docstr: Tests that the generated graph is a dag for all graph types.
docstr_tok: ["Tests","that","the","generated","graph","is","a","dag","for","all","graph","types","."]
code: def test_is_dag_graph_type(self, graph_type):
      """Tests that the generated graph is a dag for all graph types."""
      degree, d_nodes = 4, 10
      sm = generate_structure(d_nodes, degree, graph_type)
      assert is_directed_acyclic_graph(sm)
  
imports: import operator
  from typing import Hashable, Tuple, Union
  import networkx
  import numpy
  import pandas
  import pytest
  from networkx.algorithms.dag import is_directed_acyclic_graph
  from sklearn.gaussian_process.kernels import RBF
  from causalnex.structure.data_generators.core import _sample_binary_from_latent, _sample_count_from_latent, _sample_poisson, generate_structure, nonlinear_sem_generator, sem_generator
  from causalnex.structure.structuremodel import StructureModel
label_desc: Use image node_id 1 for calling the TestGenerateStructure obj's underlying member method code with example usage: obj.test_is_dag_graph_type(graph_type) without return types