PlasmaCalcs.tools.xarray_tools.xarray_indexing.xarray_map

PlasmaCalcs.tools.xarray_tools.xarray_indexing.xarray_map(array, f, *args_f, axis=None, axes=None, promote_dims_if_needed=True, missing_dims='raise', **kw_f)

func(array, *args_f, **kw_f), but axis/axes can be provided as strings!

Mainly useful if trying to apply f which expects unlabeled array & int axes inputs.

E.g. numpy.mean can use axis kwarg as iterable of ints,

but here can provide axis as a dim name str or list of dim names.

Probably not super useful for mean, since xarray provides xr.mean,

but may be useful for other functions e.g. scipy.ndimage.gaussian_filter,

which might not have an existing equivalent in xarray.

array: xarray.DataArray or Dataset

apply f to this array, or each array in this Dataset

f: callable

will be called as f(array, *args_f, **kw_f),

possibly will also be passed a value for axis or axes, if provided here

axis, axes: None, str, or iterable of strs

if provided, convert to axes positions in dataarray, and pass to f as int(s).

Also promotes these coords to dims if necessary.

promote_dims_if_needed: bool

whether to promote non-dimension coords to dimensions.

if False, raise DimensionKeyError if any relevant coord is not already a dimension.

missing_dims: str in (‘ignore’, ‘warn’, ‘raise’)

what to do if any coord is not found:

‘ignore’ –> do nothing.

‘warn’ –> raise a warning.

‘raise’ –> raise DimensionKeyError.