numpy · eric-wieser · Aug 11, 2017 · Jul 27, 2017 · Jul 27, 2017 · Jul 27, 2017
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
@@ -1436,6 +1436,10 @@ 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
@@ -1618,7 +1622,7 @@ 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):
@@ -1743,8 +1747,8 @@ 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):
@@ -1815,8 +1819,7 @@ 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
@@ -208,8 +208,8 @@ def test_exceptions(self):
             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
@@ -4328,7 +4328,7 @@ 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
@@ -4361,9 +4361,9 @@ 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
@@ -4375,8 +4375,8 @@ 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)
@@ -5032,7 +5032,7 @@ 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
@@ -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
@@ -2958,7 +2958,7 @@ def test_extended_axis(self):
         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))
@@ -3339,7 +3339,7 @@ def test_extended_axis(self):
         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
@@ -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
@@ -22,7 +22,7 @@
     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
@@ -942,7 +942,7 @@ 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
@@ -958,7 +958,7 @@ 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
 
 
@@ -1067,7 +1067,7 @@ 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)
@@ -1086,7 +1086,7 @@ 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
 
 
@@ -1458,7 +1458,7 @@ 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
@@ -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 
10000
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
@@ -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
@@ -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
@@ -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):