Author: tlinnet
Date: Mon Jun 9 19:46:25 2014
New Revision: 23758
URL: http://svn.gna.org/viewcvs/relax?rev=23758&view=rev
Log:
Moved the calculation of dw_frq out of spin and spectrometer loop.
This is done by having a special 1/0 spin numpy array, which turns on or off
the values in the numpy array multiplication.
The multiplication needs to first axis expand dw, and then tile the arrays
according to the numpy structure.
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=23758&r1=23757&r2=23758&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py Mon Jun 9
19:46:25 2014
@@ -29,6 +29,7 @@
from copy import deepcopy
from math import pi
from numpy import array, asarray, complex64, dot, float64, int16, max, ones,
sqrt, sum, zeros
+import numpy as np
# relax module imports.
from lib.dispersion.b14 import r2eff_B14
@@ -405,9 +406,12 @@
# To let the numpy array operate well together, the broadcast
size has to be equal for all shapes.
self.max_num_disp_points = max(self.num_disp_points)
+ # Define the shape of all the numpy arrays.
+ self.numpy_array_shape = back_calc_shape +
[self.max_num_disp_points]
+
# Create zero and one numpy structure.
- self.zeros_a = zeros(back_calc_shape +
[self.max_num_disp_points], float64)
- self.ones_a = ones(back_calc_shape + [self.max_num_disp_points],
float64)
+ self.zeros_a = zeros(self.numpy_array_shape, float64)
+ self.ones_a = ones(self.numpy_array_shape, float64)
# Create numpy arrays to pass to the lib function.
# All numpy arrays have to have same shape to allow to multiply
together.
@@ -425,6 +429,7 @@
self.values_a = deepcopy(self.ones_a)
self.has_missing = False
self.frqs_a = deepcopy(self.zeros_a)
+ self.spins_a = deepcopy(self.zeros_a)
# Loop over the experiment types.
@@ -448,6 +453,9 @@
# Extract the frequencies to numpy array.
self.frqs_a[ei][si][mi][oi][:num_disp_points] =
self.frqs[ei][si][mi]
+
+ # Make a spin 1/0 file.
+ self.spins_a[ei][si][mi][oi][:num_disp_points] =
ones(num_disp_points)
for di in
range(self.num_disp_points[ei][si][mi][oi]):
if self.missing[ei][si][mi][oi][di]:
@@ -530,6 +538,14 @@
@rtype: float
"""
+ # Expand dw to number of axis.
+ dw_axis = dw[None,:,None,None,None]
+ # Tile tw according to dimensions.
+ dw_axis = np.tile(dw_axis, (self.numpy_array_shape[0],
self.numpy_array_shape[2],self.numpy_array_shape[3],
self.numpy_array_shape[4]))
+
+ # Convert dw from ppm to rad/s.
+ self.dw_frq_a = dw_axis*self.spins_a*self.frqs_a
+
# Loop over the spectrometer frequencies.
for mi in range(self.num_frq):
# Extract number of dispersion points. Always the same per sin.
@@ -547,12 +563,6 @@
# Store r20a and r20b values per disp point.
self.R20A_a[0][si][mi][0][:num_disp_points] = array(
[R20A[r20_index]] * num_disp_points, float64)
self.R20B_a[0][si][mi][0][:num_disp_points] = array(
[R20B[r20_index]] * num_disp_points, float64)
-
- # Convert dw from ppm to rad/s.
- dw_frq = dw[si] * self.frqs[0][si][mi]
-
- # Store dw_frq per disp point.
- self.dw_frq_a[0][si][mi][0][:num_disp_points] = array(
[dw_frq] * num_disp_points, float64)
# Store pA and kex per disp point.
self.pA_a[0][si][mi][0][:num_disp_points] = pA_arr
r23758 - /branches/disp_spin_speed/target_functions/relax_disp.py