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# Bayes routines
# Fortran programs use fixed length arrays whereas Python has variable lenght lists
# Input : the Python list is padded to Fortrans length using procedure PadArray
# Output : the Fortran numpy array is sliced to Python length using dataY = yout[:ny]
from IndirectImport import *
if is_supported_f2py_platform():
Er = import_f2py("erange")
QLr = import_f2py("QLres")
QLd = import_f2py("QLdata")
Qse = import_f2py("QLse")
Que = import_f2py("Quest")
resnorm = import_f2py("ResNorm")
else:
from mantid.simpleapi import *
from mantid import config, logger, mtd
import sys, platform, math, os.path, numpy as np
mp = import_mantidplot()
def readASCIIFile(file_name):
workdir = config['defaultsave.directory']
file_path = os.path.join(workdir, file_name)
asc = []
with open(file_path, 'r') as handle:
for line in handle:
line = line.rstrip()
asc.append(line)
return asc
def CalcErange(inWS,ns,er,nbin):
rscl = 1.0
array_len = 4096 # length of array in Fortran
N,X,Y,E = GetXYE(inWS,ns,array_len) # get data
nout,bnorm,Xdat=Er.erange(N,X,Y,E,er,nbin,rscl) # calculate energy range
if nout[0] == 0:
error = 'Erange - calculated points is Zero'
logger.notice('ERROR *** ' + error)
sys.exit(error)
if nout[1] == 0:
error = 'Erange - calculated Imin is Zero'
logger.notice('ERROR *** ' + error)
sys.exit(error)
if nout[2] == 0:
error = 'Erange - calculated Imax is Zero'
logger.notice('ERROR *** ' + error)
sys.exit(error)
return nout,bnorm,Xdat,X,Y,E
def GetXYE(inWS,n,array_len):
Xin = mtd[inWS].readX(n)
N = len(Xin)-1 # get no. points from length of x array
Yin = mtd[inWS].readY(n)
Ein = mtd[inWS].readE(n)
X=PadArray(Xin,array_len)
Y=PadArray(Yin,array_len)
E=PadArray(Ein,array_len)
def GetResNorm(resnormWS,ngrp):
dtnorm = mtd[resnormWS+'_Intensity'].readY(0)
xscale = mtd[resnormWS+'_Stretch'].readY(0)
dtnorm = []
xscale = []
for m in range(0,ngrp):
dtnorm.append(1.0)
xscale.append(1.0)
dtn=PadArray(dtnorm,51) # pad for Fortran call
xsc=PadArray(xscale,51)
def ReadNormFile(readRes,resnormWS,nsam,Verbose): # get norm & scale values
if readRes: # use ResNorm file option=o_res
Xin = mtd[resnormWS+'_Intensity'].readX(0)
nrm = len(Xin) # no. points from length of x array
error = 'ResNorm file has no Intensity points'
logger.notice('ERROR *** ' + error)
sys.exit(error)
Xin = mtd[resnormWS+'_Stretch'].readX(0) # no. points from length of x array
if len(Xin) == 0:
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error = 'ResNorm file has no xscale points'
logger.notice('ERROR *** ' + error)
sys.exit(error)
if nrm != nsam: # check that no. groups are the same
error = 'ResNorm groups (' +str(nrm) + ') not = Sample (' +str(nsam) +')'
logger.notice('ERROR *** ' + error)
sys.exit(error)
dtn,xsc = GetResNorm(resnormWS,0)
# do not use ResNorm file
dtn,xsc = GetResNorm(resnormWS,nsam)
#Reads in a width ASCII file
def ReadWidthFile(readWidth,widthFile,numSampleGroups,Verbose):
widthY = []
widthE = []
if readWidth:
logger.notice('Width file is ' + widthFile)
# read ascii based width file
try:
wfPath = FileFinder.getFullPath(widthFile)
handle = open(wfPath, 'r')
asc = []
for line in handle:
line = line.rstrip()
