mirror of
https://github.com/pybind/pybind11.git
synced 2024-11-14 17:43:53 +00:00
503ff2a6fb
* reshape * more tests * Update numpy.h * Update test_numpy_array.py * array view * test * Update test_numpy_array.cpp * Update numpy.h * Update numpy.h * Update test_numpy_array.cpp * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix merge bug * Make clang-tidy happy * Add xfail for PyPy * Fix casting issue * Fix formatting * Apply clang-tidy * Address reviews on additional tests * Fix ordering * Do a little more reordering * Fix typo * Try improving tests * Fix error in reshape * Add one more reshape test * Fix bugs and add test * Relax test * streamlining new tests; removing a few stray msg * Fix style revert * Fix clang-tidy * Misc tweaks: * Comment: matching style in file (///), responsibility sentence, consistent punctuation. * Replacing `unsigned char` with `uint8_t` for max consistency. * Removing `1` from `array_view1` because there is only one. * Partial clang-format-diff. Co-authored-by: ncullen93 <ncullen.th@dartmouth.edu> Co-authored-by: NC Cullen <nicholas.c.cullen.th@dartmouth.edu> Co-authored-by: Aaron Gokaslan <skylion.aaron@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Ralf Grosse-Kunstleve <rwgk@google.com>
594 lines
20 KiB
Python
594 lines
20 KiB
Python
# -*- coding: utf-8 -*-
|
|
import pytest
|
|
|
|
import env # noqa: F401
|
|
from pybind11_tests import numpy_array as m
|
|
|
|
np = pytest.importorskip("numpy")
|
|
|
|
|
|
def test_dtypes():
|
|
# See issue #1328.
|
|
# - Platform-dependent sizes.
|
|
for size_check in m.get_platform_dtype_size_checks():
|
|
print(size_check)
|
|
assert size_check.size_cpp == size_check.size_numpy, size_check
|
|
# - Concrete sizes.
|
|
for check in m.get_concrete_dtype_checks():
|
|
print(check)
|
|
assert check.numpy == check.pybind11, check
|
|
if check.numpy.num != check.pybind11.num:
|
|
print(
|
|
"NOTE: typenum mismatch for {}: {} != {}".format(
|
|
check, check.numpy.num, check.pybind11.num
|
|
)
|
|
)
|
|
|
|
|
|
@pytest.fixture(scope="function")
|
|
def arr():
|
|
return np.array([[1, 2, 3], [4, 5, 6]], "=u2")
|
|
|
|
|
|
def test_array_attributes():
|
|
a = np.array(0, "f8")
|
|
assert m.ndim(a) == 0
|
|
assert all(m.shape(a) == [])
|
|
assert all(m.strides(a) == [])
|
|
with pytest.raises(IndexError) as excinfo:
|
|
m.shape(a, 0)
|
|
assert str(excinfo.value) == "invalid axis: 0 (ndim = 0)"
|
|
with pytest.raises(IndexError) as excinfo:
|
|
m.strides(a, 0)
|
|
assert str(excinfo.value) == "invalid axis: 0 (ndim = 0)"
|
|
assert m.writeable(a)
|
|
assert m.size(a) == 1
|
|
assert m.itemsize(a) == 8
|
|
assert m.nbytes(a) == 8
|
|
assert m.owndata(a)
|
|
|
|
a = np.array([[1, 2, 3], [4, 5, 6]], "u2").view()
|
|
a.flags.writeable = False
|
|
assert m.ndim(a) == 2
|
|
assert all(m.shape(a) == [2, 3])
|
|
assert m.shape(a, 0) == 2
|
|
assert m.shape(a, 1) == 3
|
|
assert all(m.strides(a) == [6, 2])
|
|
assert m.strides(a, 0) == 6
|
|
assert m.strides(a, 1) == 2
|
|
with pytest.raises(IndexError) as excinfo:
