Author: tlinnet
Date: Fri Jun 13 07:21:04 2014
New Revision: 23902
URL: http://svn.gna.org/viewcvs/relax?rev=23902&view=rev
Log:
Reordered the initialization structure of the special numpy arrays.
This was done in the init part of the target function of relaxation
dispersion.
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=23902&r1=23901&r2=23902&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py Fri Jun 13
07:21:04 2014
@@ -55,7 +55,7 @@
from lib.errors import RelaxError
from lib.float import isNaN
from target_functions.chi2 import chi2, 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_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_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_R1RHO, MODEL_B14,
MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99,
MODEL_LIST_CPMG, MODEL_LIST_CPMG_FULL, 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
class Dispersion:
@@ -427,47 +427,43 @@
self.values_a = deepcopy(zeros_a)
self.errors_a = deepcopy(ones_a)
missing_a = zeros(self.numpy_array_shape)
-
- self.cpmg_frqs_a = deepcopy(ones_a)
+
self.num_disp_points_a = deepcopy(zeros_a)
- self.inv_relax_times_a = deepcopy(zeros_a)
- self.tau_cpmg_a = deepcopy(zeros_a)
- self.power_a = ones(self.numpy_array_shape, int16)
+ self.disp_struct = deepcopy(zeros_a)
+ self.has_missing = False
+
+ # Create special numpy structures.
+ self.no_nd_struct = ones([self.NO, self.ND], float64)
+ self.nm_no_nd_struct = ones([self.NM, self.NO, self.ND], float64)
+
+ # Structure of r20a and r20b. The full and outer dimensions
structures.
+ # Structure of dw. The full and the outer dimensions structures.
+ self.r20_struct = deepcopy(zeros_a)
+ self.r20a_struct = deepcopy(zeros_a)
+ 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 )
+
+ if model in MODEL_LIST_CPMG_FULL:
+ self.cpmg_frqs_a = deepcopy(ones_a)
+
+ if model in [MODEL_B14, MODEL_B14_FULL, MODEL_MMQ_CR72,
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]:
+ # Expand relax times.
+ self.inv_relax_times_a = 1.0 / multiply.outer(
tile(self.relax_times[:,None],(1, 1, self.NS)).reshape(self.NE, self.NS,
self.NM), self.no_nd_struct )
+ self.power_a = ones(self.numpy_array_shape, int16)
+ self.tau_cpmg_a = deepcopy(zeros_a)
# For R1rho data.
- if model in [MODEL_DPL94, MODEL_TAP03]:
+ if model in MODEL_LIST_R1RHO_FULL:
self.tilt_angles_a = deepcopy(zeros_a)
self.spin_lock_omega1_squared_a = deepcopy(zeros_a)
self.spin_lock_omega1_a = deepcopy(zeros_a)
self.phi_ex_struct = deepcopy(zeros_a)
self.offset_a = deepcopy(zeros_a)
-
- self.frqs_a = deepcopy(zeros_a)
- self.disp_struct = deepcopy(zeros_a)
- self.has_missing = False
-
- # Create special numpy structures.
- # Structure of dw. The full and the outer dimensions structures.
- self.dw_struct = deepcopy(zeros_a)
- self.no_nd_struct = ones([self.NO, self.ND], float64)
- self.nm_no_nd_struct = ones([self.NM, self.NO, self.ND], float64)
-
- # Structure of r20a and r20b. The full and outer dimensions
structures.
- self.r20_struct = deepcopy(zeros_a)
- self.r20a_struct = deepcopy(zeros_a)
- self.r20b_struct = deepcopy(zeros_a)
- self.no_nd_struct = ones([self.NO, self.ND], float64)
-
- if model not in [MODEL_DPL94]:
- # Expand relax times.
- self.inv_relax_times_a = 1.0 / multiply.outer(
tile(self.relax_times[:,None],(1, 1, self.NS)).reshape(self.NE, self.NS,
self.NM), self.no_nd_struct )
-
- if model in [MODEL_DPL94, MODEL_TAP03]:
self.r1_a = multiply.outer( self.r1.reshape(self.NE,
self.NS, self.NM), self.no_nd_struct )
self.chemical_shifts_a = multiply.outer(
self.chemical_shifts, self.no_nd_struct )
-
- # 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 )
# Loop over the experiment types.
for ei in range(self.NE):
@@ -480,7 +476,7 @@
# Extract number of dispersion points.
num_disp_points =
self.num_disp_points[ei][si][mi][oi]
- if model not in [MODEL_DPL94, MODEL_TAP03]:
+ if model in MODEL_LIST_CPMG_FULL:
# 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]
@@ -491,18 +487,17 @@
# Extract the errors and values to numpy array.
self.errors_a[ei][si][mi][oi][:num_disp_points]
= self.errors[ei][si][mi][oi]
self.values_a[ei][si][mi][oi][:num_disp_points]
= self.values[ei][si][mi][oi]
-
# Loop over dispersion points.
for di in range(num_disp_points):
if self.missing[ei][si][mi][oi][di]:
self.has_missing = True
missing_a[ei][si][mi][oi][di] = 1.0
- if model in [MODEL_B14, MODEL_B14_FULL,
MODEL_TSMFK01]:
+ if model in [MODEL_B14, MODEL_B14_FULL,
MODEL_MMQ_CR72, 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]:
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_DPL94, MODEL_TAP03]:
+ if model in MODEL_LIST_R1RHO_FULL:
self.disp_struct[ei][si][mi][oi][di] =
1.0
# Extract the frequencies to numpy array.
r23902 - /branches/disp_spin_speed/target_functions/relax_disp.py