cf.Data.minimum_absolute_value

Data.minimum_absolute_value(axes=None, squeeze=False, mtol=1, inplace=False, _preserve_partitions=False)[source]

Collapse axes with their minimum absolute value.

Missing data elements are omitted from the calculation.

See also

max, min, mean, mid_range, sum, sd, var

Parameters
axes(sequence of) int, optional

TODO

squeezebool, optional

TODO

inplace: bool, optional

If True then do the operation in-place and return None.

Returns
Data or None

The collapsed data, or None if the operation was in-place.

Examples:

>>> d = cf.Data([[-1, 2, 3], [9, -8, -12]], 'm')
>>> d.minimum_absolute_value()
<CF Data(1, 1): [[1]] m>
>>> d.d.min()
<CF Data(1, 1): [[-12]] m>
>>> d.minimum_absolute_value(axes=1)
<CF Data(2, 1): [[1, 8]] m>
>>> d.min(axes=1)
<CF Data(2, 1): [[-1, -12]] m>