def _var_res_to_weights(self, var_res):
        """
        Get model weights
        """
        # transform the weights into our form
        motif_base_weights_raw = var_res["motif_base_weights"][0]
        motif_base_weights = np.swapaxes(motif_base_weights_raw, 0, 2)

        # get weights
        motif_weights = var_res["motif_weights"]
        motif_bias = var_res["motif_bias"]
        final_bias = var_res["final_bias"]
        feature_weights = var_res["feature_weights"]

        # get the GAM prediction:
        spline_pred = None
        spline_weights = None
        if self._param["n_splines"] is not None:
            spline_pred = self._splines["X_spline"].dot(var_res["spline_weights"])

            if self._param["spline_exp"] is True:
                spline_pred = np.exp(spline_pred)
            else:
                spline_pred = (spline_pred + 1)

            spline_pred.reshape([-1])
            spline_weights = var_res["spline_weights"]

        weights = {"motif_base_weights": motif_base_weights,
                   "motif_weights": motif_weights,
                   "motif_bias": motif_bias,
                   "final_bias": final_bias,
                   "feature_weights": feature_weights,
                   "spline_pred": spline_pred,
                   "spline_weights": spline_weights
                   }
        return weights
Get model weights