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# scipy.spatial.cKDTree.sparse_distance_matrix

`cKDTree.``sparse_distance_matrix`(self, other, max_distance, p=2.)

  Compute a sparse distance matrix

  Computes a distance matrix between two cKDTrees, leaving as zero any distance greater than max_distance.

  Parameters: | other : cKDTree max_distance : positive float p : float, 1<=p<=infinity Which Minkowski p-norm to use. output_type : string, optional Which container to use for output data. Options: ‘dok_matrix’, ‘coo_matrix’, ‘dict’, or ‘ndarray’. Default: ‘dok_matrix’.
  Returns: | result : dok_matrix, coo_matrix, dict or ndarray Sparse matrix representing the results in “dictionary of keys” format. If a dict is returned the keys are (i,j) tuples of indices. If output_type is ‘ndarray’ a record array with fields ‘i’, ‘j’, and ‘k’ is returned,