|
|
m.shape(a, 2)
|
|
assert str(excinfo.value) == "invalid axis: 2 (ndim = 2)"
|
|
with pytest.raises(IndexError) as excinfo:
|
|
m.strides(a, 2)
|
|
assert str(excinfo.value) == "invalid axis: 2 (ndim = 2)"
|
|
assert not m.writeable(a)
|
|
assert m.size(a) == 6
|
|
assert m.itemsize(a) == 2
|
|
assert m.nbytes(a) == 12
|
|
assert not m.owndata(a)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"args, ret", [([], 0), ([0], 0), ([1], 3), ([0, 1], 1), ([1, 2], 5)]
|
|
)
|
|
def test_index_offset(arr, args, ret):
|
|
assert m.index_at(arr, *args) == ret
|
|
assert m.index_at_t(arr, *args) == ret
|
|
assert m.offset_at(arr, *args) == ret * arr.dtype.itemsize
|
|
assert m.offset_at_t(arr, *args) == ret * arr.dtype.itemsize
|
|
|
|
|
|
def test_dim_check_fail(arr):
|
|
for func in (
|
|
m.index_at,
|
|
m.index_at_t,
|
|
m.offset_at,
|
|
m.offset_at_t,
|
|
m.data,
|
|
m.data_t,
|
|
m.mutate_data,
|
|
m.mutate_data_t,
|
|
):
|
|
with pytest.raises(IndexError) as excinfo:
|
|
func(arr, 1, 2, 3)
|
|
assert str(excinfo.value) == "too many indices for an array: 3 (ndim = 2)"
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"args, ret",
|
|
[
|
|
([], [1, 2, 3, 4, 5, 6]),
|
|
([1], [4, 5, 6]),
|
|
([0, 1], [2, 3, 4, 5, 6]),
|
|
([1, 2], [6]),
|
|
],
|
|
)
|
|
def test_data(arr, args, ret):
|
|
from sys import byteorder
|
|
|
|
assert all(m.data_t(arr, *args) == ret)
|
|
assert all(m.data(arr, *args)[(0 if byteorder == "little" else 1) :: 2] == ret)
|
|
assert all(m.data(arr, *args)[(1 if byteorder == "little" else 0) :: 2] == 0)
|
|
|
|
|
|
@pytest.mark.parametrize("dim", [0, 1, 3])
|
|
def test_at_fail(arr, dim):
|
|
for func in m.at_t, m.mutate_at_t:
|
|
with pytest.raises(IndexError) as excinfo:
|
|
func(arr, *([0] * dim))
|
|
assert str(excinfo.value) == "index dimension mismatch: {} (ndim = 2)".format(
|
|
dim
|
|
)
|
|
|
|
|
|
def test_at(arr):
|
|
assert m.at_t(arr, 0, 2) == 3
|
|
assert m.at_t(arr, 1, 0) == 4
|
|
|
|
assert all(m.mutate_at_t(arr, 0, 2).ravel() == [1, 2, 4, 4, 5, 6])
|
|
assert all(m.mutate_at_t(arr, 1, 0).ravel() == [1, 2, 4, 5, 5, 6])
|
|
|
|
|
|
def test_mutate_readonly(arr):
|
|
arr.flags.writeable = False
|
|
for func, args in (
|
|
(m.mutate_data, ()),
|
|
(m.mutate_data_t, ()),
|
|
(m.mutate_at_t, (0, 0)),
|
|
):
|
|
with pytest.raises(ValueError) as excinfo:
|
|
func(arr, *args)
|
|
assert str(excinfo.value) == "array is not writeable"
|
|
|
|
|
|
def test_mutate_data(arr):
|
|
assert all(m.mutate_data(arr).ravel() == [2, 4, 6, 8, 10, 12])
|
|
assert all(m.mutate_data(arr).ravel() == [4, 8, 12, 16, 20, 24])
|
|
assert all(m.mutate_data(arr, 1).ravel() == [4, 8, 12, 32, 40, 48])
|
|
assert all(m.mutate_data(arr, 0, 1).ravel() == [4, 16, 24, 64, 80, 96])
|
|
assert all(m.mutate_data(arr, 1, 2).ravel() == [4, 16, 24, 64, 80, 192])
|
|
|
|
assert all(m.mutate_data_t(arr).ravel() == [5, 17, 25, 65, 81, 193])
|
|
assert all(m.mutate_data_t(arr).ravel() == [6, 18, 26, 66, 82, 194])
|
|
assert all(m.mutate_data_t(arr, 1).ravel() == [6, 18, 26, 67, 83, 195])
