docs: def predict(self):
          """
          Computes all possible weighted average predictions and their variances
  
          Example::
  
              >>> from caspo import core, predict
  
              >>> networks = core.LogicalNetworkList.from_csv('behaviors.csv')
              >>> setup = core.Setup.from_json('setup.json')
  
              >>> predictor = predict.Predictor(networks, setup)
              >>> df = predictor.predict()
  
              >>> df.to_csv('predictions.csv'), index=False)
  
  
          Returns
          --------
          `pandas.DataFrame`_
              DataFrame with the weighted average predictions and variance of all readouts for each possible clamping
  
  
          .. _pandas.DataFrame: http://pandas.pydata.org/pandas-docs/stable/dsintro.html#dataframe
          """
          self._logger.info("Computing all predictions and their variance for %s logical networks...", len(self.networks))
  
          return self.networks.predictions(self.setup.filter(self.networks))