code: def init(cls, eltype, data, kdims, vdims):
      import xarray as xr
  
      element_params = eltype.param.objects()
      kdim_param = element_params["kdims"]
      vdim_param = element_params["vdims"]
  
      def retrieve_unit_and_label(dim):
          if isinstance(dim, Dimension):
              return dim
          dim = asdim(dim)
          coord = data[dim.name]
          unit = (
              coord.attrs.get("units") if dim.unit is None else dim.unit
          )
          if isinstance(unit, tuple):
              unit = unit[0]
          if isinstance(coord.attrs.get("long_name"), str):
              spec = (dim.name, coord.attrs["long_name"])
          else:
              spec = (dim.name, dim.label)
          nodata = coord.attrs.get("NODATA")
          return dim.clone(spec, unit=unit, nodata=nodata)
  
      packed = False
      if isinstance(data, xr.DataArray):
          kdim_len = (
              len(kdim_param.default) if kdims is None else len(kdims)
          )
          vdim_len = (
              len(vdim_param.default) if vdims is None else len(vdims)
          )
          if (
              vdim_len > 1
              and kdim_len == len(data.dims) - 1
              and data.shape[-1] == vdim_len
          ):
              packed = True
          elif vdims:
              vdim = vdims[0]
          elif data.name:
              vdim = Dimension(data.name)
              vdim.unit = data.attrs.get("units")
              vdim.nodata = data.attrs.get("NODATA")
              label = data.attrs.get("long_name")
              if isinstance(label, str):
                  vdim.label = label
          elif len(vdim_param.default) == 1:
              vdim = asdim(vdim_param.default[0])
              if vdim.name in data.dims:
                  raise DataError(
                      "xarray DataArray does not define a name, "
                      "and the default of '%s' clashes with a "
                      "coordinate dimension. Give the DataArray "
                      "a name or supply an explicit value dimension."
                      % vdim.name,
                      cls,
                  )
          else:
              raise DataError(
                  "xarray DataArray does not define a name "
                  "and %s does not define a default value "
                  "dimension. Give the DataArray a name or "
                  "supply an explicit vdim." % eltype.__name__,
                  cls,
              )
          if not packed:
              if vdim in data.dims:
                  data = data.to_dataset(vdim.name)
                  vdims = [asdim(vd) for vd in data.data_vars]
              else:
                  vdims = [vdim]
                  data = data.to_dataset(name=vdim.name)
  
      if not isinstance(data, (xr.Dataset, xr.DataArray)):
          if kdims is None:
              kdims = kdim_param.default
          if vdims is None:
              vdims = vdim_param.default
          kdims = [asdim(kd) for kd in kdims]
          vdims = [asdim(vd) for vd in vdims]
          if (
              isinstance(data, np.ndarray)
              and data.ndim == 2
              and data.shape[1] == len(kdims + vdims)
          ):
              data = tuple(data)
  
