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version 1.29, 2014/05/16 21:55:54 version 1.42, 2021/05/26 04:44:14
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 /*=========================================== /*===========================================
  
  The following 14 functions calculate the following spaceweather indices:   The following functions calculate these spaceweather indices from the vector magnetic field data:
  
  USFLUX Total unsigned flux in Maxwells  USFLUX Total unsigned flux in Maxwells
  MEANGAM Mean inclination angle, gamma, in degrees  MEANGAM Mean inclination angle, gamma, in degrees
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Line 18 
  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
    CMASK The total number of pixels that contributed to the calculation of all the indices listed above
   
    And these spaceweather indices from the line-of-sight magnetic field data:
    USFLUXL Total unsigned flux in Maxwells
    MEANGBL Mean value of the line-of-sight field gradient, in Gauss/Mm
    CMASKL The total number of pixels that contributed to the calculation of USFLUXL and MEANGBL
  R_VALUE Karel Schrijver's R parameter  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
Line 246  int computeB_total(float *bx_err, float
Line 253  int computeB_total(float *bx_err, float
 /*===========================================*/ /*===========================================*/
 /* Example function 5:  Derivative of B_Total SQRT( (dBt/dx)^2 + (dBt/dy)^2 ) */ /* Example function 5:  Derivative of B_Total SQRT( (dBt/dx)^2 + (dBt/dy)^2 ) */
  
 int computeBtotalderivative(float *bt, int *dims, float *mean_derivative_btotal_ptr, int *mask, int *bitmask, float *derx_bt, float *dery_bt, float *bt_err, float *mean_derivative_btotal_err_ptr)  int computeBtotalderivative(float *bt, int *dims, float *mean_derivative_btotal_ptr, int *mask, int *bitmask, float *derx_bt, float *dery_bt, float *bt_err, float *mean_derivative_btotal_err_ptr, float *err_termAt, float *err_termBt)
 { {
  
     int nx = dims[0];     int nx = dims[0];
Line 266  int computeBtotalderivative(float *bt, i
Line 273  int computeBtotalderivative(float *bt, i
             for (j = 0; j <= ny-1; j++)             for (j = 0; j <= ny-1; j++)
         {         {
             derx_bt[j * nx + i] = (bt[j * nx + i+1] - bt[j * nx + i-1])*0.5;             derx_bt[j * nx + i] = (bt[j * nx + i+1] - bt[j * nx + i-1])*0.5;
              err_termAt[j * nx + i] = (((bt[j * nx + (i+1)]-bt[j * nx + (i-1)])*(bt[j * nx + (i+1)]-bt[j * nx + (i-1)])) * (bt_err[j * nx + (i+1)]*bt_err[j * nx + (i+1)] + bt_err[j * nx + (i-1)]*bt_err[j * nx + (i-1)])) ;
         }         }
     }     }
  
Line 275  int computeBtotalderivative(float *bt, i
Line 283  int computeBtotalderivative(float *bt, i
             for (j = 1; j <= ny-2; j++)             for (j = 1; j <= ny-2; j++)
         {         {
             dery_bt[j * nx + i] = (bt[(j+1) * nx + i] - bt[(j-1) * nx + i])*0.5;             dery_bt[j * nx + i] = (bt[(j+1) * nx + i] - bt[(j-1) * nx + i])*0.5;
              err_termBt[j * nx + i] = (((bt[(j+1) * nx + i]-bt[(j-1) * nx + i])*(bt[(j+1) * nx + i]-bt[(j-1) * nx + i])) * (bt_err[(j+1) * nx + i]*bt_err[(j+1) * nx + i] + bt_err[(j-1) * nx + i]*bt_err[(j-1) * nx + i])) ;
         }         }
     }     }
  
       /* consider the edges for the arrays that contribute to the variable "sum" in the computation below.
     /* consider the edges */      ignore the edges for the error terms as those arrays have been initialized to zero.
       this is okay because the error term will ultimately not include the edge pixels as they are selected out by the mask and bitmask arrays.*/
     i=0;     i=0;
     for (j = 0; j <= ny-1; j++)     for (j = 0; j <= ny-1; j++)
     {     {
Line 304  int computeBtotalderivative(float *bt, i
Line 314  int computeBtotalderivative(float *bt, i
         dery_bt[j * nx + i] = ( (3*bt[j * nx + i]) + (-4*bt[(j-1) * nx + i]) - (-bt[(j-2) * nx + i]) )*0.5;         dery_bt[j * nx + i] = ( (3*bt[j * nx + i]) + (-4*bt[(j-1) * nx + i]) - (-bt[(j-2) * nx + i]) )*0.5;
     }     }
  
