diff --git a/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/Quest.py b/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/Quest.py
deleted file mode 100644
index 5f15cb3c2fb160048a520cf1a8bbd38c07254126..0000000000000000000000000000000000000000
--- a/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/Quest.py
+++ /dev/null
@@ -1,107 +0,0 @@
-#pylint: disable=no-init
-from mantid.api import PythonAlgorithm, AlgorithmFactory
-from mantid.kernel import StringListValidator, StringMandatoryValidator
-from mantid.simpleapi import *
-from mantid import config, logger, mtd
-import os
-
-class Quest(PythonAlgorithm):
-
- def category(self):
- return "Workflow\\MIDAS"
-
- def summary(self):
- return "This is a variation of the stretched exponential option of Quasi."
-
- def PyInit(self):
- self.declareProperty(name='InputType',defaultValue='File',validator=StringListValidator(['File','Workspace']),
- doc='Origin of data input - File (.nxs) or Workspace')
- self.declareProperty(name='Instrument',defaultValue='iris',validator=StringListValidator(['irs','iris','osi','osiris']),
- doc='Instrument')
- self.declareProperty(name='Analyser',defaultValue='graphite002',validator=StringListValidator(['graphite002','graphite004']),
- doc='Analyser & reflection')
- self.declareProperty(name='SamNumber',defaultValue='',validator=StringMandatoryValidator(), doc='Sample run number')
- self.declareProperty(name='ResInputType',defaultValue='File',validator=StringListValidator(['File','Workspace']),
- doc='Origin of res input - File (_res.nxs) or Workspace')
- self.declareProperty(name='ResNumber',defaultValue='',validator=StringMandatoryValidator(), doc='Resolution run number')
- self.declareProperty(name='ResNormInputType',defaultValue='File',validator=StringListValidator(['File','Workspace']),
- doc='Origin of ResNorm input - File (_red.nxs) or Workspace')
- self.declareProperty(name='ResNormNumber',defaultValue='',validator=StringMandatoryValidator(), doc='ResNorm run number')
- self.declareProperty(name='ElasticOption',defaultValue=True, doc='Include elastic peak in fit')
- self.declareProperty(name='BackgroundOption',defaultValue='Sloping',validator=StringListValidator(['Sloping','Flat','Zero']),
- doc='Form of background to fit')
- self.declareProperty(name='EnergyMin', defaultValue=-0.5, doc='Minimum energy for fit. Default=-0.5')
- self.declareProperty(name='EnergyMax', defaultValue=0.5, doc='Maximum energy for fit. Default=0.5')
- self.declareProperty(name='SamBinning', defaultValue=1, doc='Binning value(integer) for sample. Default=1')
- self.declareProperty(name='NumberSigma', defaultValue=50, doc='Number of sigma values. Default=50')
- self.declareProperty(name='NumberBeta', defaultValue=30, doc='Number of beta values. Default=30')
- self.declareProperty(name='Sequence',defaultValue=True, doc='Switch Sequence Off/On')
- self.declareProperty(name='Plot',defaultValue='None',validator=StringListValidator(['None','Sigma','Beta','All']),
- doc='Plot options')
- self.declareProperty(name='Verbose',defaultValue=True, doc='Switch Verbose Off/On')
- self.declareProperty(name='Save',defaultValue=False, doc='Switch Save result to nxs file Off/On')
-
- #pylint: disable=too-many-locals,too-many-branches
- def PyExec(self):
- from IndirectImport import run_f2py_compatibility_test, is_supported_f2py_platform
-
- if is_supported_f2py_platform():
- import IndirectBayes as Main
-
- run_f2py_compatibility_test()
-
- self.log().information('Quest input')
- inType = self.getPropertyValue('InputType')
- prefix = self.getPropertyValue('Instrument')
- ana = self.getPropertyValue('Analyser')
- sam = self.getPropertyValue('SamNumber')
- rinType = self.getPropertyValue('ResInputType')
- res = self.getPropertyValue('ResNumber')
- elastic = self.getProperty('ElasticOption').value
- bgd = self.getPropertyValue('BackgroundOption')
- emin = self.getPropertyValue('EnergyMin')
- emax = self.getPropertyValue('EnergyMax')
