Save xgm when binning by intra-train pulse id

DSSC.py

@@ -330,6 +330,10 @@ class DSSC:
                    
         if do_pulse_mean:
             self.module_data = xr.merge([self.module_data, self.scan.groupby('scan_variable').mean('trainId')])
+        else:
+            xgm_pumped = self.xgm[:, :self.nbunches:2].mean('trainId').to_dataset(name='xgm_pumped').rename({'dim_0':'scan_variable'})
+            xgm_unpumped = self.xgm[:, 1:self.nbunches:2].mean('trainId').to_dataset(name='xgm_unpumped').rename({'dim_0':'scan_variable'})
+            self.module_data = xr.merge([self.module_data, xgm_pumped, xgm_unpumped])
         self.module_data = self.module_data.squeeze()
         
         if do_pulse_mean:
@@ -528,7 +532,7 @@ class DSSC:
         """
         fig, [ax1, ax2] = plt.subplots(nrows=2, sharex=True, sharey=True)
 
-        xr.plot.imshow(self.azimuthal.pumped, ax=ax1, robust=True)
+        xr.plot.imshow(self.azimuthal.pumped, ax=ax1, vmin=0, robust=True)
         ax1.set_title('pumped')
         ax1.set_xlabel(self.scan_vname)
         xr.plot.imshow(self.azimuthal.pumped - self.azimuthal.unpumped, ax=ax2, robust=True)
@@ -654,7 +658,7 @@ def process_one_module(job):
 
             for var in ['pumped', 'unpumped', 'sum_count']:
                 module_data[var].loc[where] = module_data[var].loc[where] + data[var]
-
+                   
     for var in ['pumped', 'unpumped']:
         module_data[var] = module_data[var] / module_data.sum_count
     #module_data = module_data.drop('sum_count')