Move out of subdir

1 files changed, 0 insertions, 490 deletions

diff --git a/src/filters.c b/src/filters.c
deleted file mode 100644
index 1af5d4a..0000000
--- a/src/filters.c
+++ /dev/null
@@ -1,490 +0,0 @@
-/*
-    FLAM3 - cosmic recursive fractal flames
-    Copyright (C) 1992-2009 Spotworks LLC
-
-    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, see <http://www.gnu.org/licenses/>.
-*/
-
-#include "filters.h"
-
-
-/*
- * filter function definitions
- * from Graphics Gems III code
- * and ImageMagick resize.c
- */
-
-
-double flam3_spatial_support[flam3_num_spatialfilters] = {
-
-   1.5, /* gaussian */
-   1.0, /* hermite */
-   0.5, /* box */
-   1.0, /* triangle */
-   1.5, /* bell */
-   2.0, /* b spline */
-   2.0, /* mitchell */
-   1.0, /* blackman */
-   2.0, /* catrom */
-   1.0, /* hanning */
-   1.0, /* hamming */
-   3.0, /* lanczos3 */
-   2.0, /* lanczos2 */
-   1.5  /* quadratic */
-};
-
-double flam3_hermite_filter(double t) {
-   /* f(t) = 2|t|^3 - 3|t|^2 + 1, -1 <= t <= 1 */
-   if(t < 0.0) t = -t;
-   if(t < 1.0) return((2.0 * t - 3.0) * t * t + 1.0);
-   return(0.0);
-}
-
-double flam3_box_filter(double t) {
-   if((t > -0.5) && (t <= 0.5)) return(1.0);
-   return(0.0);
-}
-
-double flam3_triangle_filter(double t) {
-   if(t < 0.0) t = -t;
-   if(t < 1.0) return(1.0 - t);
-   return(0.0);
-}
-
-double flam3_bell_filter(double t) {
-   /* box (*) box (*) box */
-   if(t < 0) t = -t;
-   if(t < .5) return(.75 - (t * t));
-   if(t < 1.5) {
-      t = (t - 1.5);
-      return(.5 * (t * t));
-   }
-   return(0.0);
-}
-
-double flam3_b_spline_filter(double t) {
-
-   /* box (*) box (*) box (*) box */
-   double tt;
-
-   if(t < 0) t = -t;
-   if(t < 1) {
-      tt = t * t;
-      return((.5 * tt * t) - tt + (2.0 / 3.0));
-   } else if(t < 2) {
-      t = 2 - t;
-      return((1.0 / 6.0) * (t * t * t));
-   }
-   return(0.0);
-}
-
-double flam3_sinc(double x) {
-   x *= M_PI;
-   if(x != 0) return(sin(x) / x);
-   return(1.0);
-}
-
-double flam3_blackman_filter(double x) {
-  return(0.42+0.5*cos(M_PI*x)+0.08*cos(2*M_PI*x));
-}
-
-double flam3_catrom_filter(double x) {
-  if (x < -2.0)
-    return(0.0);
-  if (x < -1.0)
-    return(0.5*(4.0+x*(8.0+x*(5.0+x))));
-  if (x < 0.0)
-    return(0.5*(2.0+x*x*(-5.0-3.0*x)));
-  if (x < 1.0)
-    return(0.5*(2.0+x*x*(-5.0+3.0*x)));
-  if (x < 2.0)
-    return(0.5*(4.0+x*(-8.0+x*(5.0-x))));
-  return(0.0);
-}
-
-double flam3_mitchell_filter(double t) {
-   double tt;
-
-   tt = t * t;
-   if(t < 0) t = -t;
-   if(t < 1.0) {
-      t = (((12.0 - 9.0 * flam3_mitchell_b - 6.0 * flam3_mitchell_c) * (t * tt))
-         + ((-18.0 + 12.0 * flam3_mitchell_b + 6.0 * flam3_mitchell_c) * tt)
-         + (6.0 - 2 * flam3_mitchell_b));
-      return(t / 6.0);
-   } else if(t < 2.0) {
-      t = (((-1.0 * flam3_mitchell_b - 6.0 * flam3_mitchell_c) * (t * tt))
-         + ((6.0 * flam3_mitchell_b + 30.0 * flam3_mitchell_c) * tt)
-         + ((-12.0 * flam3_mitchell_b - 48.0 * flam3_mitchell_c) * t)
-         + (8.0 * flam3_mitchell_b + 24 * flam3_mitchell_c));
-      return(t / 6.0);
-   }
-   return(0.0);
-}
-
-double flam3_hanning_filter(double x) {
-  return(0.5+0.5*cos(M_PI*x));
-}
-
-double flam3_hamming_filter(double x) {
-  return(0.54+0.46*cos(M_PI*x));
-}
-
-double flam3_lanczos3_filter(double t) {
-   if(t < 0) t = -t;
-   if(t < 3.0) return(flam3_sinc(t) * flam3_sinc(t/3.0));
-   return(0.0);
-}
-
-double flam3_lanczos2_filter(double t) {
-   if(t < 0) t = -t;
-   if(t < 2.0) return(flam3_sinc(t) * flam3_sinc(t/2.0));
