Author: bugman
Date: Tue Aug 26 10:29:38 2014
New Revision: 25267
URL: http://svn.gna.org/viewcvs/relax?rev=25267&view=rev
Log:
Changed the argument and variable names in the C code chi-squared gradient
function.
Modified:
trunk/target_functions/c_chi2.c
Modified: trunk/target_functions/c_chi2.c
URL:
http://svn.gna.org/viewcvs/relax/trunk/target_functions/c_chi2.c?rev=25267&r1=25266&r2=25267&view=diff
==============================================================================
--- trunk/target_functions/c_chi2.c (original)
+++ trunk/target_functions/c_chi2.c Tue Aug 26 10:29:38 2014
@@ -61,7 +61,7 @@
}
-void dchi2(double dchi2[], double data[], double back_calc_vals[], double
back_calc_grad[][MAX_DATA], double errors[], int num_times, int M) {
+void dchi2(double dchi2[], double data[], double back_calc_vals[], double
back_calc_grad[][MAX_DATA], double errors[], int num_points, int num_params) {
/* Calculate the full chi-squared gradient.
The chi-squared gradient
@@ -96,18 +96,20 @@
@type back_calc_grad: numpy rank-2 size MxN array
@param errors: The vector of sigma_i values.
@type errors: numpy rank-1 size N array
- @param M: The dimensions of the gradient.
- @type M: int
+ @param num_points: The number of data points to sum over.
+ @type num_points: int
+ @param num_params: The dimensions of the gradient.
+ @type num_params: int
*/
/* Declarations. */
- int i, j;
+ int data_index, param_index;
/* Calculate the chi-squared gradient. */
- for (j = 0; j < M; ++j) {
- dchi2[j] = 0.0;
- for (i = 0; i < num_times; ++i) {
- dchi2[j] += -2.0 / square(errors[i]) * (data[i] -
back_calc_vals[i]) * back_calc_grad[j][i];
+ for (param_index = 0; param_index < num_params; ++param_index) {
+ dchi2[param_index] = 0.0;
+ for (data_index = 0; data_index < num_points; ++data_index) {
+ dchi2[param_index] += -2.0 / square(errors[data_index]) *
(data[data_index] - back_calc_vals[data_index]) *
back_calc_grad[param_index][data_index];
}
}
}
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