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Posted by tlinnet on May 28, 2014 - 19:17:
Author: tlinnet
Date: Wed May 28 19:17:08 2014
New Revision: 23563

URL: http://svn.gna.org/viewcvs/relax?rev=23563&view=rev
Log:
Converting back to having back_calc as a function argument to model B14.

This is to clean up the API.
There can be bo no partial measures/implementations in the relax trunk.

The problem is, that many numerical models can't be optimised further, since 
they
evolve the spin-magnetisation in a matrix.  That spin evolvement can't be put 
into
a larger numpy array.

This is related to: task #7793: (https://gna.org/task/?7793) Speed-up of 
dispersion models.

Modified:
    branches/disp_speed/lib/dispersion/b14.py
    branches/disp_speed/target_functions/relax_disp.py
    branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_b14.py

Modified: branches/disp_speed/lib/dispersion/b14.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_speed/lib/dispersion/b14.py?rev=23563&r1=23562&r2=23563&view=diff
==============================================================================
--- branches/disp_speed/lib/dispersion/b14.py   (original)
+++ branches/disp_speed/lib/dispersion/b14.py   Wed May 28 19:17:08 2014
@@ -115,7 +115,7 @@
 # Repetitive calculations (to speed up calculations).
 g_fact = 1/sqrt(2)
 
-def r2eff_B14(r20a=None, r20b=None, pA=None, pB=None, dw=None, kex=None, 
k_AB=None, k_BA=None, ncyc=None, inv_tcpmg=None, tcp=None, num_points=None):
+def r2eff_B14(r20a=None, r20b=None, pA=None, pB=None, dw=None, kex=None, 
k_AB=None, k_BA=None, ncyc=None, inv_tcpmg=None, tcp=None, back_calc=None, 
num_points=None):
     """Calculate the R2eff values for the CR72 model.
 
     See the module docstring for details.
@@ -143,13 +143,16 @@
     @type inv_tcpmg:        float
     @keyword tcp:           The tau_CPMG times (1 / 4.nu1).
     @type tcp:              numpy rank-1 float array
-    @keyword num_points:    The number of points on the dispersion curve, 
equal to the length of the cpmg_frqs.
+    @keyword back_calc:     The array for holding the back calculated R2eff 
values.  Each element corresponds to one of the CPMG nu1 frequencies.
+    @type back_calc:        numpy rank-1 float array
+    @keyword num_points:    The number of points on the dispersion curve, 
equal to the length of the cpmg_frqs and back_calc arguments.
     @type num_points:       int
     """
 
     # Catch parameter values that will result in no exchange, returning flat 
R2eff = R20 lines (when kex = 0.0, k_AB = 0.0).
     if dw == 0.0 or pA == 1.0 or k_AB == 0.0:
-        return array([r20a]*num_points)
+        back_calc[:] = array([r20a]*num_points)
+        return
 
     # Repetitive calculations (to speed up calculations).
     deltaR2 = r20a - r20b
@@ -200,7 +203,8 @@
     # Catch math domain error of sinh(val > 710).
     # This is when E0 > 710.
     if max(E0) > 700:
-        return array([r20a]*num_points)
+        back_calc[:] = array([r20a]*num_points)
+        return
 
     # Derived from chemical shifts  #E2 = complex(0,-2.0 * tcp * (F00I - 
f11I)).
     E2 =  two_tcp * g4
@@ -248,4 +252,4 @@
     if not isfinite(sum(R2eff)):
         R2eff = array([1e100]*num_points)
 
-    return R2eff
+    back_calc[:] = R2eff

Modified: branches/disp_speed/target_functions/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_speed/target_functions/relax_disp.py?rev=23563&r1=23562&r2=23563&view=diff
==============================================================================
--- branches/disp_speed/target_functions/relax_disp.py  (original)
+++ branches/disp_speed/target_functions/relax_disp.py  Wed May 28 19:17:08 
2014
@@ -439,7 +439,7 @@
                         aliased_dw = dw_frq
 
                     # Back calculate the R2eff values.
-                    self.back_calc[ei][si][mi][0] = 
r2eff_B14(r20a=R20A[r20_index], r20b=R20B[r20_index], pA=pA, pB=pB, 
dw=aliased_dw, kex=kex, k_AB=k_AB, k_BA=k_BA, ncyc=self.power[ei][mi], 
inv_tcpmg=self.inv_relax_times[ei][mi], tcp=self.tau_cpmg[ei][mi], 
num_points=self.num_disp_points[ei][si][mi][0])
+                    r2eff_B14(r20a=R20A[r20_index], r20b=R20B[r20_index], 
pA=pA, pB=pB, dw=aliased_dw, kex=kex, k_AB=k_AB, k_BA=k_BA, 
ncyc=self.power[ei][mi], inv_tcpmg=self.inv_relax_times[ei][mi], 
tcp=self.tau_cpmg[ei][mi], back_calc=self.back_calc[ei][si][mi][0], 
num_points=self.num_disp_points[ei][si][mi][0])
 
                     # 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][0]):

Modified: 
branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_b14.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_b14.py?rev=23563&r1=23562&r2=23563&view=diff
==============================================================================
--- branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_b14.py    
  (original)
+++ branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_b14.py    
  Wed May 28 19:17:08 2014
@@ -47,6 +47,7 @@
         cpmg_frqs = self.ncyc / relax_times
         self.inv_relax_times = 1.0 / relax_times
         self.tau_cpmg = 0.25 / cpmg_frqs
+        self.R2eff = zeros(self.num_points, float64)
 
         # The spin Larmor frequencies.
         self.sfrq = 200. * 1E6
@@ -59,11 +60,11 @@
         k_AB, k_BA, pB, dw_frq = self.param_conversion(pA=self.pA, 
kex=self.kex, dw=self.dw, sfrq=self.sfrq)
 
         # Calculate the R2eff values.
-        R2eff = r2eff_B14(r20a=self.r20a, r20b=self.r20b, pA=self.pA, pB=pB, 
dw=dw_frq, kex=self.kex, k_AB=k_AB, k_BA=k_BA, ncyc=self.ncyc, 
inv_tcpmg=self.inv_relax_times, tcp=self.tau_cpmg, num_points=self.num_points)
+        r2eff_B14(r20a=self.r20a, r20b=self.r20b, pA=self.pA, pB=pB, 
dw=dw_frq, kex=self.kex, k_AB=k_AB, k_BA=k_BA, ncyc=self.ncyc, 
inv_tcpmg=self.inv_relax_times, tcp=self.tau_cpmg, back_calc=self.R2eff, 
num_points=self.num_points)
 
         # Check all R2eff values.
         for i in range(self.num_points):
-            self.assertAlmostEqual(R2eff[i], self.r20a)
+            self.assertAlmostEqual(self.R2eff[i], self.r20a)
 
 
     def param_conversion(self, pA=None, kex=None, dw=None, sfrq=None):




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