-   return(0.0);
-}
-
-double flam3_gaussian_filter(double x) {
-  return(exp((-2.0*x*x))*sqrt(2.0/M_PI));
-}
-
-double flam3_quadratic_filter(double x) {
-  if (x < -1.5)
-    return(0.0);
-  if (x < -0.5)
-    return(0.5*(x+1.5)*(x+1.5));
-  if (x < 0.5)
-    return(0.75-x*x);
-  if (x < 1.5)
-    return(0.5*(x-1.5)*(x-1.5));
-  return(0.0);
-}
-
-double flam3_spatial_filter(int knum, double x) {
-
-   if (knum==0)
-      return flam3_gaussian_filter(x);
-   else if (knum==1)
-      return flam3_hermite_filter(x);
-   else if (knum==2)
-      return flam3_box_filter(x);
-   else if (knum==3)
-      return flam3_triangle_filter(x);
-   else if (knum==4)
-      return flam3_bell_filter(x);
-   else if (knum==5)
-      return flam3_b_spline_filter(x);
-   else if (knum==6)
-      return flam3_mitchell_filter(x);
-   else if (knum==7)
-      return flam3_sinc(x)*flam3_blackman_filter(x);
-   else if (knum==8)
-      return flam3_catrom_filter(x);
-   else if (knum==9)
-      return flam3_sinc(x)*flam3_hanning_filter(x);
-   else if (knum==10)
-      return flam3_sinc(x)*flam3_hamming_filter(x);
-   else if (knum==11)
-      return flam3_lanczos3_filter(x)*flam3_sinc(x/3.0);   
-   else if (knum==12)
-      return flam3_lanczos2_filter(x)*flam3_sinc(x/2.0);
-   else if (knum==13)
-      return flam3_quadratic_filter(x);
-}
-
-int normalize_vector(double *v, int n) {
-   double t = 0.0;
-   int i;
-   for (i = 0; i < n; i++)
-      t += v[i];
-   if (0.0 == t) return 1;
-   t = 1.0 / t;
-   for (i = 0; i < n; i++)
-      v[i] *= t;
-   return 0;
-}
-
-
-int flam3_create_spatial_filter(flam3_frame *spec, int field, double **filter) {
-
-   int sf_kernel = spec->genomes[0].spatial_filter_select;
-   int supersample = spec->genomes[0].spatial_oversample;
-   double sf_radius = spec->genomes[0].spatial_filter_radius;
-   double aspect_ratio = spec->pixel_aspect_ratio;   
-   double sf_supp = flam3_spatial_support[sf_kernel];
-   
-   double fw = 2.0 * sf_supp * supersample * sf_radius / aspect_ratio;
-   double adjust, ii, jj;
-   
-   int fwidth = ((int) fw) + 1;
-   int i,j;
-   
-   
-   /* Make sure the filter kernel has same parity as oversample */
-   if ((fwidth ^ supersample) & 1)
-      fwidth++;
-
-   /* Calculate the coordinate scaling factor for the kernel values */
-   if (fw > 0.0)
-      adjust = sf_supp * fwidth / fw;
-   else
-      adjust = 1.0;
-
-   /* Calling function MUST FREE THE RETURNED KERNEL, lest ye leak memory */
-   (*filter) = (double *)calloc(fwidth * fwidth,sizeof(double));
-
-   /* fill in the coefs */
-   for (i = 0; i < fwidth; i++)
-      for (j = 0; j < fwidth; j++) {
-      
-         /* Calculate the function inputs for the kernel function */
-         ii = ((2.0 * i + 1.0) / (double)fwidth - 1.0)*adjust;
-         jj = ((2.0 * j + 1.0) / (double)fwidth - 1.0)*adjust;
-
-         /* Scale for scanlines */
-         if (field) jj *= 2.0;
-
-         /* Adjust for aspect ratio */
-         jj /= aspect_ratio;
-
-         (*filter)[i + j * fwidth] = 
-               flam3_spatial_filter(sf_kernel,ii) * flam3_spatial_filter(sf_kernel,jj);
-      }
-
-
-   if (normalize_vector((*filter), fwidth * fwidth)) {
-      fprintf(stderr, "Spatial filter value is too small: %g.  Terminating.\n",sf_radius);
-      return(-1);
-   }   
-   
-   return (fwidth);
-}
-
-flam3_de_helper flam3_create_de_filters(double max_rad, double min_rad, double curve, int ss) {
-
-   flam3_de_helper de;
-   double comp_max_radius, comp_min_radius;
