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

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

Author: pre-commit-ci[bot]

znh5md/__init__.py

@@ -1,4 +1,5 @@
 """ZnH5MD: High Performance Interface for H5MD Trajectories."""
+
 import contextlib
 import importlib.metadata
 

znh5md/format/__init__.py

@@ -1,4 +1,5 @@
 """Format handler for h5md files."""
+
 import contextlib
 import dataclasses
 import typing
@@ -33,16 +34,14 @@ class GRP:
 
     @staticmethod
     def encode_boundary(value) -> np.ndarray:
-        return np.array(
-            [
-                (
-                    "periodic".encode(encoding="utf-8")
-                    if x
-                    else "none".encode(encoding="utf-8")
-                )
-                for x in value
-            ]
-        )
+        return np.array([
+            (
+                "periodic".encode(encoding="utf-8")
+                if x
+                else "none".encode(encoding="utf-8")
+            )
+            for x in value
+        ])
 
     @staticmethod
     def decode_boundary(value) -> np.ndarray:

znh5md/io/base.py

@@ -99,9 +99,9 @@ def append_to_dataset(self, dataset_group: h5py.Group):
         self.resize_by_particle_count(dataset_group)
         for key in ("value", "time", "step"):
             dataset_group[key].resize(n_current_frames + len(self), axis=0)
-            dataset_group[key][:] = np.concatenate(
-                [dataset_group[key][:n_current_frames], self.value]
-            )
+            dataset_group[key][:] = np.concatenate([
+                dataset_group[key][:n_current_frames], self.value
+            ])
 
 
 @dataclasses.dataclass
@@ -124,9 +124,9 @@ def append_to_dataset(self, dataset_group: h5py.Group):
 
         self.resize_by_particle_count(dataset_group)
         dataset_group["value"].resize(n_current_frames + len(self), axis=0)
-        dataset_group["value"][:] = np.concatenate(
-            [dataset_group["value"][:n_current_frames], self.value]
-        )
+        dataset_group["value"][:] = np.concatenate([
+            dataset_group["value"][:n_current_frames], self.value
+        ])
 
 
 CHUNK_DICT = typing.Dict[str, ExplicitStepTimeChunk]

znh5md/io/reader.py

@@ -224,9 +224,9 @@ def yield_chunks(self) -> typing.Iterator[typing.Dict[str, FixedStepTimeChunk]]:
                 if "energy" in frame.list_properties():
                     energy.append(np.copy(frame["energy"]).astype(float))
                 if "pbc" in frame.list_properties():
-                    pbc.append(
-                        [True if x == "T" else False for x in frame["pbc"].split()]
-                    )
+                    pbc.append([
+                        True if x == "T" else False for x in frame["pbc"].split()
+                    ])
 
                 if len(positions) == self.frames_per_chunk:
                     positions = self._fill_with_nan(positions).astype(float)