- nbin = self.getPropertyValue('SamBinning')
- nbins = [nbin, 1]
- nbet = self.getProperty('NumberBeta').value
- nsig = self.getProperty('NumberSigma').value
- nbs = [nbet, nsig]
-
- sname = prefix+sam+'_'+ana + '_red'
- rname = prefix+res+'_'+ana + '_res'
- erange = [float(emin), float(emax)]
- if elastic:
- o_el = 1
- else:
- o_el = 0
- fitOp = [o_el, bgd, 0, 0]
- loopOp = self.getProperty('Sequence').value
- verbOp = self.getProperty('Verbose').value
- plotOp = self.getPropertyValue('Plot')
- saveOp = self.getProperty('Save').value
-
- workdir = config['defaultsave.directory']
- if not os.path.isdir(workdir):
- workdir = os.getcwd()
- logger.information('Default Save directory is not set. Defaulting to current working Directory: ' + workdir)
-
- if inType == 'File':
- spath = os.path.join(workdir, sname+'.nxs') # path name for sample nxs file
- LoadNexusProcessed(Filename=spath, OutputWorkspace=sname)
- Smessage = 'Sample from File : '+spath
- else:
- Smessage = 'Sample from Workspace : '+sname
-
- if rinType == 'File':
- rpath = os.path.join(workdir, rname+'.nxs') # path name for res nxs file
- LoadNexusProcessed(Filename=rpath, OutputWorkspace=rname)
- Rmessage = 'Resolution from File : '+rpath
- else:
- Rmessage = 'Resolution from Workspace : '+rname
-
- if verbOp:
- logger.notice(Smessage)
- logger.notice(Rmessage)
- Main.QuestRun(sname,rname,nbs,erange,nbins,fitOp,loopOp,plotOp,saveOp)
-
-AlgorithmFactory.subscribe(Quest) # Register algorithm with Mantid
diff --git a/Testing/SystemTests/tests/analysis/ISISIndirectBayesTest.py b/Testing/SystemTests/tests/analysis/ISISIndirectBayesTest.py
index b2cf8faa7b541b6c4a3185b4f61a6be6349af43d..5cede9caa98d97d840d67bc1e04e30c1a8bed851 100644
--- a/Testing/SystemTests/tests/analysis/ISISIndirectBayesTest.py
+++ b/Testing/SystemTests/tests/analysis/ISISIndirectBayesTest.py
@@ -101,27 +101,30 @@ class QuestTest(stresstesting.MantidStressTest):
return not platform.system() == "Windows"
def runTest(self):
- import IndirectBayes as Main
- nbins = [1, 1]
- nbs = [50, 30]
sname = 'irs26176_graphite002_red'
rname = 'irs26173_graphite002_res'
- erange = [-0.5, 0.5]
- fitOp = [True, 'Sloping', False, False] #elastic, background, width, resnorm
- loopOp = False
- plotOp = 'None'
- saveOp = False
spath = sname+'.nxs' # path name for sample nxs file
- LoadNexusProcessed(Filename=spath, OutputWorkspace=sname)
+ sample = LoadNexusProcessed(Filename=spath, OutputWorkspace=sname)
rpath = rname+'.nxs' # path name for res nxs file
- LoadNexusProcessed(Filename=rpath, OutputWorkspace=rname)
- Main.QuestRun(sname,rname,nbs,erange,nbins,fitOp,loopOp,plotOp,saveOp)
+ res = LoadNexusProcessed(Filename=rpath, OutputWorkspace=rname)
+ BayesStretch(SampleWorkspace=sample,
+ ResolutionWorkspace=res,
+ EMin=-0.5,
+ EMax=0.5,
+ SampleBins=1,
+ Elastic=True,
+ Background='Sloping',
+ NumberSigma=30,
+ NumberBeta=50,
+ Loop=False,
+ OutputWorkspaceFit='fit_group',
+ OutputWorkspaceContour='contour_group')
def validate(self):
self.tolerance = 1e-1
self.disableChecking.append('SpectraMap')
- return 'irs26176_graphite002_Qst_Fit','ISISIndirectBayes_QuestTest.nxs'
+ return 'irs26176_graphite002_Stretch_Fit','ISISIndirectBayes_QuestTest.nxs'
def cleanup(self):
filenames = ['irs26176_graphite002_Qst.lpt','irs26176_graphite002_Qss.ql2',
diff --git a/docs/source/algorithms/Quest-v1.rst b/docs/source/algorithms/Quest-v1.rst
deleted file mode 100644
index 7ffd94f7162524b0f3f5ad6b4f9c32cce158ae7e..0000000000000000000000000000000000000000
--- a/docs/source/algorithms/Quest-v1.rst
+++ /dev/null
@@ -1,35 +0,0 @@
-.. algorithm::
-
-.. summary::
-
-.. alias::
-
-.. properties::
-
-Description
------------
-
-This is a variation of the stretched exponential option of
-`Quasi <http://www.mantidproject.org/IndirectBayes:Quasi>`__. For each spectrum a fit is performed
-for a grid of :math:`\beta` and :math:`\sigma` values. The distribution of goodness of fit values
-is plotted.