-   double num_de_filters_d;
-   int num_de_filters,de_max_ind;
-   int de_row_size, de_half_size;
-   int filtloop;
-   int keep_thresh=100;
-
-   de.kernel_size=-1;
-
-   if (curve <= 0.0) {
-      fprintf(stderr,"estimator curve must be > 0\n");
-      return(de);
-   }
-
-   if (max_rad < min_rad) {
-      fprintf(stderr,"estimator must be larger than estimator_minimum.\n");
-      fprintf(stderr,"(%f > %f) ? \n",max_rad,min_rad);
-      return(de);
-   }
-
-   /* We should scale the filter width by the oversample          */
-   /* The '+1' comes from the assumed distance to the first pixel */
-   comp_max_radius = max_rad*ss + 1;
-   comp_min_radius = min_rad*ss + 1;
-
-   /* Calculate how many filter kernels we need based on the decay function */
-   /*                                                                       */
-   /*    num filters = (de_max_width / de_min_width)^(1/estimator_curve)    */
-   /*                                                                       */
-   num_de_filters_d = pow( comp_max_radius/comp_min_radius, 1.0/curve );
-   if (num_de_filters_d>1e7) {
-      fprintf(stderr,"too many filters required in this configuration (%g)\n",num_de_filters_d);
-      return(de);
-   }
-   num_de_filters = (int)ceil(num_de_filters_d);
-         
-   /* Condense the smaller kernels to save space */
-   if (num_de_filters>keep_thresh) { 
-      de_max_ind = (int)ceil(DE_THRESH + pow(num_de_filters-DE_THRESH,curve))+1;
-      de.max_filtered_counts = (int)pow( (double)(de_max_ind-DE_THRESH), 1.0/curve) + DE_THRESH;
-   } else {
-      de_max_ind = num_de_filters;
-      de.max_filtered_counts = de_max_ind;
-   }
-
-   /* Allocate the memory for these filters */
-   /* and the hit/width lookup vector       */
-   de_row_size = (int)(2*ceil(comp_max_radius)-1);
-   de_half_size = (de_row_size-1)/2;
-   de.kernel_size = (de_half_size+1)*(2+de_half_size)/2;
-
-   de.filter_coefs = (double *) calloc (de_max_ind * de.kernel_size,sizeof(double));
-   de.filter_widths = (double *) calloc (de_max_ind,sizeof(double));
-
-   /* Generate the filter coefficients */
-   de.max_filter_index = 0;
-   for (filtloop=0;filtloop<de_max_ind;filtloop++) {
-
-      double de_filt_sum=0.0, de_filt_d;
-      double de_filt_h;
-      int dej,dek;
-      double adjloop;
-      int filter_coef_idx;
-
-      /* Calculate the filter width for this number of hits in a bin */
-      if (filtloop<keep_thresh)
-         de_filt_h = (comp_max_radius / pow(filtloop+1,curve));
-      else {
-         adjloop = pow(filtloop-keep_thresh,(1.0/curve)) + keep_thresh;
-         de_filt_h = (comp_max_radius / pow(adjloop+1,curve));
-      }
-
-      /* Once we've reached the min radius, don't populate any more */
-      if (de_filt_h <= comp_min_radius) {
-         de_filt_h = comp_min_radius;
-         de.max_filter_index = filtloop;
-      }
-
-      de.filter_widths[filtloop] = de_filt_h;
-
-      /* Calculate norm of kernel separately (easier) */
-      for (dej=-de_half_size; dej<=de_half_size; dej++) {
-         for (dek=-de_half_size; dek<=de_half_size; dek++) {
-            
-            de_filt_d = sqrt( (double)(dej*dej+dek*dek) ) / de_filt_h;
-
-            /* Only populate the coefs within this radius */
-            if (de_filt_d <= 1.0) {
-
-               /* Gaussian */
-               de_filt_sum += flam3_spatial_filter(flam3_gaussian_kernel,
-                        flam3_spatial_support[flam3_gaussian_kernel]*de_filt_d);
-
-               /* Epanichnikov */
