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-rw-r--r--doc/release/1.10.0-notes.rst8
-rw-r--r--numpy/core/src/multiarray/multiarraymodule.c10
-rw-r--r--numpy/core/tests/test_shape_base.py174
3 files changed, 98 insertions, 94 deletions
diff --git a/doc/release/1.10.0-notes.rst b/doc/release/1.10.0-notes.rst
index ed33cc9e3..d3b99cf76 100644
--- a/doc/release/1.10.0-notes.rst
+++ b/doc/release/1.10.0-notes.rst
@@ -52,6 +52,11 @@ relaxed stride checking
~~~~~~~~~~~~~~~~~~~~~~~
NPY_RELAXED_STRIDE_CHECKING is now true by default.
+Concatenation of 1d arrays along any but ``axis=0`` raises ``IndexError``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Using axis != 0 has raised a DeprecationWarning since NumPy 1.7, it now
+raises an error.
+
*np.ravel*, *np.diagonal* and *np.diag* now preserve subtypes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
There was inconsistent behavior between *x.ravel()* and *np.ravel(x)*, as
@@ -76,6 +81,9 @@ which now returns a view in all cases.
The dtype structure (PyArray_Descr) has a new member at the end to cache
its hash value. This shouldn't affect any well-written applications.
+The change to the concatenation function DeprecationWarning also affects
+PyArray_ConcatenateArrays,
+
recarray field return types
~~~~~~~~~~~~~~~~~~~~~~~~~~~
Previously the returned types for recarray fields accessed by attribute and by
diff --git a/numpy/core/src/multiarray/multiarraymodule.c b/numpy/core/src/multiarray/multiarraymodule.c
index f8656d8c3..3fe8611d4 100644
--- a/numpy/core/src/multiarray/multiarraymodule.c
+++ b/numpy/core/src/multiarray/multiarraymodule.c
@@ -347,16 +347,6 @@ PyArray_ConcatenateArrays(int narrays, PyArrayObject **arrays, int axis)
axis += ndim;
}
- if (ndim == 1 && axis != 0) {
- static const char msg[] = "axis != 0 for ndim == 1; "
- "this will raise an error in "
- "future versions of numpy";
- if (DEPRECATE(msg) < 0) {
- return NULL;
- }
- axis = 0;
- }
-
if (axis < 0 || axis >= ndim) {
PyErr_Format(PyExc_IndexError,
"axis %d out of bounds [0, %d)", orig_axis, ndim);
diff --git a/numpy/core/tests/test_shape_base.py b/numpy/core/tests/test_shape_base.py
index c387bc616..52001ff37 100644
--- a/numpy/core/tests/test_shape_base.py
+++ b/numpy/core/tests/test_shape_base.py
@@ -173,90 +173,96 @@ class TestVstack(TestCase):
assert_array_equal(res, desired)
-def test_concatenate_axis_None():
- a = np.arange(4, dtype=np.float64).reshape((2, 2))
- b = list(range(3))
- c = ['x']
- r = np.concatenate((a, a), axis=None)
- assert_equal(r.dtype, a.dtype)
- assert_equal(r.ndim, 1)
- r = np.concatenate((a, b), axis=None)
- assert_equal(r.size, a.size + len(b))
- assert_equal(r.dtype, a.dtype)
- r = np.concatenate((a, b, c), axis=None)
- d = array(['0.0', '1.0', '2.0', '3.0',
- '0', '1', '2', 'x'])
- assert_array_equal(r, d)
-
-
-def test_large_concatenate_axis_None():
- # When no axis is given, concatenate uses flattened versions.
- # This also had a bug with many arrays (see gh-5979).
- x = np.arange(1, 100)
- r = np.concatenate(x, None)
- assert_array_equal(x, r)
-
- # This should probably be deprecated:
- r = np.concatenate(x, 100) # axis is >= MAXDIMS
- assert_array_equal(x, r)
-
-
-def test_concatenate():
- # Test concatenate function
- # No arrays raise ValueError
- assert_raises(ValueError, concatenate, ())
- # Scalars cannot be concatenated
- assert_raises(ValueError, concatenate, (0,))
- assert_raises(ValueError, concatenate, (array(0),))
- # One sequence returns unmodified (but as array)
- r4 = list(range(4))
- assert_array_equal(concatenate((r4,)), r4)
- # Any sequence
- assert_array_equal(concatenate((tuple(r4),)), r4)
- assert_array_equal(concatenate((array(r4),)), r4)
- # 1D default concatenation
- r3 = list(range(3))
- assert_array_equal(concatenate((r4, r3)), r4 + r3)
- # Mixed sequence types
- assert_array_equal(concatenate((tuple(r4), r3)), r4 + r3)
- assert_array_equal(concatenate((array(r4), r3)), r4 + r3)
- # Explicit axis specification
- assert_array_equal(concatenate((r4, r3), 0), r4 + r3)
- # Including negative
- assert_array_equal(concatenate((r4, r3), -1), r4 + r3)
- # 2D
- a23 = array([[10, 11, 12], [13, 14, 15]])
- a13 = array([[0, 1, 2]])
- res = array([[10, 11, 12], [13, 14, 15], [0, 1, 2]])
- assert_array_equal(concatenate((a23, a13)), res)
