Hi Troels,
Is it possible to shift the mask_replace part into __init__()? That
might give more speed ups. I'm not so familiar with numpy masks, so I
couldn't have helped you with that. Anyway, those 4 hours invested is
guaranteed to save you much more than 4 hours when you use this later.
Regards,
Edward
On 10 June 2014 16:51, <tlinnet@xxxxxxxxxxxxx> wrote:
Author: tlinnet
Date: Tue Jun 10 16:51:33 2014
New Revision: 23788
URL: http://svn.gna.org/viewcvs/relax?rev=23788&view=rev
Log:
Implemented a masked array search for where "missing" array is equal 1.
This makes it possible to replace all values with this mask, from the
value array.
This eliminates the last loops over the missing values.
It took over 4 hours to figure out, that the mask should be called with
mask.mask,
to return the same fulls 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=23788&r1=23787&r2=23788&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py
(original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py Tue Jun
10 16:51:33 2014
@@ -29,6 +29,7 @@
from math import pi
from numpy import array, asarray, complex64, dot, float64, int16, max,
ones, sqrt, sum, zeros
import numpy as np
+from numpy.ma import masked_equal
# relax module imports.
from lib.dispersion.b14 import r2eff_B14
@@ -418,6 +419,7 @@
# The number of disp point can change per spectrometer, so
we make the maximum size.
self.values_a = deepcopy(self.zeros_a)
self.errors_a = deepcopy(self.ones_a)
+ self.missing_a = zeros(self.numpy_array_shape)
self.cpmg_frqs_a = deepcopy(self.ones_a)
self.num_disp_points_a = deepcopy(self.zeros_a)
@@ -456,6 +458,7 @@
for di in
range(self.num_disp_points[ei][si][mi][oi]):
if self.missing[ei][si][mi][oi][di]:
self.has_missing = True
+ self.missing_a[ei][si][mi][oi][di]
= 1.0
# Make copy of values structure.
self.back_calc_a = deepcopy(self.values_a)
@@ -574,15 +577,11 @@
## 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:
- # Loop over the spins.
- for si in range(self.num_spins):
- # Loop over the spectrometer frequencies.
- for mi in range(self.num_frq):
- # Loop over the dispersion points.
- for di in
range(self.num_disp_points[0][si][mi][0]):
- if self.missing[0][si][mi][0][di]:
- #self.back_calc[0][si][mi][0][di] =
self.values[0][si][mi][0][di]
- self.back_calc_a[0][si][mi][0][di] =
self.values[0][si][mi][0][di]
+ # Find the numpy mask, which tells where values should be
replaced.
+ mask_replace = masked_equal(self.missing_a, 1.0)
+
+ # Replace with values.
+ self.back_calc_a[mask_replace.mask] =
self.values_a[mask_replace.mask]
## Calculate the chi-squared statistic.
return sum((1.0 / self.errors_a * (self.values_a -
self.back_calc_a))**2)
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Re: r23788 - /branches/disp_spin_speed/target_functions/relax_disp.py