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-rw-r--r--numpy/core/numeric.py13
-rw-r--r--numpy/core/tests/test_shape_base.py4
-rw-r--r--numpy/lib/function_base.py14
-rw-r--r--numpy/lib/nanfunctions.py2
-rw-r--r--numpy/lib/tests/test_function_base.py4
-rw-r--r--numpy/lib/utils.py2
-rw-r--r--numpy/linalg/linalg.py6
-rw-r--r--numpy/polynomial/chebyshev.py10
-rw-r--r--numpy/polynomial/hermite.py10
-rw-r--r--numpy/polynomial/hermite_e.py10
-rw-r--r--numpy/polynomial/laguerre.py10
-rw-r--r--numpy/polynomial/legendre.py10
-rw-r--r--numpy/polynomial/polynomial.py10
13 files changed, 53 insertions, 52 deletions
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
index 7d53f2b68..e9bb39ad4 100644
--- a/numpy/core/numeric.py
+++ b/numpy/core/numeric.py
@@ -1435,6 +1435,10 @@ def rollaxis(a, axis, start=0):
"""
Roll the specified axis backwards, until it lies in a given position.
+ This function continues to be supported for backward compatibility, but you
+ should prefer `moveaxis`. The `moveaxis` function was added in NumPy
+ 1.11.
+
Parameters
----------
a : ndarray
@@ -1617,7 +1621,7 @@ def moveaxis(a, source, destination):
# fix hack in scipy which imports this function
def _move_axis_to_0(a, axis):
- return rollaxis(a, axis, 0)
+ return moveaxis(a, axis, 0)
def cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None):
@@ -1742,8 +1746,8 @@ def cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None):
axisb = normalize_axis_index(axisb, b.ndim, msg_prefix='axisb')
# Move working axis to the end of the shape
- a = rollaxis(a, axisa, a.ndim)
- b = rollaxis(b, axisb, b.ndim)
+ a = moveaxis(a, axisa, -1)
+ b = moveaxis(b, axisb, -1)
msg = ("incompatible dimensions for cross product\n"
"(dimension must be 2 or 3)")
if a.shape[-1] not in (2, 3) or b.shape[-1] not in (2, 3):
@@ -1814,8 +1818,7 @@ def cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None):
multiply(a0, b1, out=cp2)
cp2 -= a1 * b0
- # This works because we are moving the last axis
- return rollaxis(cp, -1, axisc)
+ return moveaxis(cp, -1, axisc)
# Use numarray's printing function
diff --git a/numpy/core/tests/test_shape_base.py b/numpy/core/tests/test_shape_base.py
index 9913af67a..d1fbe8e92 100644
--- a/numpy/core/tests/test_shape_base.py
+++ b/numpy/core/tests/test_shape_base.py
@@ -208,8 +208,8 @@ class TestConcatenate(object):
np.concatenate((a, b), axis=axis[0]) # OK
assert_raises(ValueError, np.concatenate, (a, b), axis=axis[1])
assert_raises(ValueError, np.concatenate, (a, b), axis=axis[2])
- a = np.rollaxis(a, -1)
- b = np.rollaxis(b, -1)
+ a = np.moveaxis(a, -1, 0)
+ b = np.moveaxis(b, -1, 0)
axis.append(axis.pop(0))
# No arrays to concatenate raises ValueError
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)
diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py
index 90120719e..79bf01281 100644
--- a/numpy/lib/nanfunctions.py
+++ b/numpy/lib/nanfunctions.py
@@ -1174,7 +1174,7 @@ def _nanpercentile(a, q, axis=None, out=None, overwrite_input=False,
