r23801 - in /branches/disp_spin_speed/target_functions: chi2.py relax_disp.py -- June 10, 2014 - 19:11

Author: tlinnet
Date: Tue Jun 10 19:11:07 2014
New Revision: 23801

URL: http://svn.gna.org/viewcvs/relax?rev=23801&view=rev
Log:
Renamed chi2_ND to chi2_rankN.

This is a better name for representing multiple axis calculation.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion 
models for Clustered analysis.

Modified:
    branches/disp_spin_speed/target_functions/chi2.py
    branches/disp_spin_speed/target_functions/relax_disp.py

Modified: branches/disp_spin_speed/target_functions/chi2.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/target_functions/chi2.py?rev=23801&r1=23800&r2=23801&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/chi2.py   (original)
+++ branches/disp_spin_speed/target_functions/chi2.py   Tue Jun 10 19:11:07 
2014
@@ -69,7 +69,7 @@
 ####################
 
 
-def chi2_ND(data, back_calc_vals, errors):
+def chi2_rankN(data, back_calc_vals, errors):
     """Function to calculate the chi-squared value for multiple numpy array 
axis.
 
     The chi-squared equation

Modified: branches/disp_spin_speed/target_functions/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/target_functions/relax_disp.py?rev=23801&r1=23800&r2=23801&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py     (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py     Tue Jun 10 
19:11:07 2014
@@ -55,7 +55,7 @@
 from lib.dispersion.tsmfk01 import r2eff_TSMFK01
 from lib.errors import RelaxError
 from lib.float import isNaN
-from target_functions.chi2 import chi2, chi2_ND
+from target_functions.chi2 import chi2, chi2_rankN
 from specific_analyses.relax_disp.variables import EXP_TYPE_CPMG_DQ, 
EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, 
EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_R1RHO, MODEL_B14, 
MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, 
MODEL_LIST_CPMG, MODEL_LIST_FULL, MODEL_LIST_MMQ, MODEL_LIST_MQ_CPMG, 
MODEL_LIST_R1RHO, MODEL_LM63, MODEL_LM63_3SITE, MODEL_M61, MODEL_M61B, 
MODEL_MP05, MODEL_MMQ_CR72, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D, 
MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED, 
MODEL_NS_CPMG_2SITE_STAR, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE, 
MODEL_NS_MMQ_3SITE, MODEL_NS_MMQ_3SITE_LINEAR, MODEL_NS_R1RHO_2SITE, 
MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_TAP03, MODEL_TP02, 
MODEL_TSMFK01
 
 
@@ -579,7 +579,7 @@
             self.back_calc_a[mask_replace.mask] = 
self.values_a[mask_replace.mask]
 
         ## Calculate the chi-squared statistic.
-        return chi2_ND(self.values_a, self.back_calc_a, self.errors_a)
+        return chi2_rankN(self.values_a, self.back_calc_a, self.errors_a)
 
 
     def calc_ns_cpmg_2site_3D_chi2(self, R20A=None, R20B=None, dw=None, 
pA=None, kex=None):