       // Calculate the sum only
     for (i = 1; i <= nx-2; i++)     for (i = 1; i <= nx-2; i++)
     {     {
         for (j = 1; j <= ny-2; j++)         for (j = 1; j <= ny-2; j++)
Line 320  int computeBtotalderivative(float *bt, i
Line 330  int computeBtotalderivative(float *bt, i
             if isnan(derx_bt[j * nx + i]) continue;             if isnan(derx_bt[j * nx + i]) continue;
             if isnan(dery_bt[j * nx + i]) continue;             if isnan(dery_bt[j * nx + i]) continue;
             sum += sqrt( derx_bt[j * nx + i]*derx_bt[j * nx + i]  + dery_bt[j * nx + i]*dery_bt[j * nx + i]  ); /* Units of Gauss */             sum += sqrt( derx_bt[j * nx + i]*derx_bt[j * nx + i]  + dery_bt[j * nx + i]*dery_bt[j * nx + i]  ); /* Units of Gauss */
             err += (((bt[(j+1) * nx + i]-bt[(j-1) * nx + i])*(bt[(j+1) * nx + i]-bt[(j-1) * nx + i])) * (bt_err[(j+1) * nx + i]*bt_err[(j+1) * nx + i] + bt_err[(j-1) * nx + i]*bt_err[(j-1) * nx + i])) / (16.0*( derx_bt[j * nx + i]*derx_bt[j * nx + i]  + dery_bt[j * nx + i]*dery_bt[j * nx + i]  ))+              err += err_termBt[j * nx + i] / (16.0*( derx_bt[j * nx + i]*derx_bt[j * nx + i]  + dery_bt[j * nx + i]*dery_bt[j * nx + i]  ))+
             (((bt[j * nx + (i+1)]-bt[j * nx + (i-1)])*(bt[j * nx + (i+1)]-bt[j * nx + (i-1)])) * (bt_err[j * nx + (i+1)]*bt_err[j * nx + (i+1)] + bt_err[j * nx + (i-1)]*bt_err[j * nx + (i-1)])) / (16.0*( derx_bt[j * nx + i]*derx_bt[j * nx + i]  + dery_bt[j * nx + i]*dery_bt[j * nx + i]  )) ;                     err_termAt[j * nx + i] / (16.0*( derx_bt[j * nx + i]*derx_bt[j * nx + i]  + dery_bt[j * nx + i]*dery_bt[j * nx + i]  )) ;
             count_mask++;             count_mask++;
         }         }
     }     }
Line 338  int computeBtotalderivative(float *bt, i
Line 348  int computeBtotalderivative(float *bt, i
 /*===========================================*/ /*===========================================*/
 /* Example function 6:  Derivative of Bh SQRT( (dBh/dx)^2 + (dBh/dy)^2 ) */ /* Example function 6:  Derivative of Bh SQRT( (dBh/dx)^2 + (dBh/dy)^2 ) */
  
 int computeBhderivative(float *bh, float *bh_err, int *dims, float *mean_derivative_bh_ptr, float *mean_derivative_bh_err_ptr, int *mask, int *bitmask, float *derx_bh, float *dery_bh)  int computeBhderivative(float *bh, float *bh_err, int *dims, float *mean_derivative_bh_ptr, float *mean_derivative_bh_err_ptr, int *mask, int *bitmask, float *derx_bh, float *dery_bh, float *err_termAh, float *err_termBh)
 { {
  
     int nx = dims[0];     int nx = dims[0];
Line 358  int computeBhderivative(float *bh, float
Line 368  int computeBhderivative(float *bh, float
             for (j = 0; j <= ny-1; j++)             for (j = 0; j <= ny-1; j++)
         {         {
             derx_bh[j * nx + i] = (bh[j * nx + i+1] - bh[j * nx + i-1])*0.5;             derx_bh[j * nx + i] = (bh[j * nx + i+1] - bh[j * nx + i-1])*0.5;
              err_termAh[j * nx + i] = (((bh[j * nx + (i+1)]-bh[j * nx + (i-1)])*(bh[j * nx + (i+1)]-bh[j * nx + (i-1)])) * (bh_err[j * nx + (i+1)]*bh_err[j * nx + (i+1)] + bh_err[j * nx + (i-1)]*bh_err[j * nx + (i-1)]));
         }         }
     }     }
  
Line 367  int computeBhderivative(float *bh, float
Line 378  int computeBhderivative(float *bh, float
             for (j = 1; j <= ny-2; j++)             for (j = 1; j <= ny-2; j++)
         {         {
             dery_bh[j * nx + i] = (bh[(j+1) * nx + i] - bh[(j-1) * nx + i])*0.5;             dery_bh[j * nx + i] = (bh[(j+1) * nx + i] - bh[(j-1) * nx + i])*0.5;
             err_termBh[j * nx + i] = (((bh[ (j+1) * nx + i]-bh[(j-1) * nx + i])*(bh[(j+1) * nx + i]-bh[(j-1) * nx + i])) * (bh_err[(j+1) * nx + i]*bh_err[(j+1) * nx + i] + bh_err[(j-1) * nx + i]*bh_err[(j-1) * nx + i]));
         }         }
     }     }
  
