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Add ability to fit individually, globally, or both #63

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Add ability to fit individually, globally, or both #63

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e1dd118
add functionality for different fit type options
jess-farmer Apr 26, 2023
e877ba7
remove function as no longer needed
jess-farmer Apr 26, 2023
a26051c
fix unit test failures
jess-farmer Apr 26, 2023
6c33460
use lm to fit instead of steepest descent
jess-farmer Apr 27, 2023
66d0f1b
allow fitting of multiple peaks and add new system test
jess-farmer Apr 27, 2023
76510f5
Exclude invalid spectra from global fit if preset
jess-farmer May 4, 2023
94f6aba
address review comments
jess-farmer May 23, 2023
8a366af
remove need to define indv/global peak tables
jess-farmer May 23, 2023
41b42e1
Compare enums instead of strings
jess-farmer May 24, 2023
0fb2ab8
fix failing tests
jess-farmer May 24, 2023
5f4ef97
add more unit tests for _fit_shared_peak
jess-farmer May 31, 2023
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140 changes: 94 additions & 46 deletions unpackaged/vesuvio_calibration/calibration_scripts/calibrate_vesuvio_analysis.py
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Original file line number Diff line number Diff line change
Expand Up @@ -137,10 +137,10 @@ def PyExec(self):
self._invalid_detectors.add_invalid_detectors(invalid_detectors)

E1_peak_fits_back = mtd[self._current_workspace + '_E1_back_Peak_Parameters'].getNames()
self._calculate_final_energy(E1_peak_fits_back, EVSGlobals.BACKSCATTERING_RANGE, self._shared_parameter_fit_type != "Individual")
self._calculate_final_energy(E1_peak_fits_back, EVSGlobals.BACKSCATTERING_RANGE, self._shared_parameter_fit_type)

# calibrate L1 for backscattering detectors based on the averaged E1 value and calibrated theta values
self._calculate_final_flight_path(E1_peak_fits_back[0], EVSGlobals.BACKSCATTERING_RANGE)
self._calculate_final_flight_path(E1_peak_fits_back, EVSGlobals.BACKSCATTERING_RANGE, self._shared_parameter_fit_type)

# calibrate L1 for frontscattering detectors based on the averaged E1 value and calibrated theta values
E1_fit_front = self._current_workspace + '_E1_front'
Expand All @@ -153,7 +153,7 @@ def PyExec(self):
self._invalid_detectors.add_invalid_detectors(invalid_detectors)

E1_peak_fits_front = mtd[self._current_workspace + '_E1_front_Peak_Parameters'].getNames()
self._calculate_final_flight_path(E1_peak_fits_front[0], EVSGlobals.FRONTSCATTERING_RANGE)
self._calculate_final_flight_path(E1_peak_fits_front, EVSGlobals.FRONTSCATTERING_RANGE, self._shared_parameter_fit_type)

# make the fitted parameters for this iteration the input to the next iteration.
table_group.append(self._current_workspace)
Expand Down Expand Up @@ -245,33 +245,61 @@ def _calculate_incident_flight_path(self, table_name, spec_list):

DeleteWorkspace(L0_param_table)

def _calculate_final_flight_path(self, peak_table, spec_list):
def _calculate_final_flight_path(self, peak_table, spec_list, fit_type):
"""
Calculate the final flight path using the values for energy.
This also uses the old value for L1 loaded from the parameter file.

@param spec_list - spectrum range to calculate t0 for.
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"""
if fit_type == 'Both':
indv_peak_table = peak_table[0]
glob_peak_table = peak_table[1]
E1 = EVSMiscFunctions.read_table_column(self._current_workspace, 'E1', spec_list)
E1 *= EVSGlobals.MEV_CONVERSION
global_E1 = EVSMiscFunctions.read_table_column(self._current_workspace, 'global_E1', spec_list)
global_E1 *= EVSGlobals.MEV_CONVERSION
elif fit_type == 'Shared':
glob_peak_table = peak_table[0]
global_E1 = EVSMiscFunctions.read_table_column(self._current_workspace, 'global_E1', spec_list)
global_E1 *= EVSGlobals.MEV_CONVERSION
else:
indv_peak_table = peak_table[0]
E1 = EVSMiscFunctions.read_table_column(self._current_workspace, 'E1', spec_list)
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E1 *= EVSGlobals.MEV_CONVERSION

