Solve issue with normalizing if total particle count is 0

examples/2_test_assign_particles.py

@@ -35,7 +35,7 @@ data_dir            = os.path.join( PROJECT_ROOT_DIR, 'data' )
 datasets_df         = pd.read_csv( data_dir + '/datasets_example.csv'  )
 selected_data_df         = datasets_df[
                                         (datasets_df['data_lbl']=='data_set_2_od')
-                                        & (datasets_df['cond']=='WT')
+                                       # & (datasets_df['cond']=='WT')
                                       ]
 
 all_cells, all_particles, all_heatmap_data = al.assign_particles_to_nuclei( data_dir,  selected_data_df )

lib/assign_particles.py

@@ -237,17 +237,27 @@ def show_quick_stats(all_cells, all_particles ):
     for mut_str in all_particles['mut'].unique():
         
         print(10*'-' + mut_str + 10*'-')
-        
-        for tt in all_particles['t'].unique():
-            sub_df      = all_particles[ (all_particles['mut']==mut_str) & (all_particles['t']==tt) ]
-            n0          = sub_df[ sub_df['p_rel_pos']==0 ].shape[0]
-            n1          = sub_df[ sub_df['p_rel_pos']==1 ].shape[0]
+        mut_df      = all_particles[ (all_particles['mut']==mut_str) ]
+
+        for tt in mut_df['t'].unique():
+            mut_t_df      = mut_df[ mut_df['t']==tt ]
+            n0          = mut_t_df[ mut_t_df['p_rel_pos']==0 ].shape[0]
+            n1          = mut_t_df[ mut_t_df['p_rel_pos']==1 ].shape[0]
             n           = n0+n1        
-            cur_nparticles  = len( sub_df )
+            cur_nparticles  = len( mut_t_df )
+            if cur_nparticles == 0:
+                print( ('%s'%tt).center(10,' ') + 
+                       ('%s'%cur_nparticles).center(20,' ') + 
+                       ('%s'%n).center(20,' ') + 
+                       (' 0 particles; cannot normalize by 0. ')
+                      )
+                continue
+            
+            # if total count is above 0, continue with normalization
             fr          = n/cur_nparticles 
             fr_corr     = fr/ normalize_tip_counts_by
-            cur_od      = sub_df['od'].unique()
-           # print( 'T: %s \t N foci total: %s \t N foci at 2 poles: %s   \t fraction: %0.2f'%(tt, cur_nparticles, n, fr ) )
+            cur_od      = mut_t_df['od'].unique()
+            # print( 'T: %s \t N foci total: %s \t N foci at 2 poles: %s   \t fraction: %0.2f'%(tt, cur_nparticles, n, fr ) )
             print( ('%s'%tt).center(10,' ') + 
                    ('%s'%cur_nparticles).center(20,' ') + 
                    ('%s'%n).center(20,' ')  +