1# -*- coding: utf-8 -*- 2import pytest 3 4from pybind11_tests import numpy_vectorize as m 5 6np = pytest.importorskip("numpy") 7 8 9def test_vectorize(capture): 10 assert np.isclose(m.vectorized_func3(np.array(3 + 7j)), [6 + 14j]) 11 12 for f in [m.vectorized_func, m.vectorized_func2]: 13 with capture: 14 assert np.isclose(f(1, 2, 3), 6) 15 assert capture == "my_func(x:int=1, y:float=2, z:float=3)" 16 with capture: 17 assert np.isclose(f(np.array(1), np.array(2), 3), 6) 18 assert capture == "my_func(x:int=1, y:float=2, z:float=3)" 19 with capture: 20 assert np.allclose(f(np.array([1, 3]), np.array([2, 4]), 3), [6, 36]) 21 assert ( 22 capture 23 == """ 24 my_func(x:int=1, y:float=2, z:float=3) 25 my_func(x:int=3, y:float=4, z:float=3) 26 """ 27 ) 28 with capture: 29 a = np.array([[1, 2], [3, 4]], order="F") 30 b = np.array([[10, 20], [30, 40]], order="F") 31 c = 3 32 result = f(a, b, c) 33 assert np.allclose(result, a * b * c) 34 assert result.flags.f_contiguous 35 # All inputs are F order and full or singletons, so we the result is in col-major order: 36 assert ( 37 capture 38 == """ 39 my_func(x:int=1, y:float=10, z:float=3) 40 my_func(x:int=3, y:float=30, z:float=3) 41 my_func(x:int=2, y:float=20, z:float=3) 42 my_func(x:int=4, y:float=40, z:float=3) 43 """ 44 ) 45 with capture: 46 a, b, c = ( 47 np.array([[1, 3, 5], [7, 9, 11]]), 48 np.array([[2, 4, 6], [8, 10, 12]]), 49 3, 50 ) 51 assert np.allclose(f(a, b, c), a * b * c) 52 assert ( 53 capture 54 == """ 55 my_func(x:int=1, y:float=2, z:float=3) 56 my_func(x:int=3, y:float=4, z:float=3) 57 my_func(x:int=5, y:float=6, z:float=3) 58 my_func(x:int=7, y:float=8, z:float=3) 59 my_func(x:int=9, y:float=10, z:float=3) 60 my_func(x:int=11, y:float=12, z:float=3) 61 """ 62 ) 63 with capture: 64 a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2 65 assert np.allclose(f(a, b, c), a * b * c) 66 assert ( 67 capture 68 == """ 69 my_func(x:int=1, y:float=2, z:float=2) 70 my_func(x:int=2, y:float=3, z:float=2) 71 my_func(x:int=3, y:float=4, z:float=2) 72 my_func(x:int=4, y:float=2, z:float=2) 73 my_func(x:int=5, y:float=3, z:float=2) 74 my_func(x:int=6, y:float=4, z:float=2) 75 """ 76 ) 77 with capture: 78 a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2 79 assert np.allclose(f(a, b, c), a * b * c) 80 assert ( 81 capture 82 == """ 83 my_func(x:int=1, y:float=2, z:float=2) 84 my_func(x:int=2, y:float=2, z:float=2) 85 my_func(x:int=3, y:float=2, z:float=2) 86 my_func(x:int=4, y:float=3, z:float=2) 87 my_func(x:int=5, y:float=3, z:float=2) 88 my_func(x:int=6, y:float=3, z:float=2) 89 """ 90 ) 91 with capture: 92 a, b, c = ( 93 np.array([[1, 2, 3], [4, 5, 6]], order="F"), 94 np.array([[2], [3]]), 95 2, 96 ) 97 assert np.allclose(f(a, b, c), a * b * c) 98 assert ( 99 capture 100 == """ 101 my_func(x:int=1, y:float=2, z:float=2) 102 my_func(x:int=2, y:float=2, z:float=2) 103 my_func(x:int=3, y:float=2, z:float=2) 104 my_func(x:int=4, y:float=3, z:float=2) 105 my_func(x:int=5, y:float=3, z:float=2) 106 my_func(x:int=6, y:float=3, z:float=2) 107 """ 108 ) 109 with capture: 110 a, b, c = np.array([[1, 2, 3], [4, 5, 6]])[::, ::2], np.array([[2], [3]]), 2 111 assert np.allclose(f(a, b, c), a * b * c) 112 assert ( 113 capture 114 == """ 115 my_func(x:int=1, y:float=2, z:float=2) 116 my_func(x:int=3, y:float=2, z:float=2) 117 my_func(x:int=4, y:float=3, z:float=2) 118 my_func(x:int=6, y:float=3, z:float=2) 119 """ 120 ) 121 with capture: 122 a, b, c = ( 123 np.array([[1, 2, 3], [4, 5, 6]], order="F")[::, ::2], 124 np.array([[2], [3]]), 125 2, 126 ) 127 assert np.allclose(f(a, b, c), a * b * c) 128 assert ( 129 capture 130 == """ 131 my_func(x:int=1, y:float=2, z:float=2) 132 my_func(x:int=3, y:float=2, z:float=2) 133 my_func(x:int=4, y:float=3, z:float=2) 134 my_func(x:int=6, y:float=3, z:float=2) 135 """ 136 ) 137 138 139def test_type_selection(): 140 assert m.selective_func(np.array([1], dtype=np.int32)) == "Int branch taken." 141 assert m.selective_func(np.array([1.0], dtype=np.float32)) == "Float branch taken." 142 assert ( 143 m.selective_func(np.array([1.0j], dtype=np.complex64)) 144 == "Complex float branch taken." 