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import pytest
pytestmark = pytest.requires_numpy
with pytest.suppress(ImportError): import numpy as np
def test_vectorize(capture): from pybind11_tests import vectorized_func, vectorized_func2, vectorized_func3
assert np.isclose(vectorized_func3(np.array(3 + 7j)), [6 + 14j])
for f in [vectorized_func, vectorized_func2]: with capture: assert np.isclose(f(1, 2, 3), 6) assert capture == "my_func(x:int=1, y:float=2, z:float=3)" with capture: assert np.isclose(f(np.array(1), np.array(2), 3), 6) assert capture == "my_func(x:int=1, y:float=2, z:float=3)" with capture: assert np.allclose(f(np.array([1, 3]), np.array([2, 4]), 3), [6, 36]) assert capture == """
my_func(x:int=1, y:float=2, z:float=3) my_func(x:int=3, y:float=4, z:float=3) """
with capture: a = np.array([[1, 2], [3, 4]], order='F') b = np.array([[10, 20], [30, 40]], order='F') c = 3 result = f(a, b, c) assert np.allclose(result, a * b * c) assert result.flags.f_contiguous # All inputs are F order and full or singletons, so we the result is in col-major order: assert capture == """
my_func(x:int=1, y:float=10, z:float=3) my_func(x:int=3, y:float=30, z:float=3) my_func(x:int=2, y:float=20, z:float=3) my_func(x:int=4, y:float=40, z:float=3) """
with capture: a, b, c = np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3 assert np.allclose(f(a, b, c), a * b * c) assert capture == """
my_func(x:int=1, y:float=2, z:float=3) my_func(x:int=3, y:float=4, z:float=3) my_func(x:int=5, y:float=6, z:float=3) my_func(x:int=7, y:float=8, z:float=3) my_func(x:int=9, y:float=10, z:float=3) my_func(x:int=11, y:float=12, z:float=3) """
with capture: a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2 assert np.allclose(f(a, b, c), a * b * c) assert capture == """
my_func(x:int=1, y:float=2, z:float=2) my_func(x:int=2, y:float=3, z:float=2) my_func(x:int=3, y:float=4, z:float=2) my_func(x:int=4, y:float=2, z:float=2) my_func(x:int=5, y:float=3, z:float=2) my_func(x:int=6, y:float=4, z:float=2) """
with capture: a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2 assert np.allclose(f(a, b, c), a * b * c) assert capture == """
my_func(x:int=1, y:float=2, z:float=2) my_func(x:int=2, y:float=2, z:float=2) my_func(x:int=3, y:float=2, z:float=2) my_func(x:int=4, y:float=3, z:float=2) my_func(x:int=5, y:float=3, z:float=2) my_func(x:int=6, y:float=3, z:float=2) """
with capture: a, b, c = np.array([[1, 2, 3], [4, 5, 6]], order='F'), np.array([[2], [3]]), 2 assert np.allclose(f(a, b, c), a * b * c) assert capture == """
my_func(x:int=1, y:float=2, z:float=2) my_func(x:int=2, y:float=2, z:float=2) my_func(x:int=3, y:float=2, z:float=2) my_func(x:int=4, y:float=3, z:float=2) my_func(x:int=5, y:float=3, z:float=2) my_func(x:int=6, y:float=3, z:float=2) """
with capture: a, b, c = np.array([[1, 2, 3], [4, 5, 6]])[::, ::2], np.array([[2], [3]]), 2 assert np.allclose(f(a, b, c), a * b * c) assert capture == """
my_func(x:int=1, y:float=2, z:float=2) my_func(x:int=3, y:float=2, z:float=2) my_func(x:int=4, y:float=3, z:float=2) my_func(x:int=6, y:float=3, z:float=2) """
with capture: a, b, c = np.array([[1, 2, 3], [4, 5, 6]], order='F')[::, ::2], np.array([[2], [3]]), 2 assert np.allclose(f(a, b, c), a * b * c) assert capture == """
my_func(x:int=1, y:float=2, z:float=2) my_func(x:int=3, y:float=2, z:float=2) my_func(x:int=4, y:float=3, z:float=2) my_func(x:int=6, y:float=3, z:float=2) """
def test_type_selection(): from pybind11_tests import selective_func
assert selective_func(np.array([1], dtype=np.int32)) == "Int branch taken." assert selective_func(np.array([1.0], dtype=np.float32)) == "Float branch taken." assert selective_func(np.array([1.0j], dtype=np.complex64)) == "Complex float branch taken."
