Fix to array shorthand not defined

sliceline/slicefinder.py

@@ -242,7 +242,7 @@ def _get_slices_masks(self, X):
  # self._top_slices_enc.sum(axis=1) is the number of predicate(s) for each top_slices_
  slices_masks = (
  slice_candidates == self._top_slices_enc.sum(axis=1)
- ).toarray().astype(int)
+ ).A.astype(int)
 
  return slices_masks
 
@@ -376,7 +376,7 @@ def _eval_slice(
  ) -> np.ndarray:
  """Compute several statistics for all the slices."""
  slice_candidates = x_encoded @ slices.T == level
- slice_sizes = slice_candidates.sum(axis=0).toarray()[0]
+ slice_sizes = slice_candidates.sum(axis=0).A[0]
  slice_errors = errors @ slice_candidates
  max_slice_errors = slice_candidates.T.multiply(errors).max(axis=1).toarray()
 
@@ -395,7 +395,7 @@ def _create_and_score_basic_slices(
  errors: np.ndarray,
  ) -> Tuple[sp.csr_matrix, np.ndarray]:
  """Initialise 1-slices, i.e. slices with one predicate."""
- slice_sizes = x_encoded.sum(axis=0).toarray()[0]
+ slice_sizes = x_encoded.sum(axis=0).A[0]
  slice_errors = errors @ x_encoded
  max_slice_errors = x_encoded.T.multiply(errors).max(axis=1).toarray()[:, 0]
 
@@ -478,7 +478,7 @@ def _prune_invalid_self_joins(
  for start, end in zip(feature_offset_start, feature_offset_end):
  valid_slices_mask = (
  valid_slices_mask
- * (pair_candidates[:, start:end].sum(axis=1) <= 1).toarray()[:, 0]
+ * (pair_candidates[:, start:end].sum(axis=1) <= 1).A[:, 0]
  )
  return (
  pair_candidates[valid_slices_mask],
@@ -505,7 +505,7 @@ def _prepare_deduplication_and_pruning(
  i = sub_pair_candidates.argmax(axis=1).T + np.any(
  sub_pair_candidates.toarray(), axis=1
  )
- ids = ids + i.toarray() * np.prod(dom[(j + 1) : dom.shape[0]])
+ ids = ids + i.A * np.prod(dom[(j + 1) : dom.shape[0]])
  return ids
 
  def _get_pair_candidates(