phpmyadmin + # restart: unless-stopped + # environment: + # PMA_HOST: mysql + # PMA_PORT: 3306 + # PMA_USER: root + # PMA_PASSWORD: ${DB_ROOT_PASSWORD} + # depends_on: + # - mysql + # networks: + # - winary_network + +# Volumes +volumes: + mysql_data: + driver: local + +# Networks +networks: + winary_network: + driver: bridge + routing_net: + driver: bridge + external: true diff --git a/3BIT/winter-semester/IIS/xnecasr00/docker-compose.yml b/3BIT/winter-semester/IIS/xnecasr00/docker-compose.yml new file mode 100644 index 0000000..be1f68e --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/docker-compose.yml @@ -0,0 +1,60 @@ +services: + # PHP & Laravel Application + app: + container_name: laravel_winary_app + restart: unless-stopped + working_dir: /var/www + volumes: + - ./:/var/www + depends_on: + - mysql + networks: + - winary_network + env_file: + - .env + build: + context: . + dockerfile: Dockerfile.app + + # MySQL Service + mysql: + image: mysql:8.0 + container_name: laravel_winary_mysql + restart: unless-stopped + environment: + MYSQL_DATABASE: ${DB_DATABASE} + MYSQL_USER: ${DB_USERNAME} + MYSQL_PASSWORD: ${DB_PASSWORD} + MYSQL_ROOT_PASSWORD: ${DB_ROOT_PASSWORD} + SERVICE_NAME: mysql + volumes: + - mysql_data:/var/lib/mysql + networks: + - winary_network + ports: + - "3306:3306" + + # phpMyAdmin Service + phpmyadmin: + image: phpmyadmin/phpmyadmin + container_name: laravel_winary_phpmyadmin + restart: unless-stopped + environment: + PMA_HOST: mysql + PMA_PORT: 3306 + PMA_USER: root + PMA_PASSWORD: ${DB_ROOT_PASSWORD} + depends_on: + - mysql + networks: + - winary_network + +# Volumes +volumes: + mysql_data: + driver: local + +# Networks +networks: + winary_network: + driver: bridge diff --git a/3BIT/winter-semester/IIS/xnecasr00/docker/app-entrypoint.sh b/3BIT/winter-semester/IIS/xnecasr00/docker/app-entrypoint.sh new file mode 100644 index 0000000..75409ff --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/docker/app-entrypoint.sh @@ -0,0 +1,161 @@ +#!/usr/bin/env bash +set -euo pipefail + +APP_DIR=${APP_DIR:-/var/www} +cd "$APP_DIR" + +DB_HOST=${DB_HOST:-mysql} +DB_PORT=${DB_PORT:-3306} +DB_USERNAME=${DB_USERNAME:-winary_user} +DB_PASSWORD=${DB_PASSWORD:-winary_password} +DB_DATABASE=${DB_DATABASE:-laravel_winary} +APP_PORT=${APP_PORT:-8741} +NPM_INSTALL_ARGS=${NPM_INSTALL_ARGS:---no-fund --no-audit --no-progress} + +prepare_cache_dirs() { + mkdir -p bootstrap/cache \ + storage/logs \ + storage/framework/cache \ + storage/framework/views \ + storage/framework/sessions \ + storage/framework/testing +} + +clear_cached_artifacts() { + rm -f bootstrap/cache/*.php +} + +ensure_php_dependencies() { + if [ -f vendor/autoload.php ]; then + return + fi + + echo "Installing PHP dependencies..." + composer install --no-dev --optimize-autoloader --no-interaction --no-progress +} + +wait_for_database() { + local attempt=0 + while true; do + if php -r " + \$host = getenv('DB_HOST') ?: 'mysql'; + \$port = getenv('DB_PORT') ?: '3306'; + \$db = getenv('DB_DATABASE') ?: 'laravel_winary'; + \$user = getenv('DB_USERNAME') ?: 'winary_user'; + \$pass = getenv('DB_PASSWORD') ?: 'winary_password'; + \$dsn = \"mysql:host=\$host;port=\$port;dbname=\$db\"; + try { + new PDO(\$dsn, \$user, \$pass, [PDO::ATTR_ERRMODE => PDO::ERRMODE_EXCEPTION]); + } catch (Exception \$e) { + fwrite(STDERR, \$e->getMessage()); + exit(1); + } + "; then + echo "Database is ready." + break + else + attempt=$((attempt + 1)) + echo "Database not ready (attempt ${attempt}), retrying in 2s..." + sleep 2 + fi + done +} + +install_node_dependencies() { + if [ -d node_modules ]; then + echo "Node dependencies already installed, skipping npm install." + else + echo "Installing Node dependencies..." + npm ci $NPM_INSTALL_ARGS + fi +} + +build_assets() { + echo "Building frontend assets..." + npm run build +} + +ensure_storage_symlink() { + local link_path="public/storage" + local