Use numpy in place of flex for large parts of cosym analysis #1581
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This is far too simplistic likely not useful.
As clusters are not guaranteed to be equal sizes not all clusters will contain all symops.
This appears to be a consequence of using np.random.rand in place of flex.random_double to initialise the starting coordinates. As a result the automatic determination of number of dimensions chooses 7 instead of 6 dimensions, which seems to tip the balance from success to failure. This highlights that this probably isn't the most robust test case - the resulting likelihood for the correct space group isn't particularly high, even when the test is working.
Codecov Report
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## master #1581 +/- ##
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- Coverage 66.71% 66.71% -0.01%
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Files 616 616
Lines 69304 69278 -26
Branches 9571 9569 -2
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- Hits 46236 46216 -20
+ Misses 21135 21129 -6
Partials 1933 1933 |
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Since we are using various scipy routines already (e.g. for cluster analysis), this removes many interconversions between flex and numpy arrays. Conversion between flex/numpy arrays is now mostly limited to the wrapper around
scitbx.lbfgs. These changes also enable the addition of an option to use scipy L-BFGS-B minimization engine (minimization.engine=scipy).