code: def select(cls, dataset, selection_mask=None, **selection):
      if selection_mask is not None:
          return dataset.data.where(selection_mask, drop=True)
  
      validated = {}
      for k, v in selection.items():
          dim = dataset.get_dimension(k, strict=True)
          if cls.irregular(dataset, dim):
              return GridInterface.select(
                  dataset, selection_mask, **selection
              )
          dim = dim.name
          if isinstance(v, slice):
              v = (v.start, v.stop)
          if isinstance(v, set):
              validated[dim] = list(v)
          elif isinstance(v, tuple):
              dim_vals = dataset.data[k].values
              upper = (
                  None
                  if v[1] is None
                  else v[1] - sys.float_info.epsilon * 10
              )
              v = v[0], upper
              if dim_vals.dtype.kind not in "OSU" and np.all(
                  dim_vals[1:] < dim_vals[:-1]
              ):
                  # If coordinates are inverted invert slice
                  v = v[::-1]
              validated[dim] = slice(*v)
          elif isinstance(v, types.FunctionType):
              validated[dim] = v(dataset[k])
          else:
              validated[dim] = v
      data = dataset.data.sel(**validated)
  
      # Restore constant dimensions
      indexed = cls.indexed(dataset, selection)
      dropped = dict(
          (d.name, np.atleast_1d(data[d.name]))
          for d in dataset.kdims
          if not data[d.name].data.shape
      )
      if dropped and not indexed:
          data = data.expand_dims(dropped)
          # see https://github.com/pydata/xarray/issues/2891
          # since we only expanded on dimensions of size 1
          # we can monkeypatch the dataarray back to writeable.
          for d in data.values():
              if hasattr(d.data, "flags"):
                  d.data.flags.writeable = True
  
      da = dask_array_module()
      if (
          indexed
          and len(data.data_vars) == 1
          and len(data[dataset.vdims[0].name].shape) == 0
      ):
          value = data[dataset.vdims[0].name]
          if da and isinstance(value.data, da.Array):
              value = value.compute()
          return value.item()
      elif indexed:
          values = []
          for vd in dataset.vdims:
              value = data[vd.name]
              if da and isinstance(value.data, da.Array):
                  value = value.compute()
              values.append(value.item())
          return np.array(values)
      return data
  
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 23 for calling the XArrayInterface obj's underlying member method code with example usage: obj.select(cls, dataset, selection_mask) and returns: data, dataset, value, GridInterface, np