From 58f227eae00565fd6114ba48c4cd632042abdb2a Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Thu, 20 Apr 2023 12:49:36 +0100
Subject: [PATCH 01/15] fix create output and clean workspaces

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py   | 26 ++++++++++++-------
 .../tests/system/test_system.py               | 17 ++++++++++++
 2 files changed, 33 insertions(+), 10 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index dba94119..f70057e6 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -420,7 +420,7 @@ def _fit_bragg_peaks(self):
         self._output_params_to_table(spec_number, num_estimated_peaks, selected_params, output_parameters_tbl_name)
 
         output_workspaces.append(
-            self._get_output_and_clean_workspaces(fit_results_unconstrained is not None, unconstrained_fit_selected, find_peaks_output_name,
+            self._get_output_and_clean_workspaces(fit_results_unconstrained is not None, fit_results_unconstrained is not False, unconstrained_fit_selected, find_peaks_output_name,
                                                   fit_peaks_output_name))
 
     if self._create_output:
@@ -466,6 +466,8 @@ def _fit_peaks_to_spectra(self, workspace_index, spec_number, peak_estimates_lis
       if peaks_found:
           return self._filter_and_fit_found_peaks(workspace_index, peak_estimates_list, find_peaks_output_name,
                                                   fit_peaks_output_name, x_range, unconstrained)
+      else:
+          return False
 
   def _filter_and_fit_found_peaks(self, workspace_index, peak_estimates_list, find_peaks_output_name, fit_peaks_output_name,
                                   x_range, unconstrained):
@@ -519,7 +521,7 @@ def _output_params_to_table(self, spec_num, num_estimated_peaks, params, output_
 
       mtd[output_table_name].addRow([spec_num] + row)
 
-  def _get_output_and_clean_workspaces(self, unconstrained_fit_performed, unconstrained_fit_selected, find_peaks_output_name,
+  def _get_output_and_clean_workspaces(self, unconstrained_fit_performed, unconstrained_peaks_found, unconstrained_fit_selected, find_peaks_output_name,
                                        fit_peaks_output_name):
       find_peaks_output_name_u = self._get_unconstrained_ws_name(find_peaks_output_name)
       fit_peaks_output_name_u = self._get_unconstrained_ws_name(fit_peaks_output_name)
@@ -530,14 +532,17 @@ def _get_output_and_clean_workspaces(self, unconstrained_fit_performed, unconstr
 
       output_workspace = fit_peaks_output_name + '_Workspace'
       if unconstrained_fit_performed:
-          DeleteWorkspace(fit_peaks_output_name_u + '_NormalisedCovarianceMatrix')
-          DeleteWorkspace(fit_peaks_output_name_u + '_Parameters')
           DeleteWorkspace(find_peaks_output_name_u)
-          if unconstrained_fit_selected:
-              output_workspace = fit_peaks_output_name_u + '_Workspace'
-              DeleteWorkspace(fit_peaks_output_name + '_Workspace')
-          else:
-              DeleteWorkspace(fit_peaks_output_name_u + '_Workspace')
+
+          if unconstrained_peaks_found:
+              DeleteWorkspace(fit_peaks_output_name_u + '_NormalisedCovarianceMatrix')
+              DeleteWorkspace(fit_peaks_output_name_u + '_Parameters')
+
+              if unconstrained_fit_selected:
+                  output_workspace = fit_peaks_output_name_u + '_Workspace'
+                  DeleteWorkspace(fit_peaks_output_name + '_Workspace')
+              else:
+                  DeleteWorkspace(fit_peaks_output_name_u + '_Workspace')
       return output_workspace
 
 
@@ -1137,8 +1142,9 @@ def _generate_fit_workspaces(self):
     """
       Output the fit workspace for each spectrum fitted.
     """
-    fit_workspaces = map(list, zip(*self._peak_fit_workspaces_by_spec))
+    fit_workspaces = map(list, zip(*self._peak_fit_workspaces))
     group_ws_names = []
+
     for i, peak_fits in enumerate(fit_workspaces):
       ws_name = self._output_workspace_name + '_%d_Workspace' % i
       ExtractSingleSpectrum(InputWorkspace=self._sample, WorkspaceIndex=i, OutputWorkspace=ws_name)
diff --git a/unpackaged/vesuvio_calibration/tests/system/test_system.py b/unpackaged/vesuvio_calibration/tests/system/test_system.py
index 0f76ab49..6636f2e8 100644
--- a/unpackaged/vesuvio_calibration/tests/system/test_system.py
+++ b/unpackaged/vesuvio_calibration/tests/system/test_system.py
@@ -319,6 +319,23 @@ def test_copper_with_multiple_iterations(self, load_file_mock):
                                                                              165, 167, 168, 169, 170, 182, 191, 192]})
         self.assert_parameters_match_expected(params_table, detector_specific_r_tols)
 
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.EVSCalibrationFit._load_file')
+    def test_copper_create_output(self, load_file_mock):
+        self._setup_copper_test()
+        self._output_workspace = "copper_analysis_test"
+
+        load_file_mock.side_effect = self._load_file_side_effect
+
+        self.create_evs_calibration_alg()
+        self._alg.setProperty("CreateOutput", True)
+        params_table = self.execute_evs_calibration_analysis()
+
+        #  Specify detectors tolerances set by user, then update with those to mask as invalid.
+        detector_specific_r_tols = {"L1": {116: 0.65, 170: 0.75}}
+        detector_specific_r_tols["L1"].update({k: INVALID_DETECTOR for k in [138, 141, 146, 147, 156, 158, 160, 163, 164,
+                                                                             165, 167, 168, 169, 170, 182, 191, 192]})
+        self.assert_parameters_match_expected(params_table, detector_specific_r_tols)
+
     def tearDown(self):
         mtd.clear()
 

From f61a6e58d987b9f50c41142f548b4469ec7b595f Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Thu, 20 Apr 2023 13:37:42 +0100
Subject: [PATCH 02/15] ensure theta fit table has correct name

---
 .../vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index f70057e6..a2d4555f 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -431,7 +431,7 @@ def _get_unconstrained_ws_name(ws_name):
       return ws_name + '_unconstrained'
 
   def _create_output_parameters_table_ws(self, output_table_name, num_estimated_peaks):
-    table = CreateEmptyTableWorkspace()
+    table = CreateEmptyTableWorkspace(OutputWorkspace=output_table_name)
 
     col_headers = self._generate_column_headers(num_estimated_peaks)
 

From 3445323b73dfc9a88eb0dab684d09e592e28025a Mon Sep 17 00:00:00 2001
From: Jess Farmer <jessica.farmer@stfc.ac.uk>
Date: Thu, 23 Mar 2023 16:27:22 +0000
Subject: [PATCH 03/15] add function for shared parameter fitting

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py   | 155 +++++++++++++++++-
 1 file changed, 148 insertions(+), 7 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index a2d4555f..dad354fc 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -25,6 +25,7 @@
 import scipy.constants
 import scipy.stats
 import numpy as np
+import time
 
 # Configuration for Uranium runs / Indium runs
 #----------------------------------------------------------------------------------------
@@ -105,6 +106,37 @@ def calculate_r_theta(sample_mass, thetas):
   r_theta = (np.cos(rad_theta) + np.sqrt( (sample_mass / NEUTRON_MASS_AMU)**2 - np.sin(rad_theta)**2 )) / ((sample_mass / NEUTRON_MASS_AMU) +1)
 
   return r_theta
+  
+#----------------------------------------------------------------------------------------
+  
+def identify_invalid_spectra(peak_table, peak_centres, peak_centres_errors, spec_list):
+  """
+    Inspect fitting results, and identify the fits associated with invalid spectra. These are spectra associated with detectors
+    which have lost foil coverage following a recent reduction in distance from source to detectors.
+
+    @param peak_table - name of table containing fitted parameters each spectra.
+    @param spec_list - spectrum range to inspect.
+    @return a list of invalid spectra.
+  """
+  peak_Gaussian_FWHM = read_fitting_result_table_column(peak_table, 'f1.GaussianFWHM', spec_list)
+  peak_Gaussian_FWHM_errors = read_fitting_result_table_column(peak_table, 'f1.GaussianFWHM_Err', spec_list)
+  peak_Lorentz_FWHM = read_fitting_result_table_column(peak_table, 'f1.LorentzFWHM', spec_list)
+  peak_Lorentz_FWHM_errors = read_fitting_result_table_column(peak_table, 'f1.LorentzFWHM_Err', spec_list)
+  peak_Lorentz_Amp = read_fitting_result_table_column(peak_table, 'f1.LorentzAmp', spec_list)
+  peak_Lorentz_Amp_errors = read_fitting_result_table_column(peak_table, 'f1.LorentzAmp_Err', spec_list)
+
+  invalid_spectra = np.argwhere((np.isinf(peak_Lorentz_Amp_errors)) | (np.isnan(peak_Lorentz_Amp_errors))  | \
+  (np.isinf(peak_centres_errors)) | (np.isnan(peak_centres_errors))  | \
+  (np.isnan(peak_Gaussian_FWHM_errors)) | (np.isinf(peak_Gaussian_FWHM_errors)) | \
+  (np.isnan(peak_Lorentz_FWHM_errors)) | (np.isinf(peak_Lorentz_FWHM_errors)) | \
+  (np.isnan(peak_Lorentz_Amp_errors)) | (np.isinf(peak_Lorentz_Amp_errors)) | \
+  (np.absolute(peak_Gaussian_FWHM_errors) > np.absolute(peak_Gaussian_FWHM)) | \
+  (np.absolute(peak_Lorentz_FWHM_errors) > np.absolute(peak_Lorentz_FWHM)) | \
+  (np.absolute(peak_Lorentz_Amp_errors) > np.absolute(peak_Lorentz_Amp)) | \
+  (np.absolute(peak_centres_errors) > np.absolute(peak_centres)))
+
+  return invalid_spectra
+
 
 #----------------------------------------------------------------------------------------
 # The IP text file load function skips the first 3 rows of the text file.
@@ -261,6 +293,8 @@ def PyInit(self):
 
     self.declareProperty('OutputWorkspace', '', StringMandatoryValidator(),
       doc="Name to call the output workspace.")
+      
+    self.declareProperty('CalculateSharedParameter', False, doc='Calculate shared parameter across all detectors')
 
 #----------------------------------------------------------------------------------------
 
@@ -299,6 +333,7 @@ def _setup_class_variables_from_properties(self):
     self._energy_estimates = self.getProperty("Energy").value
     self._sample_mass = self.getProperty("Mass").value
     self._create_output = self.getProperty("CreateOutput").value
+    self._calculate_shared_parameter = self.getProperty("CalculateSharedParameter").value
 
   def _setup_spectra_list(self):
     self._spec_list = self.getProperty("SpectrumRange").value.tolist()
@@ -754,6 +789,13 @@ def _fit_peaks(self):
 
     GroupWorkspaces(self._output_parameter_tables, OutputWorkspace=self._output_workspace_name + '_Peak_Parameters')
 
