code: def test_bad_flow(barbell):
      generator = GraphWaveGenerator(
          barbell, scales=(0.1, 2, 3, 4), degree=10
      )
      sample_points = np.linspace(0, 100, 25)
  
      with pytest.raises(
          TypeError, match="batch_size: expected.*found float"
      ):
          generator.flow(barbell.nodes(), sample_points, batch_size=4.5)
  
      with pytest.raises(
          ValueError, match="batch_size: expected.*found 0"
      ):
          generator.flow(barbell.nodes(), sample_points, batch_size=0)
  
      with pytest.raises(
          TypeError, match="shuffle: expected.*found int"
      ):
          generator.flow(
              barbell.nodes(), sample_points, batch_size=1, shuffle=1
          )
  
      with pytest.raises(
          TypeError, match="repeat: expected.*found int"
      ):
          generator.flow(
              barbell.nodes(), sample_points, batch_size=1, repeat=1
          )
  
      with pytest.raises(
          TypeError, match="num_parallel_calls: expected.*found float"
      ):
          generator.flow(
              barbell.nodes(),
              sample_points,
              batch_size=1,
              num_parallel_calls=2.2,
          )
  
      with pytest.raises(
          ValueError, match="num_parallel_calls: expected.*found 0"
      ):
          generator.flow(
              barbell.nodes(),
              sample_points,
              batch_size=1,
              num_parallel_calls=0,
          )
  
file_path: stellargraph/tests/mapper/test_graphwave_generator.py
imports: from stellargraph.core.graph import *
  from stellargraph.mapper.graphwave_generator import GraphWaveGenerator, _empirical_characteristic_function
  from ..test_utils.graphs import barbell
  import numpy
  import pytest
  import scipy.sparse
  import tensorflow
label_desc: Use image node_id 4 for calling a global function with example usage: test_bad_flow(barbell) without return types