[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

sparse/_coo/common.py

@@ -1237,7 +1237,7 @@ def take(x, indices, /, *, axis=None):
     if axis is None:
         x = x.flatten()
         return x[indices]
-    
+
     axis = normalize_axis(axis, x.ndim)
     full_index = (slice(None),) * axis + (indices, ...)
     return x[full_index]
@@ -1293,7 +1293,7 @@ def _sort_coo(
                 indices[pos:] += fill_value_count
                 break
 
-        result_indices[offset:offset+len(indices)] = indices
+        result_indices[offset : offset + len(indices)] = indices
         offset += len(indices)
 
     sort_coords[:] = result_indices

sparse/tests/test_coo.py

@@ -1779,15 +1779,18 @@ def test_input_validation(self, func):
             func(self.arr)
 
 
-@pytest.mark.parametrize("arr", [
-    np.array([[0, 0, 1, 5, 3, 0], [1, 0, 4, 0, 3, 0], [0, 1, 0, 1, 1, 0]], dtype=np.int64),
-    np.array([[[2, 0], [0, 5]], [[1, 0], [4, 0]], [[0, 1], [0, -1]]], dtype=np.float64)
-])
+@pytest.mark.parametrize(
+    "arr",
+    [
+        np.array([[0, 0, 1, 5, 3, 0], [1, 0, 4, 0, 3, 0], [0, 1, 0, 1, 1, 0]], dtype=np.int64),
+        np.array([[[2, 0], [0, 5]], [[1, 0], [4, 0]], [[0, 1], [0, -1]]], dtype=np.float64),
+    ],
+)
 @pytest.mark.parametrize("fill_value", [-1, 0, 1, 3])
 @pytest.mark.parametrize("axis", [0, 1, -1])
 @pytest.mark.parametrize("descending", [False, True])
 def test_sort(arr, fill_value, axis, descending):
-    s_arr = sparse.COO.from_numpy(arr, fill_value) 
+    s_arr = sparse.COO.from_numpy(arr, fill_value)
 
     result = sparse.sort(s_arr, axis=axis, descending=descending)
     expected = -np.sort(-arr, axis=axis) if descending else np.sort(arr, axis=axis)
@@ -1798,10 +1801,19 @@ def test_sort(arr, fill_value, axis, descending):
 @pytest.mark.parametrize("fill_value", [-1, 0, 1, 3])
 @pytest.mark.parametrize(
     "indices,axis",
-    [([1], 0,), ([2, 1], 1), ([1, 2, 3], 2), ([2, 3], -1), ([5, 3, 7, 8], None)]
+    [
+        (
+            [1],
+            0,
+        ),
+        ([2, 1], 1),
+        ([1, 2, 3], 2),
+        ([2, 3], -1),
+        ([5, 3, 7, 8], None),
+    ],
 )
 def test_take(fill_value, indices, axis):
-    arr = np.arange(24).reshape((2,3,4))
+    arr = np.arange(24).reshape((2, 3, 4))
 
     s_arr = sparse.COO.from_numpy(arr, fill_value)