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| author | Nico Schlömer <nico.schloemer@gmail.com> | 2017-08-11 03:01:06 +0200 |
|---|---|---|
| committer | Eric Wieser <wieser.eric@gmail.com> | 2017-08-10 20:01:06 -0500 |
| commit | 029863eae86b9df2de4b9a9843ca8f88c99130df (patch) | |
| tree | ced3f88544979e2dc6f7eb327963c5d2688374ef /numpy/lib/function_base.py | |
| parent | 4c18530b1e3e428a3755c6847f70322ec12bdbc2 (diff) | |
| download | numpy-029863eae86b9df2de4b9a9843ca8f88c99130df.tar.gz | |
MAINT: Use moveaxis instead of rollaxis internally (#9475)
Also add a hint to the documentation advising the use of moveaxis over rollaxis.
Tests for rollaxis are left alone.
Diffstat (limited to 'numpy/lib/function_base.py')
| -rw-r--r-- | numpy/lib/function_base.py | 14 |
1 files changed, 7 insertions, 7 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index c185f9639..b1ebcad67 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -4336,7 +4336,7 @@ def _percentile(a, q, axis=None, out=None, ap.partition(indices, axis=axis) # ensure axis with qth is first - ap = np.rollaxis(ap, axis, 0) + ap = np.moveaxis(ap, axis, 0) axis = 0 # Check if the array contains any nan's @@ -4369,9 +4369,9 @@ def _percentile(a, q, axis=None, out=None, ap.partition(concatenate((indices_below, indices_above)), axis=axis) # ensure axis with qth is first - ap = np.rollaxis(ap, axis, 0) - weights_below = np.rollaxis(weights_below, axis, 0) - weights_above = np.rollaxis(weights_above, axis, 0) + ap = np.moveaxis(ap, axis, 0) + weights_below = np.moveaxis(weights_below, axis, 0) + weights_above = np.moveaxis(weights_above, axis, 0) axis = 0 # Check if the array contains any nan's @@ -4383,8 +4383,8 @@ def _percentile(a, q, axis=None, out=None, x2 = take(ap, indices_above, axis=axis) * weights_above # ensure axis with qth is first - x1 = np.rollaxis(x1, axis, 0) - x2 = np.rollaxis(x2, axis, 0) + x1 = np.moveaxis(x1, axis, 0) + x2 = np.moveaxis(x2, axis, 0) if zerod: x1 = x1.squeeze(0) @@ -5040,7 +5040,7 @@ def insert(arr, obj, values, axis=None): # broadcasting is very different here, since a[:,0,:] = ... behaves # very different from a[:,[0],:] = ...! This changes values so that # it works likes the second case. (here a[:,0:1,:]) - values = np.rollaxis(values, 0, (axis % values.ndim) + 1) + values = np.moveaxis(values, 0, axis) numnew = values.shape[axis] newshape[axis] += numnew new = empty(newshape, arr.dtype, arrorder) |