| # -*- 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 |