          ndims = len(kdims)
          if isinstance(data, tuple):
              dimensions = [d.name for d in kdims + vdims]
              if (
                  len(data) != len(dimensions)
                  and len(data) == (ndims + 1)
                  and len(data[-1].shape) == (ndims + 1)
              ):
                  value_array = data[-1]
                  data = {d: v for d, v in zip(dimensions, data[:-1])}
                  packed = True
              else:
                  data = {d: v for d, v in zip(dimensions, data)}
          elif isinstance(data, (list, np.ndarray)) and len(data) == 0:
              dimensions = [d.name for d in kdims + vdims]
              data = {d: np.array([]) for d in dimensions[:ndims]}
              data.update(
                  {
                      d: np.empty((0,) * ndims)
                      for d in dimensions[ndims:]
                  }
              )
          if not isinstance(data, dict):
              raise TypeError(
                  "XArrayInterface could not interpret data type"
              )
          data = {
              d: np.asarray(values) if d in kdims else values
              for d, values in data.items()
          }
          coord_dims = [data[kd.name].ndim for kd in kdims]
          dims = tuple("dim_%d" % i for i in range(max(coord_dims)))[
              ::-1
          ]
          coords = {}
          for kd in kdims:
              coord_vals = data[kd.name]
              if coord_vals.ndim > 1:
                  coord = (dims[: coord_vals.ndim], coord_vals)
              else:
                  coord = coord_vals
              coords[kd.name] = coord
          xr_kwargs = {
              "dims": dims
              if max(coord_dims) > 1
              else list(coords)[::-1]
          }
          if packed:
              xr_kwargs["dims"] = list(coords)[::-1] + ["band"]
              coords["band"] = list(range(len(vdims)))
              data = xr.DataArray(
                  value_array, coords=coords, **xr_kwargs
              )
          else:
              arrays = {}
              for vdim in vdims:
                  arr = data[vdim.name]
                  if not isinstance(arr, xr.DataArray):
                      arr = xr.DataArray(
                          arr, coords=coords, **xr_kwargs
                      )
                  arrays[vdim.name] = arr
              data = xr.Dataset(arrays)
      else:
          # Started to warn in xarray 2023.12.0:
          # The return type of `Dataset.dims` will be changed to return a
          # set of dimension names in future, in order to be more consistent
          # with `DataArray.dims`. To access a mapping from dimension names to
          # lengths, please use `Dataset.sizes`.
          data_info = (
              data.sizes if hasattr(data, "sizes") else data.dims
          )
          if not data.coords:
              data = data.assign_coords(
                  **{k: range(v) for k, v in data_info.items()}
              )
          if vdims is None:
              vdims = list(data.data_vars)
          if kdims is None:
              xrdims = list(data_info)
              xrcoords = list(data.coords)
              kdims = [
                  name
                  for name in data.indexes.keys()
                  if isinstance(data[name].data, np.ndarray)
              ]
              kdims = sorted(
                  kdims,
                  key=lambda x: (
                      xrcoords.index(x)
                      if x in xrcoords
                      else float("inf"),
                      x,
                  ),
              )
              if packed:
                  kdims = kdims[:-1]
              elif set(xrdims) != set(kdims):
                  virtual_dims = [
                      xd for xd in xrdims if xd not in kdims
                  ]
                  for c in data.coords:
                      if c not in kdims and set(data[c].dims) == set(
                          virtual_dims
                      ):
                          kdims.append(c)
          kdims = [retrieve_unit_and_label(kd) for kd in kdims]
          vdims = [retrieve_unit_and_label(vd) for vd in vdims]
  
      not_found = []
      for d in kdims:
          if not any(
              d.name == k
              or (isinstance(v, xr.DataArray) and d.name in v.dims)
              for k, v in data.coords.items()
          ):
              not_found.append(d)
      if not isinstance(data, (xr.Dataset, xr.DataArray)):
          raise TypeError("Data must be be an xarray Dataset type.")
      elif not_found:
          raise DataError(
              "xarray Dataset must define coordinates "
              "for all defined kdims, %s coordinates not found."
              % not_found,
              cls,
          )
  
      for vdim in vdims:
          if packed:
              continue
          da = data[vdim.name]
          # Do not enforce validation for irregular arrays since they
          # not need to be canonicalized
          if any(len(da.coords[c].shape) > 1 for c in da.coords):
              continue
          undeclared = []
          for c in da.coords:
              if (
                  c in kdims
                  or len(da[c].shape) != 1
                  or da[c].shape[0] <= 1
              ):
                  # Skip if coord is declared, represents irregular coordinates or is constant
                  continue
              elif all(d in kdims for d in da[c].dims):
                  continue  # Skip if coord is alias for another dimension
              elif any(
                  all(d in da[kd.name].dims for d in da[c].dims)
                  for kd in kdims
              ):
                  # Skip if all the dims on the coord are present on another coord
                  continue
              undeclared.append(c)
          if undeclared and eltype.param.kdims.bounds[1] not in (
              0,
              None,
          ):
              raise DataError(
                  f"The coordinates on the {vdim.name!r} DataArray do not match the "
                  "provided key dimensions (kdims). The following coords "
                  f"were left unspecified: {undeclared!r}. If you are requesting a "
                  "lower dimensional view such as a histogram cast "
                  "the xarray to a columnar format using the .to_dataframe "
                  "or .to_dask_dataframe methods before providing it to "
                  "HoloViews."
              )
      return data, {"kdims": kdims, "vdims": vdims}, {}
  
imports: import sys
  import types
  import numpy
  import pandas
  from ..None import util
  from ..dimension import Dimension, asdim, dimension_name
  from ..element import Element
  from ..ndmapping import NdMapping, item_check, sorted_context
  from .grid import GridInterface
  from .interface import DataError, Interface
  from .util import dask_array_module, finite_range
label_desc: Use image node_id 7 for calling the XArrayInterface obj's underlying member method code with example usage: obj.init(cls, eltype, data, kdims, vdims) and returns: data,  dict,  dict, dim, dim