       /* consider the edges for the arrays that contribute to the variable "sum" in the computation below.
     /* consider the edges */      ignore the edges for the error terms as those arrays have been initialized to zero.
       this is okay because the error term will ultimately not include the edge pixels as they are selected out by the mask and bitmask arrays.*/
     i=0;     i=0;
     for (j = 0; j <= ny-1; j++)     for (j = 0; j <= ny-1; j++)
     {     {
Line 412  int computeBhderivative(float *bh, float
Line 425  int computeBhderivative(float *bh, float
             if isnan(derx_bh[j * nx + i]) continue;             if isnan(derx_bh[j * nx + i]) continue;
             if isnan(dery_bh[j * nx + i]) continue;             if isnan(dery_bh[j * nx + i]) continue;
             sum += sqrt( derx_bh[j * nx + i]*derx_bh[j * nx + i]  + dery_bh[j * nx + i]*dery_bh[j * nx + i]  ); /* Units of Gauss */             sum += sqrt( derx_bh[j * nx + i]*derx_bh[j * nx + i]  + dery_bh[j * nx + i]*dery_bh[j * nx + i]  ); /* Units of Gauss */
             err += (((bh[(j+1) * nx + i]-bh[(j-1) * nx + i])*(bh[(j+1) * nx + i]-bh[(j-1) * nx + i])) * (bh_err[(j+1) * nx + i]*bh_err[(j+1) * nx + i] + bh_err[(j-1) * nx + i]*bh_err[(j-1) * nx + i])) / (16.0*( derx_bh[j * nx + i]*derx_bh[j * nx + i]  + dery_bh[j * nx + i]*dery_bh[j * nx + i]  ))+              err += err_termBh[j * nx + i] / (16.0*( derx_bh[j * nx + i]*derx_bh[j * nx + i]  + dery_bh[j * nx + i]*dery_bh[j * nx + i]  ))+
             (((bh[j * nx + (i+1)]-bh[j * nx + (i-1)])*(bh[j * nx + (i+1)]-bh[j * nx + (i-1)])) * (bh_err[j * nx + (i+1)]*bh_err[j * nx + (i+1)] + bh_err[j * nx + (i-1)]*bh_err[j * nx + (i-1)])) / (16.0*( derx_bh[j * nx + i]*derx_bh[j * nx + i]  + dery_bh[j * nx + i]*dery_bh[j * nx + i]  )) ;                     err_termAh[j * nx + i] / (16.0*( derx_bh[j * nx + i]*derx_bh[j * nx + i]  + dery_bh[j * nx + i]*dery_bh[j * nx + i]  )) ;
             count_mask++;             count_mask++;
         }         }
     }     }
Line 429  int computeBhderivative(float *bh, float
Line 442  int computeBhderivative(float *bh, float
 /*===========================================*/ /*===========================================*/
 /* Example function 7:  Derivative of B_vertical SQRT( (dBz/dx)^2 + (dBz/dy)^2 ) */ /* Example function 7:  Derivative of B_vertical SQRT( (dBz/dx)^2 + (dBz/dy)^2 ) */
  
 int computeBzderivative(float *bz, float *bz_err, int *dims, float *mean_derivative_bz_ptr, float *mean_derivative_bz_err_ptr, int *mask, int *bitmask, float *derx_bz, float *dery_bz)  int computeBzderivative(float *bz, float *bz_err, int *dims, float *mean_derivative_bz_ptr, float *mean_derivative_bz_err_ptr, int *mask, int *bitmask, float *derx_bz, float *dery_bz, float *err_termA, float *err_termB)
 { {
  
     int nx = dims[0];     int nx = dims[0];
Line 448  int computeBzderivative(float *bz, float
Line 461  int computeBzderivative(float *bz, float
     {     {
             for (j = 0; j <= ny-1; j++)             for (j = 0; j <= ny-1; j++)
         {         {
             if isnan(bz[j * nx + i]) continue;  
             derx_bz[j * nx + i] = (bz[j * nx + i+1] - bz[j * nx + i-1])*0.5;             derx_bz[j * nx + i] = (bz[j * nx + i+1] - bz[j * nx + i-1])*0.5;
              err_termA[j * nx + i] = (((bz[j * nx + (i+1)]-bz[j * nx + (i-1)])*(bz[j * nx + (i+1)]-bz[j * nx + (i-1)])) * (bz_err[j * nx + (i+1)]*bz_err[j * nx + (i+1)] + bz_err[j * nx + (i-1)]*bz_err[j * nx + (i-1)]));
         }         }
     }     }
  
Line 458  int computeBzderivative(float *bz, float
Line 471  int computeBzderivative(float *bz, float
     {     {
             for (j = 1; j <= ny-2; j++)             for (j = 1; j <= ny-2; j++)
         {         {
             if isnan(bz[j * nx + i]) continue;  
             dery_bz[j * nx + i] = (bz[(j+1) * nx + i] - bz[(j-1) * nx + i])*0.5;             dery_bz[j * nx + i] = (bz[(j+1) * nx + i] - bz[(j-1) * nx + i])*0.5;
              err_termB[j * nx + i] = (((bz[(j+1) * nx + i]-bz[(j-1) * nx + i])*(bz[(j+1) * nx + i]-bz[(j-1) * nx + i])) * (bz_err[(j+1) * nx + i]*bz_err[(j+1) * nx + i] + bz_err[(j-1) * nx + i]*bz_err[(j-1) * nx + i]));
         }         }
     }     }
  
