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base repository: hhromic/python-bcubed
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head repository: NilsRethmeier/python-bcubed
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  • 2 commits
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Commits on Jul 7, 2017

  1. Fix: precision() returns nan 

    If mult_precision(el1, el2, cdict, ldict) = [], i.e. an empty list is returned, then numpy mean produces a nan
This leads to a nan in the list of means (input to the outer most level mean). The mean of such a list is then also precision = nan.
    Nils Rethmeier
    Nils Rethmeier authored Jul 7, 2017
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  2. FIX: precision() results in nan 

    If mult_precision() produces an empty list, the inner mean produces a nan. This results in feeding the outer mean a nan (as a list element), which produces a nan precision)
2 Possible fixes: (I'm not sure which is better)
Ignore NaN's: (no match = ignore)
1. return numpy.nanmean([numpy.mean([mult_precision(el1, el2, cdict, ldict) for el2 in cdict if cdict[el1] & cdict[el2]]) for el1 in cdict])
Replace inner nans with 0: (no/zero set overlap = 0)
2. return numpy.mean([numpy.nan_to_num(numpy.mean([mult_precision(el1, el2, cdict, ldict) for el2 in cdict if cdict[el1] & cdict[el2]])) for el1 in cdict])
    Nils Rethmeier
    Nils Rethmeier authored Jul 7, 2017
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