mindspore.numpy.isclose

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mindspore.numpy.isclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)[source]

Returns a boolean tensor where two tensors 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.

Note

For finite values, isclose uses the following equation to test whether two floating point values are equivalent. \(absolute(a - b) <= (atol + rtol * absolute(b))\) On Ascend, input arrays containing inf or NaN are not supported.

Parameters

  • a (Union[Tensor, list, tuple]) – Input first tensor to compare.

  • b (Union[Tensor, list, tuple]) – Input second tensor to compare.

  • rtol (numbers.Number, optional) – The relative tolerance parameter (see Note). Default: 1e-05 .

  • atol (numbers.Number, optional) – The absolute tolerance parameter (see Note). Default: 1e-08 .

  • equal_nan (bool, optional) – Whether to compare NaN as equal. If True, NaN in a will be considered equal to NaN in b in the output tensor. Default: False .

Returns

A bool tensor of where a and b are equal within the given tolerance.

Raises

TypeError – If inputs have types not specified above.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore.numpy as np
>>> a = np.array([0,1,2,float('inf'),float('inf'),float('nan')])
>>> b = np.array([0,1,-2,float('-inf'),float('inf'),float('nan')])
>>> print(np.isclose(a, b))
[ True  True False False  True False]
>>> print(np.isclose(a, b, equal_nan=True))
[ True  True False False  True  True]