docstr: all the connections from past variables to current variables should be there if using `full` graph_type
docstr_tok: ["all","the","connections","from","past","variables","to","current","variables","should","be","there","if","using","`","full","`","graph_type"]
code: def test_full_graph_type(self, num_nodes, p):
      """all the connections from past variables to current variables should be there if using `full` graph_type"""
      g = generate_structure_dynamic(
          num_nodes, p, 4, 4, graph_type_inter="full"
      )
      lagged_edges = sorted(
          (u, v) for u, v in g.edges if int(u.split("_lag")[1]) > 0
      )
      assert lagged_edges == sorted(
          (f"{v_f}_lag{l_}", f"{v_t}_lag0")
          for l_ in range(1, p + 1)
          for v_f in range(num_nodes)  # var from
          for v_t in range(num_nodes)  # var to
      )
  
imports: import re
  import string
  from itertools import product
  import numpy
  import pandas
  import pytest
  from scipy import stats
  from sklearn.gaussian_process.kernels import RBF
  from causalnex.structure import StructureModel
  from causalnex.structure.data_generators import gen_stationary_dyn_net_and_df, generate_binary_data, generate_binary_dataframe, generate_categorical_dataframe, generate_continuous_data, generate_continuous_dataframe, generate_count_dataframe, generate_dataframe_dynamic, generate_structure, generate_structure_dynamic
  from tests.structure.data_generators.test_core import calculate_proba
label_desc: Use image node_id 7 for calling the TestGenerateStructureDynamic obj's underlying member method code with example usage: obj.test_full_graph_type(num_nodes, p) without return types