mars.tensor.nanargmax#

mars.tensor.nanargmax(a, axis=None, out=None, combine_size=None)[source]#

Return the indices of the maximum values in the specified axis ignoring NaNs. For all-NaN slices ValueError is raised. Warning: the results cannot be trusted if a slice contains only NaNs and -Infs.

Parameters

  • a (array_like) – Input data.

  • axis (int, optional) – Axis along which to operate. By default flattened input is used.

  • out (Tensor, optional) – Alternate output tensor in which to place the result. The default is None; if provided, it must have the same shape as the expected output, but the type will be cast if necessary. See doc.ufuncs for details.

  • combine_size (int, optional) – The number of chunks to combine.

Returns

index_array – An tensor of indices or a single index value.

Return type

Tensor

See also

argmax, nanargmin

Examples

>>> import mars.tensor as mt

>>> a = mt.array([[mt.nan, 4], [2, 3]])
>>> mt.argmax(a).execute()
0
>>> mt.nanargmax(a).execute()
1
>>> mt.nanargmax(a, axis=0).execute()
array([1, 0])
>>> mt.nanargmax(a, axis=1).execute()
array([1, 1])