       /* consider the edges for the arrays that contribute to the variable "sum" in the computation below.
     /* consider the edges */      ignore the edges for the error terms as those arrays have been initialized to zero.
       this is okay because the error term will ultimately not include the edge pixels as they are selected out by the mask and bitmask arrays.*/
     i=0;     i=0;
     for (j = 0; j <= ny-1; j++)     for (j = 0; j <= ny-1; j++)
     {     {
         if isnan(bz[j * nx + i]) continue;  
         derx_bz[j * nx + i] = ( (-3*bz[j * nx + i]) + (4*bz[j * nx + (i+1)]) - (bz[j * nx + (i+2)]) )*0.5;         derx_bz[j * nx + i] = ( (-3*bz[j * nx + i]) + (4*bz[j * nx + (i+1)]) - (bz[j * nx + (i+2)]) )*0.5;
     }     }
  
     i=nx-1;     i=nx-1;
     for (j = 0; j <= ny-1; j++)     for (j = 0; j <= ny-1; j++)
     {     {
         if isnan(bz[j * nx + i]) continue;  
         derx_bz[j * nx + i] = ( (3*bz[j * nx + i]) + (-4*bz[j * nx + (i-1)]) - (-bz[j * nx + (i-2)]) )*0.5;         derx_bz[j * nx + i] = ( (3*bz[j * nx + i]) + (-4*bz[j * nx + (i-1)]) - (-bz[j * nx + (i-2)]) )*0.5;
     }     }
  
     j=0;     j=0;
     for (i = 0; i <= nx-1; i++)     for (i = 0; i <= nx-1; i++)
     {     {
         if isnan(bz[j * nx + i]) continue;  
         dery_bz[j * nx + i] = ( (-3*bz[j*nx + i]) + (4*bz[(j+1) * nx + i]) - (bz[(j+2) * nx + i]) )*0.5;         dery_bz[j * nx + i] = ( (-3*bz[j*nx + i]) + (4*bz[(j+1) * nx + i]) - (bz[(j+2) * nx + i]) )*0.5;
     }     }
  
     j=ny-1;     j=ny-1;
     for (i = 0; i <= nx-1; i++)     for (i = 0; i <= nx-1; i++)
     {     {
         if isnan(bz[j * nx + i]) continue;  
         dery_bz[j * nx + i] = ( (3*bz[j * nx + i]) + (-4*bz[(j-1) * nx + i]) - (-bz[(j-2) * nx + i]) )*0.5;         dery_bz[j * nx + i] = ( (3*bz[j * nx + i]) + (-4*bz[(j-1) * nx + i]) - (-bz[(j-2) * nx + i]) )*0.5;
     }     }
  
Line 509  int computeBzderivative(float *bz, float
Line 519  int computeBzderivative(float *bz, float
             if isnan(derx_bz[j * nx + i]) continue;             if isnan(derx_bz[j * nx + i]) continue;
             if isnan(dery_bz[j * nx + i]) continue;             if isnan(dery_bz[j * nx + i]) continue;
             sum += sqrt( derx_bz[j * nx + i]*derx_bz[j * nx + i]  + dery_bz[j * nx + i]*dery_bz[j * nx + i]  ); /* Units of Gauss */             sum += sqrt( derx_bz[j * nx + i]*derx_bz[j * nx + i]  + dery_bz[j * nx + i]*dery_bz[j * nx + i]  ); /* Units of Gauss */
             err += (((bz[(j+1) * nx + i]-bz[(j-1) * nx + i])*(bz[(j+1) * nx + i]-bz[(j-1) * nx + i])) * (bz_err[(j+1) * nx + i]*bz_err[(j+1) * nx + i] + bz_err[(j-1) * nx + i]*bz_err[(j-1) * nx + i])) /              err += err_termB[j * nx + i] / (16.0*( derx_bz[j * nx + i]*derx_bz[j * nx + i]  + dery_bz[j * nx + i]*dery_bz[j * nx + i]  )) +
             (16.0*( derx_bz[j * nx + i]*derx_bz[j * nx + i]  + dery_bz[j * nx + i]*dery_bz[j * nx + i]  )) +                     err_termA[j * nx + i] / (16.0*( derx_bz[j * nx + i]*derx_bz[j * nx + i]  + dery_bz[j * nx + i]*dery_bz[j * nx + i]  )) ;
             (((bz[j * nx + (i+1)]-bz[j * nx + (i-1)])*(bz[j * nx + (i+1)]-bz[j * nx + (i-1)])) * (bz_err[j * nx + (i+1)]*bz_err[j * nx + (i+1)] + bz_err[j * nx + (i-1)]*bz_err[j * nx + (i-1)])) /  
             (16.0*( derx_bz[j * nx + i]*derx_bz[j * nx + i]  + dery_bz[j * nx + i]*dery_bz[j * nx + i]  )) ;  
             count_mask++;             count_mask++;
         }         }
     }     }
Line 563  int computeBzderivative(float *bz, float
Line 571  int computeBzderivative(float *bz, float
 //              float *noiseby, float *noisebz) //              float *noiseby, float *noisebz)
  
