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-rw-r--r--numpy/core/_add_newdocs.py56
-rw-r--r--numpy/core/_internal.py49
-rw-r--r--numpy/core/records.py4
-rw-r--r--numpy/core/src/multiarray/buffer.c54
-rw-r--r--numpy/core/src/multiarray/ctors.c8
-rw-r--r--numpy/core/tests/test_datetime.py5
-rw-r--r--numpy/core/tests/test_einsum.py1
-rw-r--r--numpy/core/tests/test_indexing.py1
-rw-r--r--numpy/core/tests/test_multiarray.py127
-rw-r--r--numpy/core/tests/test_nditer.py1
-rw-r--r--numpy/core/tests/test_numeric.py1
-rw-r--r--numpy/core/tests/test_regression.py1
-rw-r--r--numpy/core/tests/test_scalarbuffer.py27
-rw-r--r--numpy/core/tests/test_umath.py1
-rw-r--r--numpy/lib/arraysetops.py24
-rw-r--r--numpy/lib/histograms.py32
-rw-r--r--numpy/lib/nanfunctions.py16
-rw-r--r--numpy/lib/stride_tricks.py2
-rw-r--r--numpy/lib/tests/test__datasource.py4
-rw-r--r--numpy/lib/tests/test_arraysetops.py25
-rw-r--r--numpy/lib/tests/test_histograms.py14
-rw-r--r--numpy/lib/tests/test_index_tricks.py1
-rw-r--r--numpy/lib/tests/test_io.py2
-rw-r--r--numpy/lib/tests/test_stride_tricks.py14
-rw-r--r--numpy/linalg/tests/test_linalg.py2
-rw-r--r--numpy/ma/tests/test_core.py14
-rw-r--r--numpy/random/tests/test_random.py1
-rw-r--r--numpy/testing/_private/nosetester.py20
-rw-r--r--numpy/testing/_private/utils.py21
-rw-r--r--numpy/testing/tests/test_decorators.py1
-rw-r--r--numpy/testing/tests/test_utils.py2
31 files changed, 345 insertions, 186 deletions
diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py
index b65920fde..9ebd12cbd 100644
--- a/numpy/core/_add_newdocs.py
+++ b/numpy/core/_add_newdocs.py
@@ -1454,11 +1454,10 @@ add_newdoc('numpy.core.multiarray', 'arange',
Values are generated within the half-open interval ``[start, stop)``
(in other words, the interval including `start` but excluding `stop`).
For integer arguments the function is equivalent to the Python built-in
- `range <https://docs.python.org/library/functions.html#func-range>`_ function,
- but returns an ndarray rather than a list.
+ `range` function, but returns an ndarray rather than a list.
When using a non-integer step, such as 0.1, the results will often not
- be consistent. It is better to use ``linspace`` for these cases.
+ be consistent. It is better to use `numpy.linspace` for these cases.
Parameters
----------
@@ -2843,40 +2842,19 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('ctypes',
-----
Below are the public attributes of this object which were documented
in "Guide to NumPy" (we have omitted undocumented public attributes,
- as well as documented private attributes):
-
- * data: A pointer to the memory area of the array as a Python integer.
- This memory area may contain data that is not aligned, or not in correct
- byte-order. The memory area may not even be writeable. The array
- flags and data-type of this array should be respected when passing this
- attribute to arbitrary C-code to avoid trouble that can include Python
- crashing. User Beware! The value of this attribute is exactly the same
- as self._array_interface_['data'][0].
-
- * shape (c_intp*self.ndim): A ctypes array of length self.ndim where
- the basetype is the C-integer corresponding to dtype('p') on this
- platform. This base-type could be c_int, c_long, or c_longlong
- depending on the platform. The c_intp type is defined accordingly in
- numpy.ctypeslib. The ctypes array contains the shape of the underlying
- array.
-
- * strides (c_intp*self.ndim): A ctypes array of length self.ndim where
- the basetype is the same as for the shape attribute. This ctypes array
- contains the strides information from the underlying array. This strides
- information is important for showing how many bytes must be jumped to
- get to the next element in the array.
-
- * data_as(obj): Return the data pointer cast to a particular c-types object.
- For example, calling self._as_parameter_ is equivalent to
- self.data_as(ctypes.c_void_p). Perhaps you want to use the data as a
- pointer to a ctypes array of floating-point data:
- self.data_as(ctypes.POINTER(ctypes.c_double)).
-
- * shape_as(obj): Return the shape tuple as an array of some other c-types
- type. For example: self.shape_as(ctypes.c_short).
-
- * strides_as(obj): Return the strides tuple as an array of some other
- c-types type. For example: self.strides_as(ctypes.c_longlong).
+ as well as documented private attributes):
+
+ .. autoattribute:: numpy.core._internal._ctypes.data
+
+ .. autoattribute:: numpy.core._internal._ctypes.shape
+
+ .. autoattribute:: numpy.core._internal._ctypes.strides
+
+ .. automethod:: numpy.core._internal._ctypes.data_as
+
+ .. automethod:: numpy.core._internal._ctypes.shape_as
+
+ .. automethod:: numpy.core._internal._ctypes.strides_as
Be careful using the ctypes attribute - especially on temporary
arrays or arrays constructed on the fly. For example, calling
@@ -7158,10 +7136,10 @@ add_newdoc('numpy.core.multiarray', 'datetime_data',
array(250, dtype='timedelta64[s]')
The result can be used to construct a datetime that uses the same units
- as a timedelta::
+ as a timedelta
>>> np.datetime64('2010', np.datetime_data(dt_25s))
- numpy.datetime64('2010-01-01T00:00:00','25s')
+ numpy.datetime64('2010-01-01T00:00:00', '25s')
""")
diff --git a/numpy/core/_internal.py b/numpy/core/_internal.py
index 1cf89aab0..48ede14d0 100644
--- a/numpy/core/_internal.py
+++ b/numpy/core/_internal.py
@@ -9,7 +9,7 @@ from __future__ import division, absolute_import, print_function
import re
import sys
-from numpy.compat import basestring
+from numpy.compat import basestring, unicode
from .multiarray import dtype, array, ndarray
try:
import ctypes
@@ -257,33 +257,72 @@ class _ctypes(object):
self._zerod = False
def data_as(self, obj):
+ """
+ Return the data pointer cast to a particular c-types object.
+ For example, calling ``self._as_parameter_`` is equivalent to
+ ``self.data_as(ctypes.c_void_p)``. Perhaps you want to use the data as a
+ pointer to a ctypes array of floating-point data:
+ ``self.data_as(ctypes.POINTER(ctypes.c_double))``.
