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Diff for /JSOC/proj/sharp/apps/sw_functions.c between version 1.24 and 1.30

version 1.24, 2014/02/18 23:18:07 version 1.30, 2014/06/02 19:46:44
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Line 17 
     MEANPOT Mean photospheric excess magnetic energy density in ergs per cubic centimeter     MEANPOT Mean photospheric excess magnetic energy density in ergs per cubic centimeter
     TOTPOT Total photospheric magnetic energy density in ergs per cubic centimeter     TOTPOT Total photospheric magnetic energy density in ergs per cubic centimeter
     MEANSHR Mean shear angle (measured using Btotal) in degrees     MEANSHR Mean shear angle (measured using Btotal) in degrees
    R_VALUE Karel Schrijver's R parameter
  
    The indices are calculated on the pixels in which the conf_disambig segment is greater than 70 and    The indices are calculated on the pixels in which the conf_disambig segment is greater than 70 and
    pixels in which the bitmap segment is greater than 30. These ranges are selected because the CCD    pixels in which the bitmap segment is greater than 30. These ranges are selected because the CCD
Line 1035  int computeShearAngle(float *bx_err, flo
Line 1036  int computeShearAngle(float *bx_err, flo
 } }
  
 /*===========================================*/ /*===========================================*/
   /* Example function 15: R parameter as defined in Schrijver, 2007 */
   //
   // Note that there is a restriction on the function fsample()
   // If the following occurs:
   //      nx_out > floor((ny_in-1)/scale + 1)
   //      ny_out > floor((ny_in-1)/scale + 1),
   // where n*_out are the dimensions of the output array and n*_in
   // are the dimensions of the input array, fsample() will usually result
   // in a segfault (though not always, depending on how the segfault was accessed.)
   
 int computeR(float *bz_err, float *los, int *dims, float *Rparam, float cdelt1, int computeR(float *bz_err, float *los, int *dims, float *Rparam, float cdelt1,
              float *rim, float *p1p0, float *p1n0, float *p1p, float *p1n, float *p1,              float *rim, float *p1p0, float *p1n0, float *p1p, float *p1n, float *p1,
              float *pmap, int nx1, int ny1)               float *pmap, int nx1, int ny1,
 {               int scale, float *p1pad, int nxp, int nyp, float *pmapn)
  
   {
     int nx = dims[0];     int nx = dims[0];
     int ny = dims[1];     int ny = dims[1];
     int i = 0;     int i = 0;
     int j = 0;     int j = 0;
     int index;      int index, index1;
     double sum = 0.0;     double sum = 0.0;
     double err = 0.0;     double err = 0.0;
     *Rparam = 0.0;     *Rparam = 0.0;
     struct fresize_struct fresboxcar, fresgauss;     struct fresize_struct fresboxcar, fresgauss;
     int scale = round(2.0/cdelt1);      struct fint_struct fints;
     float sigma = 10.0/2.3548;     float sigma = 10.0/2.3548;
  
       // set up convolution kernels
     init_fresize_boxcar(&fresboxcar,1,1);     init_fresize_boxcar(&fresboxcar,1,1);
   
     // set up convolution kernel  
     init_fresize_gaussian(&fresgauss,sigma,20,1);     init_fresize_gaussian(&fresgauss,sigma,20,1);
  
     // make sure convolution kernel is smaller than or equal to array size      // =============== [STEP 1] ===============
     if ((nx || ny) < 41.) return -1;      // bin the line-of-sight magnetogram down by a factor of scale
   
     fsample(los, rim, nx, ny, nx, nx1, ny1, nx1, scale, 0, 0, 0.0);     fsample(los, rim, nx, ny, nx, nx1, ny1, nx1, scale, 0, 0, 0.0);
   
       // =============== [STEP 2] ===============
       // identify positive and negative pixels greater than +/- 150 gauss
       // and label those pixels with a 1.0 in arrays p1p0 and p1n0
     for (i = 0; i < nx1; i++)     for (i = 0; i < nx1; i++)
     {     {
       for (j = 0; j < ny1; j++)       for (j = 0; j < ny1; j++)
Line 1077  int computeR(float *bz_err, float *los,
Line 1091  int computeR(float *bz_err, float *los,
       }       }
     }     }
  
