Applies the provided mask(s) to the Sv variable var_name
in the provided Dataset source_ds.
Points to a Dataset that contains the variable the mask should be applied to
The mask(s) to be applied.
Can be a single input or list that corresponds to a DataArray or a path.
Each entry in the list must have dimensions ('ping_time', 'range_sample').
Multi-channel masks are not currently supported.
If a path is provided this should point to a zarr or netcdf file with only
one data variable in it.
If the input mask is a list, a logical AND will be used to produce the final
mask that will be applied to var_name.
The Sv variable name in source_ds that the mask should be applied to.
This variable needs to have coordinates ping_time and range_sample,
and can optionally also have coordinate channel.
In the case of a multi-channel Sv data variable, the mask will be broadcast
to all channels.
Value(s) at masked indices.
If fill_value is of type np.ndarray or xr.DataArray,
it must have the same shape as each entry of mask.
Any additional parameters for the storage backend, corresponding to the
path provided for source_ds
Any additional parameters for the storage backend, corresponding to the
path provided for mask. If mask is a list, then this input should either
be a list of dictionaries or a single dictionary with storage options that
correspond to all elements in mask that are paths.
A Dataset with the same format of source_ds with the mask(s) applied to var_name