Esempio n. 1
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    def do_single_tf_fit(self, parameter_dict, output_workspace_group):
        alg = mantid.AlgorithmManager.create("CalculateMuonAsymmetry")
        output_workspace, fitting_parameters_table, function_object, output_status, output_chi_squared =\
            run_CalculateMuonAsymmetry(parameter_dict, alg)

        self._handle_single_fit_results(
            parameter_dict['ReNormalizedWorkspaceList'], function_object,
            fitting_parameters_table, output_workspace, output_workspace_group)

        return function_object.clone(), output_status, output_chi_squared
Esempio n. 2
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    def do_single_tf_fit(self, parameter_dict):
        alg = mantid.AlgorithmManager.create("CalculateMuonAsymmetry")
        output_workspace, fitting_parameters_table, function_object, output_status, output_chi_squared, covariance_matrix = \
            run_CalculateMuonAsymmetry(parameter_dict, alg)
        CopyLogs(InputWorkspace=parameter_dict['ReNormalizedWorkspaceList'], OutputWorkspace=output_workspace,
                 StoreInADS=False)
        self._handle_single_fit_results(parameter_dict['ReNormalizedWorkspaceList'], function_object,
                                        fitting_parameters_table, output_workspace, covariance_matrix)

        return function_object, output_status, output_chi_squared
Esempio n. 3
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    def do_simultaneous_tf_fit(self, parameter_dict, global_parameters):
        alg = mantid.AlgorithmManager.create("CalculateMuonAsymmetry")
        output_workspace, fitting_parameters_table, function_object, output_status, output_chi_squared, covariance_matrix = \
            run_CalculateMuonAsymmetry(parameter_dict, alg)
        if len(parameter_dict['ReNormalizedWorkspaceList']) > 1:
            for input_workspace, output in zip(parameter_dict['ReNormalizedWorkspaceList'],
                                               mantid.api.AnalysisDataService.retrieve(output_workspace).getNames()):
                CopyLogs(InputWorkspace=input_workspace, OutputWorkspace=output, StoreInADS=False)
        else:
            CopyLogs(InputWorkspace=parameter_dict['ReNormalizedWorkspaceList'][0], OutputWorkspace=output_workspace,
                     StoreInADS=False)

        self._handle_simultaneous_fit_results(parameter_dict['ReNormalizedWorkspaceList'], function_object,
                                              fitting_parameters_table, output_workspace, global_parameters,
                                              covariance_matrix)

        return function_object, output_status, output_chi_squared