# -*- 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"].dtype == np.int32 assert defaults["array_t"].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"].dtype == np.int32 assert results["array_t"].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.], 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.j])) # 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., 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(msg): 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(msg): 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(msg): a = m.create_and_resize(2) assert(a.size == 4) assert(np.all(a == 42.)) def test_index_using_ellipsis(): a = m.index_using_ellipsis(np.zeros((5, 6, 7))) assert a.shape == (6,) @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