asc.append(line)
handle.close()
except Exception, e:
error = 'Failed to read width file'
logger.notice('ERROR *** ' + error)
sys.exit(error)
numLines = len(asc)
if numLines == 0:
error = 'No groups in width file'
logger.notice('ERROR *** ' + error)
sys.exit(error)
if numLines != numSampleGroups: # check that no. groups are the same
error = 'Width groups (' +str(numLines) + ') not = Sample (' +str(numSampleGroups) +')'
logger.notice('ERROR *** ' + error)
else:
# no file: just use constant values
widthY = np.zeros(numSampleGroups)
widthE = np.zeros(numSampleGroups)
# pad for Fortran call
widthY = PadArray(widthY,51)
widthE = PadArray(widthE,51)
return widthY, widthE
def QLRun(program,samWS,resWS,resnormWS,erange,nbins,Fit,wfile,Loop,Verbose,Plot,Save):
#expand fit options
elastic, background, width, resnorm = 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 resnorm 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 = getDefaultWorkingDirectory()
facility = config['default.facility']
array_len = 4096 # length of array in Fortran
CheckXrange(erange,'Energy')
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if Verbose:
logger.notice('Sample is ' + samWS)
logger.notice('Resolution is ' + resWS)
if facility == 'ISIS':
CheckAnalysers(samWS,resWS,Verbose)
efix = getEfixed(samWS)
theta,Q = GetThetaQ(samWS)
nsam,ntc = CheckHistZero(samWS)
totalNoSam = nsam
#check if we're performing a sequential fit
if Loop != True:
nsam = 1
nres,ntr = CheckHistZero(resWS)
prog = 'QLr' # res file
prog = 'QLd' # data file
CheckHistSame(samWS,'Sample',resWS,'Resolution')
elif program == 'QSe':
prog = 'QSe' # res file
error = 'Stretched Exp ONLY works with RES file'
sys.exit(error)
if Verbose:
logger.notice('Version is ' +prog)
logger.notice(' Number of spectra = '+str(nsam))
logger.notice(' Erange : '+str(erange[0])+' to '+str(erange[1]))
Wy,We = ReadWidthFile(width,wfile,totalNoSam,Verbose)
dtn,xsc = ReadNormFile(resnorm,resnormWS,totalNoSam,Verbose)
probWS = fname + '_Prob'
fitWS = fname + '_Fit'
datWS = fname + '_Data'
wrks=os.path.join(workdir, samWS[:-4])
logger.notice(' lptfile : '+wrks+'_'+prog+'.lpt')
lwrk=len(wrks)
wrks.ljust(140,' ')
wrkr=resWS
wrkr.ljust(140,' ')
wrk = [wrks, wrkr]
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# initialise probability list
if program == 'QL':
xQ = np.array([Q[0]])
for m in range(1,nsam):
xQ = np.append(xQ,Q[m])
xProb = xQ
xProb = np.append(xProb,xQ)
xProb = np.append(xProb,xQ)
eProb = np.zeros(3*nsam)
group = ''
if Verbose:
logger.notice('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]
if prog == 'QLd':
mm = m
else:
mm = 0
Nb,Xb,Yb,Eb = GetXYE(resWS,mm,array_len) # get resolution data
numb = [nsam, nsp, ntc, Ndat, nbin, Imin, Imax, Nb, nrbin]
rscl = 1.0
reals = [efix, theta[m], rscl, bnorm]
if prog == 'QLr':
nd,xout,yout,eout,yfit,yprob=QLr.qlres(numb,Xv,Yv,Ev,reals,fitOp,
Xdat,Xb,Yb,Wy,We,dtn,xsc,
wrks,wrkr,lwrk)
message = ' Log(prob) : '+str(yprob[0])+' '+str(yprob[1])+' '+str(yprob[2])+' '+str(yprob[3])
if Verbose:
logger.notice(message)
if prog == 'QLd':
nd,xout,yout,eout,yfit,yprob=QLd.qldata(numb,Xv,Yv,Ev,reals,fitOp,
Xdat,Xb,Yb,Eb,Wy,We,
wrks,wrkr,lwrk)
