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| author | Eric Wieser <wieser.eric@gmail.com> | 2018-04-08 14:22:50 -0700 |
|---|---|---|
| committer | Eric Wieser <wieser.eric@gmail.com> | 2018-04-08 15:01:27 -0700 |
| commit | b3a2b026652f62ae998014544547721340ffb435 (patch) | |
| tree | 60e3b3185fb5d1800333d8ce6b4ddefd540c15f4 /numpy/lib | |
| parent | f4df81f8dcd5c7361a273b7c6cf294a9e8c0841c (diff) | |
| download | numpy-b3a2b026652f62ae998014544547721340ffb435.tar.gz | |
MAINT: Don't reimplement `ravel_multi_index`
Diffstat (limited to 'numpy/lib')
| -rw-r--r-- | numpy/lib/histograms.py | 5 |
1 files changed, 2 insertions, 3 deletions
diff --git a/numpy/lib/histograms.py b/numpy/lib/histograms.py index f402a02c1..f0796fbac 100644 --- a/numpy/lib/histograms.py +++ b/numpy/lib/histograms.py @@ -925,9 +925,8 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): hist = np.zeros(nbin, float).reshape(-1) # Compute the sample indices in the flattened histogram matrix. - xy = np.zeros(N, np.intp) - for i in np.arange(0, D): - xy += Ncount[i] * nbin[i+1:].prod() + # This raises an error if the array is too large. + xy = np.ravel_multi_index(Ncount, nbin) # Compute the number of repetitions in xy and assign it to the # flattened histmat. |