+ """
return self._ctypes.cast(self._data, obj)
def shape_as(self, obj):
+ """
+ Return the shape tuple as an array of some other c-types
+ type. For example: ``self.shape_as(ctypes.c_short)``.
+ """
if self._zerod:
return None
return (obj*self._arr.ndim)(*self._arr.shape)
def strides_as(self, obj):
+ """
+ Return the strides tuple as an array of some other
+ c-types type. For example: ``self.strides_as(ctypes.c_longlong)``.
+ """
if self._zerod:
return None
return (obj*self._arr.ndim)(*self._arr.strides)
def get_data(self):
+ """
+ A pointer to the memory area of the array as a Python integer.
+ This memory area may contain data that is not aligned, or not in correct
+ byte-order. The memory area may not even be writeable. The array
+ flags and data-type of this array should be respected when passing this
+ attribute to arbitrary C-code to avoid trouble that can include Python
+ crashing. User Beware! The value of this attribute is exactly the same
+ as ``self._array_interface_['data'][0]``.
+ """
return self._data
def get_shape(self):
+ """
+ (c_intp*self.ndim): A ctypes array of length self.ndim where
+ the basetype is the C-integer corresponding to ``dtype('p')`` on this
+ platform. This base-type could be `ctypes.c_int`, `ctypes.c_long`, or
+ `ctypes.c_longlong` depending on the platform.
+ The c_intp type is defined accordingly in `numpy.ctypeslib`.
+ The ctypes array contains the shape of the underlying array.
+ """
return self.shape_as(_getintp_ctype())
def get_strides(self):
+ """
+ (c_intp*self.ndim): A ctypes array of length self.ndim where
+ the basetype is the same as for the shape attribute. This ctypes array
+ contains the strides information from the underlying array. This strides
+ information is important for showing how many bytes must be jumped to
+ get to the next element in the array.
+ """
return self.strides_as(_getintp_ctype())
def get_as_parameter(self):
return self._ctypes.c_void_p(self._data)
- data = property(get_data, None, doc="c-types data")
- shape = property(get_shape, None, doc="c-types shape")
- strides = property(get_strides, None, doc="c-types strides")
+ data = property(get_data)
+ shape = property(get_shape)
+ strides = property(get_strides)
_as_parameter_ = property(get_as_parameter, None, doc="_as parameter_")
@@ -294,7 +333,7 @@ def _newnames(datatype, order):
"""
oldnames = datatype.names
nameslist = list(oldnames)
- if isinstance(order, str):
+ if isinstance(order, (str, unicode)):
order = [order]
seen = set()
if isinstance(order, (list, tuple)):
diff --git a/numpy/core/records.py b/numpy/core/records.py
index 612d39322..a483871ba 100644
--- a/numpy/core/records.py
+++ b/numpy/core/records.py
@@ -42,7 +42,7 @@ import warnings
from . import numeric as sb
from . import numerictypes as nt
-from numpy.compat import isfileobj, bytes, long
+from numpy.compat import isfileobj, bytes, long, unicode
from .arrayprint import get_printoptions
# All of the functions allow formats to be a dtype
@@ -174,7 +174,7 @@ class format_parser(object):
if (names):
if (type(names) in [list, tuple]):
pass
- elif isinstance(names, str):
+ elif isinstance(names, (str, unicode)):
names = names.split(',')
else:
raise NameError("illegal input names %s" % repr(names))
diff --git a/numpy/core/src/multiarray/buffer.c b/numpy/core/src/multiarray/buffer.c
index 0325f3c6a..c8e3da8bc 100644
--- a/numpy/core/src/multiarray/buffer.c
+++ b/numpy/core/src/multiarray/buffer.c
@@ -175,6 +175,14 @@ _is_natively_aligned_at(PyArray_Descr *descr,
return 1;
}
+/*
+ * Fill in str with an appropriate PEP 3118 format string, based on
+ * descr. For structured dtypes, calls itself recursively. Each call extends
+ * str at offset then updates offset, and uses descr->byteorder, (and
+ * possibly the byte order in obj) to determine the byte-order char.
+ *
+ * Returns 0 for success, -1 for failure
+ */
static int
_buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str,
PyObject* obj, Py_ssize_t *offset,
@@ -195,8 +203,8 @@ _buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str,
PyObject *item, *subarray_tuple;
Py_ssize_t total_count = 1;
Py_ssize_t dim_size;
+ Py_ssize_t old_offset;
char buf[128];
- int old_offset;
int ret;
if (PyTuple_Check(descr->subarray->shape)) {
@@ -230,15 +238,15 @@ _buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str,
return ret;
}
else if (PyDataType_HASFIELDS(descr)) {
- int base_offset = *offset;
+ Py_ssize_t base_offset = *offset;
_append_str(str, "T{");
for (k = 0; k < PyTuple_GET_SIZE(descr->names); ++k) {
PyObject *name, *item, *offset_obj, *tmp;
PyArray_Descr *child;
char *p;
- Py_ssize_t len;
- int new_offset;
+ Py_ssize_t len, new_offset;
+ int ret;
name = PyTuple_GET_ITEM(descr->names, k);
item = PyDict_GetItem(descr->fields, name);
@@ -266,8 +274,11 @@ _buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str,
}
/* Insert child item */
- _buffer_format_string(child, str, obj, offset,
+ ret = _buffer_format_string(child, str, obj, offset,
active_byteorder);
+ if (ret < 0) {
+ return -1;
+ }
/* Insert field name */
#if defined(NPY_PY3K)
@@ -393,8 +404,8 @@ _buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str,
case NPY_CFLOAT: if (_append_str(str, "Zf")) return -1; break;
case NPY_CDOUBLE: if (_append_str(str, "Zd")) return -1; break;
case NPY_CLONGDOUBLE: if (_append_str(str, "Zg")) return -1; break;
- /* XXX: datetime */
- /* XXX: timedelta */
+ /* XXX NPY_DATETIME */
+ /* XXX NPY_TIMEDELTA */
case NPY_OBJECT: if (_append_char(str, 'O')) return -1; break;
case NPY_STRING: {
char buf[128];
@@ -472,7 +483,29 @@ _buffer_info_new(PyObject *obj)
goto fail;
}
- if (PyArray_IsScalar(obj, Generic)) {
+ if (PyArray_IsScalar(obj, Datetime) || PyArray_IsScalar(obj, Timedelta)) {
+ /*
+ * Special case datetime64 scalars to remain backward compatible.
