class_docstr: Interface for simple dictionary-based dataset format. The dictionary
  keys correspond to the column (i.e. dimension) names and the values
  are collections representing the values in that column.
class_docstr_tok: ["Interface","for","simple","dictionary-based","dataset","format",".","The","dictionary","keys","correspond","to","the","column","(","i.e",".","dimension",")","names","and","the","values","are","collections","representing","the","values","in","that","column","."]
code: def array(cls, dataset, dimensions):
      if not dimensions:
          dimensions = dataset.dimensions(label="name")
      else:
          dimensions = [
              dataset.get_dimensions(d).name for d in dimensions
          ]
      arrays = [dataset.data[dim.name] for dim in dimensions]
      return np.column_stack(
          [
              np.full(len(dataset), arr) if isscalar(arr) else arr
              for arr in arrays
          ]
      )
  
imports: from collections import OrderedDict, defaultdict
  import numpy
  from ..None import util
  from ..dimension import dimension_name
  from ..element import Element
  from ..ndmapping import NdMapping, item_check, sorted_context
  from ..util import isscalar
  from .interface import DataError, Interface
label_desc: Use image node_id 8 for calling the DictInterface obj's underlying member method code with example usage: obj.array(cls, dataset, dimensions) and returns: np