code: def test_preprocess_type_checks(self, dist_type, X):
      dist_types = [dist_type(idx=idx) for idx in np.arange(X.shape[1])]
      for dt in dist_types:
          with pytest.raises(
              ValueError,
              match=r"All data must be positive for Poisson\.",
          ):
              X = dt.preprocess_X(X)
  
imports: import copy
  import numpy
  import pandas
  import pytest
  import torch
  from causalnex.structure.pytorch.dist_type import DistTypeBinary, DistTypeCategorical, DistTypeContinuous, DistTypeOrdinal, DistTypePoisson
  from causalnex.structure.pytorch.notears import from_numpy, from_pandas
label_desc: Use image node_id 3 for calling the TestDistTypeClasses obj's underlying member method code with example usage: obj.test_preprocess_type_checks(dist_type, X) without return types