reload_zarr_records

HSTB.kluster.xarray_helpers.reload_zarr_records(pth, skip_dask=False, sort_by=None)

After writing new data to the zarr data store, you need to refresh the xarray Dataset object so that it sees the changes. We do that here by just re-running open_zarr.

All the keyword arguments set to False are there to correctly read the saved zarr arrays. Mask_and_scale i’ve yet to configure properly, it will replace values equal to the fill_value attribute with NaN. Even when fill_value is non-zero, it seems to replace zeros with NaN. Setting it to false prevents this. You can read more here: http://xarray.pydata.org/en/stable/generated/xarray.open_zarr.html

If you are running this outside of the normal dask-enabled workflow, self.client will be None and you will not have the distributed sync object. I do this with reading attributes from the zarr datastore where I just need to open for a minute to get the attributes.

Returns

• pth – string, path to xarray Dataset stored as zarr datastore

• skip_dask – if True, skip the dask process synchronizer as you are not running dask distributed

• sort_by – optional, will sort by the dimension provided, if provided (ex: ‘time’)