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-rw-r--r--3rdparty/pybind11/tests/test_numpy_vectorize.py196
1 files changed, 196 insertions, 0 deletions
diff --git a/3rdparty/pybind11/tests/test_numpy_vectorize.py b/3rdparty/pybind11/tests/test_numpy_vectorize.py
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+++ b/3rdparty/pybind11/tests/test_numpy_vectorize.py
@@ -0,0 +1,196 @@
+import pytest
+from pybind11_tests import numpy_vectorize as m
+
+pytestmark = pytest.requires_numpy
+
+with pytest.suppress(ImportError):
+ import numpy as np
+
+
+def test_vectorize(capture):
+ assert np.isclose(m.vectorized_func3(np.array(3 + 7j)), [6 + 14j])
+
+ for f in [m.vectorized_func, m.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():
+ assert m.selective_func(np.array([1], dtype=np.int32)) == "Int branch taken."
+ assert m.selective_func(np.array([1.0], dtype=np.float32)) == "Float branch taken."
+ assert m.selective_func(np.array([1.0j], dtype=np.complex64)) == "Complex float branch taken."
+
+
+def test_docs(doc):
+ assert doc(m.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():
+ trivial, vectorized_is_trivial = m.trivial, m.vectorized_is_trivial
+
+ 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 m.vectorized_func(z1, z2, z3).flags.c_contiguous
+ assert m.vectorized_func(y1, y2, y3).flags.f_contiguous
+ assert m.vectorized_func(z1, 1, 1).flags.c_contiguous
+ assert m.vectorized_func(1, y2, 1).flags.f_contiguous
+ assert m.vectorized_func(z1[1::4, 1::4], y2, 1).flags.f_contiguous
+ assert m.vectorized_func(y1[1::4, 1::4], z2, 1).flags.c_contiguous
+
+
+def test_passthrough_arguments(doc):
+ assert doc(m.vec_passthrough) == (
+ "vec_passthrough(" + ", ".join([
+ "arg0: float",
+ "arg1: numpy.ndarray[float64]",
+ "arg2: numpy.ndarray[float64]",
+ "arg3: numpy.ndarray[int32]",
+ "arg4: int",
+ "arg5: m.numpy_vectorize.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(
+ m.vec_passthrough(1, b, c, d, 10000, m.NonPODClass(100000), g) ==
+ np.array([[1111111, 2111121, 3111131],
+ [1112111, 2112121, 3112131],
+ [1113111, 2113121, 3113131]]))
+
+
+def test_method_vectorization():
+ o = m.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():
+ assert not isinstance(m.vectorized_func(1, 2, 3), np.ndarray)
+ assert not isinstance(m.vectorized_func(np.array(1), 2, 3), np.ndarray)
+ z = m.vectorized_func([1], 2, 3)
+ assert isinstance(z, np.ndarray)
+ assert z.shape == (1, )
+ z = m.vectorized_func(1, [[[2]]], 3)
+ assert isinstance(z, np.ndarray)
+ assert z.shape == (1, 1, 1)
generated by cgit v1.2.3 (git 2.25.1) at 2024-07-08 02:20:53 +0000