src/gromacs/gmxana/dens_filter.cpp

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  36
  37 #include "gmxpre.h"
  38
  39 /* dens_filter.c
  40  * Routines for Filters and convolutions
  41  */
  42
  43 #include "dens_filter.h"
  44
  45 #include <cmath>
  46
  47 #include "gromacs/math/vec.h"
  48 #include "gromacs/utility/smalloc.h"
  49
  50 gmx_bool convolution(int dataSize, real* x, int kernelSize, const real* kernel)
  51 {
  52     int   i, j, k;
  53     real* out;
  54     snew(out, dataSize);
  55     /* check validity of params */
  56     if (!x || !kernel)
  57     {
  58         return FALSE;
  59     }
  60     if (dataSize <= 0 || kernelSize <= 0)
  61     {
  62         return FALSE;
  63     }
  64
  65     /* start convolution from out[kernelSize-1] to out[dataSize-1] (last) */
  66     for (i = kernelSize - 1; i < dataSize; ++i)
  67     {
  68         for (j = i, k = 0; k < kernelSize; --j, ++k)
  69         {
  70             out[i] += x[j] * kernel[k];
  71         }
  72     }
  73
  74     /* convolution from out[0] to out[kernelSize-2] */
  75     for (i = 0; i < kernelSize - 1; ++i)
  76     {
  77         for (j = i, k = 0; j >= 0; --j, ++k)
  78         {
  79             out[i] += x[j] * kernel[k];
  80         }
  81     }
  82
  83     for (i = 0; i < dataSize; i++)
  84     {
  85         x[i] = out[i];
  86     }
  87     sfree(out);
  88     return TRUE;
  89 }
  90
  91 /* Assuming kernel is shorter than x */
  92
  93 gmx_bool periodic_convolution(int datasize, real* x, int kernelsize, const real* kernel)
  94 {
  95     int   i, j, idx;
  96     real* filtered;
  97
  98     if (!x || !kernel)
  99     {
 100         return FALSE;
 101     }
 102     if (kernelsize <= 0 || datasize <= 0 || kernelsize > datasize)
 103     {
 104         return FALSE;
 105     }
 106
 107     snew(filtered, datasize);
 108
 109     for (i = 0; (i < datasize); i++)
 110     {
 111         for (j = 0; (j < kernelsize); j++)
 112         {
 113             // add datasize in case i-j is <0
 114             idx = i - j + datasize;
 115             filtered[i] += kernel[j] * x[idx % datasize];
 116         }
 117     }
 118     for (i = 0; i < datasize; i++)
 119     {
 120         x[i] = filtered[i];
 121     }
 122     sfree(filtered);
 123
 124     return TRUE;
 125 }
 126
 127
 128 /* returns discrete gaussian kernel of size n in *out, where n=2k+1=3,5,7,9,11 and k=1,2,3 is the
 129  * order NO checks are performed
 130  */
 131 void gausskernel(real* out, int n, real var)
 132 {
 133     int  i, j     = 0, k;
 134     real arg, tot = 0;
 135     k = n / 2;
 136
 137     for (i = -k; i <= k; i++)
 138     {
 139         arg             = (i * i) / (2 * var);
 140         tot += out[j++] = std::exp(-arg);
 141     }
 142     for (i = 0; i < j; i++)
 143     {
 144         out[i] /= tot;
 145     }
 146 }