|
|
assert all(m.mutate_data_t(arr, 0, 1).ravel() == [6, 19, 27, 68, 84, 196])
|
|
assert all(m.mutate_data_t(arr, 1, 2).ravel() == [6, 19, 27, 68, 84, 197])
|
|
|
|
|
|
def test_bounds_check(arr):
|
|
for func in (
|
|
m.index_at,
|
|
m.index_at_t,
|
|
m.data,
|
|
m.data_t,
|
|
m.mutate_data,
|
|
m.mutate_data_t,
|
|
m.at_t,
|
|
m.mutate_at_t,
|
|
):
|
|
with pytest.raises(IndexError) as excinfo:
|
|
func(arr, 2, 0)
|
|
assert str(excinfo.value) == "index 2 is out of bounds for axis 0 with size 2"
|
|
with pytest.raises(IndexError) as excinfo:
|
|
func(arr, 0, 4)
|
|
assert str(excinfo.value) == "index 4 is out of bounds for axis 1 with size 3"
|
|
|
|
|
|
def test_make_c_f_array():
|
|
assert m.make_c_array().flags.c_contiguous
|
|
assert not m.make_c_array().flags.f_contiguous
|
|
assert m.make_f_array().flags.f_contiguous
|
|
assert not m.make_f_array().flags.c_contiguous
|
|
|
|
|
|
def test_make_empty_shaped_array():
|
|
m.make_empty_shaped_array()
|
|
|
|
# empty shape means numpy scalar, PEP 3118
|
|
assert m.scalar_int().ndim == 0
|
|
assert m.scalar_int().shape == ()
|
|
assert m.scalar_int() == 42
|
|
|
|
|
|
def test_wrap():
|
|
def assert_references(a, b, base=None):
|
|
from distutils.version import LooseVersion
|
|
|
|
if base is None:
|
|
base = a
|
|
assert a is not b
|
|
assert a.__array_interface__["data"][0] == b.__array_interface__["data"][0]
|
|
assert a.shape == b.shape
|
|
assert a.strides == b.strides
|
|
assert a.flags.c_contiguous == b.flags.c_contiguous
|
|
assert a.flags.f_contiguous == b.flags.f_contiguous
|
|
assert a.flags.writeable == b.flags.writeable
|
|
assert a.flags.aligned == b.flags.aligned
|
|
if LooseVersion(np.__version__) >= LooseVersion("1.14.0"):
|
|
assert a.flags.writebackifcopy == b.flags.writebackifcopy
|
|
else:
|
|
assert a.flags.updateifcopy == b.flags.updateifcopy
|
|
assert np.all(a == b)
|
|
assert not b.flags.owndata
|
|
assert b.base is base
|
|
if a.flags.writeable and a.ndim == 2:
|
|
a[0, 0] = 1234
|
|
assert b[0, 0] == 1234
|
|
|
|
a1 = np.array([1, 2], dtype=np.int16)
|
|
assert a1.flags.owndata and a1.base is None
|
|
a2 = m.wrap(a1)
|
|
assert_references(a1, a2)
|
|
|
|
a1 = np.array([[1, 2], [3, 4]], dtype=np.float32, order="F")
|
|
assert a1.flags.owndata and a1.base is None
|
|
a2 = m.wrap(a1)
|
|
assert_references(a1, a2)
|
|
|
|
a1 = np.array([[1, 2], [3, 4]], dtype=np.float32, order="C")
|
|
a1.flags.writeable = False
|
|
a2 = m.wrap(a1)
|
|
assert_references(a1, a2)
|
|
|
|
a1 = np.random.random((4, 4, 4))
|
|
a2 = m.wrap(a1)
|
|
assert_references(a1, a2)
|
|
|
|
a1t = a1.transpose()
|
|
a2 = m.wrap(a1t)
|
|
assert_references(a1t, a2, a1)
|
|
|
|
a1d = a1.diagonal()
|
|
a2 = m.wrap(a1d)
|
|
assert_references(a1d, a2, a1)
|
|
|
|
a1m = a1[::-1, ::-1, ::-1]
|
|
a2 = m.wrap(a1m)
|
|
assert_references(a1m, a2, a1)
|
|
|
|
|
|
def test_numpy_view(capture):
|
|
with capture:
|
|
ac = m.ArrayClass()
|
|
ac_view_1 = ac.numpy_view()
|
|
ac_view_2 = ac.numpy_view()
|
|
