Re #22811 change default TOPAZ DQPixel value

Framework/PythonInterface/plugins/algorithms/IntegratePeaksProfileFitting.py

@@ -130,7 +130,7 @@ class IntegratePeaksProfileFitting(PythonAlgorithm):
             nTheta=50
             nPhi = 50
             fracHKL = 0.4
-            dQPixel = 0.006
+            dQPixel = 0.01
         elif instrumentName == 'CORELLI':
             mindtBinWidth = 2
             maxdtBinWidth = 60
@@ -232,9 +232,9 @@ class IntegratePeaksProfileFitting(PythonAlgorithm):
                 peak.setSigmaIntensity(1.0)
 
         # Cleanup
-        for wsName in mtd.getObjectNames():
-            if 'fit_' in wsName or 'bvgWS' in wsName or  'tofWS' in wsName or 'scaleWS' in wsName:
-                mtd.remove(wsName)
+        #for wsName in mtd.getObjectNames():
+         #   if 'fit_' in wsName or 'bvgWS' in wsName or  'tofWS' in wsName or 'scaleWS' in wsName:
+         #       mtd.remove(wsName)
         np.warnings.filterwarnings('default') # Re-enable on exit
         # Set the output
         self.setProperty('OutputPeaksWorkspace', peaks_ws_out)

docs/source/algorithms/IntegratePeaksProfileFitting-v1.rst

@@ -46,7 +46,7 @@ values are below:
 | Parameter    |  Description               |  MaNDi   |  TOPAZ   | CORELLI |
 +==============+============================+==========+==========+=========+
 | DQPixel      | The side length for each   |          |          |         |
-|              | voxel used for fitting.    | 0.003    | 0.006    | 0.007   |
+|              | voxel used for fitting.    | 0.003    | 0.01     | 0.007   |
 |              | Units: 1/Angstrom          |          |          |         |
 +--------------+----------------------------+----------+----------+---------+
 | FracHKL      | The distance between peaks |          |          |         |

scripts/SCD_Reduction/BVGFitTools.py

@@ -190,7 +190,7 @@ def fitScaling(n_events, box, YTOF, YBVG, goodIDX=None, neigh_length_m=3, instru
     QX, QY, QZ = ICCFT.getQXQYQZ(box)
     dP = 8
     if instrumentName == 'TOPAZ':
-        dP = 3
+        dP = 8
     fitMaxIDX = tuple(
         np.array(np.unravel_index(YJOINT.argmax(), YJOINT.shape)))
     if goodIDX is None:
@@ -517,7 +517,6 @@ def doBVGFit(box, nTheta=200, nPhi=200, zBG=1.96, fracBoxToHistogram=1.0, goodID
 
         fitResults = Fit(Function=m, InputWorkspace='bvgWS', Output='bvgfit',
                          Minimizer='Levenberg-MarquardtMD')
-
     elif forceParams is not None:
         p0 = np.zeros(7)
         p0[0] = np.max(h)