+    if self._calculate_shared_parameter == True:
+        peak_centres = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos', self._spec_list)
+        peak_centres_errors = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos_Err', self._spec_list)
+
+        invalid_spectra = identify_invalid_spectra(output_parameter_table_name, peak_centres, peak_centres_errors, self._spec_list)
+        self._fit_shared_parameter(estimated_peak_positions_all_peaks, invalid_spectra)
+
   def _fit_peak(self, peak_index, spec_index, peak_position, output_parameter_table_name, output_parameter_table_headers):
     spec_number = self._spec_list[0] + spec_index
     self._prog_reporter.report("Fitting peak %d to spectrum %d" % (peak_index, spec_number))
@@ -814,6 +856,106 @@ def _del_fit_workspaces(self, ncm, fit_params, fws):
     if not self._create_output:
       DeleteWorkspace(fws)
 
+#----------------------------------------------------------------------------------------
+
+  def _fit_shared_parameter(self, peak_positions, invalid_spectra):
+    """
+      Fit peaks to all detectors, with one set of fit parameters for all detectors.
+    """
+    
+    peak_centre = np.float(np.nanmean(peak_positions, axis=1))
+    find_peak_params = self._get_find_peak_parameters(self._spec_list[0], [peak_centre])
+    
+    peaks_table = '__' + self._sample + '_peaks_table'
+    param_names = self._create_parameter_table(peaks_table)
+    peak_table = '__' + self._sample + '_peak_table'
+    FindPeaks(InputWorkspace=self._sample, PeaksList=peak_table, **find_peak_params)
+
+    #extract data from table
+    if mtd[peak_table].rowCount() > 0:
+        peak_params = mtd[peak_table].row(0)
+        DeleteWorkspace(peak_table)
+    else:
+        logger.error('FindPeaks could not find any peaks matching the parameters:\n' + str(find_peak_params))
+        sys.exit()
+    
+    fit_func = self._build_function_string(peak_params)
+    
+    start_str = 'composite=MultiDomainFunction, NumDeriv=1;'
+ 
+    sample_ws = mtd[self._sample]
+    
+    MaskDetectors(Workspace=sample_ws, WorkspaceIndexList=invalid_spectra)
+
+    validSpecs = ExtractUnmaskedSpectra(InputWorkspace=sample_ws, OutputWorkspace='valid_spectra')
+    
+    n_valid_specs = validSpecs.getNumberHistograms()
+    
+    fit_func = ('(composite=CompositeFunction, NumDeriv=false, $domains=i;' + fit_func[:-1] + ');') * n_valid_specs
+    composite_func = start_str + fit_func[:-1]
+      
+    ties = ','.join(f'f{i}.f1.{p}=f0.f1.{p}' for p in self._func_param_names.values() for i in range(1,n_valid_specs))
+    func_string = composite_func + f';ties=({ties})' 
+    
+    fit_output_name = '__' + self._output_workspace_name + '_Peak_0'
+
+    #find x window
+    xmin, xmax = None, None
+    position = '' + self._func_param_names['Position']
+    if peak_params[position] > 0:
+      xmin = peak_params[position]-self._fit_window_range
+      xmax = peak_params[position]+self._fit_window_range
+    else:
+      logger.warning('Could not specify fit window. Using full spectrum x range.')
+
+    # create new workspace for each spectra
+    x = validSpecs.readX(0)
+    y = validSpecs.readY(0)
+    e = validSpecs.readE(0)
+    out_ws = self._sample + '_Spec_0'
+    CreateWorkspace(DataX=x, DataY=y, DataE=e, NSpec=1, OutputWorkspace=out_ws)
+    
+    other_inputs = [CreateWorkspace(DataX=validSpecs.readX(j), DataY=validSpecs.readY(j), DataE=validSpecs.readE(j),
+                                    OutputWorkspace=f'{self._sample}_Spec_{j}')
+                   for j in range(1,n_valid_specs)] 
+                                                     
+    added_args = {f'InputWorkspace_{i + 1}': v for i,v in enumerate(other_inputs)}
+    
+    print('starting global fit')
+    start = time.time()
+         
+    status, chi2, ncm, params, fws, func, cost_func = Fit(Function=func_string, InputWorkspace=out_ws, IgnoreInvalidData=True,
+                                                              StartX=xmin, EndX=xmax,
+                                                              CalcErrors=True, Output=fit_output_name,
+                                                              Minimizer='SteepestDescent,RelError=1e-8', **added_args)
+                                                              
+    end = time.time()
+    print(end-start)
+    
+    [DeleteWorkspace(f"{self._sample}_Spec_{i}") for i in range(0,n_valid_specs)]
+    
+    fit_values = dict(zip(params.column(0), params.column(1)))
+    fit_errors = dict(zip(params.column(0), params.column(2)))
+
+    row_values = [fit_values['f0.' + name] for name in param_names]
+    row_errors = [fit_errors['f0.' + name] for name in param_names]
+    row = [element for tupl in zip(row_values, row_errors) for element in tupl]
+    
+    mtd[peaks_table].addRow([0] + row)
+
+    self._parameter_tables = peaks_table
+    self._peak_fit_workspaces = fws.name()
+
+    DeleteWorkspace(ncm)
+    DeleteWorkspace(params)
+    if not self._create_output:
+      DeleteWorkspace(fws)
+
+    #self._fit_workspaces = self._peak_fit_workspaces
+    
+    GroupWorkspaces(self._parameter_tables, OutputWorkspace=self._output_workspace_name + '_Shared_Peak_Parameters')
+ 
+>>>>>>> 1b75c5c (add function for shared parameter fitting)
 #----------------------------------------------------------------------------------------
     
   def _get_find_peak_parameters(self, spec_number, peak_centre, unconstrained=False):
@@ -1300,12 +1442,11 @@ def PyExec(self):
       self._theta_peak_fits = theta_fit + '_Peak_Parameters'
       self._calculate_scattering_angle(self._theta_peak_fits, DETECTOR_RANGE)
       
-      #calibrate  E1 for backscattering detectors and use the backscattering averaged value for all detectors    
+      #calibrate  E1 for backscattering detectors and use the backscattering averaged value for all detectors
       E1_fit_back = self._current_workspace + '_E1_back'
       self._run_calibration_fit(Samples=self._samples, Function='Voigt', Mode='SingleDifference', SpectrumRange=BACKSCATTERING_RANGE,
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_back, CreateOutput=self._create_output,
-                                PeakType='Recoil')
-      
+                                PeakType='Recoil', CalculateSharedParameter=True)
       
       E1_peak_fits_back = mtd[self._current_workspace + '_E1_back_Peak_Parameters'].getNames()[0]
       self._calculate_final_energy(E1_peak_fits_back, BACKSCATTERING_RANGE)
@@ -1317,7 +1458,7 @@ def PyExec(self):
       E1_fit_front = self._current_workspace + '_E1_front'
       self._run_calibration_fit(Samples=self._samples, Function='Voigt', Mode='SingleDifference', SpectrumRange=FRONTSCATTERING_RANGE,
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_front, CreateOutput=self._create_output,
-                                PeakType='Recoil')
+                                PeakType='Recoil', CalculateSharedParameter=True)
       
       E1_peak_fits_front = mtd[self._current_workspace + '_E1_front_Peak_Parameters'].getNames()[0]
       self._calculate_final_flight_path(E1_peak_fits_front, FRONTSCATTERING_RANGE)
@@ -1434,7 +1575,7 @@ def _calculate_final_flight_path(self, peak_table, spec_list):
     
     peak_centres = read_fitting_result_table_column(peak_table, 'f1.LorentzPos', spec_list)
     peak_centres_errors = read_fitting_result_table_column(peak_table, 'f1.LorentzPos_Err', spec_list)
-    invalid_spectra = self._identify_invalid_spectra(peak_table, peak_centres, peak_centres_errors, spec_list)
+    invalid_spectra = identify_invalid_spectra(peak_table, peak_centres, peak_centres_errors, spec_list)
     peak_centres[invalid_spectra] = np.nan
 
     print(f'Invalid Spectra Index Found and Marked NAN: {invalid_spectra.flatten()} from Spectra Index List:'
@@ -1529,7 +1670,7 @@ def _calculate_scattering_angle(self, table_name, spec_list):
 
 #----------------------------------------------------------------------------------------
 
- 
+
 
   def _calculate_final_energy(self, peak_table, spec_list):
     """
@@ -1554,7 +1695,7 @@ def _calculate_final_energy(self, peak_table, spec_list):
         peak_centres = read_fitting_result_table_column(peak_table, 'f1.LorentzPos', spec_list)
         peak_centres_errors = read_fitting_result_table_column(peak_table, 'f1.LorentzPos_Err', spec_list)
 
-        invalid_spectra = self._identify_invalid_spectra(peak_table, peak_centres, peak_centres_errors, spec_list)
+        invalid_spectra = identify_invalid_spectra(peak_table, peak_centres, peak_centres_errors, spec_list)
         peak_centres[invalid_spectra] = np.nan
 
         delta_t = (peak_centres - t0) / 1e+6

From 4c9e8bcfcce925e409adb16f28e6c6bcd6bae818 Mon Sep 17 00:00:00 2001
From: Jess Farmer <jessica.farmer@stfc.ac.uk>
Date: Fri, 24 Mar 2023 15:47:14 +0000
Subject: [PATCH 04/15] set initial parameters for multifit

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py   | 40 +++++++------------
 1 file changed, 15 insertions(+), 25 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index dad354fc..7d966ea2 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -790,11 +790,21 @@ def _fit_peaks(self):
     GroupWorkspaces(self._output_parameter_tables, OutputWorkspace=self._output_workspace_name + '_Peak_Parameters')
 
     if self._calculate_shared_parameter == True:
+        init_Gaussian_FWHM = read_fitting_result_table_column(output_parameter_table_name, 'f1.GaussianFWHM', self._spec_list)
+        init_Gaussian_FWHM = np.nanmean(init_Gaussian_FWHM[init_Gaussian_FWHM != 0])
+        init_Lorentz_FWHM = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzFWHM', self._spec_list)
+        init_Lorentz_FWHM = np.nanmean(init_Lorentz_FWHM[init_Lorentz_FWHM != 0])
+        init_Lorentz_Amp = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzAmp', self._spec_list)
+        init_Lorentz_Amp = np.nanmean(init_Lorentz_Amp[init_Lorentz_Amp != 0])
+        init_Lorentz_Pos = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos', self._spec_list)
+        init_Lorentz_Pos = np.nanmean(init_Lorentz_Pos[init_Lorentz_Pos != 0])
+        
+        initial_params = {'A0': 0.0, 'A1': 0.0, 'LorentzAmp': init_Lorentz_Amp, 'LorentzPos': init_Lorentz_Pos, 'LorentzFWHM': init_Lorentz_FWHM, 'GaussianFWHM': init_Gaussian_FWHM}
+
         peak_centres = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos', self._spec_list)
         peak_centres_errors = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos_Err', self._spec_list)
-
         invalid_spectra = identify_invalid_spectra(output_parameter_table_name, peak_centres, peak_centres_errors, self._spec_list)
-        self._fit_shared_parameter(estimated_peak_positions_all_peaks, invalid_spectra)
+        self._fit_shared_parameter(invalid_spectra, initial_params, output_parameter_table_headers)
 
   def _fit_peak(self, peak_index, spec_index, peak_position, output_parameter_table_name, output_parameter_table_headers):
     spec_number = self._spec_list[0] + spec_index
@@ -843,7 +853,6 @@ def _find_fit_x_window(self, peak_params):
   def _output_fit_params_to_table_ws(self, spec_num, params, output_table_name, output_table_headers):
     fit_values = dict(zip(params.column(0), params.column(1)))
     fit_errors = dict(zip(params.column(0), params.column(2)))
-
     row_values = [fit_values[name] for name in output_table_headers]
     row_errors = [fit_errors[name] for name in output_table_headers]
     row = [element for tupl in zip(row_values, row_errors) for element in tupl]
@@ -858,37 +867,18 @@ def _del_fit_workspaces(self, ncm, fit_params, fws):
 
