experimental.to_dataarray

experimental.to_dataarray(res)

Convert a Res1D object to an xarray DataArray.

The DataArray will have dimensions (“time”, “feature”), where “feature” corresponds to an index of time series in the Res1D object. The feature dimension has coordinates for mapping to modeler semantics such as quantity, group, and id.

Parameters

Name	Type	Description	Default
res	Res1D	The Res1D object	required

Notes

The feature dimension has no semantic meaning by itself. It exists to ensure a dense array, rather than a sparse array with many NaNs. Reaches have arbitrary number of gridpoints, which can each have an arbitrary set of quantities, resulting in a sparse data structure. Use the feature coordinates to filter and select data as needed.

The feature dimension does not have a multilevel index since they are not supported by zarr. Additionally, DataTree was considered for handling sparsity where each location and quantity woudld be a separate DataSet, however, zarr does not scale well with many small arrays.

Returns

Name	Type	Description
	xr.DataArray	The xarray DataArray object.

Examples

>>> from mikeio1d.experimental import to_dataarray
>>> da = to_dataarray(res)
>>> da = da.sel(quantity="WaterLevel", group="Reach")

>>> da = da.where(da.chainage == 0, drop=True)
>>> da = da.isel(time=slice(0, 10))