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authormdubravski <41096057+mdubravski@users.noreply.github.com>2021-02-14 09:12:28 -0500
committerGitHub <noreply@github.com>2021-02-14 09:12:28 -0500
commitb15bd82a7b50e721125b54f8cc11a0850ce10a21 (patch)
tree4fd2694ba4418b8b30a3a360a5d180694fa79223
parent39acd8da404ff278a5bb1cfa97dadb9b7a813979 (diff)
downloadnumpy-b15bd82a7b50e721125b54f8cc11a0850ce10a21.tar.gz
Update numpy/core/numeric.py
Co-authored-by: Matti Picus <matti.picus@gmail.com>
-rw-r--r--numpy/core/numeric.py4
1 files changed, 3 insertions, 1 deletions
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
index 0e0bacbe7..7675386e7 100644
--- a/numpy/core/numeric.py
+++ b/numpy/core/numeric.py
@@ -721,7 +721,9 @@ def correlate(a, v, mode='valid'):
which is related to ``c_{av}[k]`` by ``c'_{av}[k] = c_{av}[-k]``.
- `numpy.correlate` may perform slowly in large arrays (i.e. n = 1e5) because it does not use the FFT to compute the convolution; in that case, `scipy.signal.correlate` might be considered.
+ `numpy.correlate` may perform slowly in large arrays (i.e. n = 1e5) because it does
+ not use the FFT to compute the convolution; in that case, `scipy.signal.correlate` might
+ be preferable.
Examples