 #----------------------------------------------------------------------------------------
 
-  def _fit_shared_parameter(self, peak_positions, invalid_spectra):
+  def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names):
     """
       Fit peaks to all detectors, with one set of fit parameters for all detectors.
     """
     
-    peak_centre = np.float(np.nanmean(peak_positions, axis=1))
-    find_peak_params = self._get_find_peak_parameters(self._spec_list[0], [peak_centre])
-    
     peaks_table = '__' + self._sample + '_peaks_table'
-    param_names = self._create_parameter_table(peaks_table)
-    peak_table = '__' + self._sample + '_peak_table'
-    FindPeaks(InputWorkspace=self._sample, PeaksList=peak_table, **find_peak_params)
-
-    #extract data from table
-    if mtd[peak_table].rowCount() > 0:
-        peak_params = mtd[peak_table].row(0)
-        DeleteWorkspace(peak_table)
-    else:
-        logger.error('FindPeaks could not find any peaks matching the parameters:\n' + str(find_peak_params))
-        sys.exit()
-    
-    fit_func = self._build_function_string(peak_params)
-    
+
+    fit_func = self._build_function_string(initial_params)
     start_str = 'composite=MultiDomainFunction, NumDeriv=1;'
- 
     sample_ws = mtd[self._sample]
-    
     MaskDetectors(Workspace=sample_ws, WorkspaceIndexList=invalid_spectra)
-
     validSpecs = ExtractUnmaskedSpectra(InputWorkspace=sample_ws, OutputWorkspace='valid_spectra')
-    
     n_valid_specs = validSpecs.getNumberHistograms()
     
     fit_func = ('(composite=CompositeFunction, NumDeriv=false, $domains=i;' + fit_func[:-1] + ');') * n_valid_specs

From a995df2de7d04db3dfe0eeba0b9c2e4cb073ba7f Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Mon, 17 Apr 2023 17:11:06 +0100
Subject: [PATCH 05/15] minimal changes to make script work

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py   | 29 ++++++++-----------
 1 file changed, 12 insertions(+), 17 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index 7d966ea2..bf739594 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -16,7 +16,8 @@
 from mantid.simpleapi import CreateEmptyTableWorkspace, DeleteWorkspace, CropWorkspace, RebinToWorkspace, Divide,\
      ReplaceSpecialValues, FindPeaks, GroupWorkspaces, mtd, Plus, LoadVesuvio, LoadRaw, ConvertToDistribution,\
      FindPeakBackground, ExtractSingleSpectrum, SumSpectra, AppendSpectra, ConvertTableToMatrixWorkspace,\
-     ConjoinWorkspaces, Transpose, PlotPeakByLogValue, CloneWorkspace, Fit, RenameWorkspace
+     ConjoinWorkspaces, Transpose, PlotPeakByLogValue, CloneWorkspace, Fit, RenameWorkspace, MaskDetectors,\
+     ExtractUnmaskedSpectra, CreateWorkspace
 
 from functools import partial
 
@@ -780,8 +781,8 @@ def _fit_peaks(self):
       output_parameter_table_name = self._output_workspace_name + '_Peak_%d_Parameters' % peak_index
       output_parameter_table_headers = self._create_parameter_table_and_output_headers(output_parameter_table_name)
       for spec_index, peak_position in enumerate(estimated_peak_positions):
-        fit_workspace_name = self._fit_peak(peak_index, spec_index, peak_position, output_parameter_table_name,
-                                            output_parameter_table_headers)
+        fit_workspace_name, x_range = self._fit_peak(peak_index, spec_index, peak_position, output_parameter_table_name,
+                                                     output_parameter_table_headers)
         self._peak_fit_workspaces_by_spec.append(fit_workspace_name)
 
       self._output_parameter_tables.append(output_parameter_table_name)
@@ -804,7 +805,7 @@ def _fit_peaks(self):
         peak_centres = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos', self._spec_list)
         peak_centres_errors = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos_Err', self._spec_list)
         invalid_spectra = identify_invalid_spectra(output_parameter_table_name, peak_centres, peak_centres_errors, self._spec_list)
-        self._fit_shared_parameter(invalid_spectra, initial_params, output_parameter_table_headers)
+        self._fit_shared_parameter(invalid_spectra, initial_params, output_parameter_table_headers, output_parameter_table_name, x_range)
 
   def _fit_peak(self, peak_index, spec_index, peak_position, output_parameter_table_name, output_parameter_table_headers):
     spec_number = self._spec_list[0] + spec_index
@@ -825,7 +826,7 @@ def _fit_peak(self, peak_index, spec_index, peak_position, output_parameter_tabl
     fit_workspace_name = fws.name()
     self._del_fit_workspaces(ncm, fit_params, fws)
 
-    return fit_workspace_name
+    return fit_workspace_name, (xmin, xmax)
 
   def _find_peaks_and_output_params(self, peak_index, spec_number, spec_index, peak_position):
     peak_table_name = '__' + self._sample + '_peaks_table_%d_%d' % (peak_index, spec_index)
@@ -867,12 +868,14 @@ def _del_fit_workspaces(self, ncm, fit_params, fws):
 
 #----------------------------------------------------------------------------------------
 
-  def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names):
+  def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names, old_peak_table, x_range):
     """
       Fit peaks to all detectors, with one set of fit parameters for all detectors.
     """
-    
+
     peaks_table = '__' + self._sample + '_peaks_table'
+    CloneWorkspace(InputWorkspace=old_peak_table, OutputWorkspace=peaks_table)
+    mtd[peaks_table].setRowCount(0)
 
     fit_func = self._build_function_string(initial_params)
     start_str = 'composite=MultiDomainFunction, NumDeriv=1;'
@@ -889,14 +892,7 @@ def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names):
     
     fit_output_name = '__' + self._output_workspace_name + '_Peak_0'
 
-    #find x window
-    xmin, xmax = None, None
-    position = '' + self._func_param_names['Position']
-    if peak_params[position] > 0:
-      xmin = peak_params[position]-self._fit_window_range
-      xmax = peak_params[position]+self._fit_window_range
-    else:
-      logger.warning('Could not specify fit window. Using full spectrum x range.')
+    xmin, xmax = x_range
 
     # create new workspace for each spectra
     x = validSpecs.readX(0)
@@ -944,8 +940,7 @@ def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names):
     #self._fit_workspaces = self._peak_fit_workspaces
     
     GroupWorkspaces(self._parameter_tables, OutputWorkspace=self._output_workspace_name + '_Shared_Peak_Parameters')
- 
->>>>>>> 1b75c5c (add function for shared parameter fitting)
+
 #----------------------------------------------------------------------------------------
     
   def _get_find_peak_parameters(self, spec_number, peak_centre, unconstrained=False):

From 755811a44b29174ca4e0845f860d6e7699b5e006 Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Thu, 20 Apr 2023 14:10:00 +0100
Subject: [PATCH 06/15] manual merge jess updates

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py   | 71 ++++++++++++-------
 1 file changed, 45 insertions(+), 26 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index bf739594..f26377f7 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -805,7 +805,7 @@ def _fit_peaks(self):
         peak_centres = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos', self._spec_list)
         peak_centres_errors = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos_Err', self._spec_list)
         invalid_spectra = identify_invalid_spectra(output_parameter_table_name, peak_centres, peak_centres_errors, self._spec_list)
-        self._fit_shared_parameter(invalid_spectra, initial_params, output_parameter_table_headers, output_parameter_table_name, x_range)
+        self._fit_shared_parameter(invalid_spectra, initial_params, output_parameter_table_headers)
 
   def _fit_peak(self, peak_index, spec_index, peak_position, output_parameter_table_name, output_parameter_table_headers):
     spec_number = self._spec_list[0] + spec_index
@@ -868,14 +868,20 @@ def _del_fit_workspaces(self, ncm, fit_params, fws):
 
 #----------------------------------------------------------------------------------------
 
-  def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names, old_peak_table, x_range):
+  def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names):
     """
       Fit peaks to all detectors, with one set of fit parameters for all detectors.
     """
 
-    peaks_table = '__' + self._sample + '_peaks_table'
-    CloneWorkspace(InputWorkspace=old_peak_table, OutputWorkspace=peaks_table)
-    mtd[peaks_table].setRowCount(0)
+    shared_peak_table = self._output_workspace_name + '_shared_peak_parameters'
+    CreateEmptyTableWorkspace(OutputWorkspace=shared_peak_table)
+
+    err_names = [name + '_Err' for name in param_names]
+    col_names = [element for tupl in zip(param_names, err_names) for element in tupl]
+
+    mtd[shared_peak_table].addColumn('int', 'Spectrum')
+    for name in col_names:
+        mtd[shared_peak_table].addColumn('double', name)
 
     fit_func = self._build_function_string(initial_params)
     start_str = 'composite=MultiDomainFunction, NumDeriv=1;'
@@ -892,7 +898,7 @@ def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names, ol
     
     fit_output_name = '__' + self._output_workspace_name + '_Peak_0'
 
-    xmin, xmax = x_range
+    xmin, xmax = None, None
 
     # create new workspace for each spectra
     x = validSpecs.readX(0)
@@ -908,16 +914,11 @@ def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names, ol
     added_args = {f'InputWorkspace_{i + 1}': v for i,v in enumerate(other_inputs)}
     
     print('starting global fit')
-    start = time.time()
          
     status, chi2, ncm, params, fws, func, cost_func = Fit(Function=func_string, InputWorkspace=out_ws, IgnoreInvalidData=True,
                                                               StartX=xmin, EndX=xmax,
                                                               CalcErrors=True, Output=fit_output_name,
                                                               Minimizer='SteepestDescent,RelError=1e-8', **added_args)
-                                                              
-    end = time.time()
-    print(end-start)
-    
     [DeleteWorkspace(f"{self._sample}_Spec_{i}") for i in range(0,n_valid_specs)]
     
     fit_values = dict(zip(params.column(0), params.column(1)))
@@ -926,20 +927,17 @@ def _fit_shared_parameter(self, invalid_spectra, initial_params, param_names, ol
     row_values = [fit_values['f0.' + name] for name in param_names]
     row_errors = [fit_errors['f0.' + name] for name in param_names]
     row = [element for tupl in zip(row_values, row_errors) for element in tupl]
-    
-    mtd[peaks_table].addRow([0] + row)
 
-    self._parameter_tables = peaks_table
-    self._peak_fit_workspaces = fws.name()
+    mtd[shared_peak_table].addRow([0] + row)
 
     DeleteWorkspace(ncm)
     DeleteWorkspace(params)
     if not self._create_output:
       DeleteWorkspace(fws)
 
