black-formatting-issue

Author: tani-dubey

package/MDAnalysis/analysis/msd.py

@@ -336,7 +336,9 @@ def __init__(
         **kwargs,
     ):
         if isinstance(u, groups.UpdatingAtomGroup):
-            raise TypeError("UpdatingAtomGroups are not valid for MSD computation")
+            raise TypeError(
+                "UpdatingAtomGroups are not valid for MSD computation"
+            )
 
         super(EinsteinMSD, self).__init__(u.universe.trajectory, **kwargs)
 
@@ -360,8 +362,12 @@ def __init__(
     def _prepare(self):
         # self.n_frames only available here
         # these need to be zeroed prior to each run() call
-        self.results.msds_by_particle = np.zeros((self.n_frames, self.n_particles))
-        self._position_array = np.zeros((self.n_frames, self.n_particles, self.dim_fac))
+        self.results.msds_by_particle = np.zeros(
+            (self.n_frames, self.n_particles)
+        )
+        self._position_array = np.zeros(
+            (self.n_frames, self.n_particles, self.dim_fac)
+        )
         # self.results.timeseries not set here
 
     def _parse_msd_type(self):
@@ -400,7 +406,9 @@ def _single_frame(self):
         r"""Constructs array of positions for MSD calculation."""
         # shape of position array set here, use span in last dimension
         # from this point on
-        self._position_array[self._frame_index] = self.ag.positions[:, self._dim]
+        self._position_array[self._frame_index] = self.ag.positions[
+            :, self._dim
+        ]
 
     def _conclude(self):
         if self.non_linear:
@@ -451,7 +459,9 @@ def _conclude_fft(self):  # with FFT, np.float64 bit prescision required.
             verbose=self._verbose,
             desc="Calculating MSD with FFT per particle",
         ):
-            self.results.msds_by_particle[:, n] = tidynamics.msd(positions[:, n, :])
+            self.results.msds_by_particle[:, n] = tidynamics.msd(
+                positions[:, n, :]
+            )
         self.results.timeseries = self.results.msds_by_particle.mean(axis=1)
         self.results.delta_t_values = np.arange(self.n_frames) * (
             self.times[1] - self.times[0]