Switched inverse function to run pseudo-inverse, to account for correlated and 0 variance variables #5
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@@ Coverage Diff @@
## master #5 +/- ##
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+ Coverage 96% 96.55% +0.55%
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Files 1 1
Lines 50 58 +8
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+ Hits 48 56 +8
Misses 2 2
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added 5 commits
May 2, 2017 16:31
… integration speed
vpolimenov
approved these changes
May 3, 2017
xulaus
requested changes
May 3, 2017
| series = Kruskals.Kruskals(ndarr, arr).driver_score() | ||
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| assert series[1] == 0.0 | ||
| assert series[4] == 0.0 |
xulaus
reviewed
May 3, 2017
| @@ -121,3 +121,26 @@ def test_that_direction_is_applied_on_directional_drivers_analysis(): | |||
| series = Kruskals.Kruskals(ndarr, arr).driver_score_to_series(True) | |||
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| assert (series.values < 0).any() | |||
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Also I think this should be a double newline
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Not given that the others aren't. We can correct in a different PR if you feel strongly
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#whitespacepolice |
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xulaus
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May 3, 2017
Rambatino
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Switched to pinv from inv
https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.pinv.html
It uses:
https://en.wikipedia.org/wiki/Moore%E2%80%93Penrose_pseudoinverse
With thanks to @jhofmeyr