#include <stdio.h>
#include <string.h>
#include "fisher.h"

/* Options for the program */
struct options {
  char *mode;
  size_t nsig;
  size_t nnoise;
};


int main(int argc, char **argv) {
  /* Set default options */
  struct options opts;
  opts.mode   = "fisher";
  opts.nsig   =  800;
  opts.nnoise = 1000;

  /* Process CLI arguments */
  for (size_t i = 1; i < argc; i++) {
         if (!strcmp(argv[i], "-m")) opts.mode = argv[++i];
    else if (!strcmp(argv[i], "-s")) opts.nsig = atol(argv[++i]);
    else if (!strcmp(argv[i], "-n")) opts.nnoise = atol(argv[++i]);
    else {
      fprintf(stderr, "Usage: %s -[hiIntp]\n", argv[0]);
      fprintf(stderr, "\t-h\tShow this message.\n");
      fprintf(stderr, "\t-m MODE\tThe disciminant to use: 'fisher' for "
                      "Fisher linear discriminant, 'percep' for perceptron.\n");
      fprintf(stderr, "\t-s N\tThe number of events in signal class.\n");
      fprintf(stderr, "\t-n N\tThe number of events in noise class.\n");
      return EXIT_FAILURE;
    }
  }

  // initialize RNG
  gsl_rng_env_setup();
  gsl_rng *r = gsl_rng_alloc(gsl_rng_default);

  /* Generate two classes of normally
   * distributed 2D points with different
   * paramters: signal and noise.
   */
  struct par par_sig   = { 0, 0, 0.3, 0.3, 0.5 };
  struct par par_noise = { 4, 4, 1.0, 1.0, 0.4 };

  sample_t *signal = generate_normal(r, opts.nsig, &par_sig);
  sample_t *noise  = generate_normal(r, opts.nnoise, &par_noise);

  if (!strcmp(opts.mode, "fisher")) {
    /* Fisher linear discriminant
     *
     * First calculate the direction w onto
     * which project the data points. Then the
     * cut which determines the class for each
     * projected point.
     */
    double ratio = opts.nsig / (double)opts.nnoise;
    gsl_vector *w = fisher_proj(signal, noise);
    double t_cut  = fisher_cut(ratio, w, signal, noise);

    fputs("# Linear Fisher discriminant\n\n", stderr);
    fprintf(stderr, "* w: [%.3f, %.3f]\n",
        gsl_vector_get(w, 0),
        gsl_vector_get(w, 1));
    fprintf(stderr, "* t_cut: %.3f\n", t_cut);

    gsl_vector_fprintf(stdout, w, "%g");
    printf("%f\n", t_cut);
  }

  /* Print data to stdout for plotting.
   * Note: we print the sizes to be able
   * to set apart the two matrices.
   */
  printf("%ld %ld %d\n", opts.nsig, opts.nnoise, 2);
  gsl_matrix_fprintf(stdout, signal->data, "%g");
  gsl_matrix_fprintf(stdout, noise->data,  "%g");

  // free memory
  gsl_rng_free(r);
  sample_t_free(signal);
  sample_t_free(noise);

  return EXIT_SUCCESS;
}