test_numpy_vectorize.py
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1 import pytest
2 
3 from pybind11_tests import numpy_vectorize as m
4 
5 np = pytest.importorskip("numpy")
6 
7 
8 def test_vectorize(capture):
9  assert np.isclose(m.vectorized_func3(np.array(3 + 7j)), [6 + 14j])
10 
11  for f in [m.vectorized_func, m.vectorized_func2]:
12  with capture:
13  assert np.isclose(f(1, 2, 3), 6)
14  assert capture == "my_func(x:int=1, y:float=2, z:float=3)"
15  with capture:
16  assert np.isclose(f(np.array(1), np.array(2), 3), 6)
17  assert capture == "my_func(x:int=1, y:float=2, z:float=3)"
18  with capture:
19  assert np.allclose(f(np.array([1, 3]), np.array([2, 4]), 3), [6, 36])
20  assert (
21  capture
22  == """
23  my_func(x:int=1, y:float=2, z:float=3)
24  my_func(x:int=3, y:float=4, z:float=3)
25  """
26  )
27  with capture:
28  a = np.array([[1, 2], [3, 4]], order="F")
29  b = np.array([[10, 20], [30, 40]], order="F")
30  c = 3
31  result = f(a, b, c)
32  assert np.allclose(result, a * b * c)
33  assert result.flags.f_contiguous
34  # All inputs are F order and full or singletons, so we the result is in col-major order:
35  assert (
36  capture
37  == """
38  my_func(x:int=1, y:float=10, z:float=3)
39  my_func(x:int=3, y:float=30, z:float=3)
40  my_func(x:int=2, y:float=20, z:float=3)
41  my_func(x:int=4, y:float=40, z:float=3)
42  """
43  )
44  with capture:
45  a, b, c = (
46  np.array([[1, 3, 5], [7, 9, 11]]),
47  np.array([[2, 4, 6], [8, 10, 12]]),
48  3,
49  )
50  assert np.allclose(f(a, b, c), a * b * c)
51  assert (
52  capture
53  == """
54  my_func(x:int=1, y:float=2, z:float=3)
55  my_func(x:int=3, y:float=4, z:float=3)
56  my_func(x:int=5, y:float=6, z:float=3)
57  my_func(x:int=7, y:float=8, z:float=3)
58  my_func(x:int=9, y:float=10, z:float=3)
59  my_func(x:int=11, y:float=12, z:float=3)
60  """
61  )
62  with capture:
63  a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2
64  assert np.allclose(f(a, b, c), a * b * c)
65  assert (
66  capture
67  == """
68  my_func(x:int=1, y:float=2, z:float=2)
69  my_func(x:int=2, y:float=3, z:float=2)
70  my_func(x:int=3, y:float=4, z:float=2)
71  my_func(x:int=4, y:float=2, z:float=2)
72  my_func(x:int=5, y:float=3, z:float=2)
73  my_func(x:int=6, y:float=4, z:float=2)
74  """
75  )
76  with capture:
77  a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2
78  assert np.allclose(f(a, b, c), a * b * c)
79  assert (
80  capture
81  == """
82  my_func(x:int=1, y:float=2, z:float=2)
83  my_func(x:int=2, y:float=2, z:float=2)
84  my_func(x:int=3, y:float=2, z:float=2)
85  my_func(x:int=4, y:float=3, z:float=2)
86  my_func(x:int=5, y:float=3, z:float=2)
87  my_func(x:int=6, y:float=3, z:float=2)
88  """
89  )
90  with capture:
91  a, b, c = (
92  np.array([[1, 2, 3], [4, 5, 6]], order="F"),
93  np.array([[2], [3]]),
94  2,
95  )
96  assert np.allclose(f(a, b, c), a * b * c)
97  assert (
98  capture
99  == """
100  my_func(x:int=1, y:float=2, z:float=2)
101  my_func(x:int=2, y:float=2, z:float=2)
102  my_func(x:int=3, y:float=2, z:float=2)
103  my_func(x:int=4, y:float=3, z:float=2)
104  my_func(x:int=5, y:float=3, z:float=2)
105  my_func(x:int=6, y:float=3, z:float=2)
106  """
107  )
108  with capture:
109  a, b, c = np.array([[1, 2, 3], [4, 5, 6]])[::, ::2], np.array([[2], [3]]), 2
110  assert np.allclose(f(a, b, c), a * b * c)
111  assert (
112  capture
113  == """
114  my_func(x:int=1, y:float=2, z:float=2)
115  my_func(x:int=3, y:float=2, z:float=2)
116  my_func(x:int=4, y:float=3, z:float=2)
117  my_func(x:int=6, y:float=3, z:float=2)
118  """
119  )
120  with capture:
121  a, b, c = (
122  np.array([[1, 2, 3], [4, 5, 6]], order="F")[::, ::2],
123  np.array([[2], [3]]),
124  2,
125  )
126  assert np.allclose(f(a, b, c), a * b * c)
127  assert (
128  capture
129  == """
130  my_func(x:int=1, y:float=2, z:float=2)
131  my_func(x:int=3, y:float=2, z:float=2)
132  my_func(x:int=4, y:float=3, z:float=2)
133  my_func(x:int=6, y:float=3, z:float=2)
134  """
135  )
136 
137 
138 def test_type_selection():
139  assert m.selective_func(np.array([1], dtype=np.int32)) == "Int branch taken."
