18165030cc755a82e0500250bde33d978507dedc,pykrige/uk3d.py,UniversalKriging3D,update_variogram_model,#UniversalKriging3D#,396

Before Change

        if self.verbose:
            print("Updating variogram mode...")

        if variogram_parameters is None:
            vp_temp = None
        elif use_psill:
            vp_temp = variogram_parameters
        else:
            if self.variogram_model in ["gaussian", "spherical", "exponential", "hole-effect"]:
                vp_temp = [variogram_parameters[0] - variogram_parameters[2],
                           variogram_parameters[1], variogram_parameters[2]]
            else:
                vp_temp = variogram_parameters
        self.lags, self.semivariance, self.variogram_model_parameters = \
            initialize_variogram_model(np.vstack((self.X_ADJUSTED, self.Y_ADJUSTED, self.Z_ADJUSTED)).T, self.VALUES,
                                       self.variogram_model, vp_temp, self.variogram_function,
                                       nlags, weight, "euclidean")

After Change

                                      [self.anisotropy_scaling_y, self.anisotropy_scaling_z],
                                      [self.anisotropy_angle_x, self.anisotropy_angle_y, self.anisotropy_angle_z]).T

        self.variogram_model = variogram_model
        if self.variogram_model not in self.variogram_dict.keys() and self.variogram_model != "custom":
            raise ValueError("Specified variogram model "%s" is not supported." % variogram_model)
        elif self.variogram_model == "custom":
            if variogram_function is None or not callable(variogram_function):
                raise ValueError("Must specify callable function for custom variogram model.")
            else:
                self.variogram_function = variogram_function
        else:
            self.variogram_function = self.variogram_dict[self.variogram_model]
        if self.verbose:
            print("Updating variogram mode...")

        vp_temp = _make_variogram_parameter_list(self.variogram_model,
                                                 variogram_parameters)
        self.lags, self.semivariance, self.variogram_model_parameters = \
            initialize_variogram_model(np.vstack((self.X_ADJUSTED,
                                                  self.Y_ADJUSTED,
                                                  self.Z_ADJUSTED)).T,

Instances