relax SVN archive

Created multi dimensional error and value numpy arrays.

This is to calculate the chi2 sum much faster.
Reordered the loop over missing data points, so it is only iniatiated if missing points is detected.

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

Added self.has_missing keyword in initialization of the Dispersion class.

This is to test once, per spin or cluster.
This saves a looping over the dipsersion points, when collection the data.

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

Critical fix for the slicing of values in target function.

This makes system test: Relax_disp.test_sod1wt_t25_to_cr72 pass.

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

Changed that special numpy structure is also created for "CR72".

This makes most system tests pass.

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

Added unit tests demonstrating edge cases 'no Rex' failures of the model 'CR72 full', for a clustered multi dimensional calculation.

This is implemented for three fields.

This is to implement catching of math domain errors, before they occur.

These tests cover all parameter value combinations which result in no exchange:

- dw = 0.0,
- pA = 1.0,
- kex = 0.0,
- dw = 0.0 and pA = 1.0,
- dw = 0.0 and kex = 0.0,
- pA = 1.0 and kex = 0.0,
- dw = 0.0, pA = 1.0, and kex = 0.0.
- kex = 1e5,
Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis.

Re-implemented safety checks in lib/dispersion/cr72.py.

This is now implemented for both rank-1 float array and of higher dimensions.

This makes the unit tests pass for multi dimensional computing.

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

Added unit tests demonstrating edge cases 'no Rex' failures of the model 'CR72 full', for a clustered multi dimensional calculation.

This is implemented for one field.

This is to implement catching of math domain errors, before they occur.

These tests cover all parameter value combinations which result in no exchange:

- dw = 0.0,
- pA = 1.0,
- kex = 0.0,
- dw = 0.0 and pA = 1.0,
- dw = 0.0 and kex = 0.0,
- pA = 1.0 and kex = 0.0,
- dw = 0.0, pA = 1.0, and kex = 0.0.
- kex = 1e5,

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

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.

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.

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.