code: def is_uniform(self,verbose=True):
          
          uni = pd.Series(self['phenotype_calls'].apply(lambda x: json.dumps(x)).unique()).\
              apply(lambda x: json.loads(x)).apply(lambda x: tuple(sorted(x.keys()))).unique()
          if len(uni) > 1: 
              if verbose: sys.stderr.write("WARNING: phenotypes differ across the dataframe \n"+str(uni)+"\n")
              return False
          uni = pd.Series(self['scored_calls'].apply(lambda x: json.dumps(x)).unique()).\
              apply(lambda x: json.loads(x)).apply(lambda x: tuple(sorted(x.keys()))).unique()
          if len(uni) > 1: 
              if verbose: sys.stderr.write("WARNING: scored_calls differ across the dataframe \n"+str(uni)+"\n")
              return False
          return True
docs: Check to make sure phenotype calls, or scored calls are consistent across all images / samples