/* filter/test_gaussian.c

 * 

 * Copyright (C) 2018 Patrick Alken

 * 

 * This program is free software; you can redistribute it and/or modify

 * it under the terms of the GNU General Public License as published by

 * the Free Software Foundation; either version 3 of the License, or (at

 * your option) any later version.

 * 

 * This program is distributed in the hope that it will be useful, but

 * WITHOUT ANY WARRANTY; without even the implied warranty of

 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU

 * General Public License for more details.

 * 

 * You should have received a copy of the GNU General Public License

 * along with this program; if not, write to the Free Software

 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.

 */

#include <gsl/gsl_math.h>

#include <gsl/gsl_vector.h>

#include <gsl/gsl_filter.h>

#include <gsl/gsl_movstat.h>

#include <gsl/gsl_test.h>

#include <gsl/gsl_rng.h>

#include <gsl/gsl_randist.h>

/* compute Gaussian filter by explicitely constructing window and computing weighted sum */

int

slow_gaussian(const gsl_filter_end_t etype, const double alpha, const size_t order, const gsl_vector * x,

              gsl_vector * y, const size_t K)

{

  const size_t n = x->size;

  const size_t H = K / 2;

  double *window = malloc(K * sizeof(double));

  double *kernel = malloc(K * sizeof(double));

  gsl_vector_view k = gsl_vector_view_array(kernel, K);

  size_t i;

  gsl_filter_gaussian_kernel(alpha, order, 1, &k.vector);

  for (i = 0; i < n; ++i)

    {

      size_t wsize = gsl_movstat_fill(etype, x, i, H, H, window);

      double sum = 0.0;

      size_t j;

      for (j = 0; j < wsize; ++j)

        sum += window[j] * kernel[wsize - j - 1];

      gsl_vector_set(y, i, sum);

    }

  free(window);

  free(kernel);

  return GSL_SUCCESS;

}

static void

fdiff(const gsl_vector * x, gsl_vector * dx)

{

  const size_t N = x->size;

  size_t i;

  for (i = 1; i < N - 1; ++i)

    {

      double xm1 = gsl_vector_get(x, i - 1);

      double xp1 = gsl_vector_get(x, i + 1);

      gsl_vector_set(dx, i, 0.5 * (xp1 - xm1));

    }

  gsl_vector_set(dx, 0, gsl_vector_get(x, 1) - gsl_vector_get(x, 0));

  gsl_vector_set(dx, N - 1, gsl_vector_get(x, N - 1) - gsl_vector_get(x, N - 2));

}

static void

test_gaussian_kernel(const double alpha, const size_t K)

{

  const size_t max_order = 3;

  gsl_vector * kernel = gsl_vector_alloc(K);

  gsl_vector * deriv = gsl_vector_alloc(K);

  gsl_vector * deriv_fd = gsl_vector_alloc(K);

  char buf[2048];

  size_t order;

  gsl_filter_gaussian_kernel(alpha, 0, 0, kernel);

  for (order = 1; order <= max_order; ++order)

    {

      gsl_filter_gaussian_kernel(alpha, order, 0, deriv);

      fdiff(kernel, deriv_fd);

      sprintf(buf, "gaussian kernel order=%zu alpha=%g K=%zu", order, alpha, K);

      compare_vectors(1.0e-2, deriv_fd, deriv, buf);

      gsl_vector_memcpy(kernel, deriv);

    }

  gsl_vector_free(kernel);

  gsl_vector_free(deriv);

  gsl_vector_free(deriv_fd);

}

static void

test_gaussian_proc(const double tol, const double alpha, const size_t order, const size_t n, const size_t K,

                   const gsl_filter_end_t etype, gsl_rng * rng_p)

{

  gsl_filter_gaussian_workspace * w = gsl_filter_gaussian_alloc(K);

  gsl_vector * x = gsl_vector_alloc(n);

  gsl_vector * y = gsl_vector_alloc(n);

  gsl_vector * z = gsl_vector_alloc(n);

  char buf[2048];

  random_vector(x, rng_p);

  /* y = filter(x) with slow brute force method */

  slow_gaussian(etype, alpha, order, x, y, K);

  /* y = filter(x) with fast method */

  gsl_filter_gaussian(etype, alpha, order, x, z, w);

