[MRG] add fast replacement for np.cov #5344
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Timings with NumPy 1.8.2 and ATLAS:
>>> X = np.random.rand(13000,60)
>>> %timeit np.cov(X)
1 loops, best of 3: 2.82 s per loop
>>> %timeit fast_cov(X)
1 loops, best of 3: 1.71 s per loop
Memory use is also halved compared to NumPy <= 1.10, at least for
n_samples >> n_features. NumPy 1.11 will have a more memory-efficient
cov implementation.
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tests are failing... otherwise looks like a good idea. |
16 tasks
| This function is faster and more memory-efficient than np.cov | ||
| (at least as of NumPy 1.10; 1.11 will receive similar optimizations). | ||
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| Based on the NumPy version. |
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Dont want to be picky, but shouldnt bias and rowvar be documented?
Since numpy 1.11 is now the minimal requirement this PR becomes unnecessary. Closing. |
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This is inspired by some recent PRs over at NumPy concerning
np.covperformance.Timings with NumPy 1.8.2 and ATLAS:
Memory use is also halved compared to NumPy <= 1.10, at least for
n_samples≫n_features. NumPy 1.11 will have a more memory-efficientcovimplementation.