assert np.all(ac_view_1 == np.array([1, 2], dtype=np.int32))
|
|
del ac
|
|
pytest.gc_collect()
|
|
assert (
|
|
capture
|
|
== """
|
|
ArrayClass()
|
|
ArrayClass::numpy_view()
|
|
ArrayClass::numpy_view()
|
|
"""
|
|
)
|
|
ac_view_1[0] = 4
|
|
ac_view_1[1] = 3
|
|
assert ac_view_2[0] == 4
|
|
assert ac_view_2[1] == 3
|
|
with capture:
|
|
del ac_view_1
|
|
del ac_view_2
|
|
pytest.gc_collect()
|
|
pytest.gc_collect()
|
|
assert (
|
|
capture
|
|
== """
|
|
~ArrayClass()
|
|
"""
|
|
)
|
|
|
|
|
|
def test_cast_numpy_int64_to_uint64():
|
|
m.function_taking_uint64(123)
|
|
m.function_taking_uint64(np.uint64(123))
|
|
|
|
|
|
def test_isinstance():
|
|
assert m.isinstance_untyped(np.array([1, 2, 3]), "not an array")
|
|
assert m.isinstance_typed(np.array([1.0, 2.0, 3.0]))
|
|
|
|
|
|
def test_constructors():
|
|
defaults = m.default_constructors()
|
|
for a in defaults.values():
|
|
assert a.size == 0
|
|
assert defaults["array"].dtype == np.array([]).dtype
|
|
assert defaults["array_t<int32>"].dtype == np.int32
|
|
assert defaults["array_t<double>"].dtype == np.float64
|
|
|
|
results = m.converting_constructors([1, 2, 3])
|
|
for a in results.values():
|
|
np.testing.assert_array_equal(a, [1, 2, 3])
|
|
assert results["array"].dtype == np.int_
|
|
assert results["array_t<int32>"].dtype == np.int32
|
|
assert results["array_t<double>"].dtype == np.float64
|
|
|
|
|
|
def test_overload_resolution(msg):
|
|
# Exact overload matches:
|
|
assert m.overloaded(np.array([1], dtype="float64")) == "double"
|
|
assert m.overloaded(np.array([1], dtype="float32")) == "float"
|
|
assert m.overloaded(np.array([1], dtype="ushort")) == "unsigned short"
|
|
assert m.overloaded(np.array([1], dtype="intc")) == "int"
|
|
assert m.overloaded(np.array([1], dtype="longlong")) == "long long"
|
|
assert m.overloaded(np.array([1], dtype="complex")) == "double complex"
|
|
assert m.overloaded(np.array([1], dtype="csingle")) == "float complex"
|
|
|
|
# No exact match, should call first convertible version:
|
|
assert m.overloaded(np.array([1], dtype="uint8")) == "double"
|
|
|
|
with pytest.raises(TypeError) as excinfo:
|
|
m.overloaded("not an array")
|
|
assert (
|
|
msg(excinfo.value)
|
|
== """
|
|
overloaded(): incompatible function arguments. The following argument types are supported:
|
|
1. (arg0: numpy.ndarray[numpy.float64]) -> str
|
|
2. (arg0: numpy.ndarray[numpy.float32]) -> str
|
|
3. (arg0: numpy.ndarray[numpy.int32]) -> str
|
|
4. (arg0: numpy.ndarray[numpy.uint16]) -> str
|
|
5. (arg0: numpy.ndarray[numpy.int64]) -> str
|
|
6. (arg0: numpy.ndarray[numpy.complex128]) -> str
|
|
7. (arg0: numpy.ndarray[numpy.complex64]) -> str
|
|
|
|
Invoked with: 'not an array'
|
|
"""
|
|
)
|
|
|
|
assert m.overloaded2(np.array([1], dtype="float64")) == "double"
|
|
assert m.overloaded2(np.array([1], dtype="float32")) == "float"
|
|
assert m.overloaded2(np.array([1], dtype="complex64")) == "float complex"
|
|
assert m.overloaded2(np.array([1], dtype="complex128")) == "double complex"
|
|
assert m.overloaded2(np.array([1], dtype="float32")) == "float"
