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import numpy as np
from numpy.testing import assert_allclose as numpy_allclose
from brian2 import prefs
from brian2.units.fundamentalunits import have_same_dimensions
def assert_allclose(actual, desired, rtol=4.5e8, atol=1e-9, **kwds):
"""
Thin wrapper around numpy's `~numpy.testing.utils.assert_allclose` function. The tolerance depends on the floating
point precision as defined by the `core.default_float_dtype` preference.
Parameters
----------
actual : `numpy.ndarray`
The results to check.
desired : `numpy.ndarray`
The expected results.
rtol : float, optional
The relative tolerance which will be multiplied with the machine epsilon of the type set as
`core.default_float_type`.
atol : float, optional
The absolute tolerance
"""
assert have_same_dimensions(actual, desired)
eps = np.finfo(prefs["core.default_float_dtype"]).eps
rtol = eps * rtol
numpy_allclose(
np.asarray(actual), np.asarray(desired), rtol=rtol, atol=atol, **kwds
)
def exc_isinstance(exc_info, expected_exception, raise_not_implemented=False):
"""
Simple helper function as an alternative to calling
`~.pytest.ExceptionInfo.errisinstance` which will take into account all
the "causing" exceptions in an exception chain.
Parameters
----------
exc_info : `pytest.ExceptionInfo` or `Exception`
The exception info as returned by `pytest.raises`.
expected_exception : `type`
The expected exception class
raise_not_implemented : bool, optional
Whether to re-raise a `NotImplementedError` – necessary for tests that
should be skipped with ``@skip_if_not_implemented``. Defaults to
``False``.
Returns
-------
correct_exception : bool
Whether the exception itself or one of the causing exceptions is of the
expected type.
"""
if exc_info is None:
return False
if hasattr(exc_info, "value"):
exc_info = exc_info.value
if isinstance(exc_info, expected_exception):
return True
elif raise_not_implemented and isinstance(exc_info, NotImplementedError):
raise exc_info
return exc_isinstance(
exc_info.__cause__,
expected_exception,
raise_not_implemented=raise_not_implemented,
)
|
