flopscope.numpy.allclose

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.

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.

a, b:array_like

Input arrays to compare.

rtol:array_like

The relative tolerance parameter (see Notes).

atol:array_like

The absolute tolerance parameter (see Notes).

equal_nan:bool

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.

allclose:bool

Returns True if the two arrays are equal within the given tolerance; False otherwise.

• we.flops.isclose
• we.flops.all
• we.flops.any
• we.flops.equal

If the following equation is element-wise True, then allclose returns True.:

absolute(a - b) <= (atol + 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 default value of atol is not appropriate when the reference value b has magnitude smaller than one. For example, it is unlikely that a = 1e-9 and b = 2e-9 should be considered "close", yet allclose(1e-9, 2e-9) is True with default settings. Be sure to select atol for the use case at hand, especially for defining the threshold below which a non-zero value in a will be considered "close" to a very small or zero value in b.

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 equal but not array_equal.

allclose is not defined for non-numeric data types. bool is considered a numeric data-type for this purpose.