class_docstr: Descriptor of a certain domain that consists of discrete elements that
  are characterized by a coordinate system and a topology:
  the coordinate system is specified through a coordinate array
  the topology encodes the neighboring system
class_docstr_tok: ["Descriptor","of","a","certain","domain","that","consists","of","discrete","elements","that","are","characterized","by","a","coordinate","system","and","a","topology",":","the","coordinate","system","is","specified","through","a","coordinate","array","the","topology","encodes","the","neighboring","system"]
docstr: Integrate  certain feature over the domain and returns the result
  
  Parameters
  ----------
  fid : string,  feature identifier,
        by default, the 1 function is integrataed, yielding domain volume
  
  Returns
  -------
  lsum = array of shape (self.feature[fid].shape[1]),
         the result
code: def integrate(self, fid):
      """Integrate  certain feature over the domain and returns the result
  
      Parameters
      ----------
      fid : string,  feature identifier,
            by default, the 1 function is integrataed, yielding domain volume
  
      Returns
      -------
      lsum = array of shape (self.feature[fid].shape[1]),
             the result
  
      """
      if fid is None:
          return np.sum(self.local_volume)
      ffid = self.features[fid]
      if np.size(ffid) == ffid.shape[0]:
          ffid = np.reshape(ffid, (self.size, 1))
      slv = np.reshape(self.local_volume, (self.size, 1))
      return np.sum(ffid * slv, 0)
  
imports: import numpy
  import scipy.sparse
  from nibabel import Nifti1Image, load, save
  from nipy.algorithms.graph import WeightedGraph, wgraph_from_3d_grid, wgraph_from_coo_matrix
  from nipy.io.nibcompat import get_affine, get_header
label_desc: Use image node_id 10 for calling the DiscreteDomain obj's underlying member method code with example usage: obj.integrate(fid) and returns: np, np