def test_docs(doc): from pybind11_tests import vectorized_func
assert doc(vectorized_func) == """
vectorized_func(arg0: numpy.ndarray[int32], arg1: numpy.ndarray[float32], arg2: numpy.ndarray[float64]) -> object """ # noqa: E501 line too long
def test_trivial_broadcasting(): from pybind11_tests import vectorized_is_trivial, trivial, vectorized_func
assert vectorized_is_trivial(1, 2, 3) == trivial.c_trivial assert vectorized_is_trivial(np.array(1), np.array(2), 3) == trivial.c_trivial assert vectorized_is_trivial(np.array([1, 3]), np.array([2, 4]), 3) == trivial.c_trivial assert trivial.c_trivial == vectorized_is_trivial( np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3) assert vectorized_is_trivial( np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2) == trivial.non_trivial assert vectorized_is_trivial( np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2) == trivial.non_trivial z1 = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype='int32') z2 = np.array(z1, dtype='float32') z3 = np.array(z1, dtype='float64') assert vectorized_is_trivial(z1, z2, z3) == trivial.c_trivial assert vectorized_is_trivial(1, z2, z3) == trivial.c_trivial assert vectorized_is_trivial(z1, 1, z3) == trivial.c_trivial assert vectorized_is_trivial(z1, z2, 1) == trivial.c_trivial assert vectorized_is_trivial(z1[::2, ::2], 1, 1) == trivial.non_trivial assert vectorized_is_trivial(1, 1, z1[::2, ::2]) == trivial.c_trivial assert vectorized_is_trivial(1, 1, z3[::2, ::2]) == trivial.non_trivial assert vectorized_is_trivial(z1, 1, z3[1::4, 1::4]) == trivial.c_trivial
y1 = np.array(z1, order='F') y2 = np.array(y1) y3 = np.array(y1) assert vectorized_is_trivial(y1, y2, y3) == trivial.f_trivial assert vectorized_is_trivial(y1, 1, 1) == trivial.f_trivial assert vectorized_is_trivial(1, y2, 1) == trivial.f_trivial assert vectorized_is_trivial(1, 1, y3) == trivial.f_trivial assert vectorized_is_trivial(y1, z2, 1) == trivial.non_trivial assert vectorized_is_trivial(z1[1::4, 1::4], y2, 1) == trivial.f_trivial assert vectorized_is_trivial(y1[1::4, 1::4], z2, 1) == trivial.c_trivial
assert vectorized_func(z1, z2, z3).flags.c_contiguous assert vectorized_func(y1, y2, y3).flags.f_contiguous assert vectorized_func(z1, 1, 1).flags.c_contiguous assert vectorized_func(1, y2, 1).flags.f_contiguous assert vectorized_func(z1[1::4, 1::4], y2, 1).flags.f_contiguous assert vectorized_func(y1[1::4, 1::4], z2, 1).flags.c_contiguous
def test_passthrough_arguments(doc): from pybind11_tests import vec_passthrough, NonPODClass
assert doc(vec_passthrough) == ( "vec_passthrough(" "arg0: float, arg1: numpy.ndarray[float64], arg2: numpy.ndarray[float64], " "arg3: numpy.ndarray[int32], arg4: int, arg5: m.NonPODClass, arg6: numpy.ndarray[float64]" ") -> object")
b = np.array([[10, 20, 30]], dtype='float64') c = np.array([100, 200]) # NOT a vectorized argument d = np.array([[1000], [2000], [3000]], dtype='int') g = np.array([[1000000, 2000000, 3000000]], dtype='int') # requires casting assert np.all( vec_passthrough(1, b, c, d, 10000, NonPODClass(100000), g) == np.array([[1111111, 2111121, 3111131], [1112111, 2112121, 3112131], [1113111, 2113121, 3113131]]))
def test_method_vectorization(): from pybind11_tests import VectorizeTestClass
o = VectorizeTestClass(3) x = np.array([1, 2], dtype='int') y = np.array([[10], [20]], dtype='float32') assert np.all(o.method(x, y) == [[14, 15], [24, 25]])
def test_array_collapse(): from pybind11_tests import vectorized_func
assert not isinstance(vectorized_func(1, 2, 3), np.ndarray) assert not isinstance(vectorized_func(np.array(1), 2, 3), np.ndarray) z = vectorized_func([1], 2, 3) assert isinstance(z, np.ndarray) assert z.shape == (1, ) z = vectorized_func(1, [[[2]]], 3) assert isinstance(z, np.ndarray) assert z.shape == (1, 1, 1)
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