Author: tlinnet
Date: Wed Jun 18 10:44:04 2014
New Revision: 24075
URL: http://svn.gna.org/viewcvs/relax?rev=24075&view=rev
Log:
Replaced double or triple hash-tags "##" with single hash-tags "#".
Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion
models for Clustered analysis.
Modified:
branches/disp_spin_speed/target_functions/relax_disp.py
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=24075&r1=24074&r2=24075&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py Wed Jun 18
10:44:04 2014
@@ -176,7 +176,7 @@
self.cpmg_frqs_orig = cpmg_frqs
self.spin_lock_nu1_orig = spin_lock_nu1
- ### Initialise higher order numpy structures.
+ # Initialise higher order numpy structures.
# Define the shape of all the numpy arrays.
# The total numbers of experiments, number of spins, number of
magnetic field strength, maximum number of offsets, maximum number of
dispersion point.
self.NE = len(self.exp_types)
@@ -351,7 +351,7 @@
# Get the tilt angles.
self.tilt_angles[ei, si, mi, oi, di] =
tilt_angles[ei][si][mi][oi][di]
self.offset[ei, si, mi, oi] =
offset[ei][si][mi][oi]
- ## Convert the spin-lock data to rad.s^-1.
+ # Convert the spin-lock data to rad.s^-1.
self.spin_lock_omega1[ei, si, mi, oi, di] =
2.0 * pi * spin_lock_nu1[ei][mi][oi][di]
self.spin_lock_omega1_squared[ei, si, mi,
oi, di] = self.spin_lock_omega1[ei, si, mi, oi, di] ** 2
@@ -521,7 +521,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -554,18 +554,18 @@
self.r20a_struct[:] = multiply.outer( R20A.reshape(self.NE, self.NS,
self.NM), self.no_nd_ones )
self.r20b_struct[:] = multiply.outer( R20B.reshape(self.NE, self.NS,
self.NM), self.no_nd_ones )
- ## Back calculate the R2eff values.
+ # Back calculate the R2eff values.
r2eff_CR72(r20a=self.r20a_struct, r20a_orig=R20A,
r20b=self.r20b_struct, r20b_orig=R20B, pA=pA, dw=self.dw_struct, dw_orig=dw,
kex=kex, cpmg_frqs=self.cpmg_frqs, back_calc=self.back_calc)
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
- if self.has_missing:
- # Replace with values.
- self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
-
- ## Calculate the chi-squared statistic.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ if self.has_missing:
+ # Replace with values.
+ self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
+
+ # Calculate the chi-squared statistic.
return chi2_rankN(self.values, self.back_calc, self.errors)
@@ -599,12 +599,12 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
- if self.has_missing:
- # Replace with values.
- self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
-
- ## Calculate the chi-squared statistic.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ if self.has_missing:
+ # Replace with values.
+ self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
+
+ # Calculate the chi-squared statistic.
return chi2_rankN(self.values, self.back_calc, self.errors)
@@ -638,12 +638,12 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
- if self.has_missing:
- # Replace with values.
- self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
-
- ## Calculate the chi-squared statistic.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ if self.has_missing:
+ # Replace with values.
+ self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
+
+ # Calculate the chi-squared statistic.
return chi2_rankN(self.values, self.back_calc, self.errors)
@@ -749,7 +749,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -805,7 +805,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -993,7 +993,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1033,7 +1033,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1081,7 +1081,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1119,7 +1119,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1158,7 +1158,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1198,7 +1198,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1238,7 +1238,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1309,12 +1309,12 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
- if self.has_missing:
- # Replace with values.
- self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
-
- ## Calculate the chi-squared statistic.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ if self.has_missing:
+ # Replace with values.
+ self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
+
+ # Calculate the chi-squared statistic.
return chi2_rankN(self.values, self.back_calc, self.errors)
@@ -1340,7 +1340,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1428,12 +1428,12 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
- if self.has_missing:
- # Replace with values.
- self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
-
- ## Calculate the chi-squared statistic.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ if self.has_missing:
+ # Replace with values.
+ self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
+
+ # Calculate the chi-squared statistic.
return chi2_rankN(self.values, self.back_calc, self.errors)
@@ -1556,7 +1556,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1658,7 +1658,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1751,7 +1751,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1791,7 +1791,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
@@ -1830,7 +1830,7 @@
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
- ## For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
if self.has_missing:
# Replace with values.
self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
r24075 - /branches/disp_spin_speed/target_functions/relax_disp.py