scipp.nanmin#

scipp.nanmin(x, dim=None)#

Minimum of elements in the input ignoring NaN’s.

Warning

Scipp returns DBL_MAX or INT_MAX for empty inputs of float or int dtype, respectively, while NumPy raises. Note that in the case of DataArray, inputs can also be “empty” if all elements contributing to an output element are masked. The same applies if all elements are NaN (or masked).

Parameters:
  • x (scipp.typing.VariableLike) – Input data.

  • dim (Optional[str], default: None) – Optional dimension along which to calculate the min. If not given, the min over all dimensions is calculated.

Returns:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any]) – The minimum of the input values.

See also

scipp.min

Element-wise minimum without special handling for NaN.

scipp.max

Element-wise maximum without special handling for NaN.

scipp.nanmax

Same as max but ignoring NaN’s.