E1 = EVSMiscFunctions.read_table_column(self._current_workspace, 'E1', spec_list)
t0 = EVSMiscFunctions.read_table_column(self._current_workspace, 't0', spec_list)
t0_error = EVSMiscFunctions.read_table_column(self._current_workspace, 't0_Err', spec_list)
L0 = EVSMiscFunctions.read_table_column(self._current_workspace, 'L0', spec_list)
theta = EVSMiscFunctions.read_table_column(self._current_workspace, 'theta', spec_list)
r_theta = EVSMiscFunctions.calculate_r_theta(self._sample_mass, theta)
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peak_centres = self._invalid_detectors.filter_peak_centres_for_invalid_detectors(spec_list, peak_table)
if fit_type != 'Shared':
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peak_centres = self._invalid_detectors.filter_peak_centres_for_invalid_detectors(spec_list, indv_peak_table)

delta_t = (peak_centres - t0) / 1e+6
delta_t_error = t0_error / 1e+6
v1 = np.sqrt( 2 * E1 /scipy.constants.m_n)
L1 = v1 * delta_t - L0 * r_theta
L1_error = v1 * delta_t_error

delta_t = (peak_centres - t0) / 1e+6
delta_t_error = t0_error / 1e+6
self._set_table_column(self._current_workspace, 'L1', L1, spec_list)
self._set_table_column(self._current_workspace, 'L1_Err', L1_error, spec_list)

E1 *= EVSGlobals.MEV_CONVERSION
v1 = np.sqrt( 2 * E1 /scipy.constants.m_n)
L1 = v1 * delta_t - L0 * r_theta
L1_error = v1 * delta_t_error
if fit_type != 'Individual':
peak_centre = EVSMiscFunctions.read_fitting_result_table_column(glob_peak_table, 'f1.LorentzPos', [0])
peak_centre_list = np.empty(spec_list[1] + 1 -spec_list[0])
peak_centre_list.fill(float(peak_centre))

self._set_table_column(self._current_workspace, 'L1', L1, spec_list)
self._set_table_column(self._current_workspace, 'L1_Err', L1_error, spec_list)
delta_t = (peak_centre_list - t0) / 1e+6
delta_t_error = t0_error / 1e+6
global_v1 = np.sqrt( 2 * global_E1 /scipy.constants.m_n)
global_L1 = global_v1 * delta_t - L0 * r_theta
global_L1_error = global_v1 * delta_t_error

self._set_table_column(self._current_workspace, 'global_L1', global_L1, spec_list)
self._set_table_column(self._current_workspace, 'global_L1_Err', global_L1_error, spec_list)
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def _calculate_scattering_angle(self, table_name, spec_list):
"""
Expand Down Expand Up @@ -315,7 +343,7 @@ def _calculate_scattering_angle(self, table_name, spec_list):
self._set_table_column(self._current_workspace, 'theta', masked_theta, spec_list)
self._set_table_column(self._current_workspace, 'theta_Err', theta_error, spec_list)

def _calculate_final_energy(self, peak_table, spec_list, calculate_global):
def _calculate_final_energy(self, peak_table, spec_list, fit_type):
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"""
Calculate the final energy using the fitted peak centres of a run.

Expand All @@ -324,57 +352,77 @@ def _calculate_final_energy(self, peak_table, spec_list, calculate_global):
"""

spec_range = EVSGlobals.DETECTOR_RANGE[1] + 1 - EVSGlobals.DETECTOR_RANGE[0]
mean_E1 = np.empty(spec_range)
E1_error = np.empty(spec_range)
global_E1 = np.empty(spec_range)
global_E1_error = np.empty(spec_range)

if not self._E1_value_and_error:

if fit_type == 'Both':
indv_peak_table = peak_table[0]
glob_peak_table = peak_table[1]
elif fit_type == 'Shared':
glob_peak_table = peak_table[0]
else:
indv_peak_table = peak_table[0]

t0 = EVSMiscFunctions.read_table_column(self._current_workspace, 't0', spec_list)
L0 = EVSMiscFunctions.read_table_column(self._current_workspace, 'L0', spec_list)