|
|
|
|
assert m.overloaded3(np.array([1], dtype="float64")) == "double"
|
|
assert m.overloaded3(np.array([1], dtype="intc")) == "int"
|
|
expected_exc = """
|
|
overloaded3(): incompatible function arguments. The following argument types are supported:
|
|
1. (arg0: numpy.ndarray[numpy.int32]) -> str
|
|
2. (arg0: numpy.ndarray[numpy.float64]) -> str
|
|
|
|
Invoked with: """
|
|
|
|
with pytest.raises(TypeError) as excinfo:
|
|
m.overloaded3(np.array([1], dtype="uintc"))
|
|
assert msg(excinfo.value) == expected_exc + repr(np.array([1], dtype="uint32"))
|
|
with pytest.raises(TypeError) as excinfo:
|
|
m.overloaded3(np.array([1], dtype="float32"))
|
|
assert msg(excinfo.value) == expected_exc + repr(np.array([1.0], dtype="float32"))
|
|
with pytest.raises(TypeError) as excinfo:
|
|
m.overloaded3(np.array([1], dtype="complex"))
|
|
assert msg(excinfo.value) == expected_exc + repr(np.array([1.0 + 0.0j]))
|
|
|
|
# Exact matches:
|
|
assert m.overloaded4(np.array([1], dtype="double")) == "double"
|
|
assert m.overloaded4(np.array([1], dtype="longlong")) == "long long"
|
|
# Non-exact matches requiring conversion. Since float to integer isn't a
|
|
# save conversion, it should go to the double overload, but short can go to
|
|
# either (and so should end up on the first-registered, the long long).
|
|
assert m.overloaded4(np.array([1], dtype="float32")) == "double"
|
|
assert m.overloaded4(np.array([1], dtype="short")) == "long long"
|
|
|
|
assert m.overloaded5(np.array([1], dtype="double")) == "double"
|
|
assert m.overloaded5(np.array([1], dtype="uintc")) == "unsigned int"
|
|
assert m.overloaded5(np.array([1], dtype="float32")) == "unsigned int"
|
|
|
|
|
|
def test_greedy_string_overload():
|
|
"""Tests fix for #685 - ndarray shouldn't go to std::string overload"""
|
|
|
|
assert m.issue685("abc") == "string"
|
|
assert m.issue685(np.array([97, 98, 99], dtype="b")) == "array"
|
|
assert m.issue685(123) == "other"
|
|
|
|
|
|
def test_array_unchecked_fixed_dims(msg):
|
|
z1 = np.array([[1, 2], [3, 4]], dtype="float64")
|
|
m.proxy_add2(z1, 10)
|
|
assert np.all(z1 == [[11, 12], [13, 14]])
|
|
|
|
with pytest.raises(ValueError) as excinfo:
|
|
m.proxy_add2(np.array([1.0, 2, 3]), 5.0)
|
|
assert (
|
|
msg(excinfo.value) == "array has incorrect number of dimensions: 1; expected 2"
|
|
)
|
|
|
|
expect_c = np.ndarray(shape=(3, 3, 3), buffer=np.array(range(3, 30)), dtype="int")
|
|
assert np.all(m.proxy_init3(3.0) == expect_c)
|
|
expect_f = np.transpose(expect_c)
|
|
assert np.all(m.proxy_init3F(3.0) == expect_f)
|
|
|
|
assert m.proxy_squared_L2_norm(np.array(range(6))) == 55
|
|
assert m.proxy_squared_L2_norm(np.array(range(6), dtype="float64")) == 55
|
|
|
|
assert m.proxy_auxiliaries2(z1) == [11, 11, True, 2, 8, 2, 2, 4, 32]
|
|
assert m.proxy_auxiliaries2(z1) == m.array_auxiliaries2(z1)
|
|
|
|
assert m.proxy_auxiliaries1_const_ref(z1[0, :])
|
|
assert m.proxy_auxiliaries2_const_ref(z1)
|
|
|
|
|
|
def test_array_unchecked_dyn_dims():
|
|
