Hi Troels,
We have a major problem in trunk caused by the recent merger of the
disp_spin_speed branch. When I run the Relax_disp system tests, the
unit tests, or the Relax_disp GUI tests, I see many, many failures due
to problems with the numpy.linalg.eig() function on numpy 1.6.1,
1.6.2, and 1.7.0. The error for one of the unit tests is:
======================================================================
ERROR: Test the r2eff_ns_cpmg_2site_3D() function for no exchange when dw
= 0.0.
----------------------------------------------------------------------
Traceback (most recent call last):
File
"/data/relax/relax-trunk/test_suite/unit_tests/_lib/_dispersion/test_ns_cpmg_2site_3d.py",
line 130, in test_ns_cpmg_2site_3D_no_rex1
self.calc_r2eff()
File
"/data/relax/relax-trunk/test_suite/unit_tests/_lib/_dispersion/test_ns_cpmg_2site_3d.py",
line 79, in calc_r2eff
r2eff_ns_cpmg_2site_3D(r180x=self.r180x, M0=self.M0,
M0_T=self.M0_T, r20a=self.r20a*a, r20b=self.r20b*a, pA=self.pA,
dw=dw_frq*a, dw_orig=dw_frq*a, kex=self.kex,
inv_tcpmg=self.inv_relax_times*a, tcp=self.tau_cpmg*a,
back_calc=self.R2eff, num_points=self.num_points*b, power=self.ncyc*a)
File "/data/relax/relax-trunk/lib/dispersion/ns_cpmg_2site_3d.py",
line 299, in r2eff_ns_cpmg_2site_3D
Rexpo_mat = matrix_exponential_rank_NE_NS_NM_NO_ND_x_x(R_mat)
File "/data/relax/relax-trunk/lib/dispersion/matrix_exponential.py",
line 78, in matrix_exponential_rank_NE_NS_NM_NO_ND_x_x
W, V = eig(A)
File "/data/python/lib/python2.5/site-packages/numpy/linalg/linalg.py",
line 1015, in eig
_assertRank2(a)
File "/data/python/lib/python2.5/site-packages/numpy/linalg/linalg.py",
line 155, in _assertRank2
two-dimensional' % len(a.shape)
LinAlgError: 7-dimensional array given. Array must be
two-dimensional
----------------------------------------------------------------------
Here are the API differences between numpy versions:
1.8.1:
http://docs.scipy.org/doc/numpy-1.8.1/reference/generated/numpy.linalg.eig.html#numpy.linalg.eig
1.8.0:
http://docs.scipy.org/doc/numpy-1.8.0/reference/generated/numpy.linalg.eig.html#numpy.linalg.eig
1.7.0:
http://docs.scipy.org/doc/numpy-1.7.0/reference/generated/numpy.linalg.eig.html#numpy.linalg.eig
1.6.0:
http://docs.scipy.org/doc/numpy-1.6.0/reference/generated/numpy.linalg.eig.html#numpy.linalg.eig
You can see that the input changes from (M, M) to (..., M, M) between
1.7.0 and 1.8.0. We cannot require numpy >= 1.8 as many current
distributions have not shifted to this version yet. Most sys admins
would kill me for even suggesting that ;) Therefore we need to come
up with a solution and quickly.
The best would be to add an eig() function to the lib.compat module.
For numpy >= 1.8.0 it will use the numpy.linalg.eig() function. For
the other versions, we need an alternative solution. Maybe using slow
Python looping over the higher dimensions would be ok.
I will not report this as a bug, as no released relax versions are
affected.
Cheers,
Edward
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relax (http://www.nmr-relax.com)
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