-
-This routine was originally part of the MODES package. Note that this algorithm
-uses F2Py and is currently only supported on windows.
-
-Usage
------
-**Example - a basic example using Quest to fit a reduced workspace.**
-
-.. code-block:: python
-
- sam = LoadNexusProcessed("irs26173_graphite002_red.nxs", OutputWorkspace='irs26173_graphite002_red')
- res = LoadNexusProcessed("irs26173_graphite002_res.nxs", OutputWorkspace='irs26173_graphite002_res')
- van = LoadNexusProcessed("irs26176_graphite002_red.nxs", OutputWorkspace='irs26176_graphite002_red')
-
- ResNorm(VanNumber='26176', ResNumber='26173', InputType='File', ResInputType='File', Instrument='irs', Analyser='graphite002', Plot='None', Version=1)
- Quest(SamNumber='26176', ResNumber='26173', ResNormNumber='26176', InputType='File', ResInputType='File', ResNormInputType='Workspace', Instrument='irs', Analyser='graphite002')
-
-.. categories::
-
-.. sourcelink::
diff --git a/scripts/Inelastic/IndirectBayes.py b/scripts/Inelastic/IndirectBayes.py
index 4f0bf3c7135f580476e502c960c28aca1419a821..105bb67b4e9583b7e754a1ee5c906663acf5db29 100644
--- a/scripts/Inelastic/IndirectBayes.py
+++ b/scripts/Inelastic/IndirectBayes.py
@@ -12,7 +12,6 @@ if is_supported_f2py_platform():
QLr = import_f2py("QLres")
QLd = import_f2py("QLdata")
Qse = import_f2py("QLse")
- Que = import_f2py("Quest")
resnorm = import_f2py("ResNorm")
else:
unsupported_message()
@@ -68,203 +67,6 @@ def GetXYE(inWS,n,array_len):
E=PadArray(Ein,array_len)
return N,X,Y,E
-# Quest programs
-def CheckBetSig(nbs):
- Nsig = int(nbs[1])
- if Nsig == 0:
- raise ValueError('Number of sigma points is Zero')
- if Nsig > 200:
- raise ValueError('Max number of sigma points is 200')
-
- Nbet = int(nbs[0])
- if Nbet == 0:
- raise ValueError('Number of beta points is Zero')
- if Nbet > 200:
- raise ValueError('Max number of beta points is 200')
-
- return Nbet,Nsig
-
-def QuestRun(samWS,resWS,nbs,erange,nbins,Fit,Loop,Plot,Save):
- StartTime('Quest')
- #expand fit options
- elastic, background, width, res_norm = Fit
-
- #convert true/false to 1/0 for fortran
- o_el = 1 if elastic else 0
- o_w1 = 1 if width else 0
- o_res = 1 if res_norm else 0
-
- #fortran code uses background choices defined using the following numbers
- if background == 'Sloping':
- o_bgd = 2
- elif background == 'Flat':
- o_bgd = 1
- elif background == 'Zero':
- o_bgd = 0
-
- fitOp = [o_el, o_bgd, o_w1, o_res]
-
- workdir = config['defaultsave.directory']
- if not os.path.isdir(workdir):
- workdir = os.getcwd()
- logger.information('Default Save directory is not set. Defaulting to current working Directory: ' + workdir)
-
- array_len = 4096 # length of array in Fortran
- CheckXrange(erange,'Energy')
- nbin,nrbin = nbins[0],nbins[1]