L1 = EVSMiscFunctions.read_table_column(self._param_table, 'L1', spec_list)
theta = EVSMiscFunctions.read_table_column(self._current_workspace, 'theta', spec_list)
r_theta = EVSMiscFunctions.calculate_r_theta(self._sample_mass, theta)

peak_centres = self._invalid_detectors.filter_peak_centres_for_invalid_detectors(spec_list, peak_table[0])
if fit_type != 'Shared':
mean_E1 = np.empty(spec_range)
E1_error = np.empty(spec_range)

delta_t = (peak_centres - t0) / 1e+6
v1 = (L0 * r_theta + L1) / delta_t
peak_centres = self._invalid_detectors.filter_peak_centres_for_invalid_detectors(spec_list, indv_peak_table)

E1 = 0.5 * scipy.constants.m_n * v1 ** 2
E1 /= EVSGlobals.MEV_CONVERSION
delta_t = (peak_centres - t0) / 1e+6
v1 = (L0 * r_theta + L1) / delta_t

mean_E1_val = np.nanmean(E1)
E1_error_val = np.nanstd(E1)
E1 = 0.5*scipy.constants.m_n*v1**2
E1 /= EVSGlobals.MEV_CONVERSION

else:
mean_E1_val = self._E1_value_and_error[0]
E1_error_val = self._E1_value_and_error[1]
mean_E1_val = np.nanmean(E1)
E1_error_val = np.nanstd(E1)

mean_E1.fill(mean_E1_val)
E1_error.fill(E1_error_val)

mean_E1.fill(mean_E1_val)
E1_error.fill(E1_error_val)
self._set_table_column(self._current_workspace, 'E1', mean_E1)
self._set_table_column(self._current_workspace, 'E1_Err', E1_error)

self._set_table_column(self._current_workspace, 'E1', mean_E1)
self._set_table_column(self._current_workspace, 'E1_Err', E1_error)
if fit_type != 'Individual':
global_E1 = np.empty(spec_range)
global_E1_error = np.empty(spec_range)

if calculate_global: # This fn will need updating for the only global option
peak_centre = EVSMiscFunctions.read_fitting_result_table_column(peak_table[1], 'f1.LorentzPos', [0])
peak_centre = [peak_centre] * len(peak_centres)
peak_centre = EVSMiscFunctions.read_fitting_result_table_column(glob_peak_table, 'f1.LorentzPos', [0])
peak_centre = [peak_centre] * spec_range

delta_t = (peak_centre - t0) / 1e+6
v1 = (L0 * r_theta + L1) / delta_t
E1 = 0.5 * scipy.constants.m_n * v1 ** 2
E1 /= EVSGlobals.MEV_CONVERSION
delta_t = (peak_centre - t0) / 1e+6
v1 = (L0 * r_theta + L1) / delta_t
E1 = 0.5*scipy.constants.m_n*v1**2
E1 /= EVSGlobals.MEV_CONVERSION

global_E1_val = np.nanmean(E1)
global_E1_error_val = np.nanstd(E1)
global_E1_val = np.nanmean(E1)
global_E1_error_val = np.nanstd(E1)

global_E1.fill(global_E1_val)
global_E1_error.fill(global_E1_error_val)

self._set_table_column(self._current_workspace, 'global_E1', global_E1)
self._set_table_column(self._current_workspace, 'global_E1_Err', global_E1_error)
else:
mean_E1 = np.empty(spec_range)
E1_error = np.empty(spec_range)

mean_E1_val = self._E1_value_and_error[0]
E1_error_val = self._E1_value_and_error[1]

global_E1.fill(global_E1_val)
global_E1_error.fill(global_E1_error_val)
mean_E1.fill(mean_E1_val)
E1_error.fill(E1_error_val)

self._set_table_column(self._current_workspace, 'global_E1', global_E1)
self._set_table_column(self._current_workspace, 'global_E1_Err', global_E1_error)
self._set_table_column(self._current_workspace, 'E1', mean_E1)
self._set_table_column(self._current_workspace, 'E1_Err', E1_error)

def _setup(self):
"""
Expand Down
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