dpnp.allclose
- dpnp.allclose(a, b, rtol=1e-05, atol=1e-08, **kwargs)[source]
Returns
True
if 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.
If either array contains one or more
NaNs
,False
is returned.Infs
are treated as equal if they are in the same place and of the same sign in both arrays.For full documentation refer to
numpy.allclose
.- Returns:
out -- A 0-dim array with
True
value if the two arrays are equal within the given tolerance; withFalse
otherwise.- Return type:
dpnp.ndarray
Limitations
Parameters a and b are supported either as
dpnp.ndarray
,dpctl.tensor.usm_ndarray
or scalars, but both a and b can not be scalars at the same time. Keyword argument kwargs is currently unsupported. Otherwise the functions will be executed sequentially on CPU. Parameters rtol and atol are supported as scalars. OtherwiseTypeError
exception will be raised. Input array data types are limited by supported integer and floating DPNP Available array data types.See also
dpnp.isclose
Test whether two arrays are element-wise equal.
dpnp.all
Test whether all elements evaluate to True.
dpnp.any
Test whether any element evaluates to True.
dpnp.equal
Return (x1 == x2) element-wise.
Examples
>>> import dpnp as np >>> a = np.array([1e10, 1e-7]) >>> b = np.array([1.00001e10, 1e-8]) >>> np.allclose(a, b) array([False])
>>> a = np.array([1.0, np.nan]) >>> b = np.array([1.0, np.nan]) >>> np.allclose(a, b) array([False])
>>> a = np.array([1.0, np.inf]) >>> b = np.array([1.0, np.inf]) >>> np.allclose(a, b) array([ True])