z1 = np.array([[1, 2], [3, 4]], dtype="float64")
|
|
m.proxy_add2_dyn(z1, 10)
|
|
assert np.all(z1 == [[11, 12], [13, 14]])
|
|
|
|
expect_c = np.ndarray(shape=(3, 3, 3), buffer=np.array(range(3, 30)), dtype="int")
|
|
assert np.all(m.proxy_init3_dyn(3.0) == expect_c)
|
|
|
|
assert m.proxy_auxiliaries2_dyn(z1) == [11, 11, True, 2, 8, 2, 2, 4, 32]
|
|
assert m.proxy_auxiliaries2_dyn(z1) == m.array_auxiliaries2(z1)
|
|
|
|
|
|
def test_array_failure():
|
|
with pytest.raises(ValueError) as excinfo:
|
|
m.array_fail_test()
|
|
assert str(excinfo.value) == "cannot create a pybind11::array from a nullptr"
|
|
|
|
with pytest.raises(ValueError) as excinfo:
|
|
m.array_t_fail_test()
|
|
assert str(excinfo.value) == "cannot create a pybind11::array_t from a nullptr"
|
|
|
|
with pytest.raises(ValueError) as excinfo:
|
|
m.array_fail_test_negative_size()
|
|
assert str(excinfo.value) == "negative dimensions are not allowed"
|
|
|
|
|
|
def test_initializer_list():
|
|
assert m.array_initializer_list1().shape == (1,)
|
|
assert m.array_initializer_list2().shape == (1, 2)
|
|
assert m.array_initializer_list3().shape == (1, 2, 3)
|
|
assert m.array_initializer_list4().shape == (1, 2, 3, 4)
|
|
|
|
|
|
def test_array_resize():
|
|
a = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype="float64")
|
|
m.array_reshape2(a)
|
|
assert a.size == 9
|
|
assert np.all(a == [[1, 2, 3], [4, 5, 6], [7, 8, 9]])
|
|
|
|
# total size change should succced with refcheck off
|
|
m.array_resize3(a, 4, False)
|
|
assert a.size == 64
|
|
# ... and fail with refcheck on
|
|
try:
|
|
m.array_resize3(a, 3, True)
|
|
except ValueError as e:
|
|
assert str(e).startswith("cannot resize an array")
|
|
# transposed array doesn't own data
|
|
b = a.transpose()
|
|
try:
|
|
m.array_resize3(b, 3, False)
|
|
except ValueError as e:
|
|
assert str(e).startswith("cannot resize this array: it does not own its data")
|
|
# ... but reshape should be fine
|
|
m.array_reshape2(b)
|
|
assert b.shape == (8, 8)
|
|
|
|
|
|
@pytest.mark.xfail("env.PYPY")
|
|
def test_array_create_and_resize():
|
|
a = m.create_and_resize(2)
|
|
assert a.size == 4
|
|
assert np.all(a == 42.0)
|
|
|
|
|
|
def test_array_view():
|
|
a = np.ones(100 * 4).astype("uint8")
|
|
a_float_view = m.array_view(a, "float32")
|
|
assert a_float_view.shape == (100 * 1,) # 1 / 4 bytes = 8 / 32
|
|
|
|
a_int16_view = m.array_view(a, "int16") # 1 / 2 bytes = 16 / 32
|
|
assert a_int16_view.shape == (100 * 2,)
|
|
|
|
|
|
def test_array_view_invalid():
|
|
a = np.ones(100 * 4).astype("uint8")
|
|
with pytest.raises(TypeError):
|
|
m.array_view(a, "deadly_dtype")
|
|
|
|
|
|
def test_reshape_initializer_list():
|
|
a = np.arange(2 * 7 * 3) + 1
|
|
x = m.reshape_initializer_list(a, 2, 7, 3)
|
|
assert x.shape == (2, 7, 3)
|
|
assert list(x[1][4]) == [34, 35, 36]
|
|
with pytest.raises(ValueError) as excinfo:
|
|
m.reshape_initializer_list(a, 1, 7, 3)
|
|
assert str(excinfo.value) == "cannot reshape array of size 42 into shape (1,7,3)"
|
|
|
|
|
|
def test_reshape_tuple():
