Fix a few warnings

netatmoqc/hollow_symmetric_matrix.py

@@ -164,7 +164,7 @@ def _to_dense(data, n, dtype):
 
     """
     dense = np.zeros(shape=(n, n), dtype=dtype)
-    for idata in prange(len(data)):
+    for idata in prange(len(data)):  # pylint: disable=not-an-iterable
         i, j = _data_index_to_matrix_index(n, idata, check_bounds=False)
         data_value = data[idata]
         dense[i, j] = data_value
@@ -195,7 +195,7 @@ def _to_compact(dense, dtype):
     n = dense.shape[0]
     n_indep = (n ** 2 - n) // 2
     compact = np.zeros(n_indep, dtype=dtype)
-    for idata in prange(len(compact)):
+    for idata in prange(len(compact)):  # pylint: disable=not-an-iterable
         i, j = _data_index_to_matrix_index(n, idata, check_bounds=False)
         compact[idata] = dense[i, j]
     return compact
@@ -617,7 +617,7 @@ class HollowSymmetricMatrix(np.lib.mixins.NDArrayOperatorsMixin):
         """Return (i, j) such that self.data[data_i] == self[i, j]."""
         return _data_index_to_matrix_index(self.order, data_i)
 
-    def __array__(self, dtype=None, copy=False, order=None):
+    def __array__(self, *args, **kwargs):
         # See <https://numpy.org/devdocs/user/basics.dispatch.html>
         # TODO: Remove the ".astype(np.float64)" when possible.
         # HDBSCAN requires that the result of np.array(self) to have
@@ -702,9 +702,9 @@ class HollowSymmetricMatrix(np.lib.mixins.NDArrayOperatorsMixin):
 
     def __setitem__(self, ij_tuple, value):
         try:
-            boolean_indexing = ij_tuple.dtype == np.bool
+            boolean_indexing = ij_tuple.dtype == bool
         except AttributeError:
-            boolean_indexing = np.array(ij_tuple).dtype == np.bool
+            boolean_indexing = np.array(ij_tuple).dtype == bool
 
         if boolean_indexing:
             if isinstance(ij_tuple, type(self)):

tests/test_hollow_symmetric_matrix.py

@@ -28,9 +28,7 @@ def gen_random_hsm(n):
 
 def gen_random_bool_mask_triu(n):
     """Return a random numpy.triu matrix with dtype numpy.bool."""
-    return np.triu(np.random.randint(n, size=n * n).reshape(n, n)).astype(
-        np.bool
-    )
+    return np.triu(np.random.randint(n, size=n * n).reshape(n, n)).astype(bool)
 
 
 def gen_random_bool_mask_tril(n):
@@ -119,7 +117,7 @@ class TestsSetitem:
             # A single diagonal element as (int, int)
             lambda n: tuple(np.repeat(np.random.randint(n), 2)),
             # All diag elements as boolean array
-            lambda n: np.eye(n).astype(np.bool),
+            lambda n: np.eye(n).astype(bool),
         ],
     )
     def test_setitem_enforces_hollow(self, random_hsm, gen_indices):