+ * This will change in a future version.
+ * Note arrays of datetime64 and strutured arrays with datetime64
+ * fields will not hit this code path and are currently unsupported
+ * in _buffer_format_string.
+ */
+ _append_char(&fmt, 'B');
+ _append_char(&fmt, '\0');
+ info->ndim = 1;
+ info->shape = malloc(sizeof(Py_ssize_t) * 2);
+ if (info->shape == NULL) {
+ PyErr_NoMemory();
+ goto fail;
+ }
+ info->strides = info->shape + info->ndim;
+ info->shape[0] = 8;
+ info->strides[0] = 1;
+ info->format = fmt.s;
+ return info;
+ }
+ else if (PyArray_IsScalar(obj, Generic)) {
descr = PyArray_DescrFromScalar(obj);
if (descr == NULL) {
goto fail;
@@ -798,8 +831,6 @@ gentype_getbuffer(PyObject *self, Py_buffer *view, int flags)
/* Fill in information */
info = _buffer_get_info(self);
if (info == NULL) {
- PyErr_SetString(PyExc_BufferError,
- "could not get scalar buffer information");
goto fail;
}
@@ -822,6 +853,9 @@ gentype_getbuffer(PyObject *self, Py_buffer *view, int flags)
}
#endif
view->len = elsize;
+ if (PyArray_IsScalar(self, Datetime) || PyArray_IsScalar(self, Timedelta)) {
+ elsize = 1; /* descr->elsize,char is 8,'M', but we return 1,'B' */
+ }
view->itemsize = elsize;
Py_DECREF(descr);
diff --git a/numpy/core/src/multiarray/ctors.c b/numpy/core/src/multiarray/ctors.c
index a2cf17f4e..f1b8a0209 100644
--- a/numpy/core/src/multiarray/ctors.c
+++ b/numpy/core/src/multiarray/ctors.c
@@ -1391,10 +1391,12 @@ _array_from_buffer_3118(PyObject *memoryview)
if (!is_ctypes) {
/* This object has no excuse for a broken PEP3118 buffer */
- PyErr_SetString(
+ PyErr_Format(
PyExc_RuntimeError,
- "Item size computed from the PEP 3118 buffer format "
- "string does not match the actual item size.");
+ "Item size %zd for PEP 3118 buffer format "
+ "string %s does not match the dtype %c item size %d.",
+ view->itemsize, view->format, descr->type,
+ descr->elsize);
Py_DECREF(descr);
return NULL;
}
diff --git a/numpy/core/tests/test_datetime.py b/numpy/core/tests/test_datetime.py
index 942554cae..8e058d5fb 100644
--- a/numpy/core/tests/test_datetime.py
+++ b/numpy/core/tests/test_datetime.py
@@ -620,6 +620,10 @@ class TestDateTime(object):
assert_equal(pickle.loads(pickle.dumps(dt)), dt)
dt = np.dtype('M8[W]')
assert_equal(pickle.loads(pickle.dumps(dt)), dt)
+ scalar = np.datetime64('2016-01-01T00:00:00.000000000')
+ assert_equal(pickle.loads(pickle.dumps(scalar)), scalar)
+ delta = scalar - np.datetime64('2015-01-01T00:00:00.000000000')
+ assert_equal(pickle.loads(pickle.dumps(delta)), delta)
# Check that loading pickles from 1.6 works
pkl = b"cnumpy\ndtype\np0\n(S'M8'\np1\nI0\nI1\ntp2\nRp3\n" + \
@@ -1698,7 +1702,6 @@ class TestDateTime(object):
assert_equal(np.busday_offset(np.datetime64('NaT'), 1, roll='preceding'),
np.datetime64('NaT'))
-
def test_datetime_busdaycalendar(self):
# Check that it removes NaT, duplicates, and weekends
# and sorts the result.
diff --git a/numpy/core/tests/test_einsum.py b/numpy/core/tests/test_einsum.py
index 8ce374a75..6b5b9c06e 100644
--- a/numpy/core/tests/test_einsum.py
+++ b/numpy/core/tests/test_einsum.py
@@ -965,7 +965,6 @@ class TestEinsumPath(object):
path, path_str = np.einsum_path(*edge_test4, optimize='optimal')
self.assert_path_equal(path, ['einsum_path', (0, 1), (0, 1, 2, 3, 4, 5)])
-
def test_path_type_input(self):
# Test explicit path handeling
path_test = self.build_operands('dcc,fce,ea,dbf->ab')
diff --git a/numpy/core/tests/test_indexing.py b/numpy/core/tests/test_indexing.py
index 276cd9f93..1934d542a 100644
--- a/numpy/core/tests/test_indexing.py
+++ b/numpy/core/tests/test_indexing.py
@@ -194,7 +194,6 @@ class TestIndexing(object):
assert_raises(IndexError, arr.__getitem__, (slice(None), index))
-
def test_boolean_indexing_onedim(self):
# Indexing a 2-dimensional array with
# boolean array of length one
diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py
index 1511f5b6b..1c59abaa7 100644
--- a/numpy/core/tests/test_multiarray.py
+++ b/numpy/core/tests/test_multiarray.py
@@ -108,7 +108,6 @@ class TestFlags(object):
assert_equal(self.a.flags['X'], False)
assert_equal(self.a.flags['WRITEBACKIFCOPY'], False)
-
def test_string_align(self):
a = np.zeros(4, dtype=np.dtype('|S4'))
assert_(a.flags.aligned)
@@ -2729,7 +2728,6 @@ class TestMethods(object):
# Order of axis argument doesn't matter:
assert_equal(b.diagonal(0, 2, 1), [[0, 3], [4, 7]])
-
def test_diagonal_view_notwriteable(self):