# Move that axis to the beginning to match percentile's
# convention.
if q.ndim != 0:
- result = np.rollaxis(result, axis)
+ result = np.moveaxis(result, axis, 0)
if out is not None:
out[...] = result
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index 151c20a4b..4c90abbf6 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -3011,7 +3011,7 @@ class TestPercentile(object):
o = np.random.normal(size=(71, 23))
x = np.dstack([o] * 10)
assert_equal(np.percentile(x, 30, axis=(0, 1)), np.percentile(o, 30))
- x = np.rollaxis(x, -1, 0)
+ x = np.moveaxis(x, -1, 0)
assert_equal(np.percentile(x, 30, axis=(-2, -1)), np.percentile(o, 30))
x = x.swapaxes(0, 1).copy()
assert_equal(np.percentile(x, 30, axis=(0, -1)), np.percentile(o, 30))
@@ -3392,7 +3392,7 @@ class TestMedian(object):
o = np.random.normal(size=(71, 23))
x = np.dstack([o] * 10)
assert_equal(np.median(x, axis=(0, 1)), np.median(o))
- x = np.rollaxis(x, -1, 0)
+ x = np.moveaxis(x, -1, 0)
assert_equal(np.median(x, axis=(-2, -1)), np.median(o))
x = x.swapaxes(0, 1).copy()
assert_equal(np.median(x, axis=(0, -1)), np.median(o))
diff --git a/numpy/lib/utils.py b/numpy/lib/utils.py
index 6e150add3..e18eda0fb 100644
--- a/numpy/lib/utils.py
+++ b/numpy/lib/utils.py
@@ -1138,7 +1138,7 @@ def _median_nancheck(data, result, axis, out):
"""
if data.size == 0:
return result
- data = np.rollaxis(data, axis, data.ndim)
+ data = np.moveaxis(data, axis, -1)
n = np.isnan(data[..., -1])
# masked NaN values are ok
if np.ma.isMaskedArray(n):
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py
index cd8999785..dd5ac6255 100644
--- a/numpy/linalg/linalg.py
+++ b/numpy/linalg/linalg.py
@@ -22,7 +22,7 @@ from numpy.core import (
array, asarray, zeros, empty, empty_like, transpose, intc, single, double,
csingle, cdouble, inexact, complexfloating, newaxis, ravel, all, Inf, dot,
add, multiply, sqrt, maximum, fastCopyAndTranspose, sum, isfinite, size,
- finfo, errstate, geterrobj, longdouble, rollaxis, amin, amax, product, abs,
+ finfo, errstate, geterrobj, longdouble, moveaxis, amin, amax, product, abs,
broadcast, atleast_2d, intp, asanyarray, isscalar, object_, ones
)
from numpy.core.multiarray import normalize_axis_index
@@ -2004,9 +2004,7 @@ def _multi_svd_norm(x, row_axis, col_axis, op):
is `numpy.amin` or `numpy.amax` or `numpy.sum`.
"""
- if row_axis > col_axis:
- row_axis -= 1
- y = rollaxis(rollaxis(x, col_axis, x.ndim), row_axis, -1)
+ y = moveaxis(x, (row_axis, col_axis), (-2, -1))
result = op(svd(y, compute_uv=0), axis=-1)
return result
diff --git a/numpy/polynomial/chebyshev.py b/numpy/polynomial/chebyshev.py
index b28ea0462..eb9797e0f 100644
--- a/numpy/polynomial/chebyshev.py
+++ b/numpy/polynomial/chebyshev.py
@@ -944,7 +944,7 @@ def chebder(c, m=1, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
n = len(c)
if cnt >= n:
c = c[:1]*0
@@ -960,7 +960,7 @@ def chebder(c, m=1, scl=1, axis=0):
der[1] = 4*c[2]
der[0] = c[1]
c = der
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -1069,7 +1069,7 @@ def chebint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
k = list(k) + [0]*(cnt - len(k))
for i in range(cnt):
n = len(c)
@@ -1088,7 +1088,7 @@ def chebint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
tmp[j - 1] -= c[j]/(2*(j - 1))
tmp[0] += k[i] - chebval(lbnd, tmp)
c = tmp
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -1460,7 +1460,7 @@ def chebvander(x, deg):
v[1] = x
for i in range(2, ideg + 1):
v[i] = v[i-1]*x2 - v[i-2]
- return np.rollaxis(v, 0, v.ndim)
+ return np.moveaxis(v, 0, -1)
def chebvander2d(x, y, deg):
diff --git a/numpy/polynomial/hermite.py b/numpy/polynomial/hermite.py
index ccf0fc146..856ac487e 100644
--- a/numpy/polynomial/hermite.py
+++ b/numpy/polynomial/hermite.py
@@ -706,7 +706,7 @@ def hermder(c, m=1, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
n = len(c)
if cnt >= n:
c = c[:1]*0
@@ -718,7 +718,7 @@ def hermder(c, m=1, scl=1, axis=0):
for j in range(n, 0, -1):
der[j - 1] = (2*j)*c[j]
c = der
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -825,7 +825,7 @@ def hermint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
k = list(k) + [0]*(cnt - len(k))
for i in range(cnt):
n = len(c)
@@ -840,7 +840,7 @@ def hermint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
tmp[j + 1] = c[j]/(2*(j + 1))
tmp[0] += k[i] - hermval(lbnd, tmp)
c = tmp
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -1229,7 +1229,7 @@ def hermvander(x, deg):
v[1] = x2