- assert_array_equal(concatenate((a23, a13), 0), res)
- assert_array_equal(concatenate((a23.T, a13.T), 1), res.T)
- assert_array_equal(concatenate((a23.T, a13.T), -1), res.T)
- # Arrays much match shape
- assert_raises(ValueError, concatenate, (a23.T, a13.T), 0)
- # 3D
- res = arange(2 * 3 * 7).reshape((2, 3, 7))
- a0 = res[..., :4]
- a1 = res[..., 4:6]
- a2 = res[..., 6:]
- assert_array_equal(concatenate((a0, a1, a2), 2), res)
- assert_array_equal(concatenate((a0, a1, a2), -1), res)
- assert_array_equal(concatenate((a0.T, a1.T, a2.T), 0), res.T)
-
-
-def test_concatenate_sloppy0():
- # Versions of numpy < 1.7.0 ignored axis argument value for 1D arrays. We
- # allow this for now, but in due course we will raise an error
- r4 = list(range(4))
- r3 = list(range(3))
- assert_array_equal(concatenate((r4, r3), 0), r4 + r3)
- with warnings.catch_warnings():
- warnings.simplefilter('ignore', DeprecationWarning)
- assert_array_equal(concatenate((r4, r3), -10), r4 + r3)
- assert_array_equal(concatenate((r4, r3), 10), r4 + r3)
- # Confirm DeprecationWarning raised
- warnings.simplefilter('error', DeprecationWarning)
- assert_raises(DeprecationWarning, concatenate, (r4, r3), 10)
+class TestConcatenate(TestCase):
+ def test_exceptions(self):
+ # test axis must be in bounds
+ for ndim in [1, 2, 3]:
+ a = np.ones((1,)*ndim)
+ np.concatenate((a, a), axis=0) # OK
+ assert_raises(IndexError, np.concatenate, (a, a), axis=ndim)
+ assert_raises(IndexError, np.concatenate, (a, a), axis=-(ndim + 1))
+
+ # Scalars cannot be concatenated
+ assert_raises(ValueError, concatenate, (0,))
+ assert_raises(ValueError, concatenate, (np.array(0),))
+
+ # test shapes must match except for concatenation axis
+ a = np.ones((1, 2, 3))
+ b = np.ones((2, 2, 3))
+ axis = list(range(3))
+ for i in range(3):
+ 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)
+ axis.append(axis.pop(0))
+
+ # No arrays to concatenate raises ValueError
+ assert_raises(ValueError, concatenate, ())
+
+ def test_concatenate_axis_None(self):
+ a = np.arange(4, dtype=np.float64).reshape((2, 2))
+ b = list(range(3))
+ c = ['x']
+ r = np.concatenate((a, a), axis=None)
+ assert_equal(r.dtype, a.dtype)
+ assert_equal(r.ndim, 1)
+ r = np.concatenate((a, b), axis=None)
+ assert_equal(r.size, a.size + len(b))
+ assert_equal(r.dtype, a.dtype)
+ r = np.concatenate((a, b, c), axis=None)
+ d = array(['0.0', '1.0', '2.0', '3.0',
+ '0', '1', '2', 'x'])
+ assert_array_equal(r, d)
+
+ def test_large_concatenate_axis_None(self):
+ # When no axis is given, concatenate uses flattened versions.
+ # This also had a bug with many arrays (see gh-5979).
+ x = np.arange(1, 100)
+ r = np.concatenate(x, None)
+ assert_array_equal(x, r)
+
+ # This should probably be deprecated:
+ r = np.concatenate(x, 100) # axis is >= MAXDIMS
+ assert_array_equal(x, r)
+
+ def test_concatenate(self):
+ # Test concatenate function
+ # One sequence returns unmodified (but as array)
+ r4 = list(range(4))
+ assert_array_equal(concatenate((r4,)), r4)
+ # Any sequence
+ assert_array_equal(concatenate((tuple(r4),)), r4)
+ assert_array_equal(concatenate((array(r4),)), r4)
+ # 1D default concatenation
+ r3 = list(range(3))
+ assert_array_equal(concatenate((r4, r3)), r4 + r3)
+ # Mixed sequence types
+ assert_array_equal(concatenate((tuple(r4), r3)), r4 + r3)
+ assert_array_equal(concatenate((array(r4), r3)), r4 + r3)
+ # Explicit axis specification
+ assert_array_equal(concatenate((r4, r3), 0), r4 + r3)
+ # Including negative
+ assert_array_equal(concatenate((r4, r3), -1), r4 + r3)
+ # 2D
+ a23 = array([[10, 11, 12], [13, 14, 15]])
+ a13 = array([[0, 1, 2]])
+ res = array([[10, 11, 12], [13, 14, 15], [0, 1, 2]])
+ assert_array_equal(concatenate((a23, a13)), res)
+ assert_array_equal(concatenate((a23, a13), 0), res)
+ assert_array_equal(concatenate((a23.T, a13.T), 1), res.T)
+ assert_array_equal(concatenate((a23.T, a13.T), -1), res.T)
+ # Arrays much match shape
+ assert_raises(ValueError, concatenate, (a23.T, a13.T), 0)
+ # 3D
+ res = arange(2 * 3 * 7).reshape((2, 3, 7))
+ a0 = res[..., :4]
+ a1 = res[..., 4:6]
+ a2 = res[..., 6:]
+ assert_array_equal(concatenate((a0, a1, a2), 2), res)
+ assert_array_equal(concatenate((a0, a1, a2), -1), res)
+ assert_array_equal(concatenate((a0.T, a1.T, a2.T), 0), res.T)
def test_stack():
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