Author: tlinnet
Date: Fri Aug 1 18:09:25 2014
New Revision: 24903
URL: http://svn.gna.org/viewcvs/relax?rev=24903&view=rev
Log:
Created the numpy array self.index target function which contains index to
store the data.
This is for situations where numpy version is under 1.8.
Modified:
trunk/target_functions/relax_disp.py
Modified: trunk/target_functions/relax_disp.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/target_functions/relax_disp.py?rev=24903&r1=24902&r2=24903&view=diff
==============================================================================
--- trunk/target_functions/relax_disp.py (original)
+++ trunk/target_functions/relax_disp.py Fri Aug 1 18:09:25 2014
@@ -26,7 +26,7 @@
# Python module imports.
from copy import deepcopy
-from numpy import arctan2, cos, dot, float64, int16, multiply, ones,
rollaxis, pi, sin, zeros
+from numpy import arctan2, cos, dot, float64, int16, multiply, ones,
rollaxis, pi, sin, version, zeros
from numpy.ma import masked_equal
# relax module imports.
@@ -36,6 +36,7 @@
from lib.dispersion.it99 import r2eff_IT99
from lib.dispersion.lm63 import r2eff_LM63
from lib.dispersion.lm63_3site import r2eff_LM63_3site
+from lib.dispersion.matrix_exponential import create_index
from lib.dispersion.m61 import r1rho_M61
from lib.dispersion.m61b import r1rho_M61b
from lib.dispersion.mp05 import r1rho_MP05
@@ -54,7 +55,7 @@
from lib.errors import RelaxError
from lib.float import isNaN
from target_functions.chi2 import chi2_rankN
-from specific_analyses.relax_disp.variables import EXP_TYPE_CPMG_DQ,
EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ,
EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST_CPMG, EXP_TYPE_R1RHO,
MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94,
MODEL_IT99, MODEL_LIST_CPMG, MODEL_LIST_FULL, MODEL_LIST_MMQ,
MODEL_LIST_MQ_CPMG, MODEL_LIST_R1RHO, MODEL_LIST_R1RHO_FULL, MODEL_LM63,
MODEL_LM63_3SITE, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_MMQ_CR72,
MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D, MODEL_NS_CPMG_2SITE_3D_FULL,
MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR,
MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE, MODEL_NS_MMQ_3SITE,
MODEL_NS_MMQ_3SITE_LINEAR, MODEL_NS_R1RHO_2SITE, MODEL_NS_R1RHO_3SITE,
MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01
+from specific_analyses.relax_disp.variables import EXP_TYPE_CPMG_DQ,
EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ,
EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST_CPMG, EXP_TYPE_R1RHO,
MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94,
MODEL_IT99, MODEL_LIST_CPMG, MODEL_LIST_FULL, MODEL_LIST_MMQ,
MODEL_LIST_MQ_CPMG, MODEL_LIST_NUMERIC, MODEL_LIST_R1RHO,
MODEL_LIST_R1RHO_FULL, MODEL_LM63, MODEL_LM63_3SITE, MODEL_M61, MODEL_M61B,
MODEL_MP05, MODEL_MMQ_CR72, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D,
MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED,
MODEL_NS_CPMG_2SITE_STAR, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE,
MODEL_NS_MMQ_3SITE, MODEL_NS_MMQ_3SITE_LINEAR, MODEL_NS_R1RHO_2SITE,
MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_TAP03, MODEL_TP02,
MODEL_TSMFK01
class Dispersion:
@@ -465,6 +466,38 @@
# Transpose M0, to prepare for dot operation. Roll the last axis
one back, corresponds to a transpose for the outer two axis.
self.M0_T = rollaxis(self.M0, 6, 5)
+
+ # If numpy version is under 1.8, it is necessary to stride through
data to calculate numpy.eig() in the matrix_exponential calculation.
+ # When calculated through the strided data matrix, the data needs to
be packed back into the higher order dimensional data.
+ # This is done by first making a numpy array which contains index
indices to store, to store the result back to the matrix.
+ if float(version.version[:3]) < 1.8 and model in MODEL_LIST_NUMERIC:
+ # 2x2 matrix of form [NE][NS][NM][NO][ND][5].
+ if model == MODEL_NS_CPMG_2SITE_STAR or model ==
MODEL_NS_CPMG_2SITE_STAR_FULL:
+ self.index = create_index(NE=self.NE, NS=self.NS,
NM=self.NM, NO=self.NO, ND=self.ND)
+
+ # 2x2 matrix of form [NS][NM][NO][ND][4].
+ if model == MODEL_NS_MMQ_2SITE:
+ self.index = create_index(NE=None, NS=self.NS, NM=self.NM,
NO=self.NO, ND=self.ND)
+
+ # 3x3 matrix of form [NS][NM][NO][ND][4].
+ if model == MODEL_NS_MMQ_3SITE or model ==
MODEL_NS_MMQ_3SITE_LINEAR:
+ self.index = create_index(NE=None, NS=self.NS, NM=self.NM,
NO=self.NO, ND=self.ND)
+
+ # 6x6 matrix of form [NE][NS][NM][NO][ND][5].
+ elif model == MODEL_NS_R1RHO_2SITE:
+ self.index = create_index(NE=self.NE, NS=self.NS,
NM=self.NM, NO=self.NO, ND=self.ND)
+
+ # 7x7 matrix of form [NE][NS][NM][NO][ND][5].
+ elif model == MODEL_NS_CPMG_2SITE_3D or model ==
MODEL_NS_CPMG_2SITE_3D_FULL:
+ self.index = create_index(NE=self.NE, NS=self.NS,
NM=self.NM, NO=self.NO, ND=self.ND)
+
+ # 9x9 matrix of form [NE][NS][NM][NO][ND][5].
+ elif model == MODEL_NS_R1RHO_3SITE or model ==
MODEL_NS_R1RHO_3SITE_LINEAR:
+ self.index = create_index(NE=self.NE, NS=self.NS,
NM=self.NM, NO=self.NO, ND=self.ND)
+
+ # For numpy versions >= 1.8, store None.
+ else:
+ self.index = None
# Set up the model.
if model == MODEL_NOREX:
r24903 - /trunk/target_functions/relax_disp.py