-    #self._fit_workspaces = self._peak_fit_workspaces
-    
-    GroupWorkspaces(self._parameter_tables, OutputWorkspace=self._output_workspace_name + '_Shared_Peak_Parameters')
+    DeleteWorkspace(validSpecs)
+
+    mtd[self._output_workspace_name + '_Peak_Parameters'].add(shared_peak_table)
 
 #----------------------------------------------------------------------------------------
     
@@ -1433,8 +1431,8 @@ def PyExec(self):
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_back, CreateOutput=self._create_output,
                                 PeakType='Recoil', CalculateSharedParameter=True)
       
-      E1_peak_fits_back = mtd[self._current_workspace + '_E1_back_Peak_Parameters'].getNames()[0]
-      self._calculate_final_energy(E1_peak_fits_back, BACKSCATTERING_RANGE)
+      E1_peak_fits_back = mtd[self._current_workspace + '_E1_back_Peak_Parameters'].getNames()
+      self._calculate_final_energy(E1_peak_fits_back[0], BACKSCATTERING_RANGE)
       
       # calibrate L1 for backscattering detectors based on the averaged E1 value  and calibrated theta values 
       self._calculate_final_flight_path(E1_peak_fits_back, BACKSCATTERING_RANGE)
@@ -1445,8 +1443,8 @@ def PyExec(self):
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_front, CreateOutput=self._create_output,
                                 PeakType='Recoil', CalculateSharedParameter=True)
       
-      E1_peak_fits_front = mtd[self._current_workspace + '_E1_front_Peak_Parameters'].getNames()[0]
-      self._calculate_final_flight_path(E1_peak_fits_front, FRONTSCATTERING_RANGE)
+      E1_peak_fits_front = mtd[self._current_workspace + '_E1_front_Peak_Parameters'].getNames()
+      self._calculate_final_flight_path(E1_peak_fits_front[0], FRONTSCATTERING_RANGE)
   
 
       #make the fitted parameters for this iteration the input to the next iteration.
@@ -1668,6 +1666,8 @@ def _calculate_final_energy(self, peak_table, spec_list):
     spec_range = DETECTOR_RANGE[1] + 1 - 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:
         t0 = read_table_column(self._current_workspace, 't0', spec_list)
@@ -1677,10 +1677,11 @@ def _calculate_final_energy(self, peak_table, spec_list):
         theta = read_table_column(self._current_workspace, 'theta', spec_list)
         r_theta = calculate_r_theta(self._sample_mass, theta)
 
-        peak_centres = read_fitting_result_table_column(peak_table, 'f1.LorentzPos', spec_list)
-        peak_centres_errors = read_fitting_result_table_column(peak_table, 'f1.LorentzPos_Err', spec_list)
+        peak_centres = read_fitting_result_table_column(peak_table[0], 'f1.LorentzPos', spec_list)
+        peak_centres_errors = read_fitting_result_table_column(peak_table[0], 'f1.LorentzPos_Err', spec_list)
 
-        invalid_spectra = identify_invalid_spectra(peak_table, peak_centres, peak_centres_errors, spec_list)
+
+        invalid_spectra = identify_invalid_spectra(peak_table[0], peak_centres, peak_centres_errors, spec_list)
         peak_centres[invalid_spectra] = np.nan
 
         delta_t = (peak_centres - t0) / 1e+6
@@ -1691,15 +1692,33 @@ def _calculate_final_energy(self, peak_table, spec_list):
 
         mean_E1_val = np.nanmean(E1)
         E1_error_val = np.nanstd(E1)
+
     else:
         mean_E1_val = self._E1_value_and_error[0]
         E1_error_val = self._E1_value_and_error[1]
-    
+
+    # calculate global energy
+    peak_centre = read_fitting_result_table_column(peak_table[1], 'f1.LorentzPos', [0])
+    peak_centre = [peak_centre] * len(peak_centres)
+
+    delta_t = (peak_centre - t0) / 1e+6
+    v1 = (L0 * r_theta + L1) / delta_t
+    E1 = 0.5*scipy.constants.m_n*v1**2
+    E1 /= MEV_CONVERSION
+
+    global_E1_val = np.nanmean(E1)
+    global_E1_error_val = np.nanstd(E1)
+
     mean_E1.fill(mean_E1_val)
     E1_error.fill(E1_error_val)
 
+    global_E1.fill(global_E1_val)
+    global_E1_error.fill(global_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, 'global_E1', global_E1)
+    self._set_table_column(self._current_workspace, 'global_E1_Err', global_E1_error)
 
 #----------------------------------------------------------------------------------------
 

From 00f6531a23380da0963e1f9617dd6dc7ad5abb3a Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Thu, 20 Apr 2023 14:55:05 +0100
Subject: [PATCH 07/15] correct merge error

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py                  | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index f26377f7..c019230e 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -1432,10 +1432,10 @@ def PyExec(self):
                                 PeakType='Recoil', CalculateSharedParameter=True)
       
       E1_peak_fits_back = mtd[self._current_workspace + '_E1_back_Peak_Parameters'].getNames()
-      self._calculate_final_energy(E1_peak_fits_back[0], BACKSCATTERING_RANGE)
+      self._calculate_final_energy(E1_peak_fits_back, BACKSCATTERING_RANGE)
       
       # calibrate L1 for backscattering detectors based on the averaged E1 value  and calibrated theta values 
-      self._calculate_final_flight_path(E1_peak_fits_back, BACKSCATTERING_RANGE)
+      self._calculate_final_flight_path(E1_peak_fits_back[0], BACKSCATTERING_RANGE)
       
       # calibrate L1 for frontscattering detectors based on the averaged E1 value  and calibrated theta values 
       E1_fit_front = self._current_workspace + '_E1_front'
@@ -1680,7 +1680,6 @@ def _calculate_final_energy(self, peak_table, spec_list):
         peak_centres = read_fitting_result_table_column(peak_table[0], 'f1.LorentzPos', spec_list)
         peak_centres_errors = read_fitting_result_table_column(peak_table[0], 'f1.LorentzPos_Err', spec_list)
 
-
         invalid_spectra = identify_invalid_spectra(peak_table[0], peak_centres, peak_centres_errors, spec_list)
         peak_centres[invalid_spectra] = np.nan
 

From 617b7eddde67fc4d920631582a95c92698ca5a88 Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Tue, 18 Apr 2023 11:00:57 +0100
Subject: [PATCH 08/15] rename shared param

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py            | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index c019230e..2984688c 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -295,7 +295,7 @@ def PyInit(self):
     self.declareProperty('OutputWorkspace', '', StringMandatoryValidator(),
       doc="Name to call the output workspace.")
       
-    self.declareProperty('CalculateSharedParameter', False, doc='Calculate shared parameter across all detectors')
+    self.declareProperty('GlobalFitSharedParameter', False, doc='Perform a global fit to calculate shared parameter across all detectors')
 
 #----------------------------------------------------------------------------------------
 
@@ -334,7 +334,7 @@ def _setup_class_variables_from_properties(self):
     self._energy_estimates = self.getProperty("Energy").value
     self._sample_mass = self.getProperty("Mass").value
     self._create_output = self.getProperty("CreateOutput").value
-    self._calculate_shared_parameter = self.getProperty("CalculateSharedParameter").value
+    self._global_fit_shared_parameter = self.getProperty("GlobalFitSharedParameter").value
 
   def _setup_spectra_list(self):
     self._spec_list = self.getProperty("SpectrumRange").value.tolist()
@@ -790,7 +790,7 @@ def _fit_peaks(self):
 
     GroupWorkspaces(self._output_parameter_tables, OutputWorkspace=self._output_workspace_name + '_Peak_Parameters')
 
-    if self._calculate_shared_parameter == True:
+    if self._global_fit_shared_parameter == True:
         init_Gaussian_FWHM = read_fitting_result_table_column(output_parameter_table_name, 'f1.GaussianFWHM', self._spec_list)
         init_Gaussian_FWHM = np.nanmean(init_Gaussian_FWHM[init_Gaussian_FWHM != 0])
         init_Lorentz_FWHM = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzFWHM', self._spec_list)
@@ -1429,7 +1429,7 @@ def PyExec(self):
       E1_fit_back = self._current_workspace + '_E1_back'
       self._run_calibration_fit(Samples=self._samples, Function='Voigt', Mode='SingleDifference', SpectrumRange=BACKSCATTERING_RANGE,
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_back, CreateOutput=self._create_output,
-                                PeakType='Recoil', CalculateSharedParameter=True)
+                                PeakType='Recoil', GlobalFitSharedParameter=False)
       
       E1_peak_fits_back = mtd[self._current_workspace + '_E1_back_Peak_Parameters'].getNames()
       self._calculate_final_energy(E1_peak_fits_back, BACKSCATTERING_RANGE)
@@ -1441,7 +1441,7 @@ def PyExec(self):
       E1_fit_front = self._current_workspace + '_E1_front'
       self._run_calibration_fit(Samples=self._samples, Function='Voigt', Mode='SingleDifference', SpectrumRange=FRONTSCATTERING_RANGE,
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_front, CreateOutput=self._create_output,
-                                PeakType='Recoil', CalculateSharedParameter=True)
+                                PeakType='Recoil', GlobalFitSharedParameter=False)
       
       E1_peak_fits_front = mtd[self._current_workspace + '_E1_front_Peak_Parameters'].getNames()
       self._calculate_final_flight_path(E1_peak_fits_front[0], FRONTSCATTERING_RANGE)

From e1ba4420eabe6f42a3bf809cbf4dca0025138eca Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Tue, 18 Apr 2023 16:58:11 +0100
Subject: [PATCH 09/15] add drop down for shared parameter fit type

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py     | 17 ++++++++++++-----
 1 file changed, 12 insertions(+), 5 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index 2984688c..2f7eae83 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -286,6 +286,10 @@ def PyInit(self):
                          doc='Choose the peak type that is being fitted.'
                          'Note that supplying a set of dspacings overrides the setting here')
 
+    shared_fit_type_validator = StringListValidator(["Individual", "Shared", "Both"])
+    self.declareProperty('SharedParameterFitType', "Individual", doc='Calculate shared parameters using an individual and/or'
+                                                              'global fit.', validator=shared_fit_type_validator)
+
     self.declareProperty(ITableWorkspaceProperty("InstrumentParameterWorkspace", "", Direction.Input, PropertyMode.Optional),
       doc='Workspace contain instrument parameters.')
 
@@ -294,8 +298,6 @@ def PyInit(self):
 
     self.declareProperty('OutputWorkspace', '', StringMandatoryValidator(),
       doc="Name to call the output workspace.")
-      
-    self.declareProperty('GlobalFitSharedParameter', False, doc='Perform a global fit to calculate shared parameter across all detectors')
 
 #----------------------------------------------------------------------------------------
 
@@ -334,7 +336,7 @@ def _setup_class_variables_from_properties(self):
     self._energy_estimates = self.getProperty("Energy").value
     self._sample_mass = self.getProperty("Mass").value
     self._create_output = self.getProperty("CreateOutput").value
-    self._global_fit_shared_parameter = self.getProperty("GlobalFitSharedParameter").value
+    self._global_fit_shared_parameter = self.getProperty("SharedParameterFitType").value
 
   def _setup_spectra_list(self):
     self._spec_list = self.getProperty("SpectrumRange").value.tolist()
@@ -1357,6 +1359,10 @@ def PyInit(self):
     self.declareProperty('Iterations', 2, validator=IntBoundedValidator(lower=1),
       doc="Number of iterations to perform. Default is 2.")
 