# this test is only for 1.9, the diagonal view will be
# writeable in 1.10.
@@ -4386,7 +4384,6 @@ class TestIO(object):
d.tofile(f)
assert_equal(os.path.getsize(self.filename), d.nbytes * 2)
-
def test_io_open_buffered_fromfile(self):
# gh-6632
self.x.tofile(self.filename)
@@ -4748,55 +4745,72 @@ class TestRecord(object):
# Error raised when multiple fields have the same name
assert_raises(ValueError, test_assign)
- if sys.version_info[0] >= 3:
- def test_bytes_fields(self):
- # Bytes are not allowed in field names and not recognized in titles
- # on Py3
- assert_raises(TypeError, np.dtype, [(b'a', int)])
- assert_raises(TypeError, np.dtype, [(('b', b'a'), int)])
-
- dt = np.dtype([((b'a', 'b'), int)])
- assert_raises(TypeError, dt.__getitem__, b'a')
-
- x = np.array([(1,), (2,), (3,)], dtype=dt)
- assert_raises(IndexError, x.__getitem__, b'a')
-
- y = x[0]
- assert_raises(IndexError, y.__getitem__, b'a')
-
- def test_multiple_field_name_unicode(self):
- def test_assign_unicode():
- dt = np.dtype([("\u20B9", "f8"),
- ("B", "f8"),
- ("\u20B9", "f8")])
-
- # Error raised when multiple fields have the same name(unicode included)
- assert_raises(ValueError, test_assign_unicode)
-
- else:
- def test_unicode_field_titles(self):
- # Unicode field titles are added to field dict on Py2
- title = u'b'
- dt = np.dtype([((title, 'a'), int)])
- dt[title]
- dt['a']
- x = np.array([(1,), (2,), (3,)], dtype=dt)
- x[title]
- x['a']
- y = x[0]
- y[title]
- y['a']
-
- def test_unicode_field_names(self):
- # Unicode field names are converted to ascii on Python 2:
- encodable_name = u'b'
- assert_equal(np.dtype([(encodable_name, int)]).names[0], b'b')
- assert_equal(np.dtype([(('a', encodable_name), int)]).names[0], b'b')
-
- # But raises UnicodeEncodeError if it can't be encoded:
- nonencodable_name = u'\uc3bc'
- assert_raises(UnicodeEncodeError, np.dtype, [(nonencodable_name, int)])
- assert_raises(UnicodeEncodeError, np.dtype, [(('a', nonencodable_name), int)])
+ @pytest.mark.skipif(sys.version_info[0] < 3, reason="Not Python 3")
+ def test_bytes_fields(self):
+ # Bytes are not allowed in field names and not recognized in titles
+ # on Py3
+ assert_raises(TypeError, np.dtype, [(b'a', int)])
+ assert_raises(TypeError, np.dtype, [(('b', b'a'), int)])
+
+ dt = np.dtype([((b'a', 'b'), int)])
+ assert_raises(TypeError, dt.__getitem__, b'a')
+
+ x = np.array([(1,), (2,), (3,)], dtype=dt)
+ assert_raises(IndexError, x.__getitem__, b'a')
+
+ y = x[0]
+ assert_raises(IndexError, y.__getitem__, b'a')
+
+ @pytest.mark.skipif(sys.version_info[0] < 3, reason="Not Python 3")
+ def test_multiple_field_name_unicode(self):
+ def test_assign_unicode():
+ dt = np.dtype([("\u20B9", "f8"),
+ ("B", "f8"),
+ ("\u20B9", "f8")])
+
+ # Error raised when multiple fields have the same name(unicode included)
+ assert_raises(ValueError, test_assign_unicode)
+
+ @pytest.mark.skipif(sys.version_info[0] >= 3, reason="Not Python 2")
+ def test_unicode_field_titles(self):
+ # Unicode field titles are added to field dict on Py2
+ title = u'b'
+ dt = np.dtype([((title, 'a'), int)])
+ dt[title]
+ dt['a']
+ x = np.array([(1,), (2,), (3,)], dtype=dt)
+ x[title]
+ x['a']
+ y = x[0]
+ y[title]
+ y['a']
+
+ @pytest.mark.skipif(sys.version_info[0] >= 3, reason="Not Python 2")
+ def test_unicode_field_names(self):
+ # Unicode field names are converted to ascii on Python 2:
+ encodable_name = u'b'
+ assert_equal(np.dtype([(encodable_name, int)]).names[0], b'b')
+ assert_equal(np.dtype([(('a', encodable_name), int)]).names[0], b'b')
+
+ # But raises UnicodeEncodeError if it can't be encoded:
+ nonencodable_name = u'\uc3bc'
+ assert_raises(UnicodeEncodeError, np.dtype, [(nonencodable_name, int)])
+ assert_raises(UnicodeEncodeError, np.dtype, [(('a', nonencodable_name), int)])
+
+ def test_fromarrays_unicode(self):
+ # A single name string provided to fromarrays() is allowed to be unicode
+ # on both Python 2 and 3:
+ x = np.core.records.fromarrays([[0], [1]], names=u'a,b', formats=u'i4,i4')
+ assert_equal(x['a'][0], 0)
+ assert_equal(x['b'][0], 1)
+
+ def test_unicode_order(self):
+ # Test that we can sort with order as a unicode field name in both Python 2 and
+ # 3:
+ name = u'b'
+ x = np.array([1, 3, 2], dtype=[(name, int)])
+ x.sort(order=name)
+ assert_equal(x[u'b'], np.array([1, 2, 3]))
def test_field_names(self):
# Test unicode and 8-bit / byte strings can be used
@@ -4909,7 +4923,6 @@ class TestRecord(object):
assert_equal(collect_warnings(c[['f0', 'f2']].view, 'i8,i8'),
[FutureWarning])
-
def test_record_hash(self):
a = np.array([(1, 2), (1, 2)], dtype='i1,i2')
a.flags.writeable = False
@@ -6470,6 +6483,14 @@ class TestNewBufferProtocol(object):
