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-rw-r--r--numpy/core/fromnumeric.py4
-rw-r--r--numpy/core/shape_base.py2
-rw-r--r--numpy/core/src/multiarray/convert_datatype.c8
-rw-r--r--numpy/core/src/multiarray/scalartypes.c.src7
-rw-r--r--numpy/core/src/npysort/npysort_common.h8
-rw-r--r--numpy/core/tests/test_datetime.py41
-rw-r--r--numpy/core/tests/test_scalarmath.py12
-rw-r--r--numpy/linalg/linalg.py11
8 files changed, 84 insertions, 9 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index 6e5f3dabf..d454480a8 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -944,6 +944,10 @@ def sort(a, axis=-1, kind=None, order=None):
'mergesort' and 'stable' are mapped to radix sort for integer data types. Radix sort is an
O(n) sort instead of O(n log n).
+ .. versionchanged:: 1.17.0
+
+ NaT now sorts to the end of arrays for consistency with NaN.
+
Examples
--------
>>> a = np.array([[1,4],[3,1]])
diff --git a/numpy/core/shape_base.py b/numpy/core/shape_base.py
index 369d956fb..31b1c20b9 100644
--- a/numpy/core/shape_base.py
+++ b/numpy/core/shape_base.py
@@ -575,7 +575,7 @@ def _concatenate_shapes(shapes, axis):
that was computed deeper in the recursion.
These are returned as tuples to ensure that they can quickly be added
- to existing slice tuple without creating a new tuple everytime.
+ to existing slice tuple without creating a new tuple every time.
"""
# Cache a result that will be reused.
diff --git a/numpy/core/src/multiarray/convert_datatype.c b/numpy/core/src/multiarray/convert_datatype.c
index 025c66013..4326448dc 100644
--- a/numpy/core/src/multiarray/convert_datatype.c
+++ b/numpy/core/src/multiarray/convert_datatype.c
@@ -877,7 +877,13 @@ PyArray_CanCastTypeTo(PyArray_Descr *from, PyArray_Descr *to,
from_order = dtype_kind_to_ordering(from->kind);
to_order = dtype_kind_to_ordering(to->kind);
- return from_order != -1 && from_order <= to_order;
+ if (to->kind == 'm') {
+ /* both types being timedelta is already handled before. */
+ int integer_order = dtype_kind_to_ordering('i');
+ return (from_order != -1) && (from_order <= integer_order);
+ }
+
+ return (from_order != -1) && (from_order <= to_order);
}
else {
return 0;
diff --git a/numpy/core/src/multiarray/scalartypes.c.src b/numpy/core/src/multiarray/scalartypes.c.src
index 32d712e0c..5da7f7738 100644
--- a/numpy/core/src/multiarray/scalartypes.c.src
+++ b/numpy/core/src/multiarray/scalartypes.c.src
@@ -4060,8 +4060,11 @@ initialize_casting_tables(void)
_npy_can_cast_safely_table[_FROM_NUM][NPY_STRING] = 1;
_npy_can_cast_safely_table[_FROM_NUM][NPY_UNICODE] = 1;
- /* Allow casts from any integer to the TIMEDELTA type */
-#if @from_isint@ || @from_isuint@
+#if @from_isint@ && NPY_SIZEOF_TIMEDELTA >= _FROM_BSIZE
+ /* Allow casts from smaller or equal signed integers to the TIMEDELTA type */
+ _npy_can_cast_safely_table[_FROM_NUM][NPY_TIMEDELTA] = 1;
+#elif @from_isuint@ && NPY_SIZEOF_TIMEDELTA > _FROM_BSIZE
+ /* Allow casts from smaller unsigned integers to the TIMEDELTA type */
_npy_can_cast_safely_table[_FROM_NUM][NPY_TIMEDELTA] = 1;
#endif
diff --git a/numpy/core/src/npysort/npysort_common.h b/numpy/core/src/npysort/npysort_common.h
index 5fd03b96f..30c0d47f3 100644
--- a/numpy/core/src/npysort/npysort_common.h
+++ b/numpy/core/src/npysort/npysort_common.h
@@ -329,6 +329,14 @@ UNICODE_LT(const npy_ucs4 *s1, const npy_ucs4 *s2, size_t len)
NPY_INLINE static int
DATETIME_LT(npy_datetime a, npy_datetime b)
{
+ if (a == NPY_DATETIME_NAT) {
+ return 0;
+ }
+
+ if (b == NPY_DATETIME_NAT) {
+ return 1;
+ }
+
return a < b;
}
diff --git a/numpy/core/tests/test_datetime.py b/numpy/core/tests/test_datetime.py
index e8ffbbb9d..41b84a69f 100644
--- a/numpy/core/tests/test_datetime.py
+++ b/numpy/core/tests/test_datetime.py
@@ -75,6 +75,15 @@ class TestDateTime(object):
# Can cast safely/same_kind from integer to timedelta
assert_(np.can_cast('i8', 'm8', casting='same_kind'))
assert_(np.can_cast('i8', 'm8', casting='safe'))
+ assert_(np.can_cast('i4', 'm8', casting='same_kind'))
+ assert_(np.can_cast('i4', 'm8', casting='safe'))
