relax SVN archive

Moved the Bloch-McConnell matrix for 2-site exchange into lib/dispersion/ns_matrices.py.

This is for consistency with the other code.

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

Fix the bug: "M2_i = M1_mat", which was causing the problems getting systemtests to pass.

Removed the specifications of which dtype, the initial matrices are created.
They can be converted later, with the specification of dtype to matrix_exponential_rankN().

All systemtests now pass.

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

Added the "dtype" argument to function matrix_exponential_rankN.

This is to force the conversion of dtype, if they are of other type.
This can be conversion from complex128 to complex64.

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

Fix for using the old matrix_exponential of m1.

Onye:
- test_korzhnev_2005_15n_sq_data

Is still failing.
That still uses the matrix_exponential_rankN.

There seems to be a problem with matrix_exponential_rankN, when doing
complex numbers.

Maybe the dtype has to get fixed?
Use it as a input argument?

It must be the einsum

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

Force complex64 in ns_mmq_2site_mq.

This solves all systemtests.

Forcing to be complex64, does not seems like a long standing solution, since
complex128 is possible.

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

Forces complex64 in ns_mmq_2site_sq_dq_zq instead complex128.

This fixes systemtests:
- test_korzhnev_2005_15n_zq_data
- test_korzhnev_2005_1h_sq_data

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

Forcing the dtype to be complex64, instead of complex128.

This solves a range of systemtests.
The one who fails now is:

-test_korzhnev_2005_15n_zq_data
-test_korzhnev_2005_1h_mq_data
-test_korzhnev_2005_1h_sq_data

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

Reinserted old code.

This fixes:
test_korzhnev_2005_15n_mq_data

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

Fix for ns_mmq_2site_mq.

Variable was wrong called.
There seems to be a serious problem more with mq.

test_korzhnev_2005_15n_dq_data
self.assertAlmostEqual(spin.r2[r20_key3], 13.6153887849344, 2)
AssertionError: 13.624172993315323 != 13.6153887849344 within 2 places

test_korzhnev_2005_15n_mq_data
self.assertAlmostEqual(spin.r2[r20_key1], 6.02016436619016, 1)
AssertionError: 0.00032836499986468263 != 6.02016436619016 within 1 places

test_korzhnev_2005_15n_sq_data
self.assertAlmostEqual(spin.kex/1000, 433.176323890829849/1000, 3)
AssertionError: 0.42987451018414946 != 0.43317632389082983 within 3 places

test_korzhnev_2005_1h_mq_data
self.assertAlmostEqual(spin.r2[r20_key2], 0.039223196112941, 2)
AssertionError: 0.033056489136372089 != 0.039223196112941 within 2 places

test_korzhnev_2005_1h_sq_data
self.assertAlmostEqual(spin.chi2, 50.3431330819767, 1)
AssertionError: 50.400683622209989 != 50.3431330819767 within 1 places

test_korzhnev_2005_all_data
self.assertAlmostEqual(spin.r2[r20_key1], 6.67288025927458, 4)
AssertionError: 6.7044178906652689 != 6.67288025927458 within 4 places

test_korzhnev_2005_all_data_disp_speed_bug
self.assertAlmostEqual(spin.chi2/1000, 162.511988511609/1000, 3)
AssertionError: 0.49707952193522587 != 0.162511988511609 within 3 places

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

Removed grid search, and lowered number of iterations for systemtest:
test_cpmg_synthetic_b14_to_ns3d_cluster
test_cpmg_synthetic_b14_to_ns_star_cluster

This is to speed them up, since they before took 30 seks.

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