def _fit_tof(self, tof_data):
"""
Runs a fit against the loaded data
"""
fit_opts = parse_fit_options(mass_values=self.getProperty("Masses").value,
profile_strs=self.getProperty("MassProfiles").value,
background_str=self.getProperty("Background").value,
constraints_str=self.getProperty("IntensityConstraints").value)
return self._run_fit(tof_data, self.getProperty("WorkspaceIndex").value, fit_opts)
def test_parse_fit_options(self):
mass_values = [1.0079, 16]
profile_strs = "function=Gaussian,width=[2,5,7];function=Gaussian,width=10.000000"
background_str = "function=Polynomial,order=2"
constraints_str = "[1,-4]"
fit_opts = parse_fit_options(mass_values, profile_strs, background_str, constraints_str)
self.assertEquals(2, len(fit_opts.mass_profiles))
self.assertTrue(isinstance(fit_opts.background, PolynomialBackground))
self.assertEquals(1, len(fit_opts.intensity_constraints))
self.assertEquals(2, len(fit_opts.intensity_constraints[0]))
def test_parse_fit_options(self):
mass_values = [1.0079, 16]
profile_strs = "function=Gaussian,width=[2,5,7];function=Gaussian,width=10.000000"
background_str = "function=Polynomial,order=2"
constraints_str = "[1,-4]"
fit_opts = parse_fit_options(mass_values, profile_strs, background_str, constraints_str)
self.assertEquals(2, len(fit_opts.mass_profiles))
self.assertTrue(isinstance(fit_opts.background, PolynomialBackground))
self.assertEquals(1, len(fit_opts.intensity_constraints))
self.assertEquals(2, len(fit_opts.intensity_constraints[0]))
def _fit_tof(self, tof_data):
"""
Runs a fit against the loaded data
"""
fit_opts = parse_fit_options(
mass_values=self.getProperty("Masses").value,
profile_strs=self.getProperty("MassProfiles").value,
background_str=self.getProperty("Background").value,
constraints_str=self.getProperty("IntensityConstraints").value)
return self._run_fit(tof_data,
self.getProperty("WorkspaceIndex").value,
fit_opts)
def _gamma_correction(self):
correction_background_ws = str(self._correction_wsg) + "_GammaBackground"
fit_opts = parse_fit_options(mass_values=self._masses,
profile_strs=self.getProperty("MassProfiles").value,
constraints_str=self.getProperty("IntensityConstraints").value)
params_dict = TableWorkspaceDictionaryFacade(self.getProperty("FitParameters").value)
func_str = fit_opts.create_function_str(params_dict)
ms.VesuvioCalculateGammaBackground(InputWorkspace=self._output_ws,
ComptonFunction=func_str,
BackgroundWorkspace=correction_background_ws,
CorrectedWorkspace='__corrected_dummy')
ms.DeleteWorkspace('__corrected_dummy')
return correction_background_ws
def _gamma_correction(self):
from mantid.simpleapi import (CalculateGammaBackground, CloneWorkspace,
DeleteWorkspace)
correction_background_ws = str(self._correction_wsg) + "_GammaBackground"
fit_opts = parse_fit_options(mass_values=self.getProperty("Masses").value,
profile_strs=self.getProperty("MassProfiles").value,
constraints_str=self.getProperty("IntensityConstraints").value)
params_ws_name = self.getPropertyValue("FitParameters")
params_dict = TableWorkspaceDictionaryFacade(mtd[params_ws_name])
func_str = fit_opts.create_function_str(params_dict)
CalculateGammaBackground(InputWorkspace=self._output_ws,
ComptonFunction=func_str,
BackgroundWorkspace=correction_background_ws,
CorrectedWorkspace='__corrected_dummy')
DeleteWorkspace('__corrected_dummy')
return correction_background_ws
def _gamma_correction(self):
correction_background_ws = str(
self._correction_wsg) + "_GammaBackground"
fit_opts = parse_fit_options(
mass_values=self._masses,
profile_strs=self.getProperty("MassProfiles").value,
constraints_str=self.getProperty("IntensityConstraints").value)
params_dict = TableWorkspaceDictionaryFacade(
self.getProperty("FitParameters").value)
func_str = fit_opts.create_function_str(params_dict)
ms.VesuvioCalculateGammaBackground(
InputWorkspace=self._output_ws,
ComptonFunction=func_str,
BackgroundWorkspace=correction_background_ws,
CorrectedWorkspace='__corrected_dummy')
ms.DeleteWorkspace('__corrected_dummy')
return correction_background_ws