+ assert_(np.can_cast('u4', 'm8', casting='same_kind'))
+ assert_(np.can_cast('u4', 'm8', casting='safe'))
+
+ # Cannot cast safely from unsigned integer of the same size, which
+ # could overflow
+ assert_(np.can_cast('u8', 'm8', casting='same_kind'))
+ assert_(not np.can_cast('u8', 'm8', casting='safe'))
# Cannot cast safely/same_kind from float to timedelta
assert_(not np.can_cast('f4', 'm8', casting='same_kind'))
@@ -136,6 +145,38 @@ class TestDateTime(object):
assert_(np.datetime64('NaT') != np.datetime64('NaT', 'us'))
assert_(np.datetime64('NaT', 'us') != np.datetime64('NaT'))
+
+
+ @pytest.mark.parametrize("size", [
+ 3, 21, 217, 1000])
+ def test_nat_argsort_stability(self, size):
+ # NaT < NaT should be False internally for
+ # sort stability
+ expected = np.arange(size)
+ arr = np.tile(np.datetime64('NaT'), size)
+ assert_equal(np.argsort(arr, kind='mergesort'), expected)
+
+ @pytest.mark.parametrize("arr, expected", [
+ # the example provided in gh-12629
+ (np.array(['NaT', 1, 2, 3], dtype='M8[ns]'),
+ np.array([1, 2, 3, 'NaT'], dtype='M8[ns]')),
+ # multiple NaTs
+ (np.array(['NaT', 9, 'NaT', -707], dtype='M8[s]'),
+ np.array([-707, 9, 'NaT', 'NaT'], dtype='M8[s]')),
+ # this sort explores another code path for NaT
+ (np.array([1, -2, 3, 'NaT'], dtype='M8[ns]'),
+ np.array([-2, 1, 3, 'NaT'], dtype='M8[ns]')),
+ # 2-D array
+ (np.array([[51, -220, 'NaT'],
+ [-17, 'NaT', -90]], dtype='M8[us]'),
+ np.array([[-220, 51, 'NaT'],
+ [-90, -17, 'NaT']], dtype='M8[us]')),
+ ])
+ def test_sort_nat(self, arr, expected):
+ # fix for gh-12629; NaT sorting to end of array
+ arr.sort()
+ assert_equal(arr, expected)
+
def test_datetime_scalar_construction(self):
# Construct with different units
assert_equal(np.datetime64('1950-03-12', 'D'),
diff --git a/numpy/core/tests/test_scalarmath.py b/numpy/core/tests/test_scalarmath.py
index 854df5590..c84380cd9 100644
--- a/numpy/core/tests/test_scalarmath.py
+++ b/numpy/core/tests/test_scalarmath.py
@@ -11,7 +11,7 @@ import numpy as np
from numpy.testing import (
assert_, assert_equal, assert_raises, assert_almost_equal,
assert_array_equal, IS_PYPY, suppress_warnings, _gen_alignment_data,
- assert_warns
+ assert_warns, assert_raises_regex,
)
types = [np.bool_, np.byte, np.ubyte, np.short, np.ushort, np.intc, np.uintc,
@@ -293,6 +293,16 @@ class TestModulus(object):
rem = operator.mod(finf, fone)
assert_(np.isnan(rem), 'dt: %s' % dt)
+ def test_inplace_floordiv_handling(self):
+ # issue gh-12927
+ # this only applies to in-place floordiv //=, because the output type
+ # promotes to float which does not fit
+ a = np.array([1, 2], np.int64)
+ b = np.array([1, 2], np.uint64)
+ pattern = 'could not be coerced to provided output parameter'
+ with assert_raises_regex(TypeError, pattern):
+ a //= b
+
class TestComplexDivision(object):
def test_zero_division(self):
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py
index 665b9fbec..f1b2c2228 100644
--- a/numpy/linalg/linalg.py
+++ b/numpy/linalg/linalg.py
@@ -2325,16 +2325,19 @@ def norm(x, ord=None, axis=None, keepdims=False):
Parameters
----------
x : array_like
- Input array. If `axis` is None, `x` must be 1-D or 2-D.
+ Input array. If `axis` is None, `x` must be 1-D or 2-D, unless `ord`
+ is None. If both `axis` and `ord` are None, the 2-norm of
+ ``x.ravel`` will be returned.
ord : {non-zero int, inf, -inf, 'fro', 'nuc'}, optional
Order of the norm (see table under ``Notes``). inf means numpy's
- `inf` object.
- axis : {int, 2-tuple of ints, None}, optional
+ `inf` object. The default is None.
+ axis : {None, int, 2-tuple of ints}, optional.
If `axis` is an integer, it specifies the axis of `x` along which to
compute the vector norms. If `axis` is a 2-tuple, it specifies the
axes that hold 2-D matrices, and the matrix norms of these matrices
are computed. If `axis` is None then either a vector norm (when `x`
- is 1-D) or a matrix norm (when `x` is 2-D) is returned.
+ is 1-D) or a matrix norm (when `x` is 2-D) is returned. The default
+ is None.
.. versionadded:: 1.8.0
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