+    shared_fit_type_validator = StringListValidator(["Individual", "Shared", "Both"])
+    self.declareProperty('SharedParameterFitType', "Individual", doc='Calculate shared parameters using an individual and/or'
+                                                              'global fit.', validator=shared_fit_type_validator)
+
     self.declareProperty('CreateOutput', False,
       doc="Whether to create output from fitting.")
 
@@ -1429,7 +1435,7 @@ def PyExec(self):
       E1_fit_back = self._current_workspace + '_E1_back'
       self._run_calibration_fit(Samples=self._samples, Function='Voigt', Mode='SingleDifference', SpectrumRange=BACKSCATTERING_RANGE,
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_back, CreateOutput=self._create_output,
-                                PeakType='Recoil', GlobalFitSharedParameter=False)
+                                PeakType='Recoil', SharedParameterFitType=self._shared_parameter_fit_type)
       
       E1_peak_fits_back = mtd[self._current_workspace + '_E1_back_Peak_Parameters'].getNames()
       self._calculate_final_energy(E1_peak_fits_back, BACKSCATTERING_RANGE)
@@ -1441,7 +1447,7 @@ def PyExec(self):
       E1_fit_front = self._current_workspace + '_E1_front'
       self._run_calibration_fit(Samples=self._samples, Function='Voigt', Mode='SingleDifference', SpectrumRange=FRONTSCATTERING_RANGE,
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_front, CreateOutput=self._create_output,
-                                PeakType='Recoil', GlobalFitSharedParameter=False)
+                                PeakType='Recoil', SharedParameterFitType=self._shared_parameter_fit_type)
       
       E1_peak_fits_front = mtd[self._current_workspace + '_E1_front_Peak_Parameters'].getNames()
       self._calculate_final_flight_path(E1_peak_fits_front[0], FRONTSCATTERING_RANGE)
@@ -1731,6 +1737,7 @@ def _setup(self):
     self._sample_mass = self.getProperty("Mass").value
     self._d_spacings = self.getProperty("DSpacings").value.tolist()
     self._E1_value_and_error = self.getProperty("E1FixedValueAndError").value.tolist()
+    self._shared_parameter_fit_type = self.getProperty("SharedParameterFitType").value
     self._calc_L0 = self.getProperty("CalculateL0").value
     self._make_IP_file = self.getProperty("CreateIPFile").value
     self._output_workspace_name = self.getPropertyValue("OutputWorkspace")

From fc2a8f1b53fb00d513063f9049c24942cbe9421b Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Thu, 20 Apr 2023 16:33:02 +0100
Subject: [PATCH 10/15] abstract global code

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py   | 37 ++++++++++---------
 1 file changed, 20 insertions(+), 17 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index 2f7eae83..1f41b547 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -336,7 +336,7 @@ def _setup_class_variables_from_properties(self):
     self._energy_estimates = self.getProperty("Energy").value
     self._sample_mass = self.getProperty("Mass").value
     self._create_output = self.getProperty("CreateOutput").value
-    self._global_fit_shared_parameter = self.getProperty("SharedParameterFitType").value
+    self._shared_parameter_fit_type = self.getProperty("SharedParameterFitType").value
 
   def _setup_spectra_list(self):
     self._spec_list = self.getProperty("SpectrumRange").value.tolist()
@@ -792,22 +792,25 @@ def _fit_peaks(self):
 
     GroupWorkspaces(self._output_parameter_tables, OutputWorkspace=self._output_workspace_name + '_Peak_Parameters')
 
-    if self._global_fit_shared_parameter == True:
-        init_Gaussian_FWHM = read_fitting_result_table_column(output_parameter_table_name, 'f1.GaussianFWHM', self._spec_list)
-        init_Gaussian_FWHM = np.nanmean(init_Gaussian_FWHM[init_Gaussian_FWHM != 0])
-        init_Lorentz_FWHM = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzFWHM', self._spec_list)
-        init_Lorentz_FWHM = np.nanmean(init_Lorentz_FWHM[init_Lorentz_FWHM != 0])
-        init_Lorentz_Amp = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzAmp', self._spec_list)
-        init_Lorentz_Amp = np.nanmean(init_Lorentz_Amp[init_Lorentz_Amp != 0])
-        init_Lorentz_Pos = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos', self._spec_list)
-        init_Lorentz_Pos = np.nanmean(init_Lorentz_Pos[init_Lorentz_Pos != 0])
-        
-        initial_params = {'A0': 0.0, 'A1': 0.0, 'LorentzAmp': init_Lorentz_Amp, 'LorentzPos': init_Lorentz_Pos, 'LorentzFWHM': init_Lorentz_FWHM, 'GaussianFWHM': init_Gaussian_FWHM}
-
-        peak_centres = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos', self._spec_list)
-        peak_centres_errors = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos_Err', self._spec_list)
-        invalid_spectra = identify_invalid_spectra(output_parameter_table_name, peak_centres, peak_centres_errors, self._spec_list)
-        self._fit_shared_parameter(invalid_spectra, initial_params, output_parameter_table_headers)
+    if self._shared_parameter_fit_type != "Individual":
+      self._shared_parameter_fit(output_parameter_table_name, output_parameter_table_headers)
+
+  def _shared_parameter_fit(self, output_parameter_table_name, output_parameter_table_headers):
+    init_Gaussian_FWHM = read_fitting_result_table_column(output_parameter_table_name, 'f1.GaussianFWHM', self._spec_list)
+    init_Gaussian_FWHM = np.nanmean(init_Gaussian_FWHM[init_Gaussian_FWHM != 0])
+    init_Lorentz_FWHM = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzFWHM', self._spec_list)
+    init_Lorentz_FWHM = np.nanmean(init_Lorentz_FWHM[init_Lorentz_FWHM != 0])
+    init_Lorentz_Amp = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzAmp', self._spec_list)
+    init_Lorentz_Amp = np.nanmean(init_Lorentz_Amp[init_Lorentz_Amp != 0])
+    init_Lorentz_Pos = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos', self._spec_list)
+    init_Lorentz_Pos = np.nanmean(init_Lorentz_Pos[init_Lorentz_Pos != 0])
+
+    initial_params = {'A0': 0.0, 'A1': 0.0, 'LorentzAmp': init_Lorentz_Amp, 'LorentzPos': init_Lorentz_Pos, 'LorentzFWHM': init_Lorentz_FWHM, 'GaussianFWHM': init_Gaussian_FWHM}
+
+    peak_centres = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos', self._spec_list)
+    peak_centres_errors = read_fitting_result_table_column(output_parameter_table_name, 'f1.LorentzPos_Err', self._spec_list)
+    invalid_spectra = identify_invalid_spectra(output_parameter_table_name, peak_centres, peak_centres_errors, self._spec_list)
+    self._fit_shared_parameter(invalid_spectra, initial_params, output_parameter_table_headers)
 
   def _fit_peak(self, peak_index, spec_index, peak_position, output_parameter_table_name, output_parameter_table_headers):
     spec_number = self._spec_list[0] + spec_index

From 30d5608d1cc30aaa444219b2199843cb8ce6cb12 Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Thu, 20 Apr 2023 17:12:31 +0100
Subject: [PATCH 11/15] fix unit tests

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py   | 11 ++-
 .../tests/unit/test_calibrate_vesuvio_fit.py  | 91 ++++++++++++++-----
 2 files changed, 76 insertions(+), 26 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index 1f41b547..2e22072b 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -458,8 +458,9 @@ def _fit_bragg_peaks(self):
         self._output_params_to_table(spec_number, num_estimated_peaks, selected_params, output_parameters_tbl_name)
 
         output_workspaces.append(
-            self._get_output_and_clean_workspaces(fit_results_unconstrained is not None, fit_results_unconstrained is not False, unconstrained_fit_selected, find_peaks_output_name,
-                                                  fit_peaks_output_name))
+            self._get_output_and_clean_workspaces(fit_results_unconstrained is not None,
+                                                  (fit_results_unconstrained is not None and fit_results_unconstrained is not False),
+                                                  unconstrained_fit_selected, find_peaks_output_name, fit_peaks_output_name))
 
     if self._create_output:
         GroupWorkspaces(','.join(output_workspaces), OutputWorkspace=self._output_workspace_name + "_Peak_Fits")
@@ -783,8 +784,8 @@ def _fit_peaks(self):
       output_parameter_table_name = self._output_workspace_name + '_Peak_%d_Parameters' % peak_index
       output_parameter_table_headers = self._create_parameter_table_and_output_headers(output_parameter_table_name)
       for spec_index, peak_position in enumerate(estimated_peak_positions):
-        fit_workspace_name, x_range = self._fit_peak(peak_index, spec_index, peak_position, output_parameter_table_name,
-                                                     output_parameter_table_headers)
+        fit_workspace_name = self._fit_peak(peak_index, spec_index, peak_position, output_parameter_table_name,
+                                            output_parameter_table_headers)
         self._peak_fit_workspaces_by_spec.append(fit_workspace_name)
 
       self._output_parameter_tables.append(output_parameter_table_name)
@@ -831,7 +832,7 @@ def _fit_peak(self, peak_index, spec_index, peak_position, output_parameter_tabl
     fit_workspace_name = fws.name()
     self._del_fit_workspaces(ncm, fit_params, fws)
 
-    return fit_workspace_name, (xmin, xmax)
+    return fit_workspace_name
 
   def _find_peaks_and_output_params(self, peak_index, spec_number, spec_index, peak_position):
     peak_table_name = '__' + self._sample + '_peaks_table_%d_%d' % (peak_index, spec_index)
diff --git a/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_fit.py b/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_fit.py
index bc4181e2..cc3e0921 100644
--- a/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_fit.py
+++ b/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_fit.py
@@ -641,12 +641,13 @@ def test_load_file_raw(self, mock_load_vesuvio, mock_load_raw, mock_convert_to_d
         mock_convert_to_dist.assert_called_once_with(output_name, EnableLogging=False)
 
     @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.GroupWorkspaces')
-    def test_fit_peaks(self, group_workspaces_mock):
+    def test_fit_peaks_individual(self, group_workspaces_mock):
         alg = EVSCalibrationFit()
         alg._estimate_peak_positions = MagicMock(return_value=np.asarray([[5, 10, 15], [2.5, 7.5, 10.5]]))
         alg._create_parameter_table_and_output_headers = MagicMock(return_value=['a', 'b', 'c'])
         alg._fit_peak = MagicMock(side_effect=lambda a, b, c, d, e: f'fit_ws_{a}_{b}')
         alg._output_workspace_name = 'output_ws_name'
+        alg._shared_parameter_fit_type = 'Individual'
         alg._fit_peaks()
         alg._create_parameter_table_and_output_headers.assert_has_calls([call('output_ws_name_Peak_0_Parameters'),
                                                                          call('output_ws_name_Peak_1_Parameters')])
@@ -661,6 +662,54 @@ def test_fit_peaks(self, group_workspaces_mock):
         group_workspaces_mock.assert_called_once_with(['output_ws_name_Peak_0_Parameters', 'output_ws_name_Peak_1_Parameters'],
                                                       OutputWorkspace='output_ws_name_Peak_Parameters')
 
