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# This file is part of Hypothesis, which may be found at
# https://github.com/HypothesisWorks/hypothesis/
#
# Copyright the Hypothesis Authors.
# Individual contributors are listed in AUTHORS.rst and the git log.
#
# This Source Code Form is subject to the terms of the Mozilla Public License,
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at https://mozilla.org/MPL/2.0/.
import numpy
import pytest
from hypothesis import strategies as st
from hypothesis.errors import InvalidArgument
from hypothesis.extra import numpy as nps
from tests.common.debug import check_can_generate_examples
from tests.common.utils import checks_deprecated_behaviour
def e(a, **kwargs):
kw = ", ".join(f"{k}={v!r}" for k, v in kwargs.items())
return pytest.param(a, kwargs, id=f"{a.__name__}({kw})")
@pytest.mark.parametrize(
("function", "kwargs"),
[
e(nps.array_dtypes, min_size=2, max_size=1),
e(nps.array_dtypes, min_size=-1),
e(nps.array_shapes, min_side=2, max_side=1),
e(nps.array_shapes, min_dims=3, max_dims=2),
e(nps.array_shapes, min_dims=-1),
e(nps.array_shapes, min_side=-1),
e(nps.array_shapes, min_side="not an int"),
e(nps.array_shapes, max_side="not an int"),
e(nps.array_shapes, min_dims="not an int"),
e(nps.array_shapes, max_dims="not an int"),
e(nps.array_shapes, min_dims=33),
e(nps.array_shapes, max_dims=33),
e(nps.arrays, dtype=float, shape=(0.5,)),
e(nps.arrays, dtype=object, shape=1),
e(nps.arrays, dtype=float, shape=1, fill=3),
e(nps.arrays, dtype="U", shape=1, elements=st.just("abc\0\0")),
e(nps.arrays, dtype=int, shape=1, elements="not a strategy"),
e(nps.byte_string_dtypes, min_len=-1),
e(nps.byte_string_dtypes, min_len=2, max_len=1),
e(nps.byte_string_dtypes, min_len=0, max_len=0),
e(nps.datetime64_dtypes, max_period=11),
e(nps.datetime64_dtypes, min_period=11),
e(nps.datetime64_dtypes, min_period="Y", max_period="M"),
e(nps.timedelta64_dtypes, max_period=11),
e(nps.timedelta64_dtypes, min_period=11),
e(nps.timedelta64_dtypes, min_period="Y", max_period="M"),
e(nps.unicode_string_dtypes, min_len=-1),
e(nps.unicode_string_dtypes, min_len=2, max_len=1),
e(nps.unicode_string_dtypes, min_len=0, max_len=0),
e(nps.unsigned_integer_dtypes, endianness=3),
e(nps.unsigned_integer_dtypes, sizes=()),
e(nps.unsigned_integer_dtypes, sizes=(3,)),
e(nps.from_dtype, dtype="float64"),
e(nps.from_dtype, dtype=float),
e(nps.from_dtype, dtype=numpy.int8),
e(nps.from_dtype, dtype=1),
e(nps.from_dtype, dtype=numpy.dtype("uint8"), min_value=-999),
e(nps.from_dtype, dtype=numpy.dtype("uint8"), max_value=999),
e(nps.from_dtype, dtype=numpy.dtype("int8"), min_value=-999),
e(nps.from_dtype, dtype=numpy.dtype("int8"), max_value=999),
e(nps.from_dtype, dtype=numpy.dtype("S4"), max_size=5),
e(nps.from_dtype, dtype=numpy.dtype("U4"), max_size=5),
e(nps.valid_tuple_axes, ndim=-1),
e(nps.valid_tuple_axes, ndim=2, min_size=-1),
e(nps.valid_tuple_axes, ndim=2, min_size=3, max_size=10),
e(nps.valid_tuple_axes, ndim=2, min_size=2, max_size=1),
e(nps.valid_tuple_axes, ndim=2.0, min_size=2, max_size=1),
e(nps.valid_tuple_axes, ndim=2, min_size=1.0, max_size=2),
e(nps.valid_tuple_axes, ndim=2, min_size=1, max_size=2.0),
e(nps.valid_tuple_axes, ndim=2, min_size=1, max_size=3),
e(nps.broadcastable_shapes, shape="a"),
e(nps.broadcastable_shapes, shape=(2, 2), min_side="a"),
e(nps.broadcastable_shapes, shape=(2, 2), min_dims="a"),
e(nps.broadcastable_shapes, shape=(2, 2), max_side="a"),
e(nps.broadcastable_shapes, shape=(2, 2), max_dims="a"),
e(nps.broadcastable_shapes, shape=(2, 2), min_side=-1),
e(nps.broadcastable_shapes, shape=(2, 2), min_dims=-1),
e(nps.broadcastable_shapes, shape=(2, 2), min_dims=33, max_dims=None),
e(nps.broadcastable_shapes, shape=(2, 2), min_dims=1, max_dims=33),
e(nps.broadcastable_shapes, shape=(2, 2), min_side=1, max_side=0),
e(nps.broadcastable_shapes, shape=(2, 2), min_dims=1, max_dims=0),
e(
nps.broadcastable_shapes, # max_side too small
shape=(5, 1),
min_dims=2,
max_dims=4,
min_side=2,
max_side=3,
),
e(
nps.broadcastable_shapes, # min_side too large
shape=(0, 1),
min_dims=2,
max_dims=4,
min_side=2,
max_side=3,
),
e(
nps.broadcastable_shapes, # default max_dims unsatisfiable
shape=(5, 3, 2, 1),
min_dims=3,
max_dims=None,
min_side=2,
max_side=3,
),
e(
nps.broadcastable_shapes, # default max_dims unsatisfiable
