Re #22067 remove commented out logging lines

Framework/PythonInterface/plugins/functions/BivariateGaussian.py

@@ -127,8 +127,8 @@ class BivariateGaussian(IFunction1D):
                     self.log().information('Setting constraints on mbvg; reversing bounds')
                     self.addConstraints("{:4.4e} < A < {:4.4e}".format(boundsDict[param][1], boundsDict[param][0]))
             except ValueError:
-                self.log().warning('Cannot set parameter {:s} for mbvg.  Valid choices are ' +
-                                   '(\'A\', \'MuX\', \'MuY\', \'SigX\', \'SigY\', \'SigP\', \'Bg\')'.format(param))
+                self.log().warning("Cannot set parameter {:s} for mbvg.  Valid choices are " +
+                                   "('A', 'MuX', 'MuY', 'SigX', 'SigY', 'SigP', 'Bg')".format(param))
 
     def function2D(self, t):
         """

scripts/SCD_Reduction/BVGFitTools.py

@@ -193,7 +193,6 @@ def fitScaling(n_events, box, YTOF, YBVG, goodIDX=None, neigh_length_m=3):
     YRET = A1 * YJOINT + A0
     chiSqRed = fitResultsScaling[1]
 
-    #logger.information( '{:2.2f} is chiSqRed'.format(chiSq))
     return YRET, chiSqRed, A1
 
 
@@ -469,7 +468,6 @@ def doBVGFit(box, nTheta=200, nPhi=200, zBG=1.96, fracBoxToHistogram=1.0, goodID
         m.setAttributeValue('nX', h.shape[0])
         m.setAttributeValue('nY', h.shape[1])
         m.setConstraints(boundsDict)
-        # logger.information('before: ' + str(m))
         # Do the fit
         bvgWS = CreateWorkspace(OutputWorkspace='bvgWS', DataX=pos.ravel(
         ), DataY=H.ravel(), DataE=np.sqrt(H.ravel()))
@@ -477,7 +475,6 @@ 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')
 
-        #logger.information('after' + str(m))
     elif forceParams is not None:
         p0 = np.zeros(7)
         p0[0] = np.max(h)
@@ -528,7 +525,6 @@ def doBVGFit(box, nTheta=200, nPhi=200, zBG=1.96, fracBoxToHistogram=1.0, goodID
         m.setAttributeValue('nX', h.shape[0])
         m.setAttributeValue('nY', h.shape[1])
         m.setConstraints(boundsDict)
-        #logger.information('before: ' + str(m))
 
         # Do the fit
         #plt.figure(18); plt.clf(); plt.imshow(m.function2D(pos)); plt.title('BVG Initial guess')
@@ -537,7 +533,6 @@ def doBVGFit(box, nTheta=200, nPhi=200, zBG=1.96, fracBoxToHistogram=1.0, goodID
         fitResults = Fit(Function=fitFun, InputWorkspace=bvgWS,
                          Output='bvgfit', Minimizer='Levenberg-MarquardtMD')
 
-        #system.logger('after: ' + str(m))
     # Recover the result
     m = BivariateGaussian.BivariateGaussian()
     m.init()

scripts/SCD_Reduction/ICCFitTools.py

@@ -290,11 +290,8 @@ def getOptimizedGoodIDX(n_events, padeCoefficients, zBG=1.96, neigh_length_m=3,
             break
         except KeyboardInterrupt:
             sys.exit()
-    #logger.information( '\n'.join([str(v)
-    #                 for v in zip(chiSqList[:i+1], ISIGList[:i+1], IList[:i+1])]))
     use_ppl = np.argmin(np.abs(chiSqList[:i+1]-1.0))
     pp_lambda = pp_lambda_toCheck[use_ppl]
-    #logger.information('USING PP_LAMBDA', pp_lambda, 'WITH CHISQ:', chiSqList[use_ppl])
     goodIDX, _ = getBGRemovedIndices(n_events, pp_lambda=pp_lambda)
     chiSq, h, intens, sigma = getQuickTOFWS(box, peak, padeCoefficients, goodIDX=goodIDX, qMask=qMask,
                                             pp_lambda=pp_lambda, minppl_frac=minppl_frac, maxppl_frac=maxppl_frac,