 int computeJz(float *bx_err, float *by_err, float *bx, float *by, int *dims, float *jz, float *jz_err, float *jz_err_squared, int computeJz(float *bx_err, float *by_err, float *bx, float *by, int *dims, float *jz, float *jz_err, float *jz_err_squared,
               int *mask, int *bitmask, float cdelt1, double rsun_ref, double rsun_obs,float *derx, float *dery)                int *mask, int *bitmask, float cdelt1, double rsun_ref, double rsun_obs,float *derx, float *dery, float *err_term1, float *err_term2)
  
  
 { {
Line 582  int computeJz(float *bx_err, float *by_e
Line 590  int computeJz(float *bx_err, float *by_e
     {     {
             for (j = 0; j <= ny-1; j++)             for (j = 0; j <= ny-1; j++)
         {         {
             if isnan(by[j * nx + i]) continue;  
             derx[j * nx + i] = (by[j * nx + i+1] - by[j * nx + i-1])*0.5;             derx[j * nx + i] = (by[j * nx + i+1] - by[j * nx + i-1])*0.5;
              err_term1[j * nx + i] = (by_err[j * nx + i+1])*(by_err[j * nx + i+1]) + (by_err[j * nx + i-1])*(by_err[j * nx + i-1]);
         }         }
     }     }
  
Line 591  int computeJz(float *bx_err, float *by_e
Line 599  int computeJz(float *bx_err, float *by_e
     {     {
             for (j = 1; j <= ny-2; j++)             for (j = 1; j <= ny-2; j++)
         {         {
             if isnan(bx[j * nx + i]) continue;  
             dery[j * nx + i] = (bx[(j+1) * nx + i] - bx[(j-1) * nx + i])*0.5;             dery[j * nx + i] = (bx[(j+1) * nx + i] - bx[(j-1) * nx + i])*0.5;
              err_term2[j * nx + i] = (bx_err[(j+1) * nx + i])*(bx_err[(j+1) * nx + i]) + (bx_err[(j-1) * nx + i])*(bx_err[(j-1) * nx + i]);
         }         }
     }     }
  
     // consider the edges      /* consider the edges for the arrays that contribute to the variable "sum" in the computation below.
       ignore the edges for the error terms as those arrays have been initialized to zero.
       this is okay because the error term will ultimately not include the edge pixels as they are selected out by the mask and bitmask arrays.*/
   
     i=0;     i=0;
     for (j = 0; j <= ny-1; j++)     for (j = 0; j <= ny-1; j++)
     {     {
         if isnan(by[j * nx + i]) continue;  
         derx[j * nx + i] = ( (-3*by[j * nx + i]) + (4*by[j * nx + (i+1)]) - (by[j * nx + (i+2)]) )*0.5;         derx[j * nx + i] = ( (-3*by[j * nx + i]) + (4*by[j * nx + (i+1)]) - (by[j * nx + (i+2)]) )*0.5;
     }     }
  
     i=nx-1;     i=nx-1;
     for (j = 0; j <= ny-1; j++)     for (j = 0; j <= ny-1; j++)
     {     {
         if isnan(by[j * nx + i]) continue;  
         derx[j * nx + i] = ( (3*by[j * nx + i]) + (-4*by[j * nx + (i-1)]) - (-by[j * nx + (i-2)]) )*0.5;         derx[j * nx + i] = ( (3*by[j * nx + i]) + (-4*by[j * nx + (i-1)]) - (-by[j * nx + (i-2)]) )*0.5;
     }     }
  
     j=0;     j=0;
     for (i = 0; i <= nx-1; i++)     for (i = 0; i <= nx-1; i++)
     {     {
         if isnan(bx[j * nx + i]) continue;  
         dery[j * nx + i] = ( (-3*bx[j*nx + i]) + (4*bx[(j+1) * nx + i]) - (bx[(j+2) * nx + i]) )*0.5;         dery[j * nx + i] = ( (-3*bx[j*nx + i]) + (4*bx[(j+1) * nx + i]) - (bx[(j+2) * nx + i]) )*0.5;
     }     }
  
     j=ny-1;     j=ny-1;
     for (i = 0; i <= nx-1; i++)     for (i = 0; i <= nx-1; i++)
     {     {
         if isnan(bx[j * nx + i]) continue;  
         dery[j * nx + i] = ( (3*bx[j * nx + i]) + (-4*bx[(j-1) * nx + i]) - (-bx[(j-2) * nx + i]) )*0.5;         dery[j * nx + i] = ( (3*bx[j * nx + i]) + (-4*bx[(j-1) * nx + i]) - (-bx[(j-2) * nx + i]) )*0.5;
     }     }
  
     for (i = 1; i <= nx-2; i++)  
       for (i = 0; i <= nx-1; i++)
     {     {
         for (j = 1; j <= ny-2; j++)          for (j = 0; j <= ny-1; j++)
         {         {
             // calculate jz at all points             // calculate jz at all points
   