desired_target="../storage/app/public" + + mkdir -p storage/app/public + + if [ -L "$link_path" ]; then + local current_target + current_target=$(readlink "$link_path") + if [ "$current_target" = "$desired_target" ] || [ "$current_target" = "/var/www/storage/app/public" ]; then + return + fi + + echo "Updating storage symlink (was pointing to $current_target)..." + rm "$link_path" + elif [ -e "$link_path" ]; then + echo "Removing existing public/storage to recreate symlink..." + rm -rf "$link_path" + fi + + if php artisan storage:link --relative >/dev/null 2>&1; then + return + fi + + ln -s "$desired_target" "$link_path" +} + +ensure_docs_symlink() { + local source_path="doc.html" + local link_path="public/doc.html" + + if [ ! -f "$source_path" ]; then + echo "doc.html not found at $source_path, skipping docs symlink." + return + fi + + mkdir -p public + + if [ -L "$link_path" ]; then + local current_target + current_target=$(readlink "$link_path") + if [ "$current_target" = "../doc.html" ] || [ "$current_target" = "/var/www/doc.html" ]; then + return + fi + + echo "Updating doc.html symlink (was pointing to $current_target)..." + rm "$link_path" + elif [ -e "$link_path" ]; then + echo "Removing existing public/doc.html to recreate symlink..." + rm -rf "$link_path" + fi + + ln -s ../doc.html "$link_path" +} + +fix_permissions() { + # Ensure runtime-writable dirs are accessible even on bind mounts + chown -R www-data:www-data storage bootstrap/cache public/storage || true + chmod -R ug+rwX storage bootstrap/cache public/storage || true +} + +prepare_cache_dirs +clear_cached_artifacts + +wait_for_database + +ensure_php_dependencies +php artisan migrate:fresh --seed --force + +install_node_dependencies +build_assets +ensure_storage_symlink +ensure_docs_symlink +fix_permissions + +# Normalize command to always serve on configured APP_PORT when using artisan serve +if [ "$#" -eq 0 ]; then + set -- php artisan serve --host=0.0.0.0 --port="${APP_PORT}" +elif [ "$1" = "php" ] && [ "${2:-}" = "artisan" ] && [ "${3:-}" = "serve" ]; then + shift 3 + set -- php artisan serve --host=0.0.0.0 --port="${APP_PORT}" "$@" +fi + +exec "$@" diff --git a/3BIT/winter-semester/IIS/xnecasr00/erd.png b/3BIT/winter-semester/IIS/xnecasr00/erd.png new file mode 100644 index 0000000..1bb5b48 Binary files /dev/null and b/3BIT/winter-semester/IIS/xnecasr00/erd.png differ diff --git a/3BIT/winter-semester/IIS/xnecasr00/package.json b/3BIT/winter-semester/IIS/xnecasr00/package.json new file mode 100644 index 0000000..4466834 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/package.json @@ -0,0 +1,20 @@ +{ + "$schema": "https://json.schemastore.org/package.json", + "private": true, + "type": "module", + "scripts": { + "build": "vite build", + "dev": "vite" + }, + "dependencies": { + "jquery": "^3.7.1" + }, + "devDependencies": { + "@tailwindcss/vite": "^4.0.0", + "axios": "^1.11.0", + "concurrently": "^9.0.1", + "laravel-vite-plugin": "^2.0.0", + "tailwindcss": "^4.0.0", + "vite": "^7.2.2" + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/public/.htaccess b/3BIT/winter-semester/IIS/xnecasr00/public/.htaccess new file mode 100644 index 0000000..b574a59 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/public/.htaccess @@ -0,0 +1,25 @@ + + + Options -MultiViews -Indexes + + + RewriteEngine On + + # Handle Authorization Header + RewriteCond %{HTTP:Authorization} . + RewriteRule .* - [E=HTTP_AUTHORIZATION:%{HTTP:Authorization}] + + # Handle X-XSRF-Token Header + RewriteCond %{HTTP:x-xsrf-token} . + RewriteRule .* - [E=HTTP_X_XSRF_TOKEN:%{HTTP:X-XSRF-Token}] + + # Redirect Trailing Slashes If Not A Folder... + RewriteCond %{REQUEST_FILENAME} !-d + RewriteCond %{REQUEST_URI} (.+)/$ + RewriteRule ^ %1 [L,R=301] + + # Send Requests To Front Controller... + RewriteCond %{REQUEST_FILENAME} !-d + RewriteCond %{REQUEST_FILENAME} !