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.EVSCalibrationFit._shared_parameter_fit')
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.GroupWorkspaces')
+    def test_fit_peaks_shared(self, group_workspaces_mock, shared_parameter_fit_mock):
+        alg = EVSCalibrationFit()
+        alg._estimate_peak_positions = MagicMock(return_value=np.asarray([[5, 10, 15], [2.5, 7.5, 10.5]]))
+        alg._create_parameter_table_and_output_headers = MagicMock(return_value=['a', 'b', 'c'])
+        alg._fit_peak = MagicMock(side_effect=lambda a, b, c, d, e: f'fit_ws_{a}_{b}')
+        alg._output_workspace_name = 'output_ws_name'
+        alg._shared_parameter_fit_type = 'Shared'
+        alg._fit_peaks()
+        alg._create_parameter_table_and_output_headers.assert_has_calls([call('output_ws_name_Peak_0_Parameters'),
+                                                                         call('output_ws_name_Peak_1_Parameters')])
+        alg._fit_peak.assert_has_calls([call(0, 0, 5, 'output_ws_name_Peak_0_Parameters', ['a', 'b', 'c']),
+                                        call(0, 1, 10, 'output_ws_name_Peak_0_Parameters', ['a', 'b', 'c']),
+                                        call(0, 2, 15, 'output_ws_name_Peak_0_Parameters', ['a', 'b', 'c']),
+                                        call(1, 0, 2.5, 'output_ws_name_Peak_1_Parameters', ['a', 'b', 'c']),
+                                        call(1, 1, 7.5, 'output_ws_name_Peak_1_Parameters', ['a', 'b', 'c']),
+                                        call(1, 2, 10.5, 'output_ws_name_Peak_1_Parameters', ['a', 'b', 'c'])])
+        self.assertEqual([['fit_ws_0_0', 'fit_ws_0_1', 'fit_ws_0_2'], ['fit_ws_1_0', 'fit_ws_1_1', 'fit_ws_1_2']],
+                         alg._peak_fit_workspaces)
+        group_workspaces_mock.assert_called_once_with(['output_ws_name_Peak_0_Parameters', 'output_ws_name_Peak_1_Parameters'],
+                                                      OutputWorkspace='output_ws_name_Peak_Parameters')
+        shared_parameter_fit_mock.assert_called_once_with('output_ws_name_Peak_1_Parameters', ['a', 'b', 'c'])
+
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.EVSCalibrationFit._shared_parameter_fit')
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.GroupWorkspaces')
+    def test_fit_peaks_both(self, group_workspaces_mock, shared_parameter_fit_mock):
+        alg = EVSCalibrationFit()
+        alg._estimate_peak_positions = MagicMock(return_value=np.asarray([[5, 10, 15], [2.5, 7.5, 10.5]]))
+        alg._create_parameter_table_and_output_headers = MagicMock(return_value=['a', 'b', 'c'])
+        alg._fit_peak = MagicMock(side_effect=lambda a, b, c, d, e: f'fit_ws_{a}_{b}')
+        alg._output_workspace_name = 'output_ws_name'
+        alg._shared_parameter_fit_type = 'Both'
+        alg._fit_peaks()
+        alg._create_parameter_table_and_output_headers.assert_has_calls([call('output_ws_name_Peak_0_Parameters'),
+                                                                         call('output_ws_name_Peak_1_Parameters')])
+        alg._fit_peak.assert_has_calls([call(0, 0, 5, 'output_ws_name_Peak_0_Parameters', ['a', 'b', 'c']),
+                                        call(0, 1, 10, 'output_ws_name_Peak_0_Parameters', ['a', 'b', 'c']),
+                                        call(0, 2, 15, 'output_ws_name_Peak_0_Parameters', ['a', 'b', 'c']),
+                                        call(1, 0, 2.5, 'output_ws_name_Peak_1_Parameters', ['a', 'b', 'c']),
+                                        call(1, 1, 7.5, 'output_ws_name_Peak_1_Parameters', ['a', 'b', 'c']),
+                                        call(1, 2, 10.5, 'output_ws_name_Peak_1_Parameters', ['a', 'b', 'c'])])
+        self.assertEqual([['fit_ws_0_0', 'fit_ws_0_1', 'fit_ws_0_2'], ['fit_ws_1_0', 'fit_ws_1_1', 'fit_ws_1_2']],
+                         alg._peak_fit_workspaces)
+        group_workspaces_mock.assert_called_once_with(['output_ws_name_Peak_0_Parameters', 'output_ws_name_Peak_1_Parameters'],
+                                                      OutputWorkspace='output_ws_name_Peak_Parameters')
+        shared_parameter_fit_mock.assert_called_once_with('output_ws_name_Peak_1_Parameters', ['a', 'b', 'c'])
+
     @staticmethod
     def _setup_alg_mocks_fit_peak():
         alg = EVSCalibrationFit()
@@ -907,7 +956,7 @@ def test_get_output_and_clean_workspaces_unconstrained_not_performed(self, mock_
         alg = EVSCalibrationFit()
         find_peaks_output_name = 'test_find_output_name'
         fit_peaks_output_name = 'test_fit_output_name'
-        output_ws = alg._get_output_and_clean_workspaces(False, False, find_peaks_output_name, fit_peaks_output_name)
+        output_ws = alg._get_output_and_clean_workspaces(False, False, False, find_peaks_output_name, fit_peaks_output_name)
         mock_delete_ws.assert_has_calls([call(fit_peaks_output_name + '_NormalisedCovarianceMatrix'),
                                          call(fit_peaks_output_name + '_Parameters'),
                                          call(find_peaks_output_name)])
@@ -918,14 +967,14 @@ def test_get_output_and_clean_workspaces_unconstrained_performed(self, mock_dele
         alg = EVSCalibrationFit()
         find_peaks_output_name = 'test_find_output_name'
         fit_peaks_output_name = 'test_fit_output_name'
-        output_ws = alg._get_output_and_clean_workspaces(True, False, find_peaks_output_name, fit_peaks_output_name)
+        output_ws = alg._get_output_and_clean_workspaces(True, True, False, find_peaks_output_name, fit_peaks_output_name)
         mock_delete_ws.assert_has_calls([call(fit_peaks_output_name + '_NormalisedCovarianceMatrix'),
-                                         call(fit_peaks_output_name + '_Parameters'),
-                                         call(find_peaks_output_name),
-                                         call(fit_peaks_output_name + '_unconstrained' + '_NormalisedCovarianceMatrix'),
-                                         call(fit_peaks_output_name + '_unconstrained' + '_Parameters'),
-                                         call(find_peaks_output_name + '_unconstrained'),
-                                         call(fit_peaks_output_name + '_unconstrained' + '_Workspace')])
+                                        call(fit_peaks_output_name + '_Parameters'),
+                                        call(find_peaks_output_name),
+                                        call(find_peaks_output_name + '_unconstrained'),
+                                        call(fit_peaks_output_name + '_unconstrained_NormalisedCovarianceMatrix'),
+                                        call(fit_peaks_output_name + '_unconstrained_Parameters'),
+                                        call(fit_peaks_output_name + '_unconstrained_Workspace')])
         self.assertEqual(output_ws, fit_peaks_output_name + '_Workspace')
 
     @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.DeleteWorkspace')
@@ -933,14 +982,14 @@ def test_get_output_and_clean_workspaces_unconstrained_performed_and_selected(se
         alg = EVSCalibrationFit()
         find_peaks_output_name = 'test_find_output_name'
         fit_peaks_output_name = 'test_fit_output_name'
-        output_ws = alg._get_output_and_clean_workspaces(True, True, find_peaks_output_name, fit_peaks_output_name)
+        output_ws = alg._get_output_and_clean_workspaces(True, True, True, find_peaks_output_name, fit_peaks_output_name)
         mock_delete_ws.assert_has_calls([call(fit_peaks_output_name + '_NormalisedCovarianceMatrix'),
-                                         call(fit_peaks_output_name + '_Parameters'),
-                                         call(find_peaks_output_name),
-                                         call(fit_peaks_output_name + '_unconstrained' + '_NormalisedCovarianceMatrix'),
-                                         call(fit_peaks_output_name + '_unconstrained' + '_Parameters'),
-                                         call(find_peaks_output_name + '_unconstrained'),
-                                         call(fit_peaks_output_name + '_Workspace')])
+                                        call(fit_peaks_output_name + '_Parameters'),
+                                        call(find_peaks_output_name),
+                                        call(find_peaks_output_name + '_unconstrained'),
+                                        call(fit_peaks_output_name + '_unconstrained_NormalisedCovarianceMatrix'),
+                                        call(fit_peaks_output_name + '_unconstrained_Parameters'),
+                                        call(fit_peaks_output_name + '_Workspace')])
         self.assertEqual(output_ws, fit_peaks_output_name + '_unconstrained' + '_Workspace')
 
     def test_generate_column_headers(self):
@@ -1145,7 +1194,7 @@ def test_fit_peaks_to_spectra_not_unconstrained_peaks_not_found(self):
         alg._get_find_peak_parameters.assert_called_once_with(spec_number, peak_estimates_list, False)
         alg._run_find_peaks.assert_called_once_with(workspace_index, find_peaks_output_name, 'find_peaks_params', False)
         alg._filter_and_fit_found_peaks.assert_not_called()
-        self.assertEqual(result, None)
+        self.assertEqual(result, False)
 
     @staticmethod
     def _setup_fit_bragg_peaks_mocks(fit_results, selected_params, output_workspaces):
@@ -1191,8 +1240,8 @@ def test_fit_bragg_peaks_success(self, group_workspaces_mock):
                                                       call(2, fit_result_ret_val, None)])
         alg._output_params_to_table.assert_has_calls([call(1, 2, selected_params[0], 'output_Peak_Parameters'),
                                                       call(2, 2, selected_params[1], 'output_Peak_Parameters')])
-        alg._get_output_and_clean_workspaces.assert_has_calls([call(False, False, 'sample_peaks_table_1', 'output_Spec_1'),
-                                                               call(False, False, 'sample_peaks_table_2', 'output_Spec_2')])
+        alg._get_output_and_clean_workspaces.assert_has_calls([call(False, False, False, 'sample_peaks_table_1', 'output_Spec_1'),
+                                                               call(False, False, False, 'sample_peaks_table_2', 'output_Spec_2')])
         group_workspaces_mock.assert_called_once_with(','.join(output_workspaces), OutputWorkspace='output_Peak_Fits')
 
     @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.GroupWorkspaces')
@@ -1217,8 +1266,8 @@ def test_fit_bragg_peaks_not_success(self, group_workspaces_mock):
                                                       call(2, fit_res, rit_u_res)])
         alg._output_params_to_table.assert_has_calls([call(1, 2, selected_params[0], 'output_Peak_Parameters'),
                                                       call(2, 2, selected_params[1], 'output_Peak_Parameters')])
-        alg._get_output_and_clean_workspaces.assert_has_calls([call(True, False, 'sample_peaks_table_1', 'output_Spec_1'),
-                                                               call(True, False, 'sample_peaks_table_2', 'output_Spec_2')])
+        alg._get_output_and_clean_workspaces.assert_has_calls([call(True, True, False, 'sample_peaks_table_1', 'output_Spec_1'),
+                                                               call(True, True, False, 'sample_peaks_table_2', 'output_Spec_2')])
         group_workspaces_mock.assert_called_once_with(','.join(output_workspaces), OutputWorkspace='output_Peak_Fits')
 