             jz[j * nx + i]            = (derx[j * nx + i]-dery[j * nx + i]);       // jz is in units of Gauss/pix             jz[j * nx + i]            = (derx[j * nx + i]-dery[j * nx + i]);       // jz is in units of Gauss/pix
             jz_err[j * nx + i]        = 0.5*sqrt( (bx_err[(j+1) * nx + i]*bx_err[(j+1) * nx + i]) + (bx_err[(j-1) * nx + i]*bx_err[(j-1) * nx + i]) +              jz_err[j * nx + i]        = 0.5*sqrt( err_term1[j * nx + i] + err_term2[j * nx + i] ) ;
                                                  (by_err[j * nx + (i+1)]*by_err[j * nx + (i+1)]) + (by_err[j * nx + (i-1)]*by_err[j * nx + (i-1)]) ) ;  
             jz_err_squared[j * nx + i]= (jz_err[j * nx + i]*jz_err[j * nx + i]);             jz_err_squared[j * nx + i]= (jz_err[j * nx + i]*jz_err[j * nx + i]);
             count_mask++;             count_mask++;
   
         }         }
     }     }
         return 0;         return 0;
Line 832  int computeHelicity(float *jz_err, float
Line 837  int computeHelicity(float *jz_err, float
 /* Example function 12:  Sum of Absolute Value per polarity  */ /* Example function 12:  Sum of Absolute Value per polarity  */
  
 //  The Sum of the Absolute Value per polarity is defined as the following: //  The Sum of the Absolute Value per polarity is defined as the following:
 //  fabs(sum(jz gt 0)) + fabs(sum(jz lt 0)) and the units are in Amperes.  //  fabs(sum(jz gt 0)) + fabs(sum(jz lt 0)) and the units are in Amperes per square arcsecond.
 //  The units of jz are in G/pix. In this case, we would have the following: //  The units of jz are in G/pix. In this case, we would have the following:
 //  Jz = (Gauss/pix)(1/CDELT1)(0.00010)(1/MUNAUGHT)(RSUN_REF/RSUN_OBS)(RSUN_REF/RSUN_OBS)(RSUN_OBS/RSUN_REF), //  Jz = (Gauss/pix)(1/CDELT1)(0.00010)(1/MUNAUGHT)(RSUN_REF/RSUN_OBS)(RSUN_REF/RSUN_OBS)(RSUN_OBS/RSUN_REF),
 //     = (Gauss/pix)(1/CDELT1)(0.00010)(1/MUNAUGHT)(RSUN_REF/RSUN_OBS) //     = (Gauss/pix)(1/CDELT1)(0.00010)(1/MUNAUGHT)(RSUN_REF/RSUN_OBS)
Line 869  int computeSumAbsPerPolarity(float *jz_e
Line 874  int computeSumAbsPerPolarity(float *jz_e
         }         }
     }     }
  
         *totaljzptr    = fabs(sum1) + fabs(sum2);  /* Units are A */      *totaljzptr    = fabs(sum1) + fabs(sum2);  /* Units are Amperes per arcsecond */
     *totaljz_err_ptr = sqrt(err)*(1/cdelt1)*fabs((0.00010)*(1/MUNAUGHT)*(rsun_ref/rsun_obs));     *totaljz_err_ptr = sqrt(err)*(1/cdelt1)*fabs((0.00010)*(1/MUNAUGHT)*(rsun_ref/rsun_obs));
     //printf("SAVNCPP=%g\n",*totaljzptr);     //printf("SAVNCPP=%g\n",*totaljzptr);
     //printf("SAVNCPP_err=%g\n",*totaljz_err_ptr);     //printf("SAVNCPP_err=%g\n",*totaljz_err_ptr);
Line 1023  int computeShearAngle(float *bx_err, flo
Line 1028  int computeShearAngle(float *bx_err, flo
     }     }
     /* For mean 3D shear angle, area with shear greater than 45*/     /* For mean 3D shear angle, area with shear greater than 45*/
     *meanshear_angleptr = (sumsum)/(count);                 /* Units are degrees */     *meanshear_angleptr = (sumsum)/(count);                 /* Units are degrees */
   
       // For the error in the mean 3D shear angle:
       // If count_mask is 0, then we run into a divide by zero error. In this case, set *meanshear_angle_err_ptr to NAN
       // If count_mask is greater than zero, then compute the error.
       if (count_mask == 0)
           *meanshear_angle_err_ptr = NAN;
       else
     *meanshear_angle_err_ptr = (sqrt(err)/count_mask)*(180./PI);     *meanshear_angle_err_ptr = (sqrt(err)/count_mask)*(180./PI);
  
     /* The area here is a fractional area -- the % of the total area. This has no error associated with it. */     /* The area here is a fractional area -- the % of the total area. This has no error associated with it. */
     *area_w_shear_gt_45ptr   = (count_mask/(count))*(100.0);     *area_w_shear_gt_45ptr   = (count_mask/(count))*(100.0);
  