# Issue #4015.
self._check_roundtrip(0)
+ def test_invalid_buffer_format(self):
+ # datetime64 cannot be used fully in a buffer yet
+ # Should be fixed in the next Numpy major release
+ dt = np.dtype([('a', 'uint16'), ('b', 'M8[s]')])
+ a = np.empty(3, dt)
+ assert_raises((ValueError, BufferError), memoryview, a)
+ assert_raises((ValueError, BufferError), memoryview, np.array((3), 'M8[D]'))
+
def test_export_simple_1d(self):
x = np.array([1, 2, 3, 4, 5], dtype='i')
y = memoryview(x)
diff --git a/numpy/core/tests/test_nditer.py b/numpy/core/tests/test_nditer.py
index 13bc6b34a..5e8165bc5 100644
--- a/numpy/core/tests/test_nditer.py
+++ b/numpy/core/tests/test_nditer.py
@@ -2358,7 +2358,6 @@ class TestIterNested(object):
j.close()
assert_equal(a, [[1, 2, 3], [4, 5, 6]])
-
def test_dtype_buffered(self):
# Test nested iteration with buffering to change dtype
diff --git a/numpy/core/tests/test_numeric.py b/numpy/core/tests/test_numeric.py
index a1a92ef32..e7181736f 100644
--- a/numpy/core/tests/test_numeric.py
+++ b/numpy/core/tests/test_numeric.py
@@ -1275,7 +1275,6 @@ class TestArrayComparisons(object):
assert_equal(a == None, [False, False, False])
assert_equal(a != None, [True, True, True])
-
def test_array_equiv(self):
res = np.array_equiv(np.array([1, 2]), np.array([1, 2]))
assert_(res)
diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py
index 36478ddb7..8244dfe20 100644
--- a/numpy/core/tests/test_regression.py
+++ b/numpy/core/tests/test_regression.py
@@ -1828,7 +1828,6 @@ class TestRegression(object):
assert_equal(oct(a), oct(0))
assert_equal(hex(a), hex(0))
-
def test_object_array_self_copy(self):
# An object array being copied into itself DECREF'ed before INCREF'ing
# causing segmentation faults (gh-3787)
diff --git a/numpy/core/tests/test_scalarbuffer.py b/numpy/core/tests/test_scalarbuffer.py
index 6d57a5014..cb6c521e1 100644
--- a/numpy/core/tests/test_scalarbuffer.py
+++ b/numpy/core/tests/test_scalarbuffer.py
@@ -5,7 +5,7 @@ import sys
import numpy as np
import pytest
-from numpy.testing import assert_, assert_equal
+from numpy.testing import assert_, assert_equal, assert_raises
# PEP3118 format strings for native (standard alignment and byteorder) types
scalars_and_codes = [
@@ -77,3 +77,28 @@ class TestScalarPEP3118(object):
mv_a = memoryview(a)
assert_equal(mv_x.itemsize, mv_a.itemsize)
assert_equal(mv_x.format, mv_a.format)
+
+ def test_datetime_memoryview(self):
+ # gh-11656
+ # Values verified with v1.13.3, shape is not () as in test_scalar_dim
+ def as_dict(m):
+ return dict(strides=m.strides, shape=m.shape, itemsize=m.itemsize,
+ ndim=m.ndim, format=m.format)
+
+ dt1 = np.datetime64('2016-01-01')
+ dt2 = np.datetime64('2017-01-01')
+ expected = {'strides': (1,), 'itemsize': 1, 'ndim': 1,
+ 'shape': (8,), 'format': 'B'}
+ v = memoryview(dt1)
+ res = as_dict(v)
+ assert_equal(res, expected)
+
+ v = memoryview(dt2 - dt1)
+ res = as_dict(v)
+ assert_equal(res, expected)
+
+ dt = np.dtype([('a', 'uint16'), ('b', 'M8[s]')])
+ a = np.empty(1, dt)
+ # Fails to create a PEP 3118 valid buffer
+ assert_raises((ValueError, BufferError), memoryview, a[0])
+
diff --git a/numpy/core/tests/test_umath.py b/numpy/core/tests/test_umath.py
index 85c9a4929..d4bdb3d4e 100644
--- a/numpy/core/tests/test_umath.py
+++ b/numpy/core/tests/test_umath.py
@@ -1173,7 +1173,6 @@ class TestBitwiseUFuncs(object):
assert_(np.bitwise_xor(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_and(zeros, zeros).dtype == dt, msg)
-
def test_identity(self):
assert_(np.bitwise_or.identity == 0, 'bitwise_or')
assert_(np.bitwise_xor.identity == 0, 'bitwise_xor')
diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py
index 5880ea154..d84455a8f 100644
--- a/numpy/lib/arraysetops.py
+++ b/numpy/lib/arraysetops.py
@@ -312,12 +312,12 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False):
If True, the input arrays are both assumed to be unique, which
can speed up the calculation. Default is False.
return_indices : bool
- If True, the indices which correspond to the intersection of the
- two arrays are returned. The first instance of a value is used
- if there are multiple. Default is False.
-
- .. versionadded:: 1.15.0
-
+ If True, the indices which correspond to the intersection of the two
+ arrays are returned. The first instance of a value is used if there are
+ multiple. Default is False.
+
+ .. versionadded:: 1.15.0
+
Returns
-------
intersect1d : ndarray
@@ -326,7 +326,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False):
The indices of the first occurrences of the common values in `ar1`.
Only provided if `return_indices` is True.
comm2 : ndarray
- The indices of the first occurrences of the common values in `ar2`.
+ The indices of the first occurrences of the common values in `ar2`.
Only provided if `return_indices` is True.
@@ -345,7 +345,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False):
>>> from functools import reduce
>>> reduce(np.intersect1d, ([1, 3, 4, 3], [3, 1, 2, 1], [6, 3, 4, 2]))
array([3])
-
+
To return the indices of the values common to the input arrays
along with the intersected values:
>>> x = np.array([1, 1, 2, 3, 4])
@@ -355,8 +355,11 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False):
(array([0, 2, 4]), array([1, 0, 2]))
>>> xy, x[x_ind], y[y_ind]
(array([1, 2, 4]), array([1, 2, 4]), array([1, 2, 4]))
-
+
"""
+ ar1 = np.asanyarray(ar1)
+ ar2 = np.asanyarray(ar2)
+
if not assume_unique:
if return_indices:
ar1, ind1 = unique(ar1, return_index=True)
@@ -367,7 +370,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False):
else:
ar1 = ar1.ravel()
ar2 = ar2.ravel()
-
+
aux = np.concatenate((ar1, ar2))
if return_indices:
aux_sort_indices = np.argsort(aux, kind='mergesort')
@@ -389,6 +392,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False):
else:
return int1d
+
def setxor1d(ar1, ar2, assume_unique=False):
"""
Find the set exclusive-or of two arrays.
diff --git a/numpy/lib/histograms.py b/numpy/lib/histograms.py
index 422b356f7..f03f30fb0 100644
--- a/numpy/lib/histograms.py
+++ b/numpy/lib/histograms.py
@@ -260,6 +260,32 @@ def _get_outer_edges(a, range):
return first_edge, last_edge
+def _unsigned_subtract(a, b):
+ """
+ Subtract two values where a >= b, and produce an unsigned result
+
+ This is needed when finding the difference between the upper and lower
+ bound of an int16 histogram
+ """
+ # coerce to a single type
+ signed_to_unsigned = {
+ np.byte: np.ubyte,
+ np.short: np.ushort,
+ np.intc: np.uintc,
+ np.int_: np.uint,
+ np.longlong: np.ulonglong
+ }
+ dt = np.result_type(a, b)
+ try:
+ dt = signed_to_unsigned[dt.type]
+ except KeyError:
+ return np.subtract(a, b, dtype=dt)
+ else:
+ # we know the inputs are integers, and we are deliberately casting
+ # signed to unsigned
+ return np.subtract(a, b, casting='unsafe', dtype=dt)
+
+
def _get_bin_edges(a, bins, range, weights):
"""
Computes the bins used internally by `histogram`.
