Author: tlinnet
Date: Sun Jun 15 15:15:19 2014
New Revision: 23961
URL: http://svn.gna.org/viewcvs/relax?rev=23961&view=rev
Log:
Changed the target function of NS CPMG 2site STAR, to reflect the input to
the function.
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=23961&r1=23960&r2=23961&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py Sun Jun 15
15:15:19 2014
@@ -396,7 +396,7 @@
# Setup special numpy array structures, for higher dimensional
computation.
- test_models = [MODEL_B14, MODEL_B14_FULL, MODEL_CR72,
MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LM63, MODEL_M61, MODEL_M61B,
MODEL_MP05, MODEL_NS_CPMG_2SITE_3D, MODEL_NS_CPMG_2SITE_3D_FULL,
MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01]
+ test_models = [MODEL_B14, MODEL_B14_FULL, MODEL_CR72,
MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LM63, MODEL_M61, MODEL_M61B,
MODEL_MP05, MODEL_NS_CPMG_2SITE_3D, MODEL_NS_CPMG_2SITE_3D_FULL,
MODEL_NS_CPMG_2SITE_STAR, MODEL_NS_CPMG_2SITE_STAR_FULL,
MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01]
if model in test_models + [MODEL_NOREX]:
# Get the shape of back_calc structure.
@@ -666,47 +666,26 @@
@rtype: float
"""
- # Once off parameter conversions.
- pB = 1.0 - pA
- k_BA = pA * kex
- k_AB = pB * kex
-
- # Set up the matrix that contains the exchange terms between the two
states A and B.
- self.Rex[0, 0] = -k_AB
- self.Rex[0, 1] = k_BA
- self.Rex[1, 0] = k_AB
- self.Rex[1, 1] = -k_BA
-
- # This is a vector that contains the initial magnetizations
corresponding to the A and B state transverse magnetizations.
- self.M0[0] = pA
- self.M0[1] = pB
-
- # Chi-squared initialisation.
- chi2_sum = 0.0
-
- # 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
-
- # Convert dw from ppm to rad/s.
- dw_frq = dw[si] * self.frqs[0][si][mi]
-
- # Back calculate the R2eff values.
- r2eff_ns_cpmg_2site_star(Rr=self.Rr, Rex=self.Rex,
RCS=self.RCS, R=self.R, M0=self.M0, r20a=R20A[r20_index],
r20b=R20B[r20_index], dw=dw_frq, inv_tcpmg=self.inv_relax_times[0][mi],
tcp=self.tau_cpmg[0][mi], back_calc=self.back_calc[0][si][mi][0],
num_points=self.num_disp_points[0][si][mi][0], power=self.power[0][mi])
-
- # 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[0][si][mi][0]):
- if self.missing[0][si][mi][0][di]:
- self.back_calc[0][si][mi][0][di] =
self.values[0][si][mi][0][di]
-
- # Calculate and return the chi-squared value.
- chi2_sum += chi2(self.values[0][si][mi][0],
self.back_calc[0][si][mi][0], self.errors[0][si][mi][0])
-
- # Return the total chi-squared value.
- return chi2_sum
+ # Convert dw from ppm to rad/s. Use the out argument, to pass
directly to structure.
+ multiply( multiply.outer( dw.reshape(self.NE, self.NS),
self.nm_no_nd_struct ), self.frqs_a, out=self.dw_struct )
+
+ # Reshape R20A and R20B to per experiment, spin and frequency.
+ self.r20a_struct[:] = multiply.outer( R20A.reshape(self.NE, self.NS,
self.NM), self.no_nd_struct )
+ self.r20b_struct[:] = multiply.outer( R20B.reshape(self.NE, self.NS,
self.NM), self.no_nd_struct )
+
+ # Back calculate the R2eff values.
+ r2eff_ns_cpmg_2site_star(Rr=self.Rr, Rex=self.Rex, RCS=self.RCS,
R=self.R, M0=self.M0, r20a=self.r20a_struct, r20b=self.r20b_struct, pA=pA,
dw=self.dw_struct, dw_orig=dw, kex=kex, inv_tcpmg=self.inv_relax_times_a,
tcp=self.tau_cpmg_a, back_calc=self.back_calc_a,
num_points=self.num_disp_points_a, power=self.power_a)
+
+ # Clean the data for all values, which is left over at the end of
arrays.
+ self.back_calc_a = self.back_calc_a*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_a[self.mask_replace_blank.mask] =
self.values_a[self.mask_replace_blank.mask]
+
+ ## Calculate the chi-squared statistic.
+ return chi2_rankN(self.values_a, self.back_calc_a, self.errors_a)
def calc_ns_mmq_3site_chi2(self, R20A=None, R20B=None, R20C=None,
dw_AB=None, dw_BC=None, dwH_AB=None, dwH_BC=None, pA=None, pB=None,
kex_AB=None, kex_BC=None, kex_AC=None):
r23961 - /branches/disp_spin_speed/target_functions/relax_disp.py