class_docstr: Args:
      ids (sequence): the IDs of each element
      sources (numpy.ndarray): the ilocs of the source of each edge
      targets (numpy.ndarray): the ilocs of the target of each edge
      weight (numpy.ndarray): the weight of each edge
      type_info (list of tuple of type name, numpy array): the associated feature vectors of each type, where the size of the first dimension defines the elements of that type
      number_of_nodes (int): the total number of nodes in the graph
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docstr: Return the integer locations of the edges for the given node_id
  
  Args:
      node_id: the ID of the node
  
  
  Returns:
      The integer locations of the edges for the given node_id.
code: def edge_ilocs(self, node_id, *, ins, outs) -> np.ndarray:
      """
      Return the integer locations of the edges for the given node_id
  
      Args:
          node_id: the ID of the node
  
  
      Returns:
          The integer locations of the edges for the given node_id.
      """
  
      return self._adj_lookup(ins=ins, outs=outs)[node_id]
  
imports: import itertools
  from collections import defaultdict
  import numpy
  import pandas
  import scipy.sparse
  from ..globalvar import SOURCE, TARGET, WEIGHT, TYPE_ATTR_NAME
  from .validation import require_dataframe_has_columns, comma_sep
label_desc: Use image node_id 8 for calling the EdgeData obj's underlying member method code with example usage: obj.edge_ilocs(node_id) and returns: self