       // =============== [STEP 3] ===============
       // smooth each of the negative and positive pixel bitmaps
     fresize(&fresboxcar, p1p0, p1p, nx1, ny1, nx1, nx1, ny1, nx1, 0, 0, 0.0);     fresize(&fresboxcar, p1p0, p1p, nx1, ny1, nx1, nx1, ny1, nx1, 0, 0, 0.0);
     fresize(&fresboxcar, p1n0, p1n, nx1, ny1, nx1, nx1, ny1, nx1, 0, 0, 0.0);     fresize(&fresboxcar, p1n0, p1n, nx1, ny1, nx1, nx1, ny1, nx1, 0, 0, 0.0);
  
       // =============== [STEP 4] ===============
       // find the pixels for which p1p and p1n are both equal to 1.
       // this defines the polarity inversion line
     for (i = 0; i < nx1; i++)     for (i = 0; i < nx1; i++)
     {     {
       for (j = 0; j < ny1; j++)       for (j = 0; j < ny1; j++)
       {       {
         index = j * nx1 + i;         index = j * nx1 + i;
         if (p1p[index] > 0 && p1n[index] > 0)              if ((p1p[index] > 0.0) && (p1n[index] > 0.0))
           p1[index]=1.0;           p1[index]=1.0;
         else         else
           p1[index]=0.0;           p1[index]=0.0;
       }       }
     }     }
  
     fresize(&fresgauss, p1, pmap, nx1, ny1, nx1, nx1, ny1, nx1, 0, 0, 0.0);      // pad p1 with zeroes so that the gaussian colvolution in step 5
       // does not cut off data within hwidth of the edge
   
       // step i: zero p1pad
       for (i = 0; i < nxp; i++)
       {
           for (j = 0; j < nyp; j++)
           {
               index = j * nxp + i;
               p1pad[index]=0.0;
           }
       }
   
       // step ii: place p1 at the center of p1pad
       for (i = 0; i < nx1; i++)
       {
          for (j = 0; j < ny1; j++)
          {
               index  = j * nx1 + i;
               index1 = (j+20) * nxp + (i+20);
               p1pad[index1]=p1[index];
           }
       }
   
       // =============== [STEP 5] ===============
       // convolve the polarity inversion line map with a gaussian
       // to identify the region near the plarity inversion line
       // the resultant array is called pmap
       fresize(&fresgauss, p1pad, pmap, nxp, nyp, nxp, nxp, nyp, nxp, 0, 0, 0.0);
   
   
      // select out the nx1 x ny1 non-padded array  within pmap
       for (i = 0; i < nx1; i++)
       {
          for (j = 0; j < ny1; j++)
          {
               index  = j * nx1 + i;
               index1 = (j+20) * nxp + (i+20);
               pmapn[index]=pmap[index1];
           }
       }
  
       // =============== [STEP 6] ===============
       // the R parameter is calculated
     for (i = 0; i < nx1; i++)     for (i = 0; i < nx1; i++)
     {     {
       for (j = 0; j < ny1; j++)       for (j = 0; j < ny1; j++)
       {       {
         index = j * nx1 + i;         index = j * nx1 + i;
         sum += pmap[index]*abs(rim[index]);              sum += pmapn[index]*abs(rim[index]);
       }       }
     }     }
  
Line 1112  int computeR(float *bz_err, float *los,
Line 1173  int computeR(float *bz_err, float *los,
     free_fresize(&fresgauss);     free_fresize(&fresgauss);
  
     return 0;     return 0;
 }  
  
   }
  
 /*==================KEIJI'S CODE =========================*/ /*==================KEIJI'S CODE =========================*/
  
Line 1233  void greenpot(float *bx, float *by, floa
Line 1294  void greenpot(float *bx, float *by, floa
  
 char *sw_functions_version() // Returns CVS version of sw_functions.c char *sw_functions_version() // Returns CVS version of sw_functions.c
 { {
   return strdup("$Id$");      return strdup("$Id");
 } }
  
 /* ---------------- end of this file ----------------*/ /* ---------------- end of this file ----------------*/


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Karen Tian
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