mailr23928 - /branches/disp_spin_speed/target_functions/relax_disp.py


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Posted by tlinnet on June 13, 2014 - 12:16:
Author: tlinnet
Date: Fri Jun 13 12:16:52 2014
New Revision: 23928

URL: http://svn.gna.org/viewcvs/relax?rev=23928&view=rev
Log:
Replaced target function for model MP05, to use higher dimensional numpy 
array structures.

That makes the model much faster.

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=23928&r1=23927&r2=23928&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py     (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py     Fri Jun 13 
12:16:52 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_M61, MODEL_M61B, MODEL_TAP03, MODEL_TP02, 
MODEL_TSMFK01]
+        test_models = [MODEL_B14, MODEL_B14_FULL, MODEL_CR72, 
MODEL_CR72_FULL, MODEL_DPL94, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_TAP03, 
MODEL_TP02, MODEL_TSMFK01]
 
         if model in test_models + [MODEL_NOREX]:
             # Get the shape of back_calc structure.
@@ -1327,37 +1327,25 @@
         pA = params[self.end_index[1]]
         kex = params[self.end_index[1]+1]
 
-        # Once off parameter conversions.
-        pB = 1.0 - pA
-
-        # Initialise.
-        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]
-
-                # Loop over the offsets.
-                for oi in range(self.num_offsets[0][si][mi]):
-                    # Back calculate the R1rho values.
-                    r1rho_MP05(r1rho_prime=R20[r20_index], 
omega=self.chemical_shifts[0][si][mi], offset=self.offset[0][si][mi][oi], 
pA=pA, pB=pB, dw=dw_frq, kex=kex, R1=self.r1[si, mi], 
spin_lock_fields=self.spin_lock_omega1[0][mi][oi], 
spin_lock_fields2=self.spin_lock_omega1_squared[0][mi][oi], 
back_calc=self.back_calc[0][si][mi][oi], 
num_points=self.num_disp_points[0][si][mi][oi])
-
-                    # 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][oi]):
-                        if self.missing[0][si][mi][oi][di]:
-                            self.back_calc[0][si][mi][oi][di] = 
self.values[0][si][mi][oi][di]
-
-                    # Calculate and return the chi-squared value.
-                    chi2_sum += chi2(self.values[0][si][mi][oi], 
self.back_calc[0][si][mi][oi], self.errors[0][si][mi][oi])
+        # 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 R20 to per experiment, spin and frequency.
+        self.r20_struct[:] = multiply.outer( R20.reshape(self.NE, self.NS, 
self.NM), self.no_nd_struct )
+
+        # Back calculate the R1rho values.
+        r1rho_MP05(r1rho_prime=self.r20_struct, 
omega=self.chemical_shifts_a, offset=self.offset_a, pA=pA, dw=self.dw_struct, 
kex=kex, R1=self.r1_a, spin_lock_fields=self.spin_lock_omega1_a, 
spin_lock_fields2=self.spin_lock_omega1_squared_a, back_calc=self.back_calc_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]
 
         # Return the total chi-squared value.
-        return chi2_sum
+        return chi2_rankN(self.values_a, self.back_calc_a, self.errors_a)
 
 
     def func_mmq_CR72(self, params):




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