-//             de_filt_sum += (1.0 - (de_filt_d * de_filt_d));
-            }
-         }
-      }
-
-      filter_coef_idx = filtloop*de.kernel_size;
-
-      /* Calculate the unique entries of the kernel */
-      for (dej=0; dej<=de_half_size; dej++) {
-         for (dek=0; dek<=dej; dek++) {
-            de_filt_d = sqrt( (double)(dej*dej+dek*dek) ) / de_filt_h;
-
-            /* Only populate the coefs within this radius */
-            if (de_filt_d>1.0)
-               de.filter_coefs[filter_coef_idx] = 0.0;
-            else {
-
-               /* Gaussian */
-               de.filter_coefs[filter_coef_idx] = flam3_spatial_filter(flam3_gaussian_kernel,
-                        flam3_spatial_support[flam3_gaussian_kernel]*de_filt_d)/de_filt_sum; 
-                            
-               /* Epanichnikov */
-//             de_filter_coefs[filter_coef_idx] = (1.0 - (de_filt_d * de_filt_d))/de_filt_sum;
-            }
-                  
-            filter_coef_idx ++;
-         }
-      }
-
-      if (de.max_filter_index>0)
-         break;
-   }
-
-   if (de.max_filter_index==0)
-      de.max_filter_index = de_max_ind-1;
-
-   
-   return(de);
-}                       
-
-double flam3_create_temporal_filter(int numsteps, int filter_type, double filter_exp, double filter_width,
-                                    double **temporal_filter, double **temporal_deltas) {
-
-   double maxfilt = 0.0;
-   double sumfilt = 0.0;
-   double slpx,halfsteps;
-   double *deltas, *filter;
-   
-   int i;
-
-   /* Allocate memory - this must be freed in the calling routine! */   
-   deltas = (double *)malloc(numsteps*sizeof(double));
-   filter = (double *)malloc(numsteps*sizeof(double));
-   
-   /* Deal with only one step */
-   if (numsteps==1) {
-      deltas[0] = 0;
-      filter[0] = 1.0;
-      *temporal_deltas = deltas;
-      *temporal_filter = filter;
-      return(1.0);
-   }
-      
-   /* Define the temporal deltas */   
-   for (i = 0; i < numsteps; i++)
-      deltas[i] = ((double)i /(double)(numsteps - 1) - 0.5)*filter_width;
-      
-   /* Define the filter coefs */
-   if (flam3_temporal_exp == filter_type) {
-
-      for (i=0; i < numsteps; i++) {
-
-         if (filter_exp>=0)
-            slpx = ((double)i+1.0)/numsteps;
-         else
-            slpx = (double)(numsteps - i)/numsteps;
-
-         /* Scale the color based on these values */
-         filter[i] = pow(slpx,fabs(filter_exp));
-         
-         /* Keep the max */
-         if (filter[i]>maxfilt)
-            maxfilt = filter[i];
-      }
-
-   } else if (flam3_temporal_gaussian == filter_type) {
-
-      halfsteps = numsteps/2.0;
-      for (i=0; i < numsteps; i++) {
-      
-         /* Gaussian */
-         filter[i] = flam3_spatial_filter(flam3_gaussian_kernel,
-                           flam3_spatial_support[flam3_gaussian_kernel]*fabs(i - halfsteps)/halfsteps);
-         /* Keep the max */
-         if (filter[i]>maxfilt)
-            maxfilt = filter[i];
-      }
-      
-   } else { // (flam3_temporal_box)
-
-      for (i=0; i < numsteps; i++)
-         filter[i] = 1.0;
-         
-	   maxfilt = 1.0;
-	   
-   }
-
-   /* Adjust the filter so that the max is 1.0, and */
-   /* calculate the K2 scaling factor  */
-   for (i=0;i<numsteps;i++) {
-      filter[i] /= maxfilt;
-      sumfilt += filter[i];
-   }
-         
-   sumfilt /= numsteps;
-   
-   *temporal_deltas = deltas;
-   *temporal_filter = filter;
-   
-   return(sumfilt);
-}                                     
-