- logger.information('Sample is ' + samWS)
- logger.information('Resolution is ' + resWS)
- CheckAnalysers(samWS,resWS)
- nsam,ntc = CheckHistZero(samWS)
-
- if Loop != True:
- nsam = 1
-
- efix = getEfixed(samWS)
- theta,Q = GetThetaQ(samWS)
- nres = CheckHistZero(resWS)[0]
- if nres == 1:
- prog = 'Qst' # res file
- else:
- raise ValueError('Stretched Exp ONLY works with RES file')
- logger.information(' Number of spectra = '+str(nsam))
- logger.information(' Erange : '+str(erange[0])+' to '+str(erange[1]))
-
- fname = samWS[:-4] + '_'+ prog
- wrks=os.path.join(workdir, samWS[:-4])
- logger.information(' lptfile : ' + wrks +'_Qst.lpt')
- lwrk=len(wrks)
- wrks.ljust(140,' ')
- wrkr=resWS
- wrkr.ljust(140,' ')
- Nbet,Nsig = nbs[0], nbs[1]
- eBet0 = np.zeros(Nbet) # set errors to zero
- eSig0 = np.zeros(Nsig) # set errors to zero
- rscl = 1.0
- Qaxis = ''
- for m in range(0,nsam):
- logger.information('Group ' +str(m)+ ' at angle '+ str(theta[m]))
- nsp = m+1
- nout,bnorm,Xdat,Xv,Yv,Ev = CalcErange(samWS,m,erange,nbin)
- Ndat = nout[0]
- Imin = nout[1]
- Imax = nout[2]
- Nb,Xb,Yb,_ = GetXYE(resWS,0,array_len)
- numb = [nsam, nsp, ntc, Ndat, nbin, Imin, Imax, Nb, nrbin, Nbet, Nsig]
- reals = [efix, theta[m], rscl, bnorm]
- xsout,ysout,xbout,ybout,zpout=Que.quest(numb,Xv,Yv,Ev,reals,fitOp,\
- Xdat,Xb,Yb,wrks,wrkr,lwrk)
- dataXs = xsout[:Nsig] # reduce from fixed Fortran array
- dataYs = ysout[:Nsig]
- dataXb = xbout[:Nbet]
- dataYb = ybout[:Nbet]
- zpWS = fname + '_Zp' +str(m)
- if m > 0:
- Qaxis += ','
- Qaxis += str(Q[m])
-
- dataXz = []
- dataYz = []
- dataEz = []
-
- for n in range(0,Nsig):
- yfit_list = np.split(zpout[:Nsig*Nbet],Nsig)
- dataYzp = yfit_list[n]
-
- dataXz = np.append(dataXz,xbout[:Nbet])
- dataYz = np.append(dataYz,dataYzp[:Nbet])
- dataEz = np.append(dataEz,eBet0)
-
- CreateWorkspace(OutputWorkspace=zpWS, DataX=dataXz, DataY=dataYz, DataE=dataEz,
- Nspec=Nsig, UnitX='MomentumTransfer',
- VerticalAxisUnit='MomentumTransfer', VerticalAxisValues=dataXs)
-
- unitx = mtd[zpWS].getAxis(0).setUnit("Label")
- unitx.setLabel('beta' , '')
- unity = mtd[zpWS].getAxis(1).setUnit("Label")
- unity.setLabel('sigma' , '')
-
- if m == 0:
- xSig = dataXs
- ySig = dataYs
- eSig = eSig0
- xBet = dataXb
- yBet = dataYb
- eBet = eBet0
- groupZ = zpWS
- else:
- xSig = np.append(xSig,dataXs)
- ySig = np.append(ySig,dataYs)
- eSig = np.append(eSig,eSig0)
- xBet = np.append(xBet,dataXb)
- yBet = np.append(yBet,dataYb)
- eBet = np.append(eBet,eBet0)
- groupZ = groupZ +','+ zpWS
-
- #create workspaces for sigma and beta
- CreateWorkspace(OutputWorkspace=fname+'_Sigma', DataX=xSig, DataY=ySig, DataE=eSig,\
- Nspec=nsam, UnitX='', VerticalAxisUnit='MomentumTransfer', VerticalAxisValues=Qaxis)
