allclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)
The tolerance values are positive, typically very small numbers. The relative difference (:None:None:`rtol` * abs(b)) and the absolute difference :None:None:`atol` are added together to compare against the absolute difference between a and b.
NaNs are treated as equal if they are in the same place and if equal_nan=True
. Infs are treated as equal if they are in the same place and of the same sign in both arrays.
If the following equation is element-wise True, then allclose returns True.
absolute(
a-b) <= (:None:None:`atol`+:None:None:`rtol`* absolute(b))
The above equation is not symmetric in a and b, so that allclose(a, b)
might be different from allclose(b, a)
in some rare cases.
The comparison of a and b uses standard broadcasting, which means that a and b need not have the same shape in order for allclose(a, b)
to evaluate to True. The same is true for :None:None:`equal` but not array_equal
.
allclose
is not defined for non-numeric data types. :None:None:`bool` is considered a numeric data-type for this purpose.
Input arrays to compare.
The relative tolerance parameter (see Notes).
The absolute tolerance parameter (see Notes).
Whether to compare NaN's as equal. If True, NaN's in a will be considered equal to NaN's in b in the output array.
Returns True if the two arrays are equal within the given tolerance; False otherwise.
Returns True if two arrays are element-wise equal within a tolerance.
>>> np.allclose([1e10,1e-7], [1.00001e10,1e-8]) False
>>> np.allclose([1e10,1e-8], [1.00001e10,1e-9]) True
>>> np.allclose([1e10,1e-8], [1.0001e10,1e-9]) False
>>> np.allclose([1.0, np.nan], [1.0, np.nan]) False
>>> np.allclose([1.0, np.nan], [1.0, np.nan], equal_nan=True) TrueSee :
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