shape=(0, 3, 2, 1),
min_dims=3,
max_dims=None,
min_side=2,
max_side=3,
),
e(nps.mutually_broadcastable_shapes),
e(nps.mutually_broadcastable_shapes, num_shapes=0),
e(nps.mutually_broadcastable_shapes, num_shapes="a"),
e(nps.mutually_broadcastable_shapes, num_shapes=2, base_shape="a"),
e(
nps.mutually_broadcastable_shapes, # min_side is invalid type
num_shapes=2,
min_side="a",
),
e(
nps.mutually_broadcastable_shapes, # min_dims is invalid type
num_shapes=2,
min_dims="a",
),
e(
nps.mutually_broadcastable_shapes, # max_side is invalid type
num_shapes=2,
max_side="a",
),
e(
nps.mutually_broadcastable_shapes, # max_side is invalid type
num_shapes=2,
max_dims="a",
),
e(
nps.mutually_broadcastable_shapes, # min_side is out of domain
num_shapes=2,
min_side=-1,
),
e(
nps.mutually_broadcastable_shapes, # min_dims is out of domain
num_shapes=2,
min_dims=-1,
),
e(
nps.mutually_broadcastable_shapes, # min_dims is out of domain
num_shapes=2,
min_dims=33,
),
e(
nps.mutually_broadcastable_shapes, # max_dims is out of domain
num_shapes=2,
max_dims=33,
),
e(
nps.mutually_broadcastable_shapes, # max_side < min_side
num_shapes=2,
min_side=1,
max_side=0,
),
e(
nps.mutually_broadcastable_shapes, # max_dims < min_dims
num_shapes=2,
min_dims=1,
max_dims=0,
),
e(
nps.mutually_broadcastable_shapes, # max_side too small
num_shapes=2,
base_shape=(5, 1),
min_dims=2,
max_dims=4,
min_side=2,
max_side=3,
),
e(
nps.mutually_broadcastable_shapes, # min_side too large
num_shapes=2,
base_shape=(0, 1),
min_dims=2,
max_dims=4,
min_side=2,
max_side=3,
),
e(
nps.mutually_broadcastable_shapes, # user-specified max_dims unsatisfiable
num_shapes=1,
base_shape=(5, 3, 2, 1),
min_dims=3,
max_dims=4,
min_side=2,
max_side=3,
),
e(
nps.mutually_broadcastable_shapes, # user-specified max_dims unsatisfiable
num_shapes=2,
base_shape=(0, 3, 2, 1),
min_dims=3,
max_dims=4,
min_side=2,
max_side=3,
),
e(
nps.mutually_broadcastable_shapes, # valid to pass num_shapes xor gufunc
num_shapes=2,
signature="()->()",
),
e(
nps.mutually_broadcastable_shapes, # element-wise ufunc has signature=None
signature=numpy.add.signature,
),
e(
nps.mutually_broadcastable_shapes, # multiple outputs not yet supported
signature="()->(),()",
),
e(
nps.mutually_broadcastable_shapes, # output has dimension not in inputs
signature="()->(i)",
),
e(
nps.mutually_broadcastable_shapes, # frozen-optional is ambiguous & banned
signature="(2?)->()",
),
e(
nps.mutually_broadcastable_shapes, # signature must be in string format
signature=([(), ()], [()]),
),
e(
nps.mutually_broadcastable_shapes, # string must match signature regex
signature="this string isn't a valid signature",
),
e(
nps.mutually_broadcastable_shapes, # shape with too many dimensions
signature="(" + ",".join(f"d{n}" for n in range(33)) + ")->()",
),
e(
nps.mutually_broadcastable_shapes, # max_dims too large given ufunc
signature=numpy.matmul.signature,
max_dims=32,
),
e(
nps.mutually_broadcastable_shapes, # least valid max_dims is < min_dims
signature=numpy.matmul.signature,
min_dims=32,
),
e(nps.basic_indices, shape=0),
e(nps.basic_indices, shape=("1", "2")),
e(nps.basic_indices, shape=(0, -1)),
e(nps.basic_indices, shape=(0, 0), allow_newaxis=None),
e(nps.basic_indices, shape=(0, 0), allow_ellipsis=None),
e(nps.basic_indices, shape=(0, 0), min_dims=-1),
e(nps.basic_indices, shape=(0, 0), min_dims=1.0),
e(nps.basic_indices, shape=(0, 0), max_dims=-1),
e(nps.basic_indices, shape=(0, 0), max_dims=1.0),
e(nps.basic_indices, shape=(0, 0), min_dims=2, max_dims=1),
e(nps.basic_indices, shape=(3, 3, 3), max_dims="not an int"),
e(nps.integer_array_indices, shape=()),
e(nps.integer_array_indices, shape=(2, 0)),
e(nps.integer_array_indices, shape="a"),
e(nps.integer_array_indices, shape=(2,), result_shape=(2, 2)),
e(nps.integer_array_indices, shape=(2,), dtype=float),
],
)
def test_raise_invalid_argument(function, kwargs):
with pytest.raises(InvalidArgument):
check_can_generate_examples(function(**kwargs))
@pytest.mark.parametrize(
("function", "kwargs"),
[
e(nps.basic_indices, shape=(0, 0), min_dims=50),
e(nps.basic_indices, shape=(0, 0), max_dims=50),
],
)
@checks_deprecated_behaviour
def test_raise_invalid_argument_deprecated(function, kwargs):
with pytest.raises(InvalidArgument):
check_can_generate_examples(function(**kwargs))
|