message = ' Log(prob) : '+str(yprob[0])+' '+str(yprob[1])+' '+str(yprob[2])+' '+str(yprob[3])
if Verbose:
logger.notice(message)
if prog == 'QSe':
nd,xout,yout,eout,yfit,yprob=Qse.qlstexp(numb,Xv,Yv,Ev,reals,fitOp,
Xdat,Xb,Yb,Wy,We,dtn,xsc,
wrks,wrkr,lwrk)
dataX = xout[:nd]
dataX = np.append(dataX,2*xout[nd-1]-xout[nd-2])
yfit_list = np.split(yfit[:4*nd],4)
dataF0 = yfit_list[0]
dataF1 = yfit_list[1]
dataF2 = yfit_list[2]
dataF3 = yfit_list[3]
datX = dataX
datY = yout[:nd]
datE = eout[:nd]
datX = np.append(datX,dataX)
datY = np.append(datY,dataF1[:nd])
datE = np.append(datE,dataG)
res1 = dataF1[:nd] - yout[:nd]
datX = np.append(datX,dataX)
datY = np.append(datY,res1)
datE = np.append(datE,dataG)
nsp = 3
names = 'data,fit.1,diff.1'
res_plot = [0, 1, 2]
datX = np.append(datX,dataX)
datY = np.append(datY,dataF2[:nd])
datE = np.append(datE,dataG)
res2 = dataF2[:nd] - yout[:nd]
datX = np.append(datX,dataX)
datY = np.append(datY,res2)
datE = np.append(datE,dataG)
nsp += 2
names += ',fit.2,diff.2'
res_plot.append(4)
prob0.append(yprob[0])
prob1.append(yprob[1])
prob2.append(yprob[2])
# create result workspace
fitWS = fname+'_Result'
fout = fitWS +'_'+ str(m)
CreateWorkspace(OutputWorkspace=fout, DataX=datX, DataY=datY, DataE=datE,
Nspec=nsp, UnitX='DeltaE', VerticalAxisUnit='Text', VerticalAxisValues=names)
# append workspace to list of results
group += fout + ','
GroupWorkspaces(InputWorkspaces=group,OutputWorkspace=fitWS)
yPr0 = np.array([prob0[0]])
yPr1 = np.array([prob1[0]])
yPr2 = np.array([prob2[0]])
for m in range(1,nsam):
yPr0 = np.append(yPr0,prob0[m])
yPr1 = np.append(yPr1,prob1[m])
yPr2 = np.append(yPr2,prob2[m])
yProb = yPr0
yProb = np.append(yProb,yPr1)
yProb = np.append(yProb,yPr2)
CreateWorkspace(OutputWorkspace=probWS, DataX=xProb, DataY=yProb, DataE=eProb,
outWS = C2Fw(samWS[:-4],fname)
QLPlotQL(fname,Plot,res_plot,Loop)
QLPlotQSe(fname,Plot,res_plot,Loop)
#Add some sample logs to the output workspace
AddSampleLog(Workspace=outWS, LogName="Fit Program", LogType="String", LogText=prog)
AddSampleLog(Workspace=outWS, LogName="Energy min", LogType="Number", LogText=str(erange[0]))
AddSampleLog(Workspace=outWS, LogName="Energy max", LogType="Number", LogText=str(erange[1]))
AddSampleLog(Workspace=outWS, LogName="Elastic", LogType="String", LogText=str(elastic))
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AddSampleLog(Workspace=outWS, LogName="ResNorm", LogType="String", LogText=str(resnorm))
if resnorm:
AddSampleLog(Workspace=outWS, LogName="ResNorm file", LogType="String", LogText=resnormWS)
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AddSampleLog(Workspace=outWS, LogName="Width", LogType="String", LogText=str(width))
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if width:
AddSampleLog(Workspace=outWS, LogName="Width file", LogType="String", LogText=wfile)
if Save:
fit_path = os.path.join(workdir,fitWS+'.nxs')
SaveNexusProcessed(InputWorkspace=fitWS, Filename=fit_path)
out_path = os.path.join(workdir, outWS+'.nxs') # path name for nxs file
SaveNexusProcessed(InputWorkspace=outWS, Filename=out_path)
logger.notice('Output fit file created : ' + fit_path)
logger.notice('Output paramter file created : ' + out_path)
