flake8 xgm

src/toolbox_scs/detectors/xgm.py

@@ -13,8 +13,7 @@ import xarray as xr
 import matplotlib.pyplot as plt
 
 from ..misc.bunch_pattern_external import is_sase_1, is_sase_3
-from ..mnemonics_machinery import (mnemonics_to_process,
-                                   mnemonics_for_run)
+from ..mnemonics_machinery import mnemonics_for_run
 from toolbox_scs.load import (get_array, load_bpt, get_sase_pId)
 
 __all__ = [
@@ -25,6 +24,7 @@ __all__ = [
 
 log = logging.getLogger(__name__)
 
+
 def get_xgm(run, mnemonics=None, merge_with=None,
             indices=slice(0, None)):
     """
@@ -75,7 +75,7 @@ def get_xgm(run, mnemonics=None, merge_with=None,
     if len(m2) == 0:
         log.info('no XGM mnemonics to process. Skipping.')
         return merge_with
-    mnemonics = list(set(m2))    
+    mnemonics = list(set(m2))
     # Prepare the dataset of non-XGM data to merge with
     if bool(merge_with):
         ds_mw = merge_with.drop(mnemonics, errors='ignore')
@@ -106,8 +106,8 @@ def get_xgm(run, mnemonics=None, merge_with=None,
                     ds_mw = ds_mw.merge(bpt, join='inner')
             else:
                 xgm_val = da_xgm.values
-                xgm_val[xgm_val==1] = np.nan
-                xgm_val[xgm_val==0] = np.nan
+                xgm_val[xgm_val == 1] = np.nan
+                xgm_val[xgm_val == 0] = np.nan
                 da_xgm.values = xgm_val
                 da_xgm = da_xgm.dropna(dim='XGMbunchId', how='all')
                 ds_xgm = da_xgm.fillna(0).sel(XGMbunchId=indices).to_dataset()
@@ -143,15 +143,15 @@ def load_xgm_array(run, xgm, mnemonic, sase1, sase3):
         the dataset containing the aligned XGM variable(s).
     """
     xgm_val = xgm.values
-    xgm_val[xgm_val==1] = np.nan
-    xgm_val[xgm_val==0] = np.nan
+    xgm_val[xgm_val == 1] = np.nan
+    xgm_val[xgm_val == 0] = np.nan
     xgm.values = xgm_val
     xgm = xgm.dropna(dim='XGMbunchId', how='all')
     xgm = xgm.fillna(0)
     if 'XGM' in mnemonic:
         sase1_3 = np.sort(np.concatenate([sase1, sase3]))
-        sase1_idx = [np.argwhere(sase1_3==i)[0][0] for i in sase1]
-        sase3_idx = [np.argwhere(sase1_3==i)[0][0] for i in sase3]
+        sase1_idx = [np.argwhere(sase1_3 == i)[0][0] for i in sase1]
+        sase3_idx = [np.argwhere(sase1_3 == i)[0][0] for i in sase3]
         xgm_sa1 = xgm.isel(XGMbunchId=sase1_idx).rename(XGMbunchId='sa1_pId')
         xgm_sa1 = xgm_sa1.assign_coords(sa1_pId=sase1)
         xgm_sa1 = xgm_sa1.rename(mnemonic.replace('XGM', 'SA1'))