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[r24170] by tlinnet

Fix to the matrix_exponential_rankN, to return the exact exponential for any higher dimensional square matrix
of shape [NE][NS][NM][NO][ND][X][X].

The fix was to the eye(X), to make the shape the same as the input shape.

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

2014-06-19 18:52:55 Tree
[r24169] by tlinnet

Made the function use the new multidimensional R_mat matrix.

Systemtest: test_tp02_data_to_ns_r1rho_2site
still passes.

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

2014-06-19 18:52:53 Tree
[r24168] by tlinnet

Added a check, that the pre- relax_time multiplied multidimensional array, equal the previous.

It does, to the sum of 1.0e-13.

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

2014-06-19 18:52:51 Tree
[r24167] by tlinnet

Added the relax_time to collection of rr1rho_3d_rankN matrix collection.

This is to pre-multiply all elements with the time.

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

2014-06-19 18:52:49 Tree
[r24166] by tlinnet

Added a check in lib/dispersion/ns_r1hro_2site.py, to see if the newly created multidimensional
ns matrix of rank NE][NS][NM][NO][ND][6][6], is equal to the previous [6][6] matrix.

It is.

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

2014-06-19 18:17:49 Tree
[r24165] by tlinnet

Added the ns matrice, rr1rho_3d_rankN, to collect the multi dimensional 3D exchange matrix, of rank [NE][NS][NM][NO][ND][6][6].

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

2014-06-19 18:17:47 Tree
[r24164] by tlinnet

Changed back from einsum to dot method, since dot method it faster for square matrixes.

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

2014-06-19 15:42:28 Tree
[r24163] by tlinnet

Replaced the inner dot product with numpy einsum.

This though slows it down from 8.5 s to 13 s.
This is only as an intermediate step, how to figure to dot product inner parts of the big matrix.

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

2014-06-19 15:42:25 Tree
[r24162] by tlinnet

Removed unused variables in NS CPMG 2site 3D, to clean up the code.

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

2014-06-19 15:42:23 Tree
[r24161] by tlinnet

Implemeted systemtest: test_cpmg_synthetic_b14_to_ns3d_cluster

This is to cathc failures of the model, when data is clusted.

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

2014-06-19 15:42:20 Tree
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