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def yield_floats(block):
#yield a list of floats from a list of lines of text
#encapsulates the iteration over a block of lines
for line in block:
yield ExtractFloat(line)
def read_ql_file(file_name, nl):
#offet to ignore header
header_offset = 8
block_size = 4+nl*3
asc = readASCIIFile(file_name)
#extract number of blocks from the file header
num_blocks = int(ExtractFloat(asc[3])[0])
q_data = []
amp_data, FWHM_data, height_data = [], [], []
amp_error, FWHM_error, height_error = [], [], []
#iterate over each block of fit parameters in the file
for block_num in xrange(num_blocks):
lower_index = header_offset+(block_size*block_num)
upper_index = lower_index+block_size
#create iterator for each line in the block
line_pointer = yield_floats(asc[lower_index:upper_index])
#Q,AMAX,HWHM,BSCL,GSCL
line = line_pointer.next()
Q, AMAX, HWHM, BSCL, GSCL = line
q_data.append(Q)
#A0,A1,A2,A4
line = line_pointer.next()
block_height = AMAX*line[0]
#parse peak data from block
block_FWHM = []
block_amplitude = []
for i in range(nl):
#Amplitude,FWHM for each peak
line = line_pointer.next()
amp = AMAX*line[0]
FWHM = 2.*HWHM*line[1]
block_amplitude.append(amp)
block_FWHM.append(FWHM)
#next parse error data from block
#SIG0
line = line_pointer.next()
block_height_e = line[0]
block_FWHM_e = []
block_amplitude_e = []
for i in range(nl):
#Amplitude error,FWHM error for each peak
#SIGIK
line = line_pointer.next()
amp = AMAX*math.sqrt(math.fabs(line[0])+1.0e-20)
block_amplitude_e.append(amp)
#SIGFK
line = line_pointer.next()
FWHM = 2.0*HWHM*math.sqrt(math.fabs(line[0])+1.0e-20)
block_FWHM_e.append(FWHM)
amp_data.append(block_amplitude)
FWHM_data.append(block_FWHM)
height_data.append(block_height)
amp_error.append(block_amplitude_e)
FWHM_error.append(block_FWHM_e)
height_error.append(block_height_e)
return q_data, (amp_data, FWHM_data, height_data), (amp_error, FWHM_error, height_error)
output_workspace = sname+'_Workspace'
axis_names = []
x, y, e = [], [], []
amplitude_data, width_data = [], []
amplitude_error, width_error = [], []
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#read data from file output by fortran code
file_name = sname + '.ql' +str(nl)
x_data, peak_data, peak_error = read_ql_file(file_name, nl)
amplitude_data, width_data, height_data = peak_data
amplitude_error, width_error, height_error = peak_error
#transpose y and e data into workspace rows
amplitude_data, width_data = np.asarray(amplitude_data).T, np.asarray(width_data).T
amplitude_error, width_error = np.asarray(amplitude_error).T, np.asarray(width_error).T
x_data = np.asarray(x_data)
#interlace amplitudes and widths of the peaks
y.append(np.asarray(height_data))
for amp, width in zip(amplitude_data, width_data):
y.append(amp)
y.append(width)
#iterlace amplitude and width errors of the peaks
e.append(np.asarray(height_error))
for amp, width in zip(amplitude_error, width_error):
e.append(amp)
e.append(width)
#create x data and axis names for each function
axis_names.append('f'+str(nl-1)+'.f0.'+'Height')
x.append(x_data)
for j in range(1,nl+1):
axis_names.append('f'+str(nl-1)+'.f'+str(j)+'.Amplitude')
x.append(x_data)