- unitx = mtd[fname+'_Sigma'].getAxis(0).setUnit("Label")
- unitx.setLabel('sigma' , '')
-
- CreateWorkspace(OutputWorkspace=fname+'_Beta', DataX=xBet, DataY=yBet, DataE=eBet,\
- Nspec=nsam, UnitX='', VerticalAxisUnit='MomentumTransfer', VerticalAxisValues=Qaxis)
- unitx = mtd[fname+'_Beta'].getAxis(0).setUnit("Label")
- unitx.setLabel('beta' , '')
-
- group = fname + '_Sigma,'+ fname + '_Beta'
-
- fit_workspace = fname+'_Fit'
- contour_workspace = fname+'_Contour'
- GroupWorkspaces(InputWorkspaces=group,OutputWorkspace=fit_workspace)
- GroupWorkspaces(InputWorkspaces=groupZ,OutputWorkspace=contour_workspace)
-
- #add sample logs to the output workspaces
- CopyLogs(InputWorkspace=samWS, OutputWorkspace=fit_workspace)
- QuestAddSampleLogs(fit_workspace, resWS, background, elastic, erange, nbin, Nsig, Nbet)
- CopyLogs(InputWorkspace=samWS, OutputWorkspace=contour_workspace)
- QuestAddSampleLogs(contour_workspace, resWS, background, elastic, erange, nbin, Nsig, Nbet)
-
- if Save:
- fpath = os.path.join(workdir,fit_workspace+'.nxs')
- SaveNexusProcessed(InputWorkspace=fit_workspace, Filename=fpath)
-
- cpath = os.path.join(workdir,contour_workspace+'.nxs')
- SaveNexusProcessed(InputWorkspace=contour_workspace, Filename=cpath)
-
- logger.information('Output file for Fit : ' + fpath)
- logger.information('Output file for Contours : ' + cpath)
-
- if Plot != 'None' and Loop == True:
- QuestPlot(fname,Plot)
- EndTime('Quest')
-
-def QuestAddSampleLogs(workspace, res_workspace, background, elastic_peak, e_range, sample_binning, sigma, beta):
- energy_min, energy_max = e_range
-
- AddSampleLog(Workspace=workspace, LogName="res_file",
- LogType="String", LogText=res_workspace)
- AddSampleLog(Workspace=workspace, LogName="background",
- LogType="String", LogText=str(background))
- AddSampleLog(Workspace=workspace, LogName="elastic_peak",
- LogType="String", LogText=str(elastic_peak))
- AddSampleLog(Workspace=workspace, LogName="energy_min",
- LogType="Number", LogText=str(energy_min))
- AddSampleLog(Workspace=workspace, LogName="energy_max",
- LogType="Number", LogText=str(energy_max))
- AddSampleLog(Workspace=workspace, LogName="sample_binning",
- LogType="Number", LogText=str(sample_binning))
- AddSampleLog(Workspace=workspace, LogName="sigma",
- LogType="Number", LogText=str(sigma))
- AddSampleLog(Workspace=workspace, LogName="beta",
- LogType="Number", LogText=str(beta))
-
-
-def QuestPlot(inputWS,Plot):
- if Plot == 'Sigma' or Plot == 'All':
- MTD_PLOT.importMatrixWorkspace(inputWS+'_Sigma').plotGraph2D()
- if Plot == 'Beta' or Plot == 'All':
- MTD_PLOT.importMatrixWorkspace(inputWS+'_Beta').plotGraph2D()
# ResNorm programs
def ResNormRun(vname,rname,erange,nbin,Plot='None',Save=False):