Follow-up Comment #4, bug #22032 (project relax):
Acccording to these guys:
http://stackoverflow.com/questions/6736590/fast-check-for-nan-in-numpy
The fastest way to check for numpy errors is a sum of the list.
That can then be checked for isfinite() or isnan()
# Skip the error search.
etapos = etapos_part / cpmg_frqs
etaneg = etaneg_part / cpmg_frqs
fact = Dpos * cosh(etapos) - Dneg * cos(etaneg)
if isfinite(sum(fact)):
R2eff = r20_kex - cpmg_frqs * arccosh(fact)
for i in range(num_points):
back_calc[i] = R2eff[i]
else:
R2eff = array([10**7]*num_points)
for i in range(num_points):
back_calc[i] = R2eff[i]
http://docs.scipy.org/doc/numpy/reference/generated/numpy.isfinite.html
http://docs.scipy.org/doc/numpy/reference/generated/numpy.isnan.html
http://docs.scipy.org/doc/numpy/reference/generated/numpy.isinf.html
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