axis_names.append('f'+str(nl-1)+'.f'+str(j)+'.FWHM')
x.append(x_data)
x = np.asarray(x).flatten()
y = np.asarray(y).flatten()
e = np.asarray(e).flatten()
CreateWorkspace(OutputWorkspace=output_workspace, DataX=x, DataY=y, DataE=e, Nspec=n_hist,
UnitX='MomentumTransfer', YUnitLabel='', VerticalAxisUnit='Text', VerticalAxisValues=axis_names)
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return output_workspace
def SeBlock(a,first): #read Ascii block of Integers
line1 = a[first]
first += 1
val = ExtractFloat(a[first]) #Q,AMAX,HWHM
Q = val[0]
AMAX = val[1]
HWHM = val[2]
first += 1
val = ExtractFloat(a[first]) #AI,FWHM first peak
fw = [2.*HWHM*val[1]]
int = [AMAX*val[0]]
first += 1
int.append(AMAX*math.sqrt(math.fabs(val[0])+1.0e-20))
first += 1
fw.append(2.0*HWHM*math.sqrt(math.fabs(val[0])+1.0e-20))
first += 1
be.append(math.sqrt(math.fabs(val[0])+1.0e-20))
first += 1
return first,Q,int0,fw,int,be #values as list
def C2Se(sname):
prog = 'QSe'
outWS = sname+'_Workspace'
asc = readASCIIFile(sname+'.qse')
lasc = len(asc)
var = asc[3].split() #split line on spaces
nspec = var[0]
ndat = var[1]
first = 7
Xout = []
Yf = []
Ef = []
Yi = []
Ei = []
Yb = []
Eb = []
ns = int(nspec)
dataX = np.array([])
dataY = np.array([])
dataE = np.array([])
for m in range(0,ns):
first,Q,int0,fw,it,be = SeBlock(asc,first)
Xout.append(Q)
Yf.append(fw[0])
Ef.append(fw[1])
Yi.append(it[0])
Ei.append(it[1])
Yb.append(be[0])
Eb.append(be[1])
dataX = np.append(dataX,np.array(Xout))
dataY = np.append(dataY,np.array(Yi))
dataE = np.append(dataE,np.array(Ei))
dataX = np.append(dataX, np.array(Xout))
dataY = np.append(dataY, np.array(Yf))
dataE = np.append(dataE, np.array(Ef))
nhist += 1
Vaxis.append('FWHM')
dataX = np.append(dataX,np.array(Xout))
dataY = np.append(dataY,np.array(Yb))
dataE = np.append(dataE,np.array(Eb))
logger.notice('Vaxis=' + str(Vaxis))
CreateWorkspace(OutputWorkspace=outWS, DataX=dataX, DataY=dataY, DataE=dataE, Nspec=nhist,
UnitX='MomentumTransfer', VerticalAxisUnit='Text', VerticalAxisValues=Vaxis, YUnitLabel='')
return outWS
def QLPlotQL(inputWS,Plot,res_plot,Loop):
ws_name = inputWS + '_Workspace'
nhist = mtd[ws_name].getNumberHistograms()
if (Plot == 'Amplitude' or Plot == 'All'):
plotSpectra(ws_name, 'Amplitude', indicies=range(0,nhist,3))
if (Plot == 'FWHM' or Plot == 'All'):
plotSpectra(ws_name, 'Full width half maximum (meV)', indicies=range(2,nhist,3))
if (Plot == 'Prob' or Plot == 'All'):
pWS = inputWS+'_Prob'
p_plot=mp.plotSpectrum(pWS,[1,2],False)
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fWS = inputWS+'_Result_0'
f_plot=mp.plotSpectrum(fWS,res_plot,False)
def QLPlotQSe(inputWS,Plot,res_plot,Loop):
ws_name = inputWS+'_Workspace'
if (Plot == 'Amplitude' or Plot == 'All'):
plotSpectra(ws_name, 'Amplitude', indicies=[0])
if (Plot == 'FWHM' or Plot == 'All'):
plotSpectra(ws_name, 'Full width half maximum (meV)', indicies=[1])
if (Plot == 'Beta' or Plot == 'All'):
plotSpectra(ws_name, 'Beta', indicies=[2])
fWS = inputWS+'_Result_0'
f_plot=mp.plotSpectrum(fWS,res_plot,False)
def plotSpectra(ws, axis_title, indicies=[]):
if len(indicies) > 0:
plot = mp.plotSpectrum(ws, indicies, True)
layer = plot.activeLayer()
