diff --git a/scripts/Muon/GUI/Common/fitting_tab_widget/fitting_tab_model.py b/scripts/Muon/GUI/Common/fitting_tab_widget/fitting_tab_model.py index 8e652fc7300046b70f4f9c6a1436ece9b7fd4b1e..eb8aa3a9e78d5f75b3d284eae3c59913271add9f 100644 --- a/scripts/Muon/GUI/Common/fitting_tab_widget/fitting_tab_model.py +++ b/scripts/Muon/GUI/Common/fitting_tab_widget/fitting_tab_model.py @@ -102,7 +102,7 @@ class FittingTabModel(object): self._handle_single_fit_results(parameter_dict['InputWorkspace'], function_object, fitting_parameters_table, output_workspace, covariance_matrix, plot_fit) - return function_object.clone(), output_status, output_chi_squared + return function_object, output_status, output_chi_squared def do_single_tf_fit(self, parameter_dict, plot_fit=True): alg = mantid.AlgorithmManager.create("CalculateMuonAsymmetry") @@ -114,7 +114,7 @@ class FittingTabModel(object): fitting_parameters_table, output_workspace, covariance_matrix, plot_fit) - return function_object.clone(), output_status, output_chi_squared + return function_object, output_status, output_chi_squared def do_single_fit_and_return_workspace_parameters_and_fit_function( self, parameters_dict): @@ -210,7 +210,6 @@ class FittingTabModel(object): output_chi_squared_list = [] for i, input_workspace in enumerate(workspace_list): - params = self.get_parameters_for_single_fit(input_workspace) if not use_initial_values and i >= 1: @@ -220,8 +219,8 @@ class FittingTabModel(object): function_object, output_status, output_chi_squared = self.do_single_fit(params, plot_fit) - function_object_list.append(function_object) + function_object_list.append(function_object) output_status_list.append(output_status) output_chi_squared_list.append(output_chi_squared) @@ -245,7 +244,6 @@ class FittingTabModel(object): self.global_parameters, plot_fit) function_object_list.append(function_object) - output_status_list.append(output_status) output_chi_squared_list.append(output_chi_squared) @@ -261,14 +259,13 @@ class FittingTabModel(object): if not use_initial_values and i >= 1: previous_values = self.get_fit_function_parameter_values(function_object_list[i - 1]) - self.set_fit_function_parameter_values(params['Function'], + self.set_fit_function_parameter_values(params['InputFunction'], previous_values) function_object, output_status, output_chi_squared = self.do_single_tf_fit(params, plot_fit) function_object_list.append(function_object) - output_status_list.append(output_status) output_chi_squared_list.append(output_chi_squared) @@ -284,7 +281,7 @@ class FittingTabModel(object): if not use_initial_values and i >= 1: previous_values = self.get_fit_function_parameter_values(function_object_list[i - 1]) - self.set_fit_function_parameter_values(params['Function'], + self.set_fit_function_parameter_values(params['InputFunction'], previous_values) function_object, output_status, output_chi_squared = self.do_simultaneous_tf_fit(params, @@ -292,7 +289,6 @@ class FittingTabModel(object): plot_fit) function_object_list.append(function_object) - output_status_list.append(output_status) output_chi_squared_list.append(output_chi_squared)