145 ) 146 147 148def test_docs(doc): 149 assert ( 150 doc(m.vectorized_func) 151 == """ 152 vectorized_func(arg0: numpy.ndarray[numpy.int32], arg1: numpy.ndarray[numpy.float32], arg2: numpy.ndarray[numpy.float64]) -> object 153 """ # noqa: E501 line too long 154 ) 155 156 157def test_trivial_broadcasting(): 158 trivial, vectorized_is_trivial = m.trivial, m.vectorized_is_trivial 159 160 assert vectorized_is_trivial(1, 2, 3) == trivial.c_trivial 161 assert vectorized_is_trivial(np.array(1), np.array(2), 3) == trivial.c_trivial 162 assert ( 163 vectorized_is_trivial(np.array([1, 3]), np.array([2, 4]), 3) 164 == trivial.c_trivial 165 ) 166 assert trivial.c_trivial == vectorized_is_trivial( 167 np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3 168 ) 169 assert ( 170 vectorized_is_trivial(np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2) 171 == trivial.non_trivial 172 ) 173 assert ( 174 vectorized_is_trivial(np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2) 175 == trivial.non_trivial 176 ) 177 z1 = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype="int32") 178 z2 = np.array(z1, dtype="float32") 179 z3 = np.array(z1, dtype="float64") 180 assert vectorized_is_trivial(z1, z2, z3) == trivial.c_trivial 181 assert vectorized_is_trivial(1, z2, z3) == trivial.c_trivial 182 assert vectorized_is_trivial(z1, 1, z3) == trivial.c_trivial 183 assert vectorized_is_trivial(z1, z2, 1) == trivial.c_trivial 184 assert vectorized_is_trivial(z1[::2, ::2], 1, 1) == trivial.non_trivial 185 assert vectorized_is_trivial(1, 1, z1[::2, ::2]) == trivial.c_trivial 186 assert vectorized_is_trivial(1, 1, z3[::2, ::2]) == trivial.non_trivial 187 assert vectorized_is_trivial(z1, 1, z3[1::4, 1::4]) == trivial.c_trivial 188 189 y1 = np.array(z1, order="F") 190 y2 = np.array(y1) 191 y3 = np.array(y1) 192 assert vectorized_is_trivial(y1, y2, y3) == trivial.f_trivial 193 assert vectorized_is_trivial(y1, 1, 1) == trivial.f_trivial 194 assert vectorized_is_trivial(1, y2, 1) == trivial.f_trivial 195 assert vectorized_is_trivial(1, 1, y3) == trivial.f_trivial 196 assert vectorized_is_trivial(y1, z2, 1) == trivial.non_trivial 197 assert vectorized_is_trivial(z1[1::4, 1::4], y2, 1) == trivial.f_trivial 198 assert vectorized_is_trivial(y1[1::4, 1::4], z2, 1) == trivial.c_trivial 199 200 assert m.vectorized_func(z1, z2, z3).flags.c_contiguous 201 assert m.vectorized_func(y1, y2, y3).flags.f_contiguous 202 assert m.vectorized_func(z1, 1, 1).flags.c_contiguous 203 assert m.vectorized_func(1, y2, 1).flags.f_contiguous 204 assert m.vectorized_func(z1[1::4, 1::4], y2, 1).flags.f_contiguous 205 assert m.vectorized_func(y1[1::4, 1::4], z2, 1).flags.c_contiguous 206 207 208def test_passthrough_arguments(doc): 209 assert doc(m.vec_passthrough) == ( 210 "vec_passthrough(" 211 + ", ".join( 212 [ 213 "arg0: float", 214 "arg1: numpy.ndarray[numpy.float64]", 215 "arg2: numpy.ndarray[numpy.float64]", 216 "arg3: numpy.ndarray[numpy.int32]", 217 "arg4: int", 218 "arg5: m.numpy_vectorize.NonPODClass", 219 "arg6: numpy.ndarray[numpy.float64]", 220 ] 221 ) 222 + ") -> object" 223 ) 224 225 b = np.array([[10, 20, 30]], dtype="float64") 226 c = np.array([100, 200]) # NOT a vectorized argument 227 d = np.array([[1000], [2000], [3000]], dtype="int") 228 g = np.array([[1000000, 2000000, 3000000]], dtype="int") # requires casting 229 assert np.all( 230 m.vec_passthrough(1, b, c, d, 10000, m.NonPODClass(100000), g) 231 == np.array( 232 [ 233 [1111111, 2111121, 3111131], 234 [1112111, 2112121, 3112131], 235 [1113111, 2113121, 3113131], 236 ] 237 ) 238 ) 239 240 241def test_method_vectorization(): 242 o = m.VectorizeTestClass(3) 243 x = np.array([1, 2], dtype="int") 244 y = np.array([[10], [20]], dtype="float32") 245 assert np.all(o.method(x, y) == [[14, 15], [24, 25]]) 246 247 248def test_array_collapse(): 249 assert not isinstance(m.vectorized_func(1, 2, 3), np.ndarray) 250 assert not isinstance(m.vectorized_func(np.array(1), 2, 3), np.ndarray) 251 z = m.vectorized_func([1], 2, 3) 252 assert isinstance(z, np.ndarray) 253 assert z.shape == (1,) 254 z = m.vectorized_func(1, [[[2]]], 3) 255 assert isinstance(z, np.ndarray) 256 assert z.shape == (1, 1, 1) 257 258 259def test_vectorized_noreturn(): 260 x = m.NonPODClass(0) 261 assert x.value == 0 262 m.add_to(x, [1, 2, 3, 4]) 263 assert x.value == 10 264 m.add_to(x, 1) 265 assert x.value == 11 266 m.add_to(x, [[1, 1], [2, 3]]) 267 assert x.value == 18 268