     //printf("MEANSHR=%f\n",*meanshear_angleptr);     //printf("MEANSHR=%f\n",*meanshear_angleptr);
     //printf("MEANSHR_err=%f\n",*meanshear_angle_err_ptr);      //printf("ERRMSHA=%f\n",*meanshear_angle_err_ptr);
     //printf("SHRGT45=%f\n",*area_w_shear_gt_45ptr);     //printf("SHRGT45=%f\n",*area_w_shear_gt_45ptr);
   
         return 0;         return 0;
 } }
  
Line 1048  int computeShearAngle(float *bx_err, flo
Line 1059  int computeShearAngle(float *bx_err, flo
  
 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);
  
       // =============== [STEP 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 1085  int computeR(float *bz_err, float *los,
Line 1102  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 (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]);              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 (j = 0; j < ny1; j++)
           {
               index = j * nx1 + i;
               if isnan(pmapn[index]) continue;
               if isnan(rim[index]) continue;
               sum += pmapn[index]*abs(rim[index]);
         }         }
     }     }
  
Line 1116  int computeR(float *bz_err, float *los,
Line 1182  int computeR(float *bz_err, float *los,
     else     else
         *Rparam = log10(sum);         *Rparam = log10(sum);
  
       //printf("R_VALUE=%f\n",*Rparam);
   
     free_fresize(&fresboxcar);     free_fresize(&fresboxcar);
     free_fresize(&fresgauss);     free_fresize(&fresgauss);
  
     return 0;     return 0;
   
   }
   
   /*===========================================*/
   /* Example function 16: Lorentz force as defined in Fisher, 2012 */
   //
   // This calculation is adapted from Xudong's code
   // at /proj/cgem/lorentz/apps/lorentz.c
   
   int computeLorentz(float *bx,  float *by, float *bz, float *fx, float *fy, float *fz, int *dims,
                      float *totfx_ptr, float *totfy_ptr, float *totfz_ptr, float *totbsq_ptr,
                      float *epsx_ptr, float *epsy_ptr, float *epsz_ptr, int *mask, int *bitmask,
                      float cdelt1, double rsun_ref, double rsun_obs)
   
   {
   
       int nx = dims[0];
       int ny = dims[1];
       int nxny = nx*ny;
       int j = 0;
       int index;
       double totfx = 0, totfy = 0, totfz = 0;
       double bsq = 0, totbsq = 0;
       double epsx = 0, epsy = 0, epsz = 0;
       double area = cdelt1*cdelt1*(rsun_ref/rsun_obs)*(rsun_ref/rsun_obs)*100.0*100.0;
       double k_h = -1.0 * area / (4. * PI) / 1.0e20;
       double k_z = area / (8. * PI) / 1.0e20;
   
       if (nx <= 0 || ny <= 0) return 1;
   
       for (int i = 0; i < nxny; i++)
       {
          if ( mask[i] < 70 || bitmask[i] < 30 ) continue;
          if isnan(bx[i]) continue;
          if isnan(by[i]) continue;
          if isnan(bz[i]) continue;
          fx[i]  = bx[i] * bz[i] * k_h;
          fy[i]  = by[i] * bz[i] * k_h;
          fz[i]  = (bx[i] * bx[i] + by[i] * by[i] - bz[i] * bz[i]) * k_z;
          bsq    = bx[i] * bx[i] + by[i] * by[i] + bz[i] * bz[i];
          totfx  += fx[i]; totfy += fy[i]; totfz += fz[i];
          totbsq += bsq;
       }
   
       *totfx_ptr  = totfx;
       *totfy_ptr  = totfy;
       *totfz_ptr  = totfz;
       *totbsq_ptr = totbsq;
       *epsx_ptr   = (totfx / k_h) / totbsq;
       *epsy_ptr   = (totfy / k_h) / totbsq;
       *epsz_ptr   = (totfz / k_z) / totbsq;
   
       //printf("TOTBSQ=%f\n",*totbsq_ptr);
   
       return 0;
   
 } }
  
   /*===========================================*/
   
   /* Example function 17: Compute total unsigned flux in units of G/cm^2 on the LOS field */
   
   //  To compute the unsigned flux, we simply calculate
   //  flux = surface integral [(vector LOS) dot (normal vector)],
   //       = surface integral [(magnitude LOS)*(magnitude normal)*(cos theta)].
   //  However, since the field is radial, we will assume cos theta = 1.
   //  Therefore the pixels only need to be corrected for the projection.
   