@@ -311,7 +337,7 @@ def _get_bin_edges(a, bins, range, weights):
# Do not call selectors on empty arrays
width = _hist_bin_selectors[bin_name](a)
if width:
- n_equal_bins = int(np.ceil((last_edge - first_edge) / width))
+ n_equal_bins = int(np.ceil(_unsigned_subtract(last_edge, first_edge) / width))
else:
# Width can be zero for some estimators, e.g. FD when
# the IQR of the data is zero.
@@ -703,7 +729,7 @@ def histogram(a, bins=10, range=None, normed=None, weights=None,
n = np.zeros(n_equal_bins, ntype)
# Pre-compute histogram scaling factor
- norm = n_equal_bins / (last_edge - first_edge)
+ norm = n_equal_bins / _unsigned_subtract(last_edge, first_edge)
# We iterate over blocks here for two reasons: the first is that for
# large arrays, it is actually faster (for example for a 10^8 array it
@@ -731,7 +757,7 @@ def histogram(a, bins=10, range=None, normed=None, weights=None,
# Compute the bin indices, and for values that lie exactly on
# last_edge we need to subtract one
- f_indices = (tmp_a - first_edge) * norm
+ f_indices = _unsigned_subtract(tmp_a, first_edge) * norm
indices = f_indices.astype(np.intp)
indices[indices == n_equal_bins] -= 1
diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py
index abd2da1a2..8d6b0f139 100644
--- a/numpy/lib/nanfunctions.py
+++ b/numpy/lib/nanfunctions.py
@@ -1178,13 +1178,15 @@ def nanquantile(a, q, axis=None, out=None, overwrite_input=False,
This optional parameter specifies the interpolation method to
use when the desired quantile lies between two data points
``i < j``:
- * linear: ``i + (j - i) * fraction``, where ``fraction``
- is the fractional part of the index surrounded by ``i``
- and ``j``.
- * lower: ``i``.
- * higher: ``j``.
- * nearest: ``i`` or ``j``, whichever is nearest.
- * midpoint: ``(i + j) / 2``.
+
+ * linear: ``i + (j - i) * fraction``, where ``fraction``
+ is the fractional part of the index surrounded by ``i``
+ and ``j``.
+ * lower: ``i``.
+ * higher: ``j``.
+ * nearest: ``i`` or ``j``, whichever is nearest.
+ * midpoint: ``(i + j) / 2``.
+
keepdims : bool, optional
If this is set to True, the axes which are reduced are left in
the result as dimensions with size one. With this option, the
diff --git a/numpy/lib/stride_tricks.py b/numpy/lib/stride_tricks.py
index bc5993802..ca13738c1 100644
--- a/numpy/lib/stride_tricks.py
+++ b/numpy/lib/stride_tricks.py
@@ -242,7 +242,7 @@ def broadcast_arrays(*args, **kwargs):
subok = kwargs.pop('subok', False)
if kwargs:
raise TypeError('broadcast_arrays() got an unexpected keyword '
- 'argument {!r}'.format(kwargs.keys()[0]))
+ 'argument {!r}'.format(list(kwargs.keys())[0]))
args = [np.array(_m, copy=False, subok=subok) for _m in args]
shape = _broadcast_shape(*args)
diff --git a/numpy/lib/tests/test__datasource.py b/numpy/lib/tests/test__datasource.py
index 70fff3bb0..85788941c 100644
--- a/numpy/lib/tests/test__datasource.py
+++ b/numpy/lib/tests/test__datasource.py
@@ -33,14 +33,14 @@ def urlopen_stub(url, data=None):
old_urlopen = None
-def setup():
+def setup_module():
global old_urlopen
old_urlopen = urllib_request.urlopen
urllib_request.urlopen = urlopen_stub
-def teardown():
+def teardown_module():
urllib_request.urlopen = old_urlopen
# A valid website for more robust testing
diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py
index dace5ade8..c76afb8e5 100644
--- a/numpy/lib/tests/test_arraysetops.py
+++ b/numpy/lib/tests/test_arraysetops.py
@@ -30,19 +30,30 @@ class TestSetOps(object):
ed = np.array([1, 2, 5])
c = intersect1d(a, b)
assert_array_equal(c, ed)
-
assert_array_equal([], intersect1d([], []))
-
+
+ def test_intersect1d_array_like(self):
+ # See gh-11772
+ class Test(object):
+ def __array__(self):
+ return np.arange(3)
+
+ a = Test()
+ res = intersect1d(a, a)
+ assert_array_equal(res, a)
+ res = intersect1d([1, 2, 3], [1, 2, 3])
+ assert_array_equal(res, [1, 2, 3])
+
def test_intersect1d_indices(self):
# unique inputs
- a = np.array([1, 2, 3, 4])
+ a = np.array([1, 2, 3, 4])
b = np.array([2, 1, 4, 6])
c, i1, i2 = intersect1d(a, b, assume_unique=True, return_indices=True)
ee = np.array([1, 2, 4])
assert_array_equal(c, ee)
assert_array_equal(a[i1], ee)
assert_array_equal(b[i2], ee)
-
+
# non-unique inputs
a = np.array([1, 2, 2, 3, 4, 3, 2])
b = np.array([1, 8, 4, 2, 2, 3, 2, 3])
@@ -51,7 +62,7 @@ class TestSetOps(object):
assert_array_equal(c, ef)
assert_array_equal(a[i1], ef)
assert_array_equal(b[i2], ef)
-
+
# non1d, unique inputs
a = np.array([[2, 4, 5, 6], [7, 8, 1, 15]])
b = np.array([[3, 2, 7, 6], [10, 12, 8, 9]])
@@ -61,7 +72,7 @@ class TestSetOps(object):
ea = np.array([2, 6, 7, 8])
assert_array_equal(ea, a[ui1])
assert_array_equal(ea, b[ui2])
-
+
# non1d, not assumed to be uniqueinputs
a = np.array([[2, 4, 5, 6, 6], [4, 7, 8, 7, 2]])
b = np.array([[3, 2, 7, 7], [10, 12, 8, 7]])
@@ -71,7 +82,7 @@ class TestSetOps(object):
ea = np.array([2, 7, 8])
assert_array_equal(ea, a[ui1])
