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[r23735] by tlinnet

Important fix for the creation of the multi dimensional pA numpy array.

It should be created as numpy.zeros([ei][si][mi][oi]) instead of numpy.ones([ei][si][mi][oi]).

This allows for rapid testing of all dimensions with np.allclose(pA, numpy.ones(dw.shape)).
pA can have missing filled out values, when the number of dispersion points are different
per spectrometer frequency.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

2014-06-08 17:48:31 Tree
[r23734] by tlinnet

Made it easier to switch between single and cluster reporting in profiling script.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

2014-06-08 17:48:29 Tree
[r23733] by tlinnet

Important fix for extracting the correct shape to create new arrays.

If using just one field, or having the same number of dispersion points, the shape would extend to the dispersion number.
It would report [ei][si][mi][oi][di] when calling ndarray.shape.

Shape always has to be reported as: [ei][si][mi][oi].

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

2014-06-08 17:48:27 Tree
[r23732] by tlinnet

Re-inserted safety checks in lin/dispersion/cr72.py file.

This is re-inserted for the rank_1 cases.

This makes the unit-tests pass again.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

2014-06-08 17:48:25 Tree
[r23731] by tlinnet

Fix for calculation of the larmor frequency per spin in profiling script.

The frq loop should also be up-shifted.
It was now extracted as 0.0.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

2014-06-08 17:48:23 Tree
[r23730] by tlinnet

In profiling script, moved up the calculation of values one level.

This is to better see the output of the profiling iterations for cr72.py.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

2014-06-08 11:14:38 Tree
[r23729] by tlinnet

Removing looping over exp and offset indicies in calc_chi2. They are always 0 anyway.

This brings a little speed.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

----
Profiling.

1000 iterations
100 spins
3 sfrq
('sfrq: ', 600000000.0, 'number of cpmg frq', 15, array([ 2., 6., 10., 14., 18., 22., 26., 30., 34., 38., 42.,
46., 50., 54., 58.]
))
('sfrq: ', 800000000.0, 'number of cpmg frq', 20, array([ 2., 6., 10., 14., 18., 22., 26., 30., 34., 38., 42.,
46., 50., 54., 58., 62., 66., 70., 74., 78.]
))
('sfrq: ', 900000000.0, 'number of cpmg frq', 22, array([ 2., 6., 10., 14., 18., 22., 26., 30., 34., 38., 42.,
46., 50., 54., 58., 62., 66., 70., 74., 78., 82., 86.]
))
('chi2 cluster:', 0.0)

TRUNK
ncalls tottime percall cumtime percall filename:lineno(function)
1000 5.221 0.005 53.578 0.054 relax_disp.py:456(calc_CR72_chi2)

BEFORE
ncalls tottime percall cumtime percall filename:lineno(function)
1000 14.871 0.015 43.084 0.043 relax_disp.py:494(calc_CR72_chi2)

AFTER removing looping over exp and offset indicies. They are always 0.
ncalls tottime percall cumtime percall filename:lineno(function)
1000 12.831 0.013 38.248 0.038 relax_disp.py:494(calc_CR72_chi2)

2014-06-08 11:14:36 Tree
[r23728] by tlinnet

Modified profiling script to calculate correct values when setting up R2eff values.

This is to test, that the return of chi2 gets zero.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

2014-06-08 11:14:34 Tree
[r23727] by tlinnet

Moved the creation of special numpy structures outside target function.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

2014-06-07 21:18:18 Tree
[r23726] by tlinnet

Added print out of chi2 to profile script.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

2014-06-07 21:18:15 Tree
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