   //  To convert G to G*cm^2, simply multiply by the number of square centimeters per pixel.
   //  As an order of magnitude estimate, we can assign 0.5 to CDELT1 and 722500m/arcsec to (RSUN_REF/RSUN_OBS).
   //  (Gauss/pix^2)(CDELT1)^2(RSUN_REF/RSUN_OBS)^2(100.cm/m)^2
   //  =Gauss*cm^2
   
   int computeAbsFlux_los(float *los, int *dims, float *absFlux_los,
                          float *mean_vf_los_ptr, float *count_mask_los_ptr,
                          int *bitmask, float cdelt1, double rsun_ref, double rsun_obs)
   
   {
   
       int nx = dims[0];
       int ny = dims[1];
       int i = 0;
       int j = 0;
       int count_mask_los = 0;
       int countabit = 0;
       double sum = 0.0;
       *absFlux_los = 0.0;
       *mean_vf_los_ptr = 0.0;
   
   
       if (nx <= 0 || ny <= 0) return 1;
   
           for (i = 0; i < nx; i++)
           {
              for (j = 0; j < ny; j++)
              {
               if ( bitmask[j * nx + i] < 30 ) continue;
               if isnan(los[j * nx + i])
                 {countabit++; continue;}
               sum += (fabs(los[j * nx + i]));
               count_mask_los++;
              }
           }
   
       *mean_vf_los_ptr     = sum*cdelt1*cdelt1*(rsun_ref/rsun_obs)*(rsun_ref/rsun_obs)*100.0*100.0;
       *count_mask_los_ptr  = count_mask_los;
   
       //printf("USFLUXL=%f\n",*mean_vf_los_ptr);
       //printf("CMASKL=%f\n",*count_mask_los_ptr);
   
       return 0;
   }
   
   /*===========================================*/
   /* Example function 18:  Derivative of B_LOS (approximately B_vertical) = SQRT( ( dLOS/dx )^2 + ( dLOS/dy )^2 ) */
   
   int computeLOSderivative(float *los, int *dims, float *mean_derivative_los_ptr, int *bitmask, float *derx_los, float *dery_los)
   {
   
       int nx = dims[0];
       int ny = dims[1];
       int i = 0;
       int j = 0;
       int count_mask = 0;
       double sum = 0.0;
       *mean_derivative_los_ptr = 0.0;
   
       if (nx <= 0 || ny <= 0) return 1;
   
       /* brute force method of calculating the derivative (no consideration for edges) */
       for (i = 1; i <= nx-2; i++)
       {
           for (j = 0; j <= ny-1; j++)
           {
              derx_los[j * nx + i] = (los[j * nx + i+1] - los[j * nx + i-1])*0.5;
           }
       }
   
       /* brute force method of calculating the derivative (no consideration for edges) */
       for (i = 0; i <= nx-1; i++)
       {
           for (j = 1; j <= ny-2; j++)
           {
              dery_los[j * nx + i] = (los[(j+1) * nx + i] - los[(j-1) * nx + i])*0.5;
           }
       }
   
       /* consider the edges for the arrays that contribute to the variable "sum" in the computation below.
       ignore the edges for the error terms as those arrays have been initialized to zero.
       this is okay because the error term will ultimately not include the edge pixels as they are selected out by the mask and bitmask arrays.*/
       i=0;
       for (j = 0; j <= ny-1; j++)
       {
           derx_los[j * nx + i] = ( (-3*los[j * nx + i]) + (4*los[j * nx + (i+1)]) - (los[j * nx + (i+2)]) )*0.5;
       }
   
       i=nx-1;
       for (j = 0; j <= ny-1; j++)
       {
           derx_los[j * nx + i] = ( (3*los[j * nx + i]) + (-4*los[j * nx + (i-1)]) - (-los[j * nx + (i-2)]) )*0.5;
       }
   
       j=0;
       for (i = 0; i <= nx-1; i++)
       {
           dery_los[j * nx + i] = ( (-3*los[j*nx + i]) + (4*los[(j+1) * nx + i]) - (los[(j+2) * nx + i]) )*0.5;
       }
   
       j=ny-1;
       for (i = 0; i <= nx-1; i++)
       {
           dery_los[j * nx + i] = ( (3*los[j * nx + i]) + (-4*los[(j-1) * nx + i]) - (-los[(j-2) * nx + i]) )*0.5;
       }
   
   
       for (i = 0; i <= nx-1; i++)
       {
           for (j = 0; j <= ny-1; j++)
           {
               if ( bitmask[j * nx + i] < 30 ) continue;
               if isnan(los[j * nx + i])      continue;
               if isnan(los[(j+1) * nx + i])  continue;
               if isnan(los[(j-1) * nx + i])  continue;
               if isnan(los[j * nx + i-1])    continue;
               if isnan(los[j * nx + i+1])    continue;
               if isnan(derx_los[j * nx + i]) continue;
               if isnan(dery_los[j * nx + i]) continue;
               sum += sqrt( derx_los[j * nx + i]*derx_los[j * nx + i]  + dery_los[j * nx + i]*dery_los[j * nx + i] ); /* Units of Gauss */
               count_mask++;
           }
       }
   
       *mean_derivative_los_ptr = (sum)/(count_mask); // would be divided by ((nx-2)*(ny-2)) if shape of count_mask = shape of magnetogram
   
       //printf("MEANGBL=%f\n",*mean_derivative_los_ptr);
   
           return 0;
   }
  
 /*==================KEIJI'S CODE =========================*/ /*==================KEIJI'S CODE =========================*/
  


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Karen Tian
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