assert_array_equal(ea, b[ui2])
-
+
def test_setxor1d(self):
a = np.array([5, 7, 1, 2])
b = np.array([2, 4, 3, 1, 5])
diff --git a/numpy/lib/tests/test_histograms.py b/numpy/lib/tests/test_histograms.py
index f136b5c81..561f5f938 100644
--- a/numpy/lib/tests/test_histograms.py
+++ b/numpy/lib/tests/test_histograms.py
@@ -310,6 +310,20 @@ class TestHistogram(object):
assert_equal(d_edge.dtype, dates.dtype)
assert_equal(t_edge.dtype, td)
+ def do_signed_overflow_bounds(self, dtype):
+ exponent = 8 * np.dtype(dtype).itemsize - 1
+ arr = np.array([-2**exponent + 4, 2**exponent - 4], dtype=dtype)
+ hist, e = histogram(arr, bins=2)
+ assert_equal(e, [-2**exponent + 4, 0, 2**exponent - 4])
+ assert_equal(hist, [1, 1])
+
+ def test_signed_overflow_bounds(self):
+ self.do_signed_overflow_bounds(np.byte)
+ self.do_signed_overflow_bounds(np.short)
+ self.do_signed_overflow_bounds(np.intc)
+ self.do_signed_overflow_bounds(np.int_)
+ self.do_signed_overflow_bounds(np.longlong)
+
def do_precision_lower_bound(self, float_small, float_large):
eps = np.finfo(float_large).eps
diff --git a/numpy/lib/tests/test_index_tricks.py b/numpy/lib/tests/test_index_tricks.py
index 315251daa..7e9c026e4 100644
--- a/numpy/lib/tests/test_index_tricks.py
+++ b/numpy/lib/tests/test_index_tricks.py
@@ -113,7 +113,6 @@ class TestRavelUnravelIndex(object):
assert_(x.flags.writeable)
assert_(y.flags.writeable)
-
def test_0d(self):
# gh-580
x = np.unravel_index(0, ())
diff --git a/numpy/lib/tests/test_io.py b/numpy/lib/tests/test_io.py
index f58c9e33d..1f3664d92 100644
--- a/numpy/lib/tests/test_io.py
+++ b/numpy/lib/tests/test_io.py
@@ -348,7 +348,6 @@ class TestSaveTxt(object):
assert_raises(ValueError, np.savetxt, c, np.array(1))
assert_raises(ValueError, np.savetxt, c, np.array([[[1], [2]]]))
-
def test_record(self):
a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
c = BytesIO()
@@ -2025,7 +2024,6 @@ M 33 21.99
assert_equal(test['f0'], 0)
assert_equal(test['f1'], "testNonethe" + utf8.decode("UTF-8"))
-
def test_utf8_file_nodtype_unicode(self):
# bytes encoding with non-latin1 -> unicode upcast
utf8 = u'\u03d6'
diff --git a/numpy/lib/tests/test_stride_tricks.py b/numpy/lib/tests/test_stride_tricks.py
index 3c2ca8b87..b2bd7da3e 100644
--- a/numpy/lib/tests/test_stride_tricks.py
+++ b/numpy/lib/tests/test_stride_tricks.py
@@ -3,7 +3,8 @@ from __future__ import division, absolute_import, print_function
import numpy as np
from numpy.core._rational_tests import rational
from numpy.testing import (
- assert_equal, assert_array_equal, assert_raises, assert_
+ assert_equal, assert_array_equal, assert_raises, assert_,
+ assert_raises_regex
)
from numpy.lib.stride_tricks import (
as_strided, broadcast_arrays, _broadcast_shape, broadcast_to
@@ -57,6 +58,17 @@ def test_same():
assert_array_equal(x, bx)
assert_array_equal(y, by)
+def test_broadcast_kwargs():
+ # ensure that a TypeError is appropriately raised when
+ # np.broadcast_arrays() is called with any keyword
+ # argument other than 'subok'
+ x = np.arange(10)
+ y = np.arange(10)
+
+ with assert_raises_regex(TypeError,
+ r'broadcast_arrays\(\) got an unexpected keyword*'):
+ broadcast_arrays(x, y, dtype='float64')
+
def test_one_off():
x = np.array([[1, 2, 3]])
diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py
index ce4a37b09..98a77d8f5 100644
--- a/numpy/linalg/tests/test_linalg.py
+++ b/numpy/linalg/tests/test_linalg.py
@@ -959,7 +959,6 @@ class TestMatrixPower(object):
#FIXME the 'e' dtype might work in future
dtnoinv = [object, np.dtype('e'), np.dtype('g'), np.dtype('G')]
-
def test_large_power(self, dt):
power = matrix_power
rshft = self.rshft_1.astype(dt)
@@ -1022,7 +1021,6 @@ class TestMatrixPower(object):
assert_raises(TypeError, matrix_power, mat, 1.5)
assert_raises(TypeError, matrix_power, mat, [1])
-
def test_exceptions_non_square(self, dt):
assert_raises(LinAlgError, matrix_power, np.array([1], dt), 1)
assert_raises(LinAlgError, matrix_power, np.array([[1], [2]], dt), 1)
diff --git a/numpy/ma/tests/test_core.py b/numpy/ma/tests/test_core.py
index 129809b5d..a08a0d956 100644
--- a/numpy/ma/tests/test_core.py
+++ b/numpy/ma/tests/test_core.py
@@ -514,8 +514,6 @@ class TestMaskedArray(object):
fill_value=999999)''')
)
-
-
def test_str_repr_legacy(self):
oldopts = np.get_printoptions()
np.set_printoptions(legacy='1.13')
@@ -788,7 +786,6 @@ class TestMaskedArray(object):
control = "(0, [[--, 0.0, --], [0.0, 0.0, --]], 0.0)"
assert_equal(str(t_2d0), control)
-
def test_flatten_structured_array(self):
# Test flatten_structured_array on arrays
# On ndarray
@@ -3174,18 +3171,13 @@ class TestMaskedArrayMethods(object):
assert_equal(test.mask, mask_first.mask)
# Test sort on dtype with subarray (gh-8069)
+ # Just check that the sort does not error, structured array subarrays
+ # are treated as byte strings and that leads to differing behavior
+ # depending on endianess and `endwith`.