140  assert m.selective_func(np.array([1.0], dtype=np.float32)) == "Float branch taken."
141  assert (
142  m.selective_func(np.array([1.0j], dtype=np.complex64))
143  == "Complex float branch taken."
144  )
145 
146 
147 def test_docs(doc):
148  assert (
149  doc(m.vectorized_func)
150  == """
151  vectorized_func(arg0: numpy.ndarray[numpy.int32], arg1: numpy.ndarray[numpy.float32], arg2: numpy.ndarray[numpy.float64]) -> object
152  """ # noqa: E501 line too long
153  )
154 
155 
156 def test_trivial_broadcasting():
157  trivial, vectorized_is_trivial = m.trivial, m.vectorized_is_trivial
158 
159  assert vectorized_is_trivial(1, 2, 3) == trivial.c_trivial
160  assert vectorized_is_trivial(np.array(1), np.array(2), 3) == trivial.c_trivial
161  assert (
162  vectorized_is_trivial(np.array([1, 3]), np.array([2, 4]), 3)
163  == trivial.c_trivial
164  )
165  assert trivial.c_trivial == vectorized_is_trivial(
166  np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3
167  )
168  assert (
169  vectorized_is_trivial(np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2)
170  == trivial.non_trivial
171  )
172  assert (
173  vectorized_is_trivial(np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2)
174  == trivial.non_trivial
175  )
176  z1 = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype="int32")
177  z2 = np.array(z1, dtype="float32")
178  z3 = np.array(z1, dtype="float64")
179  assert vectorized_is_trivial(z1, z2, z3) == trivial.c_trivial
180  assert vectorized_is_trivial(1, z2, z3) == trivial.c_trivial
181  assert vectorized_is_trivial(z1, 1, z3) == trivial.c_trivial
182  assert vectorized_is_trivial(z1, z2, 1) == trivial.c_trivial
183  assert vectorized_is_trivial(z1[::2, ::2], 1, 1) == trivial.non_trivial
184  assert vectorized_is_trivial(1, 1, z1[::2, ::2]) == trivial.c_trivial
185  assert vectorized_is_trivial(1, 1, z3[::2, ::2]) == trivial.non_trivial
186  assert vectorized_is_trivial(z1, 1, z3[1::4, 1::4]) == trivial.c_trivial
187 
188  y1 = np.array(z1, order="F")
189  y2 = np.array(y1)
190  y3 = np.array(y1)
191  assert vectorized_is_trivial(y1, y2, y3) == trivial.f_trivial
192  assert vectorized_is_trivial(y1, 1, 1) == trivial.f_trivial
193  assert vectorized_is_trivial(1, y2, 1) == trivial.f_trivial
194  assert vectorized_is_trivial(1, 1, y3) == trivial.f_trivial
195  assert vectorized_is_trivial(y1, z2, 1) == trivial.non_trivial
196  assert vectorized_is_trivial(z1[1::4, 1::4], y2, 1) == trivial.f_trivial
197  assert vectorized_is_trivial(y1[1::4, 1::4], z2, 1) == trivial.c_trivial
198 
199  assert m.vectorized_func(z1, z2, z3).flags.c_contiguous
200  assert m.vectorized_func(y1, y2, y3).flags.f_contiguous
201  assert m.vectorized_func(z1, 1, 1).flags.c_contiguous
202  assert m.vectorized_func(1, y2, 1).flags.f_contiguous
203  assert m.vectorized_func(z1[1::4, 1::4], y2, 1).flags.f_contiguous
204  assert m.vectorized_func(y1[1::4, 1::4], z2, 1).flags.c_contiguous
205 
206 
207 def test_passthrough_arguments(doc):
