correct eps term in placzek correction

Framework/Algorithms/src/CalculatePlaczekSelfScattering.cpp

@@ -114,10 +114,10 @@ void CalculatePlaczekSelfScattering::exec() {
     phi1.push_back((xLambda[i] + dx) * incidentPrime[i] / incident[i]);
   }
   // set detector law term (eps1)
-  const double lambdaD = 1.44;
   std::vector<double> eps1;
+  const double lambdaD = 1.44;
   for (size_t i = 0; i < xLambda.size() - 1; i++) {
-    double xTerm = -(xLambda[i] + dx) / lambdaD;
+    double xTerm = (xLambda[i] + dx) / lambdaD;
     eps1.push_back(xTerm * exp(xTerm) / (1.0 - exp(xTerm)));
   }
   /* Placzek
@@ -163,10 +163,9 @@ void CalculatePlaczekSelfScattering::exec() {
                             specInfo.twoTheta(specIndex), 0, 1.0, 1.0);
       for (size_t xIndex = 0; xIndex < xLambda.size() - 1; xIndex++) {
         const double term1 = (f - 1.0) * phi1[xIndex];
-        const double term2 = -f * eps1[xIndex];
-        const double term3 = f - 3.0;
+        const double term2 = f * (1.0 - eps1[xIndex]);
         const double inelasticPlaczekSelfCorrection =
-            2.0 * (term1 + term2 + term3) * sinThetaBy2 * sinThetaBy2 *
+            2.0 * (term1 + term2 - 3) * sinThetaBy2 * sinThetaBy2 *
             summationTerm;
         x[xIndex] = wavelength.singleToTOF(xLambda[xIndex]);
         y[xIndex] = inelasticPlaczekSelfCorrection;

scripts/Diffraction/isis_powder/polaris_routines/polaris_algs.py

@@ -151,8 +151,8 @@ def _generate_grouped_ts_pdf(run_number, focused_ws, q_lims, cal_file_name, samp
     width_x = (max_x-min_x)/x_data.size
     fit_spectra = mantid.FitIncidentSpectrum(InputWorkspace=monitor,
                                              BinningForCalc=[min_x, 1*width_x, max_x],
-                                             BinningForFit=[min_x, 50*width_x, max_x],
-                                             FitSpectrumWith="GaussConvCubicSpline")
+                                             BinningForFit=[min_x, 1*width_x, max_x],
+                                             FitSpectrumWith="CubicSpline")
     placzek = mantid.CalculatePlaczekSelfScattering(InputWorkspace=raw_ws, IncidentSpecta=fit_spectra)
     mantid.ConvertFromDistribution(Workspace=placzek)
     cal_workspace = mantid.LoadCalFile(InputWorkspace=placzek,
@@ -174,10 +174,6 @@ def _generate_grouped_ts_pdf(run_number, focused_ws, q_lims, cal_file_name, samp
     mantid.Subtract(LHSWorkspace=focused_data_combined,
                     RHSWorkspace=placzek,
                     OutputWorkspace=focused_data_combined)
-
-    mantid.MatchSpectra(InputWorkspace=focused_data_combined,
-                        OutputWorkspace=focused_data_combined,
-                        ReferenceSpectrum=1)
     if type(q_lims) == str:
         q_min = []
         q_max = []
@@ -202,6 +198,9 @@ def _generate_grouped_ts_pdf(run_number, focused_ws, q_lims, cal_file_name, samp
         q_max[i] = pdf_x_array[np.amax(np.where(pdf_x_array <= q_max[i]))]
         bin_width = min(pdf_x_array[1] - pdf_x_array[0], bin_width)
     focused_data_combined = mantid.CropWorkspaceRagged(InputWorkspace=focused_data_combined, XMin=q_min, XMax=q_max)
+    mantid.MatchSpectra(InputWorkspace=focused_data_combined,
+                        OutputWorkspace=focused_data_combined,
+                        ReferenceSpectrum=1)
     focused_data_combined = mantid.Rebin(InputWorkspace=focused_data_combined,
                                          Params=[min(q_min), bin_width, max(q_max)])
     focused_data_combined = mantid.SumSpectra(InputWorkspace=focused_data_combined,