dt = np.dtype([('v', int, 2)])
a = a.view(dt)
- mask_last = mask_last.view(dt)
- mask_first = mask_first.view(dt)
-
test = sort(a)
- assert_equal(test, mask_last)
- assert_equal(test.mask, mask_last.mask)
-
test = sort(a, endwith=False)
- assert_equal(test, mask_first)
- assert_equal(test.mask, mask_first.mask)
def test_argsort(self):
# Test argsort
diff --git a/numpy/random/tests/test_random.py b/numpy/random/tests/test_random.py
index 2e0885024..8328c69c0 100644
--- a/numpy/random/tests/test_random.py
+++ b/numpy/random/tests/test_random.py
@@ -1454,7 +1454,6 @@ class TestBroadcast(object):
assert_raises(ValueError, zipf, np.nan)
assert_raises(ValueError, zipf, [0, 0, np.nan])
-
def test_geometric(self):
p = [0.5]
bad_p_one = [-1]
diff --git a/numpy/testing/_private/nosetester.py b/numpy/testing/_private/nosetester.py
index c2cf58377..1728d9d1f 100644
--- a/numpy/testing/_private/nosetester.py
+++ b/numpy/testing/_private/nosetester.py
@@ -338,12 +338,14 @@ class NoseTester(object):
Identifies the tests to run. This can be a string to pass to
the nosetests executable with the '-A' option, or one of several
special values. Special values are:
+
* 'fast' - the default - which corresponds to the ``nosetests -A``
option of 'not slow'.
* 'full' - fast (as above) and slow tests as in the
'no -A' option to nosetests - this is the same as ''.
* None or '' - run all tests.
- attribute_identifier - string passed directly to nosetests as '-A'.
+ * attribute_identifier - string passed directly to nosetests as '-A'.
+
verbose : int, optional
Verbosity value for test outputs, in the range 1-10. Default is 1.
extra_argv : list, optional
@@ -352,16 +354,14 @@ class NoseTester(object):
If True, run doctests in module. Default is False.
coverage : bool, optional
If True, report coverage of NumPy code. Default is False.
- (This requires the `coverage module:
- <http://nedbatchelder.com/code/modules/coverage.html>`_).
+ (This requires the
+ `coverage module <https://nedbatchelder.com/code/modules/coveragehtml>`_).
raise_warnings : None, str or sequence of warnings, optional
This specifies which warnings to configure as 'raise' instead
- of being shown once during the test execution. Valid strings are:
-
- - "develop" : equals ``(Warning,)``
- - "release" : equals ``()``, don't raise on any warnings.
+ of being shown once during the test execution. Valid strings are:
- The default is to use the class initialization value.
+ * "develop" : equals ``(Warning,)``
+ * "release" : equals ``()``, do not raise on any warnings.
timer : bool or int, optional
Timing of individual tests with ``nose-timer`` (which needs to be
installed). If True, time tests and report on all of them.
@@ -489,12 +489,14 @@ class NoseTester(object):
Identifies the benchmarks to run. This can be a string to pass to
the nosetests executable with the '-A' option, or one of several
special values. Special values are:
+
* 'fast' - the default - which corresponds to the ``nosetests -A``
option of 'not slow'.
* 'full' - fast (as above) and slow benchmarks as in the
'no -A' option to nosetests - this is the same as ''.
* None or '' - run all tests.
- attribute_identifier - string passed directly to nosetests as '-A'.
+ * attribute_identifier - string passed directly to nosetests as '-A'.
+
verbose : int, optional
Verbosity value for benchmark outputs, in the range 1-10. Default is 1.
extra_argv : list, optional
diff --git a/numpy/testing/_private/utils.py b/numpy/testing/_private/utils.py
index 0e2f8ba91..a3832fcde 100644
--- a/numpy/testing/_private/utils.py
+++ b/numpy/testing/_private/utils.py
@@ -687,6 +687,8 @@ def assert_array_compare(comparison, x, y, err_msg='', verbose=True,
equal_inf=True):
__tracebackhide__ = True # Hide traceback for py.test
from numpy.core import array, isnan, inf, bool_
+ from numpy.core.fromnumeric import all as npall
+
x = array(x, copy=False, subok=True)
y = array(y, copy=False, subok=True)
@@ -697,14 +699,21 @@ def assert_array_compare(comparison, x, y, err_msg='', verbose=True,
return x.dtype.char in "Mm"
def func_assert_same_pos(x, y, func=isnan, hasval='nan'):
- """Handling nan/inf: combine results of running func on x and y,
- checking that they are True at the same locations."""
- # Both the != True comparison here and the cast to bool_ at
- # the end are done to deal with `masked`, which cannot be
- # compared usefully, and for which .all() yields masked.
+ """Handling nan/inf.
+
+ Combine results of running func on x and y, checking that they are True
+ at the same locations.
+
+ """
+ # Both the != True comparison here and the cast to bool_ at the end are
+ # done to deal with `masked`, which cannot be compared usefully, and
+ # for which np.all yields masked. The use of the function np.all is
+ # for back compatibility with ndarray subclasses that changed the
+ # return values of the all method. We are not committed to supporting
+ # such subclasses, but some used to work.
x_id = func(x)
y_id = func(y)
- if (x_id == y_id).all() != True:
+ if npall(x_id == y_id) != True:
msg = build_err_msg([x, y],
err_msg + '\nx and y %s location mismatch:'
% (hasval), verbose=verbose, header=header,
diff --git a/numpy/testing/tests/test_decorators.py b/numpy/testing/tests/test_decorators.py
index ea684140d..d00820b80 100644
--- a/numpy/testing/tests/test_decorators.py
+++ b/numpy/testing/tests/test_decorators.py
@@ -53,7 +53,6 @@ class TestNoseDecorators(object):
assert_(f_istest.__test__)
assert_(not f_isnottest.__test__)
-
def test_skip_functions_hardcoded(self):
@dec.skipif(True)
def f1(x):
diff --git a/numpy/testing/tests/test_utils.py b/numpy/testing/tests/test_utils.py
index 84d310992..2c60e2867 100644
--- a/numpy/testing/tests/test_utils.py
+++ b/numpy/testing/tests/test_utils.py
@@ -1391,7 +1391,6 @@ class TestAssertNoGcCycles(object):
assert_no_gc_cycles(no_cycle)
-
def test_asserts(self):
def make_cycle():
a = []
@@ -1406,7 +1405,6 @@ class TestAssertNoGcCycles(object):
with assert_raises(AssertionError):
assert_no_gc_cycles(make_cycle)
-
def test_fails(self):
"""
Test that in cases where the garbage cannot be collected, we raise an