|
|
a = np.arange(3 * 7 * 2) + 1
|
|
x = m.reshape_tuple(a, (3, 7, 2))
|
|
assert x.shape == (3, 7, 2)
|
|
assert list(x[1][4]) == [23, 24]
|
|
y = m.reshape_tuple(x, (x.size,))
|
|
assert y.shape == (42,)
|
|
with pytest.raises(ValueError) as excinfo:
|
|
m.reshape_tuple(a, (3, 7, 1))
|
|
assert str(excinfo.value) == "cannot reshape array of size 42 into shape (3,7,1)"
|
|
with pytest.raises(ValueError) as excinfo:
|
|
m.reshape_tuple(a, ())
|
|
assert str(excinfo.value) == "cannot reshape array of size 42 into shape ()"
|
|
|
|
|
|
def test_index_using_ellipsis():
|
|
a = m.index_using_ellipsis(np.zeros((5, 6, 7)))
|
|
assert a.shape == (6,)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"test_func",
|
|
[
|
|
m.test_fmt_desc_float,
|
|
m.test_fmt_desc_double,
|
|
m.test_fmt_desc_const_float,
|
|
m.test_fmt_desc_const_double,
|
|
],
|
|
)
|
|
def test_format_descriptors_for_floating_point_types(test_func):
|
|
assert "numpy.ndarray[numpy.float" in test_func.__doc__
|
|
|
|
|
|
@pytest.mark.parametrize("forcecast", [False, True])
|
|
@pytest.mark.parametrize("contiguity", [None, "C", "F"])
|
|
@pytest.mark.parametrize("noconvert", [False, True])
|
|
@pytest.mark.filterwarnings(
|
|
"ignore:Casting complex values to real discards the imaginary part:numpy.ComplexWarning"
|
|
)
|
|
def test_argument_conversions(forcecast, contiguity, noconvert):
|
|
function_name = "accept_double"
|
|
if contiguity == "C":
|
|
function_name += "_c_style"
|
|
elif contiguity == "F":
|
|
function_name += "_f_style"
|
|
if forcecast:
|
|
function_name += "_forcecast"
|
|
if noconvert:
|
|
function_name += "_noconvert"
|
|
function = getattr(m, function_name)
|
|
|
|
for dtype in [np.dtype("float32"), np.dtype("float64"), np.dtype("complex128")]:
|
|
for order in ["C", "F"]:
|
|
for shape in [(2, 2), (1, 3, 1, 1), (1, 1, 1), (0,)]:
|
|
if not noconvert:
|
|
# If noconvert is not passed, only complex128 needs to be truncated and
|
|
# "cannot be safely obtained". So without `forcecast`, the argument shouldn't
|
|
# be accepted.
|
|
should_raise = dtype.name == "complex128" and not forcecast
|
|
else:
|
|
# If noconvert is passed, only float64 and the matching order is accepted.
|
|
# If at most one dimension has a size greater than 1, the array is also
|
|
# trivially contiguous.
|
|
trivially_contiguous = sum(1 for d in shape if d > 1) <= 1
|
|
should_raise = dtype.name != "float64" or (
|
|
contiguity is not None
|
|
and contiguity != order
|
|
and not trivially_contiguous
|
|
)
|
|
|
|
array = np.zeros(shape, dtype=dtype, order=order)
|
|
if not should_raise:
|
|
function(array)
|
|
else:
|
|
with pytest.raises(
|
|
TypeError, match="incompatible function arguments"
|
|
):
|
|
function(array)
|
|
|
|
|
|
@pytest.mark.xfail("env.PYPY")
|
|
def test_dtype_refcount_leak():
|
|
from sys import getrefcount
|
|
|
|
dtype = np.dtype(np.float_)
|
|
a = np.array([1], dtype=dtype)
|
|
before = getrefcount(dtype)
|
|
m.ndim(a)
|
|
after = getrefcount(dtype)
|
|
assert after == before
|