Author: tlinnet
Date: Fri Jun 13 10:10:04 2014
New Revision: 23908
URL: http://svn.gna.org/viewcvs/relax?rev=23908&view=rev
Log:
Made the NOREX model af faster numpy array 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/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=23908&r1=23907&r2=23908&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py Fri Jun 13
10:10:04 2014
@@ -394,8 +394,11 @@
if model == MODEL_NS_MMQ_3SITE_LINEAR:
self.func = self.func_ns_mmq_3site_linear
+
# Setup special numpy array structures, for higher dimensional
computation.
- if model in [MODEL_B14, MODEL_B14_FULL, MODEL_CR72,
MODEL_CR72_FULL, MODEL_DPL94, MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01]:
+ test_models = [MODEL_B14, MODEL_B14_FULL, MODEL_CR72,
MODEL_CR72_FULL, MODEL_DPL94, MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01]
+
+ if model in test_models + [MODEL_NOREX]:
# Get the shape of back_calc structure.
# If using just one field, or having the same number of
dispersion points, the shape would extend to that number.
# Shape has to be: [ei][si][mi][oi].
@@ -443,8 +446,11 @@
self.r20b_struct = deepcopy(zeros_a)
self.dw_struct = deepcopy(zeros_a)
- # Extract the frequencies to numpy array.
- self.frqs_a = multiply.outer(
asarray(self.frqs).reshape(self.NE, self.NS, self.NM), self.no_nd_struct )
+ # Setup special numpy array structures, for higher dimensional
computation.
+ if model in test_models + [MODEL_NOREX]:
+ if model in test_models:
+ # Extract the frequencies to numpy array.
+ self.frqs_a = multiply.outer(
asarray(self.frqs).reshape(self.NE, self.NS, self.NM), self.no_nd_struct )
if model in MODEL_LIST_CPMG_FULL:
self.cpmg_frqs_a = deepcopy(ones_a)
@@ -476,7 +482,7 @@
# Extract number of dispersion points.
num_disp_points =
self.num_disp_points[ei][si][mi][oi]
- if model in MODEL_LIST_CPMG_FULL:
+ if model in MODEL_LIST_CPMG_FULL and model !=
MODEL_NOREX:
# Extract cpmg_frqs and num_disp_points
from lists.
self.cpmg_frqs_a[ei][si][mi][oi][:num_disp_points] =
self.cpmg_frqs[ei][mi][oi]
self.num_disp_points_a[ei][si][mi][oi][:num_disp_points] =
self.num_disp_points[ei][si][mi][oi]
@@ -497,7 +503,7 @@
self.power_a[ei][si][mi][oi][di] =
int(round(self.cpmg_frqs[ei][mi][0][di] * self.relax_times[ei][mi]))
self.tau_cpmg_a[ei][si][mi][oi][di] =
0.25 / self.cpmg_frqs[ei][mi][0][di]
# For R1rho data.
- if model in MODEL_LIST_R1RHO_FULL:
+ if model in MODEL_LIST_R1RHO_FULL and
model != MODEL_NOREX:
self.disp_struct[ei][si][mi][oi][di] =
1.0
# Extract the frequencies to numpy
array.
@@ -511,11 +517,12 @@
else:
self.num_disp_points_a[ei][si][mi][oi][di] = 0
+ if model in test_models:
+ # Pre calculate frqs structure
+ self.frqs_struct = self.frqs_a * self.disp_struct
+
# Make copy of values structure.
self.back_calc_a = deepcopy(self.values_a)
-
- # Pre calculate frqs structure
- self.frqs_struct = self.frqs_a * self.disp_struct
# Find the numpy mask, which tells where values should be
replaced.
self.mask_replace_blank = masked_equal(missing_a, 1.0)
@@ -1465,34 +1472,16 @@
# Unpack the parameter values.
R20 = params
- # Initialise.
- chi2_sum = 0.0
-
- # Loop over the experiment types.
- for ei in range(self.num_exp):
- # Loop over the spins.
- for si in range(self.num_spins):
- # Loop over the spectrometer frequencies.
- for mi in range(self.num_frq):
- # The R20 index.
- r20_index = mi + si*self.num_frq
-
- # Loop over the offsets.
- for oi in range(self.num_offsets[ei][si][mi]):
- # The R2eff values as R20 values.
- for di in
range(self.num_disp_points[ei][si][mi][oi]):
- self.back_calc[ei][si][mi][oi][di] =
R20[r20_index]
-
- # 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 di in
range(self.num_disp_points[ei][si][mi][oi]):
- if self.missing[ei][si][mi][oi][di]:
- self.back_calc[ei][si][mi][oi][di] =
self.values[ei][si][mi][oi][di]
-
- # Calculate and return the chi-squared value.
- chi2_sum += chi2(self.values[ei][si][mi][oi],
self.back_calc[ei][si][mi][oi], self.errors[ei][si][mi][oi])
+ # Reshape R20 to per experiment, spin and frequency.
+ self.back_calc_a[:] = multiply.outer( R20.reshape(self.NE,
self.NS, self.NM), self.no_nd_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_a[self.mask_replace_blank.mask] =
self.values_a[self.mask_replace_blank.mask]
# Return the total chi-squared value.
- return chi2_sum
+ return chi2_rankN(self.values_a, self.back_calc_a, self.errors_a)
def func_ns_cpmg_2site_3D(self, params):
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Re: r23908 - /branches/disp_spin_speed/target_functions/relax_disp.py