-f + RewriteRule ^ index.php [L] + diff --git a/3BIT/winter-semester/IIS/xnecasr00/public/favicon.ico b/3BIT/winter-semester/IIS/xnecasr00/public/favicon.ico new file mode 100644 index 0000000..e69de29 diff --git a/3BIT/winter-semester/IIS/xnecasr00/public/index.php b/3BIT/winter-semester/IIS/xnecasr00/public/index.php new file mode 100644 index 0000000..ee8f07e --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/public/index.php @@ -0,0 +1,20 @@ +handleRequest(Request::capture()); diff --git a/3BIT/winter-semester/IIS/xnecasr00/public/robots.txt b/3BIT/winter-semester/IIS/xnecasr00/public/robots.txt new file mode 100644 index 0000000..eb05362 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/public/robots.txt @@ -0,0 +1,2 @@ +User-agent: * +Disallow: diff --git a/3BIT/winter-semester/IIS/xnecasr00/resources/css/app.css b/3BIT/winter-semester/IIS/xnecasr00/resources/css/app.css new file mode 100644 index 0000000..3e6abea --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/resources/css/app.css @@ -0,0 +1,11 @@ +@import 'tailwindcss'; + +@source '../../vendor/laravel/framework/src/Illuminate/Pagination/resources/views/*.blade.php'; +@source '../../storage/framework/views/*.php'; +@source '../**/*.blade.php'; +@source '../**/*.js'; + +@theme { + --font-sans: 'Instrument Sans', ui-sans-serif, system-ui, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', + 'Segoe UI Symbol', 'Noto Color Emoji'; +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/resources/js/app.js b/3BIT/winter-semester/IIS/xnecasr00/resources/js/app.js new file mode 100644 index 0000000..ea19579 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/resources/js/app.js @@ -0,0 +1,25 @@ +import './bootstrap'; + +const pageRoot = document.querySelector('[data-page]'); + +if (pageRoot) { + const pageKey = pageRoot.getAttribute('data-page'); + + const loaders = { + 'vineyard-map-index': () => import('./vineyard/map-index').then((module) => module.default?.()), + 'vineyard-map-edit': () => import('./vineyard/map-edit').then((module) => module.default?.()), + 'vineyard-add-plants': () => import('./vineyard/add-plants').then((module) => module.default?.()), + 'plan-watering': () => import('./planned-tasks/form').then((module) => module.init('watering')), + 'plan-pruning': () => import('./planned-tasks/form').then((module) => module.init('pruning')), + 'plan-fertilisation': () => import('./planned-tasks/form').then((module) => module.init('fertilization')), + 'plan-pesticide': () => import('./planned-tasks/form').then((module) => module.init('spraying')), + 'plan-harvest': () => import('./planned-tasks/form').then((module) => module.init('harvest')), + 'vineyard-overview': () => import('./vineyard/overview'), + }; + + const loader = loaders[pageKey]; + + if (typeof loader === 'function') { + Promise.resolve(loader()).catch((error) => console.error('Failed to initialize page module:', error)); + } +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/resources/js/bootstrap.js b/3BIT/winter-semester/IIS/xnecasr00/resources/js/bootstrap.js new file mode 100644 index 0000000..4785a33 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/resources/js/bootstrap.js @@ -0,0 +1,10 @@ +import axios from 'axios'; +window.axios = axios; + +window.axios.defaults.headers.common['X-Requested-With'] = 'XMLHttpRequest'; + +const tokenMeta = document.head.querySelector('meta[name="csrf-token"]'); + +if (tokenMeta) { + window.axios.defaults.headers.common['X-CSRF-TOKEN'] = tokenMeta.content; +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/resources/js/planned-tasks/form.js b/3BIT/winter-semester/IIS/xnecasr00/resources/js/planned-tasks/form.js new file mode 100644 index 0000000..e5d0ee8 --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/resources/js/planned-tasks/form.js @@ -0,0 +1,148 @@ +import axios from 'axios'; + +function showToast(message, type = 'error') { + let container = document.querySelector('[data-role="toast-container"]'); + if (!container) { + container = document.createElement('div'); + container.dataset.role = 'toast-container'; + container.style.position = 'fixed'; + container.style.top = '1rem'; + container.style.right = '1rem'; + container.style.zIndex = '9999'; + container.style.display = 'flex'; + container.style.flexDirection = 'column'; + container.style.gap = '0.5rem'; + document.body.appendChild(container); + } + + const toast = document.createElement('div'); + toast.textContent = message; + toast.style.padding = '0.6rem 0.9rem'; + toast.style.borderRadius = '6px'; + toast.style.boxShadow = '0 4px 12px rgba(0,0,0,0.15)'; + toast.style.color = '#0f172a'; + toast.style.fontSize = '0.9rem'; + toast.style.backgroundColor = type === 'success' ? '#bbf7d0' : '#fee2e2'; + + container.appendChild(toast); + + setTimeout(() => { + toast.remove(); + if (!container.children.length) { + container.remove(); + } + }, 3000); +} + +function getPageRoot() { + return document.querySelector('[data-page^="plan-"]'); +} + +function normalizeDetails(formData) { + const details = {}; + + for (const [key, value] of formData.entries()) { + if (!key.startsWith('details[')) { + continue; + } + + const field = key.slice('details['.length, -1); + if (value === '') { + continue; + } + + details[field] = value; + } + + return details; +} + +function parseRows(formData) { + return formData.getAll('rows[]').map((value) => parseInt(value, 10)).filter((value) => !Number.isNaN(value)); +} + +function getPlannedDateFromUrl() { + try { + const params = new URLSearchParams(window.location.search); + const value = params.get('date'); + return value || null; + } catch (error) { + console.error('Unable to read planned date from URL', error); + return null; + } +} + +function buildPayload(form, actionKey) { + const formData = new FormData(form); + console.log(Object.fromEntries(formData.entries())); + const payload = { + action: actionKey, + planned_date: getPlannedDateFromUrl(), + execution_date: formData.get('execution_date') || null, + note: formData.get('note') || null, + rows: parseRows(formData), + details: normalizeDetails(formData), + }; + + return payload; +} + +export function init(actionKey) { + const root = getPageRoot(); + if (!root) { + return; + } + + const storeUrl = root.dataset.storeUrl; + const form = root.querySelector('form[data-role="planned-task-form"]'); + + if (!form || !storeUrl) { + return; + } + + form.addEventListener('submit', async (event) => { + event.preventDefault(); + + const payload = buildPayload(form, actionKey); + console.log(payload); + + if (payload.rows.length === 0) { + showToast('Select at least one row for the planned task.', 'error'); + return; + } + + try { + const response = await axios.post(storeUrl, payload); + if (response.data?.success) { + showToast('Planned tasks created successfully.', 'success'); + const url = new URL(window.location.href); + url.pathname = '/vineyard/map'; + url.search = ''; + window.location.assign(url.toString()); + } else { + showToast('Some rows could not be processed. Please review the details.', 'error'); + } + } catch (error) { + console.error('Failed to create planned tasks', error); + + const data = error.response?.data; + if (data?.errors && typeof data.errors === 'object') { + const messages = Object.values(data.errors) + .flat() + .filter((value) => typeof value === 'string'); + + if (messages.length) { + showToast(messages[0], 'error'); + return; + } + } + + if (data?.message && typeof data.message === 'string') { + showToast(data.message, 'error'); + return; + } + + showToast('Unable to create planned tasks. Please check the form inputs.', 'error'); + } + }); +} diff --git a/3BIT/winter-semester/IIS/xnecasr00/resources/js/vineyard/add-plants.js b/3BIT/winter-semester/IIS/xnecasr00/resources/js/vineyard/add-plants.js new file mode 100644 index 0000000..ecda58b --- /dev/null +++ b/3BIT/winter-semester/IIS/xnecasr00/resources/js/vineyard/add-plants.js @@ -0,0 +1,166 @@ +import $ from 'jquery'; +import axios from 'axios'; + +function showToast(message, type = 'error') { + let container = document.querySelector('[data-role="toast-container"]'); + if (!container) { + container = document.createElement('div'); + container.dataset.role = 'toast-container'; + container.style.position = 'fixed'; + container.style.top = '1rem'; + container.style.right = '1rem'; + container.style.zIndex = '9999'; + container.style.display = 'flex'; + container.style.flexDirection = 'column'; + container.style.gap = '0.5rem'; + document.body.appendChild(container); + } + + const toast = document.createElement('div'); + toast.textContent = message; + toast.style.padding = '0.6rem 0.9rem'; + toast.style.borderRadius = '6px'; + toast.style.boxShadow = '0 4px 12px rgba(0,0,0,0.15)'; + toast.style.color = '#0f172a'; + toast.style.fontSize = '0.9rem'; + toast.style.backgroundColor = type === 'success' ? '#bbf7d0' : '#fee2e2'; + + container.appendChild(toast); + + setTimeout(() => { + toast.remove(); + if (!container.children.length) { + container.remove(); + } + }, 3000); +} + +function parseJson(id, fallback) { + const node = document.getElementById(id); + if (!node) { + return fallback; + } + + try { + return JSON.parse(node.textContent ?? 'null') ?? fallback; + } catch (error) { + console.error(`Unable to parse JSON from ${id}`, error); + return fallback; + } +} + + +function parseRows(formData) { + return formData.getAll('rows[]').map((value) => parseInt(value, 10)).filter((value) => !Number.isNaN(value)); +} + +function buildPayload(form) { + const formData = new FormData(form); + console.log(Object.fromEntries(formData.entries())); + const payload = { + rows: parseRows(formData), + variety_variation_id: formData.get('variety_variation_id') || null, + }; + + // If no variation selected, build creation object + if (!payload.variety_variation_id) { + payload.create_variation = { + grape_variety_id: formData.get('grape_variety_id') || null, + grape_variety_name: formData.get('grape_variety_name') || null, + color: formData.get('color'), + description: formData.get('description') || null, + typical_sugar_content: formData.get('typical_sugar_content') || null, + typical_alcohol: formData.get('typical_alcohol') || null, + ripening_period: formData.get('ripening_period') || null, + }; + } + + return payload; +} + +export default function initAddPlants() { + const $root = $('[data-page="vineyard-add-plants"]'); + if (!$root.length) { + return; + } + + const apiRoutes = parseJson('add-plants-api', {}); + const rows = parseJson('add-plants-rows', []); + + const $form = $root.find('#assign-plants-form'); + const $variationSelect = $form.find('[name="variety_variation_id"]'); + const $createSection = $root.find('[data-role="create-variation"]'); + + $root.find('[data-control="toggle-create"]').on('click', (event) => { + event.preventDefault(); + $createSection.toggleClass('hidden'); + }); + + $createSection.find('[data-control="submit-variation"]').on('click', async () => { + const payload = { + grape_variety_id: $createSection.find('[name="grape_variety_id"]').val() || null, + grape_variety_name: $createSection.find('[name="grape_variety_name"]').val() || null, + color: $createSection.find('[name="color"]').val(), + description: $createSection.find('[name="description"]').val() || null, + typical_sugar_content: $createSection.find('[name="typical_sugar_content"]').val() || null, + typical_alcohol: $createSection.find('[name="typical_alcohol"]').val() || null, + ripening_period: $createSection.find('[name="ripening_period"]').val() || null, + }; + + if (!payload.color) { + showToast('Choose a color for the new variation.', 'error'); + return; + } + + try { + const response = await axios.post(apiRoutes.createVariation, payload); + const variation = response.data?.variation; + if (!variation) { + return; + } + + const option = $('