layer.setAxisTitle(mp.Layer.Left, axis_title)
def CheckBetSig(nbs):
Nsig = int(nbs[1])
if Nsig == 0:
error = 'Number of sigma points is Zero'
logger.notice('ERROR *** ' + error)
sys.exit(error)
if Nsig > 200:
error = 'Max number of sigma points is 200'
logger.notice('ERROR *** ' + error)
sys.exit(error)
Nbet = int(nbs[0])
if Nbet == 0:
error = 'Number of beta points is Zero'
logger.notice('ERROR *** ' + error)
sys.exit(error)
if Nbet > 200:
error = 'Max number of beta points is 200'
logger.notice('ERROR *** ' + error)
sys.exit(error)
return Nbet,Nsig
def QuestRun(samWS,resWS,nbs,erange,nbins,Fit,Loop,Verbose,Plot,Save):
#expand fit options
elastic, background, width, resnorm = 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 resnorm 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 = getDefaultWorkingDirectory()
array_len = 4096 # length of array in Fortran
CheckXrange(erange,'Energy')
nbin,nrbin = nbins[0],nbins[1]
logger.notice('Sample is ' + samWS)
logger.notice('Resolution is ' + resWS)
CheckAnalysers(samWS,resWS,Verbose)
nsam,ntc = CheckHistZero(samWS)
if Loop != True:
nsam = 1
efix = getEfixed(samWS)
theta,Q = GetThetaQ(samWS)
nres,ntr = CheckHistZero(resWS)
if nres == 1:
prog = 'Qst' # res file
else:
error = 'Stretched Exp ONLY works with RES file'
logger.notice('ERROR *** ' + error)
sys.exit(error)
if Verbose:
logger.notice(' Number of spectra = '+str(nsam))
logger.notice(' Erange : '+str(erange[0])+' to '+str(erange[1]))
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wrks=os.path.join(workdir, samWS[:-4])
if Verbose:
logger.notice(' lptfile : ' + wrks +'_Qst.lpt')
lwrk=len(wrks)
wrks.ljust(140,' ')
wrkr=resWS
wrkr.ljust(140,' ')
wrk = [wrks, wrkr]
Nbet,Nsig = nbs[0], nbs[1]
eBet0 = np.zeros(Nbet) # set errors to zero
eSig0 = np.zeros(Nsig) # set errors to zero
if Verbose:
logger.notice('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,Eb = 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]
if (m > 0):
Qaxis += ','
Qaxis += str(Q[m])
dataXz = []
dataYz = []
dataEz = []
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' , '')
xSig = dataXs
ySig = dataYs
eSig = eSig0
xBet = dataXb
yBet = dataYb
eBet = eBet0
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)
#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' , '')
GroupWorkspaces(InputWorkspaces=group,OutputWorkspace=fname+'_Fit')
GroupWorkspaces(InputWorkspaces=groupZ,OutputWorkspace=fname+'_Contour')
if Save:
fpath = os.path.join(workdir,fname+'_Fit.nxs')
SaveNexusProcessed(InputWorkspace=fname+'_Fit', Filename=fpath)
cpath = os.path.join(workdir,fname+'_Contour.nxs')
SaveNexusProcessed(InputWorkspace=fname+'_Contour', Filename=cpath)
if Verbose:
logger.notice('Output file for Fit : ' + fpath)
logger.notice('Output file for Contours : ' + cpath)
if (Plot != 'None'):
QuestPlot(fname,Plot)
def QuestPlot(inputWS,Plot):
if (Plot == 'Sigma' or Plot == 'All'):
sig_plot=mp.importMatrixWorkspace(inputWS+'_Sigma').plotGraph2D()
if (Plot == 'Beta' or Plot == 'All'):
beta_plot=mp.importMatrixWorkspace(inputWS+'_Beta').plotGraph2D()
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def ResNormRun(vname,rname,erange,nbin,Verbose=False,Plot='None',Save=False):
