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- import numpy as np
- class _FakeMatrix:
- def __init__(self, data):
- self._data = data
- self.__array_interface__ = data.__array_interface__
- class _FakeMatrix2:
- def __init__(self, data):
- self._data = data
- def __array__(self):
- return self._data
- def _get_array(shape, dtype):
- """
- Get a test array of given shape and data type.
- Returned NxN matrices are posdef, and 2xN are banded-posdef.
- """
- if len(shape) == 2 and shape[0] == 2:
- # yield a banded positive definite one
- x = np.zeros(shape, dtype=dtype)
- x[0, 1:] = -1
- x[1] = 2
- return x
- elif len(shape) == 2 and shape[0] == shape[1]:
- # always yield a positive definite matrix
- x = np.zeros(shape, dtype=dtype)
- j = np.arange(shape[0])
- x[j, j] = 2
- x[j[:-1], j[:-1]+1] = -1
- x[j[:-1]+1, j[:-1]] = -1
- return x
- else:
- np.random.seed(1234)
- return np.random.randn(*shape).astype(dtype)
- def _id(x):
- return x
- def assert_no_overwrite(call, shapes, dtypes=None):
- """
- Test that a call does not overwrite its input arguments
- """
- if dtypes is None:
- dtypes = [np.float32, np.float64, np.complex64, np.complex128]
- for dtype in dtypes:
- for order in ["C", "F"]:
- for faker in [_id, _FakeMatrix, _FakeMatrix2]:
- orig_inputs = [_get_array(s, dtype) for s in shapes]
- inputs = [faker(x.copy(order)) for x in orig_inputs]
- call(*inputs)
- msg = "call modified inputs [%r, %r]" % (dtype, faker)
- for a, b in zip(inputs, orig_inputs):
- np.testing.assert_equal(a, b, err_msg=msg)
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