for i in range(2, ideg + 1):
v[i] = (v[i-1]*x2 - v[i-2]*(2*(i - 1)))
- return np.rollaxis(v, 0, v.ndim)
+ return np.moveaxis(v, 0, -1)
def hermvander2d(x, y, deg):
diff --git a/numpy/polynomial/hermite_e.py b/numpy/polynomial/hermite_e.py
index 2fafea4af..e83b26327 100644
--- a/numpy/polynomial/hermite_e.py
+++ b/numpy/polynomial/hermite_e.py
@@ -705,7 +705,7 @@ def hermeder(c, m=1, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
n = len(c)
if cnt >= n:
return c[:1]*0
@@ -717,7 +717,7 @@ def hermeder(c, m=1, scl=1, axis=0):
for j in range(n, 0, -1):
der[j - 1] = j*c[j]
c = der
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -824,7 +824,7 @@ def hermeint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
k = list(k) + [0]*(cnt - len(k))
for i in range(cnt):
n = len(c)
@@ -839,7 +839,7 @@ def hermeint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
tmp[j + 1] = c[j]/(j + 1)
tmp[0] += k[i] - hermeval(lbnd, tmp)
c = tmp
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -1226,7 +1226,7 @@ def hermevander(x, deg):
v[1] = x
for i in range(2, ideg + 1):
v[i] = (v[i-1]*x - v[i-2]*(i - 1))
- return np.rollaxis(v, 0, v.ndim)
+ return np.moveaxis(v, 0, -1)
def hermevander2d(x, y, deg):
diff --git a/numpy/polynomial/laguerre.py b/numpy/polynomial/laguerre.py
index 387d986fa..60373b8c8 100644
--- a/numpy/polynomial/laguerre.py
+++ b/numpy/polynomial/laguerre.py
@@ -703,7 +703,7 @@ def lagder(c, m=1, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
n = len(c)
if cnt >= n:
c = c[:1]*0
@@ -717,7 +717,7 @@ def lagder(c, m=1, scl=1, axis=0):
c[j - 1] += c[j]
der[0] = -c[1]
c = der
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -825,7 +825,7 @@ def lagint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
k = list(k) + [0]*(cnt - len(k))
for i in range(cnt):
n = len(c)
@@ -841,7 +841,7 @@ def lagint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
tmp[j + 1] = -c[j]
tmp[0] += k[i] - lagval(lbnd, tmp)
c = tmp
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -1228,7 +1228,7 @@ def lagvander(x, deg):
v[1] = 1 - x
for i in range(2, ideg + 1):
v[i] = (v[i-1]*(2*i - 1 - x) - v[i-2]*(i - 1))/i
- return np.rollaxis(v, 0, v.ndim)
+ return np.moveaxis(v, 0, -1)
def lagvander2d(x, y, deg):
diff --git a/numpy/polynomial/legendre.py b/numpy/polynomial/legendre.py
index d4b4dd130..5128643cd 100644
--- a/numpy/polynomial/legendre.py
+++ b/numpy/polynomial/legendre.py
@@ -742,7 +742,7 @@ def legder(c, m=1, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
n = len(c)
if cnt >= n:
c = c[:1]*0
@@ -758,7 +758,7 @@ def legder(c, m=1, scl=1, axis=0):
der[1] = 3*c[2]
der[0] = c[1]
c = der
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -867,7 +867,7 @@ def legint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
k = list(k) + [0]*(cnt - len(k))
for i in range(cnt):
n = len(c)
@@ -886,7 +886,7 @@ def legint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
tmp[j - 1] -= t
tmp[0] += k[i] - legval(lbnd, tmp)
c = tmp
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -1259,7 +1259,7 @@ def legvander(x, deg):
v[1] = x
for i in range(2, ideg + 1):
v[i] = (v[i-1]*x*(2*i - 1) - v[i-2]*(i - 1))/i
- return np.rollaxis(v, 0, v.ndim)
+ return np.moveaxis(v, 0, -1)
def legvander2d(x, y, deg):
diff --git a/numpy/polynomial/polynomial.py b/numpy/polynomial/polynomial.py
index 4b343bf7d..1528de342 100644
--- a/numpy/polynomial/polynomial.py
+++ b/numpy/polynomial/polynomial.py
@@ -546,7 +546,7 @@ def polyder(c, m=1, scl=1, axis=0):
if cnt == 0:
return c
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
n = len(c)
if cnt >= n:
c = c[:1]*0
@@ -558,7 +558,7 @@ def polyder(c, m=1, scl=1, axis=0):
for j in range(n, 0, -1):
der[j - 1] = j*c[j]
c = der
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -662,7 +662,7 @@ def polyint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
return c
k = list(k) + [0]*(cnt - len(k))
- c = np.rollaxis(c, iaxis)
+ c = np.moveaxis(c, iaxis, 0)
for i in range(cnt):
n = len(c)
c *= scl
@@ -676,7 +676,7 @@ def polyint(c, m=1, k=[], lbnd=0, scl=1, axis=0):
tmp[j + 1] = c[j]/(j + 1)
tmp[0] += k[i] - polyval(lbnd, tmp)
c = tmp
- c = np.rollaxis(c, 0, iaxis + 1)
+ c = np.moveaxis(c, 0, iaxis)
return c
@@ -1147,7 +1147,7 @@ def polyvander(x, deg):
v[1] = x
for i in range(2, ideg + 1):
v[i] = v[i-1]*x
- return np.rollaxis(v, 0, v.ndim)
+ return np.moveaxis(v, 0, -1)
def polyvander2d(x, y, deg):
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