[MRG] Disregard NaNs in preprocessing

[eliwoods]

This is a redo of #175; rebasing to the dev branch got hairy so I'm just making a new PR along with the suggested additions from #175 (comment)

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If a time series with any NaN values is passed to TimeSeriesScalerMeanVariance.fit_transform() or TimeSeriesScalerMinMax.fit_transform() the transformed time series returns as all NaN

E.g:

In [1]: from tslearn.preprocessing import TimeSeriesScalerMeanVariance                                                                

In [2]: from numpy import nan                                                                                                         

In [3]: TimeSeriesScalerMeanVariance().fit_transform([0, nan, 6])                                                                     
Out[3]: 
array([[[nan],
        [nan],
        [nan]]])

This could be fixed by using the NaN disregarding numpy equivalent functions in the respective transform methods. This also makes tslearn in line with sklearn in terms of NaN's and preprocessing: scikit-learn/scikit-learn#10404

[pep8speaks]

Hello @eliwoods! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻

Comment last updated at 2020-01-08 21:50:30 UTC

[eliwoods]

@rtavenar addressed your additions. Should I make the update to CHANGELOG.md in this branch as well? I don't see anything in the contribution guidelines about the correct order.

[rtavenar]

@eliwoods yes, please document your change in CHANGELOG.md and I will merge your PR asap. Thanks for your contribution, it will be integrated in tslearn from version 0.3!

[eliwoods]

@rtavenar change log updated; feel free to merge. Cheers!