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underchemist / nanonispy / 19 / 2
97%
master: 97%

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DEFAULT BRANCH: master
Ran 26 Dec 2015 11:19PM UTC
Files 4
Run time 1s
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26 Dec 2015 11:17PM UTC coverage: 99.708% (+0.01%) from 99.695%
19.2

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underchemist
Added two new methods, which are just wrappers to numpy.save and numpy.load

The idea I had was that since pickling matplotlib figures is so tricky,
it would still be beneficial to be able to generate the figures without having to preprocess everything all over again. So once you have your data analyzed,
dump it into a numpy binary .npy file and load it up in a separate figure generation script.

Added some basic array roundtrip checks, for coverage purposes.

342 of 343 relevant lines covered (99.71%)

1.0 hits per line

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