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| author | Eric Wieser <wieser.eric@gmail.com> | 2018-04-08 14:30:21 -0700 |
|---|---|---|
| committer | Eric Wieser <wieser.eric@gmail.com> | 2018-04-08 15:01:27 -0700 |
| commit | f4df81f8dcd5c7361a273b7c6cf294a9e8c0841c (patch) | |
| tree | 5cea10c30c415d40d70736f562c825adce25377b /numpy/lib/histograms.py | |
| parent | dbaca82d6d8c63f4d48ec08ae07e45e5b7bc2000 (diff) | |
| download | numpy-f4df81f8dcd5c7361a273b7c6cf294a9e8c0841c.tar.gz | |
MAINT: Don't use a dict with numeric keys when a tuple would do fine
Diffstat (limited to 'numpy/lib/histograms.py')
| -rw-r--r-- | numpy/lib/histograms.py | 7 |
1 files changed, 4 insertions, 3 deletions
diff --git a/numpy/lib/histograms.py b/numpy/lib/histograms.py index 49f741dd4..f402a02c1 100644 --- a/numpy/lib/histograms.py +++ b/numpy/lib/histograms.py @@ -899,9 +899,10 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): return np.zeros(nbin-2), edges # Compute the bin number each sample falls into. - Ncount = {} - for i in np.arange(D): - Ncount[i] = np.digitize(sample[:, i], edges[i]) + Ncount = tuple( + np.digitize(sample[:, i], edges[i]) + for i in np.arange(D) + ) # Using digitize, values that fall on an edge are put in the right bin. # For the rightmost bin, we want values equal to the right edge to be |