 

From 1df69836b1f579e1899c35ed22cdea30a55976f6 Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Mon, 24 Apr 2023 13:44:54 +0100
Subject: [PATCH 12/15] add unit test for global fit

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py   | 43 ++++++++++---------
 .../tests/system/test_system.py               | 27 ++++++++++++
 2 files changed, 49 insertions(+), 21 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index 2e22072b..dc94df87 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -1440,9 +1440,9 @@ def PyExec(self):
       self._run_calibration_fit(Samples=self._samples, Function='Voigt', Mode='SingleDifference', SpectrumRange=BACKSCATTERING_RANGE,
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_back, CreateOutput=self._create_output,
                                 PeakType='Recoil', SharedParameterFitType=self._shared_parameter_fit_type)
-      
+
       E1_peak_fits_back = mtd[self._current_workspace + '_E1_back_Peak_Parameters'].getNames()
-      self._calculate_final_energy(E1_peak_fits_back, BACKSCATTERING_RANGE)
+      self._calculate_final_energy(E1_peak_fits_back, BACKSCATTERING_RANGE, self._shared_parameter_fit_type != "Individual")
       
       # 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], BACKSCATTERING_RANGE)
@@ -1452,7 +1452,7 @@ def PyExec(self):
       self._run_calibration_fit(Samples=self._samples, Function='Voigt', Mode='SingleDifference', SpectrumRange=FRONTSCATTERING_RANGE,
                                 InstrumentParameterWorkspace=self._param_table, Mass=self._sample_mass, OutputWorkspace=E1_fit_front, CreateOutput=self._create_output,
                                 PeakType='Recoil', SharedParameterFitType=self._shared_parameter_fit_type)
-      
+
       E1_peak_fits_front = mtd[self._current_workspace + '_E1_front_Peak_Parameters'].getNames()
       self._calculate_final_flight_path(E1_peak_fits_front[0], FRONTSCATTERING_RANGE)
   
@@ -1665,7 +1665,7 @@ def _calculate_scattering_angle(self, table_name, spec_list):
 
 
 
-  def _calculate_final_energy(self, peak_table, spec_list):
+  def _calculate_final_energy(self, peak_table, spec_list, calculate_global):
     """
       Calculate the final energy using the fitted peak centres of a run.
 
@@ -1706,28 +1706,29 @@ def _calculate_final_energy(self, peak_table, spec_list):
         mean_E1_val = self._E1_value_and_error[0]
         E1_error_val = self._E1_value_and_error[1]
 
-    # calculate global energy
-    peak_centre = read_fitting_result_table_column(peak_table[1], 'f1.LorentzPos', [0])
-    peak_centre = [peak_centre] * len(peak_centres)
-
-    delta_t = (peak_centre - t0) / 1e+6
-    v1 = (L0 * r_theta + L1) / delta_t
-    E1 = 0.5*scipy.constants.m_n*v1**2
-    E1 /= MEV_CONVERSION
-
-    global_E1_val = np.nanmean(E1)
-    global_E1_error_val = np.nanstd(E1)
-
     mean_E1.fill(mean_E1_val)
     E1_error.fill(E1_error_val)
 
-    global_E1.fill(global_E1_val)
-    global_E1_error.fill(global_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, 'global_E1', global_E1)
-    self._set_table_column(self._current_workspace, 'global_E1_Err', global_E1_error)
+
+    if calculate_global:  # This fn will need updating for the only global option
+        peak_centre = read_fitting_result_table_column(peak_table[1], 'f1.LorentzPos', [0])
+        peak_centre = [peak_centre] * len(peak_centres)
+
+        delta_t = (peak_centre - t0) / 1e+6
+        v1 = (L0 * r_theta + L1) / delta_t
+        E1 = 0.5*scipy.constants.m_n*v1**2
+        E1 /= MEV_CONVERSION
+
+        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)
 
 #----------------------------------------------------------------------------------------
 
diff --git a/unpackaged/vesuvio_calibration/tests/system/test_system.py b/unpackaged/vesuvio_calibration/tests/system/test_system.py
index 6636f2e8..aa52bf06 100644
--- a/unpackaged/vesuvio_calibration/tests/system/test_system.py
+++ b/unpackaged/vesuvio_calibration/tests/system/test_system.py
@@ -336,6 +336,24 @@ def test_copper_create_output(self, load_file_mock):
                                                                              165, 167, 168, 169, 170, 182, 191, 192]})
         self.assert_parameters_match_expected(params_table, detector_specific_r_tols)
 
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.EVSCalibrationFit._load_file')
+    def test_copper_with_individual_and_global_fit(self, load_file_mock):
+        self._setup_copper_test()
+        self._output_workspace = "copper_analysis_test"
+
+        load_file_mock.side_effect = self._load_file_side_effect
+
+        self.create_evs_calibration_alg()
+        self._alg.setProperty("SharedParameterFitType", "Both")
+        params_table = self.execute_evs_calibration_analysis()
+
+        #  Specify detectors tolerances set by user, then update with those to mask as invalid.
+        detector_specific_r_tols = {"L1": {116: 0.65, 170: 0.75}}
+        detector_specific_r_tols["L1"].update({k: INVALID_DETECTOR for k in [138, 141, 146, 147, 156, 158, 160, 163, 164,
+                                                                             165, 167, 168, 169, 170, 182, 191, 192]})
+        self.assert_parameters_match_expected(params_table, detector_specific_r_tols)
+        self.assert_E1_parameters_match_expected(params_table, 3e-3, "Both")
+
     def tearDown(self):
         mtd.clear()
 
@@ -366,6 +384,15 @@ def assert_L1_parameters_match_expected(self, params_table, rel_tolerance):
         return _assert_allclose_excluding_bad_detectors(np.ma.masked_array(actual_L1, mask=invalid_detector_mask),
                                                         np.ma.masked_array(L1, mask=invalid_detector_mask), rel_tolerance)
 
+    def assert_E1_parameters_match_expected(self, params_table, rel_tolerance, fit_type):
+        if fit_type != "Shared":
+            E1 = params_table.column('E1')[0]
+            self.assertAlmostEqual(E1, ENERGY_ESTIMATE, delta=ENERGY_ESTIMATE*rel_tolerance)
+
+        if fit_type != "Individual":
+            global_E1 = params_table.column('global_E1')[0]
+            self.assertAlmostEqual(global_E1, ENERGY_ESTIMATE, delta=ENERGY_ESTIMATE*rel_tolerance)
+
     def assert_parameters_match_expected(self, params_table, tolerances=None):
         rel_tol_theta, rel_tol_L1 = self._extract_tolerances(tolerances)
         theta_errors = self.assert_theta_parameters_match_expected(params_table, rel_tol_theta)

From 3a92c591b88d9aa0e2bcc5864898cc2132b83b7c Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Mon, 24 Apr 2023 15:18:51 +0100
Subject: [PATCH 13/15] remove duplicated fn

---
 .../calibrate_vesuvio_uranium_martyn_MK5.py   | 37 +------------------
 1 file changed, 2 insertions(+), 35 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index dc94df87..1caae9cd 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -138,7 +138,6 @@ def identify_invalid_spectra(peak_table, peak_centres, peak_centres_errors, spec
 
   return invalid_spectra
 
-
 #----------------------------------------------------------------------------------------
 # The IP text file load function skips the first 3 rows of the text file.
 # This assumes that there is one line for the file header and 2 lines for
@@ -288,7 +287,7 @@ def PyInit(self):
 
     shared_fit_type_validator = StringListValidator(["Individual", "Shared", "Both"])
     self.declareProperty('SharedParameterFitType', "Individual", doc='Calculate shared parameters using an individual and/or'
-                                                              'global fit.', validator=shared_fit_type_validator)
+                         'global fit.', validator=shared_fit_type_validator)
 
     self.declareProperty(ITableWorkspaceProperty("InstrumentParameterWorkspace", "", Direction.Input, PropertyMode.Optional),
       doc='Workspace contain instrument parameters.')
@@ -1365,7 +1364,7 @@ def PyInit(self):
 
     shared_fit_type_validator = StringListValidator(["Individual", "Shared", "Both"])
     self.declareProperty('SharedParameterFitType', "Individual", doc='Calculate shared parameters using an individual and/or'
-                                                              'global fit.', validator=shared_fit_type_validator)
+                         'global fit.', validator=shared_fit_type_validator)
 
     self.declareProperty('CreateOutput', False,
       doc="Whether to create output from fitting.")
@@ -1585,38 +1584,6 @@ def _calculate_final_flight_path(self, peak_table, spec_list):
     self._set_table_column(self._current_workspace, 'L1', L1, spec_list)
     self._set_table_column(self._current_workspace, 'L1_Err', L1_error, spec_list)
 
-#----------------------------------------------------------------------------------------
-
-  def _identify_invalid_spectra(self, peak_table, peak_centres, peak_centres_errors, spec_list):
-    """
-      Inspect fitting results, and identify the fits associated with invalid spectra. These are spectra associated with detectors
-      which have lost foil coverage following a recent reduction in distance from source to detectors.
-
-      @param peak_table - name of table containing fitted parameters each spectra.
-      @param peak_centres - a list of the found peak centres
-      @param peak_centres_errors - a list of errors associated with the peak centres
-      @param spec_list - spectrum range to inspect.
-      @return a list of invalid spectra.
-    """
-    peak_Gaussian_FWHM = read_fitting_result_table_column(peak_table, 'f1.GaussianFWHM', spec_list)
-    peak_Gaussian_FWHM_errors = read_fitting_result_table_column(peak_table, 'f1.GaussianFWHM_Err', spec_list)
-    peak_Lorentz_FWHM = read_fitting_result_table_column(peak_table, 'f1.LorentzFWHM', spec_list)
-    peak_Lorentz_FWHM_errors = read_fitting_result_table_column(peak_table, 'f1.LorentzFWHM_Err', spec_list)
-    peak_Lorentz_Amp = read_fitting_result_table_column(peak_table, 'f1.LorentzAmp', spec_list)
-    peak_Lorentz_Amp_errors = read_fitting_result_table_column(peak_table, 'f1.LorentzAmp_Err', spec_list)
-
-    invalid_spectra = np.argwhere((np.isinf(peak_Lorentz_Amp_errors)) | (np.isnan(peak_Lorentz_Amp_errors))  | \
-    (np.isinf(peak_centres_errors)) | (np.isnan(peak_centres_errors))  | \
-    (np.isnan(peak_Gaussian_FWHM_errors)) | (np.isinf(peak_Gaussian_FWHM_errors)) | \
-    (np.isnan(peak_Lorentz_FWHM_errors)) | (np.isinf(peak_Lorentz_FWHM_errors)) | \
-    (np.isnan(peak_Lorentz_Amp_errors)) | (np.isinf(peak_Lorentz_Amp_errors)) | \
-    (np.absolute(peak_Gaussian_FWHM_errors) > np.absolute(peak_Gaussian_FWHM)) | \
-    (np.absolute(peak_Lorentz_FWHM_errors) > np.absolute(peak_Lorentz_FWHM)) | \
-    (np.absolute(peak_Lorentz_Amp_errors) > np.absolute(peak_Lorentz_Amp)) | \
-    (np.absolute(peak_centres_errors) > np.absolute(peak_centres)))
-
-    return invalid_spectra
-
  # ----------------------------------------------------------------------------------------
 
   def _calculate_scattering_angle(self, table_name, spec_list):