208  assert doc(m.vec_passthrough) == (
209  "vec_passthrough("
210  + ", ".join(
211  [
212  "arg0: float",
213  "arg1: numpy.ndarray[numpy.float64]",
214  "arg2: numpy.ndarray[numpy.float64]",
215  "arg3: numpy.ndarray[numpy.int32]",
216  "arg4: int",
217  "arg5: m.numpy_vectorize.NonPODClass",
218  "arg6: numpy.ndarray[numpy.float64]",
219  ]
220  )
221  + ") -> object"
222  )
223 
224  b = np.array([[10, 20, 30]], dtype="float64")
225  c = np.array([100, 200]) # NOT a vectorized argument
226  d = np.array([[1000], [2000], [3000]], dtype="int")
227  g = np.array([[1000000, 2000000, 3000000]], dtype="int") # requires casting
228  assert np.all(
229  m.vec_passthrough(1, b, c, d, 10000, m.NonPODClass(100000), g)
230  == np.array(
231  [
232  [1111111, 2111121, 3111131],
233  [1112111, 2112121, 3112131],
234  [1113111, 2113121, 3113131],
235  ]
236  )
237  )
238 
239 
240 def test_method_vectorization():
241  o = m.VectorizeTestClass(3)
242  x = np.array([1, 2], dtype="int")
243  y = np.array([[10], [20]], dtype="float32")
244  assert np.all(o.method(x, y) == [[14, 15], [24, 25]])
245 
246 
247 def test_array_collapse():
248  assert not isinstance(m.vectorized_func(1, 2, 3), np.ndarray)
249  assert not isinstance(m.vectorized_func(np.array(1), 2, 3), np.ndarray)
250  z = m.vectorized_func([1], 2, 3)
251  assert isinstance(z, np.ndarray)
252  assert z.shape == (1,)
253  z = m.vectorized_func(1, [[[2]]], 3)
254  assert isinstance(z, np.ndarray)
255  assert z.shape == (1, 1, 1)
256 
257 
258 def test_vectorized_noreturn():
259  x = m.NonPODClass(0)
260  assert x.value == 0
261  m.add_to(x, [1, 2, 3, 4])
262  assert x.value == 10
263  m.add_to(x, 1)
264  assert x.value == 11
265  m.add_to(x, [[1, 1], [2, 3]])
266  assert x.value == 18
test_numpy_vectorize.test_vectorized_noreturn
def test_vectorized_noreturn()
Definition: test_numpy_vectorize.py:258
test_numpy_vectorize.test_type_selection
def test_type_selection()
Definition: test_numpy_vectorize.py:138
doc
Annotation for documentation.
Definition: attr.h:42
test_numpy_vectorize.test_docs
def test_docs(doc)
Definition: test_numpy_vectorize.py:147
test_numpy_vectorize.test_vectorize
def test_vectorize(capture)
Definition: test_numpy_vectorize.py:8
isinstance
bool isinstance(handle obj)
Definition: pytypes.h:700
test_numpy_vectorize.test_trivial_broadcasting
def test_trivial_broadcasting()
Definition: test_numpy_vectorize.py:156
tree::f
Point2(* f)(const Point3 &, OptionalJacobian< 2, 3 >)
Definition: testExpression.cpp:218
test_numpy_vectorize.test_method_vectorization
def test_method_vectorization()
Definition: test_numpy_vectorize.py:240
test_numpy_vectorize.test_array_collapse
def test_array_collapse()
Definition: test_numpy_vectorize.py:247
test_numpy_vectorize.test_passthrough_arguments
def test_passthrough_arguments(doc)
Definition: test_numpy_vectorize.py:207

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autogenerated on Tue Jul 4 2023 02:37:46