diff options
Diffstat (limited to 'src/trainMSVMMajdataset.c')
| -rw-r--r-- | src/trainMSVMMajdataset.c | 186 |
1 files changed, 186 insertions, 0 deletions
diff --git a/src/trainMSVMMajdataset.c b/src/trainMSVMMajdataset.c new file mode 100644 index 0000000..7c3385c --- /dev/null +++ b/src/trainMSVMMajdataset.c @@ -0,0 +1,186 @@ +#include <time.h> + +#include "crossval.h" +#include "MSVMMaj.h" +#include "msvmmaj_pred.h" +#include "msvmmaj_train.h" +#include "msvmmaj_train_dataset.h" +#include "strutil.h" +#include "util.h" + +#define MINARGS 2 + +extern FILE *MSVMMAJ_OUTPUT_FILE; + +void print_null(const char *s) {} +void exit_with_help(); +void parse_command_line(int argc, char **argv, char *input_filename); +void read_training_from_file(char *input_filename, struct Training *training); + +void exit_with_help() +{ + printf("This is MSVMMaj, version %1.1f\n\n", VERSION); + printf("Usage: trainMSVMMajdataset [options] training_file\n"); + printf("Options:\n"); + printf("-h | -help : print this help.\n"); + printf("-q : quiet mode (no output)\n"); + + exit(0); +} + +int main(int argc, char **argv) +{ + char input_filename[MAX_LINE_LENGTH]; + + struct Training *training = Malloc(struct Training, 1); + struct MajData *train_data = Malloc(struct MajData, 1); + struct MajData *test_data = Malloc(struct MajData, 1); + + if (argc < MINARGS || msvmmaj_check_argv(argc, argv, "-help") + || msvmmaj_check_argv_eq(argc, argv, "-h") ) + exit_with_help(); + parse_command_line(argc, argv, input_filename); + + training->repeats = 0; + note("Reading training file\n"); + read_training_from_file(input_filename, training); + + note("Reading data from %s\n", training->train_data_file); + msvmmaj_read_data(train_data, training->train_data_file); + if (training->traintype == TT) { + note("Reading data from %s\n", training->test_data_file); + msvmmaj_read_data(test_data, training->test_data_file); + } + + note("Creating queue\n"); + struct Queue *q = Malloc(struct Queue, 1); + make_queue(training, q, train_data, test_data); + + srand(time(NULL)); + + note("Starting training\n"); + if (training->traintype == TT) + start_training_tt(q); + else + start_training_cv(q); + note("Training finished\n"); + + if (training->repeats > 0) { + consistency_repeats(q, training->repeats, training->traintype); + } + + free_queue(q); + free(training); + msvmmaj_free_data(train_data); + msvmmaj_free_data(test_data); + + note("Done.\n"); + return 0; +} + +void parse_command_line(int argc, char **argv, char *input_filename) +{ + int i; + + MSVMMAJ_OUTPUT_FILE = stdout; + + for (i=1; i<argc; i++) { + if (argv[i][0] != '-') break; + if (++i>=argc) + exit_with_help(); + switch (argv[i-1][1]) { + case 'q': + MSVMMAJ_OUTPUT_FILE = NULL; + i--; + break; + default: + fprintf(stderr, "Unknown option: -%c\n", argv[i-1][1]); + exit_with_help(); + } + } + + if (i >= argc) + exit_with_help(); + + strcpy(input_filename, argv[i]); +} + +void read_training_from_file(char *input_filename, struct Training *training) +{ + long i, nr = 0; + FILE *fid; + char buffer[MAX_LINE_LENGTH]; + char train_filename[MAX_LINE_LENGTH]; + char test_filename[MAX_LINE_LENGTH]; + double *params = Calloc(double, MAX_LINE_LENGTH); + long *lparams = Calloc(long, MAX_LINE_LENGTH); + + fid = fopen(input_filename, "r"); + if (fid == NULL) { + fprintf(stderr, "Error opening training file %s\n", input_filename); + exit(1); + } + training->traintype = CV; + while ( fgets(buffer, MAX_LINE_LENGTH, fid) != NULL ) { + Memset(params, double, MAX_LINE_LENGTH); + Memset(lparams, long, MAX_LINE_LENGTH); + if (str_startswith(buffer, "train:")) { + sscanf(buffer, "train: %s\n", train_filename); + training->train_data_file = Calloc(char, MAX_LINE_LENGTH); + strcpy(training->train_data_file, train_filename); + } else if (str_startswith(buffer, "test:")) { + sscanf(buffer, "test: %s\n", test_filename); + training->test_data_file = Calloc(char, MAX_LINE_LENGTH); + strcpy(training->test_data_file, test_filename); + training->traintype = TT; + } else if (str_startswith(buffer, "p:")) { + nr = all_doubles_str(buffer, 2, params); + training->ps = Calloc(double, nr); + for (i=0; i<nr; i++) + training->ps[i] = params[i]; + training->Np = nr; + } else if (str_startswith(buffer, "lambda:")) { + nr = all_doubles_str(buffer, 7, params); + training->lambdas = Calloc(double, nr); + for (i=0; i<nr; i++) + training->lambdas[i] = params[i]; + training->Nl = nr; + } else if (str_startswith(buffer, "kappa:")) { + nr = all_doubles_str(buffer, 6, params); + training->kappas = Calloc(double, nr); + for (i=0; i<nr; i++) + training->kappas[i] = params[i]; + training->Nk = nr; + } else if (str_startswith(buffer, "epsilon:")) { + nr = all_doubles_str(buffer, 8, params); + training->epsilons = Calloc(double, nr); + for (i=0; i<nr; i++) + training->epsilons[i] = params[i]; + training->Ne = nr; + } else if (str_startswith(buffer, "weight:")) { + nr = all_longs_str(buffer, 7, lparams); + training->weight_idxs = Calloc(int, nr); + for (i=0; i<nr; i++) + training->weight_idxs[i] = lparams[i]; + training->Nw = nr; + } else if (str_startswith(buffer, "folds:")) { + nr = all_longs_str(buffer, 6, lparams); + training->folds = lparams[0]; + if (nr > 1) + fprintf(stderr, "Field \"folds\" only takes one value. " + "Additional fields are ignored.\n"); + } else if (str_startswith(buffer, "repeats:")) { + nr = all_longs_str(buffer, 8, lparams); + training->repeats = lparams[0]; + if (nr > 1) + fprintf(stderr, "Field \"repeats\" only takes one value. " + "Additional fields are ignored.\n"); + } else { + fprintf(stderr, "Cannot find any parameters on line: %s\n", buffer); + } + } + + free(params); + free(lparams); + fclose(fid); +} |