  /* test y = z */

  sprintf(buf, "n=%zu K=%zu endtype=%u alpha=%g order=%zu gaussian random", n, K, etype, alpha, order);

  compare_vectors(tol, z, y, buf);

  /* z = filter(x) in-place */

  gsl_vector_memcpy(z, x);

  gsl_filter_gaussian(etype, alpha, order, z, z, w);

  sprintf(buf, "n=%zu K=%zu endtype=%u alpha=%g order=%zu gaussian random in-place", n, K, etype, alpha, order);

  compare_vectors(tol, z, y, buf);

  gsl_filter_gaussian_free(w);

  gsl_vector_free(x);

  gsl_vector_free(y);

  gsl_vector_free(z);

}

static void

test_gaussian_deriv(const double alpha, const size_t n, const size_t K)

{

#if 0

  const double f_low = 1.0;

  const double f_high = 50.0;

  const double gamma = 2.0 * M_PI / (n - 1.0);

  const double dt = 1.0 / (n - 1.0);

  gsl_vector *x = gsl_vector_alloc(n);

  gsl_vector *dx = gsl_vector_alloc(n);

  gsl_vector *y1 = gsl_vector_alloc(n);

  gsl_vector *y2 = gsl_vector_alloc(n);

  gsl_filter_gaussian_workspace *w = gsl_filter_gaussian_alloc(K);

  size_t i;

  /* make input signal composed of two sine waves at different frequencies */

  for (i = 0; i < n; ++i)

    {

      double xi = sin(gamma * f_low * i) + sin(gamma * f_high * i);

      double dxi = gamma * f_low * cos(gamma * f_low * i) +

                   gamma * f_high * cos(gamma * f_high * i);

      gsl_vector_set(x, i, xi);

      gsl_vector_set(dx, i, dxi);

    }

  /* compute y1 = G * dx(t)/dt */

  gsl_filter_gaussian(alpha, 0, dx, y1, w);

  /* compute y2 = dG/dt * x(t) */

  gsl_filter_gaussian(alpha, 1, x, y2, w);

  for (i = 0; i < n; ++i)

    {

      printf("%zu %.12e %.12e %.12e %.12e\n",

             i,

             gsl_vector_get(x, i),

             gsl_vector_get(dx, i),

             gsl_vector_get(y1, i),

             gsl_vector_get(y2, i));

    }

  gsl_vector_free(x);

  gsl_vector_free(dx);

  gsl_vector_free(y1);

  gsl_vector_free(y2);

  gsl_filter_gaussian_free(w);

#endif

}

static void

test_gaussian(gsl_rng * r)

{

  const double tol = 1.0e-10;

  size_t order;

  test_gaussian_kernel(3.0, 2001);

  for (order = 0; order <= 3; ++order)

    {

      test_gaussian_proc(tol, 2.5, order, 1000, 21, GSL_FILTER_END_PADZERO, r);

      test_gaussian_proc(tol, 3.0, order, 500, 11, GSL_FILTER_END_PADZERO, r);

      test_gaussian_proc(tol, 1.0, order, 50, 101, GSL_FILTER_END_PADZERO, r);

      test_gaussian_proc(tol, 2.0, order, 50, 11, GSL_FILTER_END_PADZERO, r);

      test_gaussian_proc(tol, 2.5, order, 1000, 21, GSL_FILTER_END_PADVALUE, r);

      test_gaussian_proc(tol, 3.0, order, 500, 11, GSL_FILTER_END_PADVALUE, r);

      test_gaussian_proc(tol, 1.0, order, 50, 101, GSL_FILTER_END_PADVALUE, r);

      test_gaussian_proc(tol, 2.0, order, 50, 11, GSL_FILTER_END_PADVALUE, r);

      test_gaussian_proc(tol, 2.5, order, 1000, 21, GSL_FILTER_END_TRUNCATE, r);

      test_gaussian_proc(tol, 3.0, order, 500, 11, GSL_FILTER_END_TRUNCATE, r);

      test_gaussian_proc(tol, 1.0, order, 50, 101, GSL_FILTER_END_TRUNCATE, r);

      test_gaussian_proc(tol, 2.0, order, 50, 11, GSL_FILTER_END_TRUNCATE, r);

    }

}