workdir = getDefaultWorkingDirectory()
array_len = 4096 # length of Fortran array
CheckXrange(erange,'Energy')
CheckAnalysers(vname,rname,Verbose)
nvan,ntc = CheckHistZero(vname)
theta,Q = GetThetaQ(vname)
efix = getEfixed(vname)
nres,ntr = CheckHistZero(rname)
nout,bnorm,Xdat,Xv,Yv,Ev = CalcErange(vname,0,erange,nbin)
Ndat = nout[0]
Imin = nout[1]
Imax = nout[2]
wrks=os.path.join(workdir, vname[:-4])
if Verbose:
logger.notice(' Number of spectra = '+str(nvan))
logger.notice(' lptfile : ' + wrks +'_resnrm.lpt')
lwrk=len(wrks)
wrks.ljust(140,' ') # pad for fioxed Fortran length
Nb,Xb,Yb,Eb = GetXYE(rname,0,array_len)
xPar = np.array([theta[0]])
for m in range(1,nvan):
xPar = np.append(xPar,theta[m])
ePar = np.zeros(nvan)
fname = vname[:-4]
for m in range(0,nvan):
if Verbose:
logger.notice('Group ' +str(m)+ ' at angle '+ str(theta[m]))
ntc,Xv,Yv,Ev = GetXYE(vname,m,array_len)
nsp = m+1
numb = [nvan, nsp, ntc, Ndat, nbin, Imin, Imax, Nb]
reals = [efix, theta[0], rscl, bnorm]
nd,xout,yout,eout,yfit,pfit=resnorm.resnorm(numb,Xv,Yv,Ev,reals,
Xdat,Xb,Yb,wrks,wrkr,lwrk)
if Verbose:
message = ' Fit paras : '+str(pfit[0])+' '+str(pfit[1])
logger.notice(message)
dataX = xout[:nd]
dataX = np.append(dataX,2*xout[nd-1]-xout[nd-2])
yPar1 = np.array([pfit[0]])
yPar2 = np.array([pfit[1]])
CreateWorkspace(OutputWorkspace='Data', DataX=dataX, DataY=yout[:nd], DataE=eout[:nd],
CreateWorkspace(OutputWorkspace='Fit', DataX=dataX, DataY=yfit[:nd], DataE=np.zeros(nd),
yPar1 = np.append(yPar1,pfit[0])
yPar2 = np.append(yPar2,pfit[1])
CreateWorkspace(OutputWorkspace='__datmp', DataX=dataX, DataY=yout[:nd], DataE=eout[:nd],
NSpec=1, UnitX='DeltaE')
ConjoinWorkspaces(InputWorkspace1='Data', InputWorkspace2='__datmp', CheckOverlapping=False)
CreateWorkspace(OutputWorkspace='__f1tmp', DataX=dataX, DataY=yfit[:nd], DataE=np.zeros(nd),
NSpec=1, UnitX='DeltaE')
ConjoinWorkspaces(InputWorkspace1='Fit', InputWorkspace2='__f1tmp', CheckOverlapping=False)
CreateWorkspace(OutputWorkspace=fname+'_ResNorm_Intensity', DataX=xPar, DataY=yPar1, DataE=xPar,
CreateWorkspace(OutputWorkspace=fname+'_ResNorm_Stretch', DataX=xPar, DataY=yPar2, DataE=xPar,
group = fname + '_ResNorm_Intensity,'+ fname + '_ResNorm_Stretch'
GroupWorkspaces(InputWorkspaces=group,OutputWorkspace=fname+'_ResNorm')
GroupWorkspaces(InputWorkspaces='Data,Fit',OutputWorkspace=fname+'_ResNorm_Fit')
par_path = os.path.join(workdir,fname+'_ResNorm.nxs')
SaveNexusProcessed(InputWorkspace=fname+'_ResNorm', Filename=par_path)
fit_path = os.path.join(workdir,fname+'_ResNorm_Fit.nxs')
SaveNexusProcessed(InputWorkspace=fname+'_ResNorm_Fit', Filename=fit_path)
if Verbose:
logger.notice('Parameter file created : ' + par_path)
logger.notice('Fit file created : ' + fit_path)
def ResNormPlot(inputWS,Plot):
if (Plot == 'Intensity' or Plot == 'All'):
iWS = inputWS + '_ResNorm_Intensity'
i_plot=mp.plotSpectrum(iWS,0,False)
if (Plot == 'Stretch' or Plot == 'All'):
sWS = inputWS + '_ResNorm_Stretch'
s_plot=mp.plotSpectrum(sWS,0,False)
if (Plot == 'Fit' or Plot == 'All'):
fWS = inputWS + '_ResNorm_Fit'
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f_plot=mp.plotSpectrum(fWS,0,False)