Black formatting

Author: cophus

README.md

@@ -1,6 +1,3 @@
-this is a test -- 
-
-
 > :warning: **py4DSTEM version 0.14 update** :warning: Warning: this is a major update and we expect some workflows to break.  You can still install previous versions of py4DSTEM [as discussed here](#legacyinstall)
 
 > :warning: **Phase retrieval refactor version 0.14.9** :warning: Warning: The phase-retrieval modules in py4DSTEM (DPC, parallax, and ptychography) underwent a major refactor in version 0.14.9 and as such older tutorial notebooks will not work as expected. Notably, class names have been pruned to remove the trailing "Reconstruction" (`DPCReconstruction` -> `DPC` etc.), and regularization functions have dropped the `_iter` suffix (and are instead specified as boolean flags). See the [updated tutorials](https://github.com/py4dstem/py4DSTEM_tutorials) for more information.

py4DSTEM/process/__init__.py

@@ -21,4 +21,3 @@
         raise exc
 
 from py4DSTEM.process.utils import Cluster
-

py4DSTEM/process/diffraction/crystal_phase.py

@@ -102,7 +102,7 @@ def quantify_single_pattern(
         plot_correlation_radius=False,
         scale_markers_experiment=40,
         scale_markers_calculated=200,
-        max_marker_size = 400,
+        max_marker_size=400,
         crystal_inds_plot=None,
         phase_colors=None,
         figsize=(10, 7),
@@ -629,8 +629,7 @@ def quantify_single_pattern(
                 qx,
                 # s = scale_markers_experiment * intensity,
                 s=np.minimum(
-                    scale_markers_experiment 
-                    * bragg_peaks.data["intensity"][keep],
+                    scale_markers_experiment * bragg_peaks.data["intensity"][keep],
                     max_marker_size,
                 ),
                 marker="o",
@@ -1230,7 +1229,7 @@ def plot_dominant_phase(
         self,
         use_correlation_scores=False,
         reliability_range=(0.0, 1.0),
-        normalize_exp_intensity = True,
+        normalize_exp_intensity=True,
         sigma=0.0,
         phase_colors=None,
         ticks=True,
@@ -1319,7 +1318,6 @@ def plot_dominant_phase(
         # if normalize_exp_intensity:
         #     phase_sig /= self.int_total[None,:,:]
 
-
         # find highest correlation score for each crystal and match index
         for a0 in range(self.num_crystals):
             sub = phase_sig[a0] > phase_corr
@@ -1349,7 +1347,6 @@ def plot_dominant_phase(
             if normalize_exp_intensity:
                 phase_rel /= self.int_total
 
-
             phase_scale = np.clip(
                 (phase_rel - reliability_range[0])
                 / (reliability_range[1] - reliability_range[0]),