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

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reciprocalspaceship/dataset.py

@@ -53,7 +53,7 @@ class DataSet(pd.DataFrame):
     centrics : rs.DataSet
         Access only the centric reflections in this dataset
     hkls : ndarray, shape=(n_reflections, 3)
-        Miller indices in DataSet. 
+        Miller indices in DataSet.
     merged : bool
         Whether this is a merged dataset or unmerged
 
@@ -157,27 +157,29 @@ def hkls(self):
         return hkl
 
     def get_hkls(self):
-        """ For backwards compatibility retain the get_hkls method in addition to the dataset.hkls attribute """
+        """For backwards compatibility retain the get_hkls method in addition to the dataset.hkls attribute"""
         return self.hkls
 
     @hkls.setter
     @range_indexed
     def hkls(self, hkls):
         if isinstance(hkls, DataSet):
-            """ Convert to numpy if hkls is a dataset """
+            """Convert to numpy if hkls is a dataset"""
             hkls = hkls.hkls
         if isinstance(hkls, np.ndarray):
-            h,k,l = hkls[...,0], hkls[...,1], hkls[...,2]
+            h, k, l = hkls[..., 0], hkls[..., 1], hkls[..., 2]
         else:
-            """ Try coercing to numpy """
+            """Try coercing to numpy"""
             try:
                 hkls = np.array(hkls)
-                h,k,l = hkls[...,0], hkls[...,1], hkls[...,2]
+                h, k, l = hkls[..., 0], hkls[..., 1], hkls[..., 2]
             except:
-                raise ValueError("Unable to convert hkls to a suitable type. Please ensure hkls is a numpy array or rs.DataSet")
-        self['H'] = DataSeries(h, index = self.index, dtype='H')
-        self['K'] = DataSeries(k, index = self.index, dtype='H')
-        self['L'] = DataSeries(l, index = self.index, dtype='H')
+                raise ValueError(
+                    "Unable to convert hkls to a suitable type. Please ensure hkls is a numpy array or rs.DataSet"
+                )
+        self["H"] = DataSeries(h, index=self.index, dtype="H")
+        self["K"] = DataSeries(k, index=self.index, dtype="H")
+        self["L"] = DataSeries(l, index=self.index, dtype="H")
 
     @property
     def centrics(self):

tests/test_dataset.py

@@ -716,7 +716,9 @@ def test_select_mtzdtype_ValueError(data_merged, dtype):
 @pytest.mark.parametrize("merged", [True, False])
 @pytest.mark.parametrize("hkl_as_ds", [True, False])
 @pytest.mark.parametrize("range_index", [True, False])
-def test_hkls_property_setter(data_merged, data_unmerged, merged, hkl_as_ds, range_index):
+def test_hkls_property_setter(
+    data_merged, data_unmerged, merged, hkl_as_ds, range_index
+):
     """
     Test the setter for the .hkls property of rs datasets
     """
@@ -733,20 +735,20 @@ def test_hkls_property_setter(data_merged, data_unmerged, merged, hkl_as_ds, ran
     hmax = 20
     n = len(ds)
 
-    hkls = np.random.randint(-hmax, hmax+1, size=(n, 3))
+    hkls = np.random.randint(-hmax, hmax + 1, size=(n, 3))
     if hkl_as_ds:
-        hkls = rs.DataSet({
-            'H' : hkls[...,0],
-            'K' : hkls[...,1],
-            'L' : hkls[...,2],
-        })
-
+        hkls = rs.DataSet(
+            {
+                "H": hkls[..., 0],
+                "K": hkls[..., 1],
+                "L": hkls[..., 2],
+            }
+        )
+
     ds.hkls = hkls
     assert np.array_equal(hkls, ds.hkls)
 
     # Test that all data remained the same
     for k in input_ds:
-        if k not in ['H', 'K', 'L']:
+        if k not in ["H", "K", "L"]:
             assert np.array_equal(ds[k], input_ds[k])
-
-