From ec8ddc3c1b95ac48fb07dbc55488f9ead093d731 Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Mon, 24 Apr 2023 15:32:49 +0100
Subject: [PATCH 14/15] move unit tests

---
 .../unit/test_calibrate_vesuvio_analysis.py   | 54 +------------------
 .../tests/unit/test_calibrate_vesuvio_misc.py | 50 ++++++++++++++++-
 2 files changed, 51 insertions(+), 53 deletions(-)

diff --git a/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_analysis.py b/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_analysis.py
index 6e2cb6af..eca5ce17 100644
--- a/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_analysis.py
+++ b/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_analysis.py
@@ -1,8 +1,6 @@
 from unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5 import EVSCalibrationAnalysis
-from mock import MagicMock, patch
 
 import unittest
-import numpy as np
 
 
 class TestVesuvioCalibrationAnalysis(unittest.TestCase):
@@ -13,56 +11,8 @@ def setUpClass(cls):
     def setUp(self):
         pass
 
-    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.mtd')
-    def test_identify_invalid_spectra_no_invalid(self, mock_mtd):
-        alg = EVSCalibrationAnalysis()
-        ws_mock = MagicMock()
-        mock_column_output_dict = {'f1.GaussianFWHM': [1, 2, 3], 'f1.GaussianFWHM_Err': [0.1, 0.2, 0.3],
-                                   'f1.LorentzFWHM': [1.1, 2.1, 3.1], 'f1.LorentzFWHM_Err': [0.11, 0.21, 0.31],
-                                   'f1.LorentzAmp': [1.2, 2.2, 3.2], 'f1.LorentzAmp_Err': [0.12, 0.22, 0.32]}
-        ws_mock.column.side_effect = lambda key: mock_column_output_dict[key]
-        mock_mtd.__getitem__.return_value = ws_mock
-
-        np.testing.assert_equal(np.argwhere([]), alg._identify_invalid_spectra('peak_table', [5, 10, 20], [0.1, 0.15, 0.2], [0, 2]))
-
-    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.mtd')
-    def test_identify_invalid_spectra_nan_in_errors(self, mock_mtd):
-        alg = EVSCalibrationAnalysis()
-        ws_mock = MagicMock()
-        mock_column_output_dict = {'f1.GaussianFWHM': [1, 2, 3], 'f1.GaussianFWHM_Err': [np.nan, 0.2, 0.3],
-                                   'f1.LorentzFWHM': [1.1, 2.1, 3.1], 'f1.LorentzFWHM_Err': [0.11, 0.21, 0.31],
-                                   'f1.LorentzAmp': [1.2, 2.2, 3.2], 'f1.LorentzAmp_Err': [0.12, 0.22, np.nan]}
-        ws_mock.column.side_effect = lambda key: mock_column_output_dict[key]
-        mock_mtd.__getitem__.return_value = ws_mock
-
-        np.testing.assert_equal(np.argwhere(np.array([True, False, True])),
-                                alg._identify_invalid_spectra('peak_table', [5, 10, 20], [0.1, 0.15, 0.2], [0, 2]))
-
-    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.mtd')
-    def test_identify_invalid_spectra_inf_in_errors(self, mock_mtd):
-        alg = EVSCalibrationAnalysis()
-        ws_mock = MagicMock()
-        mock_column_output_dict = {'f1.GaussianFWHM': [1, 2, 3], 'f1.GaussianFWHM_Err': [0.1, 0.2, 0.3],
-                                   'f1.LorentzFWHM': [1.1, 2.1, 3.1], 'f1.LorentzFWHM_Err': [np.inf, 0.21, 0.31],
-                                   'f1.LorentzAmp': [1.2, 2.2, 3.2], 'f1.LorentzAmp_Err': [0.12, np.inf, 0.32]}
-        ws_mock.column.side_effect = lambda key: mock_column_output_dict[key]
-        mock_mtd.__getitem__.return_value = ws_mock
-
-        np.testing.assert_equal(np.argwhere(np.array([True, True, False])),
-                                alg._identify_invalid_spectra('peak_table', [5, 10, 20], [0.1, 0.15, 0.2], [0, 2]))
-
-    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.mtd')
-    def test_identify_invalid_spectra_error_greater_than_peak(self, mock_mtd):
-        alg = EVSCalibrationAnalysis()
-        ws_mock = MagicMock()
-        mock_column_output_dict = {'f1.GaussianFWHM': [1, 2, 3], 'f1.GaussianFWHM_Err': [0.1, 0.2, 0.3],
-                                   'f1.LorentzFWHM': [1.1, 2.1, 3.1], 'f1.LorentzFWHM_Err': [0.11, 10, 0.31],
-                                   'f1.LorentzAmp': [1.2, 2.2, 3.2], 'f1.LorentzAmp_Err': [0.12, 0.22, 10]}
-        ws_mock.column.side_effect = lambda key: mock_column_output_dict[key]
-        mock_mtd.__getitem__.return_value = ws_mock
-
-        np.testing.assert_equal(np.argwhere(np.array([False, True, True])),
-                                alg._identify_invalid_spectra('peak_table', [5, 10, 20], [0.1, 0.15, 0.2], [0, 2]))
+    def test_placeholder(self):
+        pass
 
 
 if __name__ == '__main__':
diff --git a/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_misc.py b/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_misc.py
index 6019ab8d..08d1269c 100644
--- a/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_misc.py
+++ b/unpackaged/vesuvio_calibration/tests/unit/test_calibrate_vesuvio_misc.py
@@ -1,7 +1,8 @@
-from unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5 import generate_fit_function_header
+from unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5 import generate_fit_function_header, identify_invalid_spectra
 from mock import MagicMock, patch
 
 import unittest
+import numpy as np
 
 
 class TestVesuvioCalibrationMisc(unittest.TestCase):
@@ -33,6 +34,53 @@ def test_generate_header_function_invalid(self):
         with self.assertRaises(ValueError):
             generate_fit_function_header("Invalid")
 
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.mtd')
+    def test_identify_invalid_spectra_no_invalid(self, mock_mtd):
+        ws_mock = MagicMock()
+        mock_column_output_dict = {'f1.GaussianFWHM': [1, 2, 3], 'f1.GaussianFWHM_Err': [0.1, 0.2, 0.3],
+                                   'f1.LorentzFWHM': [1.1, 2.1, 3.1], 'f1.LorentzFWHM_Err': [0.11, 0.21, 0.31],
+                                   'f1.LorentzAmp': [1.2, 2.2, 3.2], 'f1.LorentzAmp_Err': [0.12, 0.22, 0.32]}
+        ws_mock.column.side_effect = lambda key: mock_column_output_dict[key]
+        mock_mtd.__getitem__.return_value = ws_mock
+
+        np.testing.assert_equal(np.argwhere([]), identify_invalid_spectra('peak_table', [5, 10, 20], [0.1, 0.15, 0.2], [0, 2]))
+
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.mtd')
+    def test_identify_invalid_spectra_nan_in_errors(self, mock_mtd):
+        ws_mock = MagicMock()
+        mock_column_output_dict = {'f1.GaussianFWHM': [1, 2, 3], 'f1.GaussianFWHM_Err': [np.nan, 0.2, 0.3],
+                                   'f1.LorentzFWHM': [1.1, 2.1, 3.1], 'f1.LorentzFWHM_Err': [0.11, 0.21, 0.31],
+                                   'f1.LorentzAmp': [1.2, 2.2, 3.2], 'f1.LorentzAmp_Err': [0.12, 0.22, np.nan]}
+        ws_mock.column.side_effect = lambda key: mock_column_output_dict[key]
+        mock_mtd.__getitem__.return_value = ws_mock
+
+        np.testing.assert_equal(np.argwhere(np.array([True, False, True])),
+                                identify_invalid_spectra('peak_table', [5, 10, 20], [0.1, 0.15, 0.2], [0, 2]))
+
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.mtd')
+    def test_identify_invalid_spectra_inf_in_errors(self, mock_mtd):
+        ws_mock = MagicMock()
+        mock_column_output_dict = {'f1.GaussianFWHM': [1, 2, 3], 'f1.GaussianFWHM_Err': [0.1, 0.2, 0.3],
+                                   'f1.LorentzFWHM': [1.1, 2.1, 3.1], 'f1.LorentzFWHM_Err': [np.inf, 0.21, 0.31],
+                                   'f1.LorentzAmp': [1.2, 2.2, 3.2], 'f1.LorentzAmp_Err': [0.12, np.inf, 0.32]}
+        ws_mock.column.side_effect = lambda key: mock_column_output_dict[key]
+        mock_mtd.__getitem__.return_value = ws_mock
+
+        np.testing.assert_equal(np.argwhere(np.array([True, True, False])),
+                                identify_invalid_spectra('peak_table', [5, 10, 20], [0.1, 0.15, 0.2], [0, 2]))
+
+    @patch('unpackaged.vesuvio_calibration.calibrate_vesuvio_uranium_martyn_MK5.mtd')
+    def test_identify_invalid_spectra_error_greater_than_peak(self, mock_mtd):
+        ws_mock = MagicMock()
+        mock_column_output_dict = {'f1.GaussianFWHM': [1, 2, 3], 'f1.GaussianFWHM_Err': [0.1, 0.2, 0.3],
+                                   'f1.LorentzFWHM': [1.1, 2.1, 3.1], 'f1.LorentzFWHM_Err': [0.11, 10, 0.31],
+                                   'f1.LorentzAmp': [1.2, 2.2, 3.2], 'f1.LorentzAmp_Err': [0.12, 0.22, 10]}
+        ws_mock.column.side_effect = lambda key: mock_column_output_dict[key]
+        mock_mtd.__getitem__.return_value = ws_mock
+
+        np.testing.assert_equal(np.argwhere(np.array([False, True, True])),
+                                identify_invalid_spectra('peak_table', [5, 10, 20], [0.1, 0.15, 0.2], [0, 2]))
+
 
 if __name__ == '__main__':
     unittest.main()

From d2d18e0d79a7c9982e368ea4c10a5e8962555fd5 Mon Sep 17 00:00:00 2001
From: MialLewis <95620982+MialLewis@users.noreply.github.com>
Date: Mon, 24 Apr 2023 15:36:08 +0100
Subject: [PATCH 15/15] remove unused import

---
 .../vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py  | 1 -
 1 file changed, 1 deletion(-)

diff --git a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
index 1caae9cd..b7317059 100644
--- a/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
+++ b/unpackaged/vesuvio_calibration/calibrate_vesuvio_uranium_martyn_MK5.py
@@ -26,7 +26,6 @@
 import scipy.constants
 import scipy.stats
 import numpy as np
-import time
 
 # Configuration for Uranium runs / Indium runs
 #----------------------------------------------------------------------------------------