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