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| author | Bastian Eichenberger <45177685+BBQuercus@users.noreply.github.com> | 2019-07-13 13:58:46 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2019-07-13 13:58:46 +0200 |
| commit | de9ab5fc1f360afe94d8a2cce5a5e58addfc0bb2 (patch) | |
| tree | 8640a60d0c9bec5817932c3b8e4f6d1877987ff6 /numpy/doc/broadcasting.py | |
| parent | 4f7d5eb13394ec2b13fe9e22855fa009579cb49b (diff) | |
| download | numpy-de9ab5fc1f360afe94d8a2cce5a5e58addfc0bb2.tar.gz | |
Spellcheck @numpy/doc/broadcasting.py
Diffstat (limited to 'numpy/doc/broadcasting.py')
| -rw-r--r-- | numpy/doc/broadcasting.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/numpy/doc/broadcasting.py b/numpy/doc/broadcasting.py index 0bdb6ae7d..f7bd2515b 100644 --- a/numpy/doc/broadcasting.py +++ b/numpy/doc/broadcasting.py @@ -42,7 +42,7 @@ We can think of the scalar ``b`` being *stretched* during the arithmetic operation into an array with the same shape as ``a``. The new elements in ``b`` are simply copies of the original scalar. The stretching analogy is only conceptual. NumPy is smart enough to use the original scalar value -without actually making copies, so that broadcasting operations are as +without actually making copies so that broadcasting operations are as memory and computationally efficient as possible. The code in the second example is more efficient than that in the first @@ -52,7 +52,7 @@ because broadcasting moves less memory around during the multiplication General Broadcasting Rules ========================== When operating on two arrays, NumPy compares their shapes element-wise. -It starts with the trailing dimensions, and works its way forward. Two +It starts with the trailing dimensions and works its way forward. Two dimensions are compatible when 1) they are equal, or |