numpy.isclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)[source]
Returns a boolean array where two arrays are element-wise equal within a tolerance.
The tolerance values are positive, typically very small numbers. The relative difference (rtol
* abs(b
)) and the absolute difference atol
are added together to compare against the absolute difference between a
and b
.
Parameters: |
a, b : array_like Input arrays to compare. rtol : float The relative tolerance parameter (see Notes). atol : float The absolute tolerance parameter (see Notes). equal_nan : bool Whether to compare NaN’s as equal. If True, NaN’s in |
---|---|
Returns: |
y : array_like Returns a boolean array of where |
See also
New in version 1.7.0.
For finite values, isclose uses the following equation to test whether two floating point values are equivalent.
absolute(a
- b
) <= (atol
+ rtol
* absolute(b
)) The above equation is not symmetric in a
and b
, so that isclose(a, b)
might be different from isclose(b, a)
in some rare cases.
>>> np.isclose([1e10,1e-7], [1.00001e10,1e-8]) array([True, False]) >>> np.isclose([1e10,1e-8], [1.00001e10,1e-9]) array([True, True]) >>> np.isclose([1e10,1e-8], [1.0001e10,1e-9]) array([False, True]) >>> np.isclose([1.0, np.nan], [1.0, np.nan]) array([True, False]) >>> np.isclose([1.0, np.nan], [1.0, np.nan], equal_nan=True) array([True, True])
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.isclose.html