def Run(self):
## Create lists from config file options
l_saveAs = PythonUtils.makeListFromString(self.saveAs, ',')
## Check the .list files exist
l_listFile = [
self.axisList, self.fitList, self.histoList, self.legendList,
self.textList, self.variableList, self.histFile
]
for file in l_listFile:
PythonUtils.doesFileExist(file)
## Create the tuples from the .list files
t_axisList = PythonUtils.makeTupleFromFile(self.axisList, ',')
t_fitList = PythonUtils.makeTupleFromFile(self.fitList, ',')
t_histoList = PythonUtils.makeTupleFromFile(self.histoList, ',')
t_legendList = PythonUtils.makeTupleFromFile(self.legendList, ',')
t_textList = PythonUtils.makeTupleFromFile(self.textList, ',')
## Math the first titems
l_tuples = [t_fitList, t_histoList, t_legendList, t_textList]
for item in l_tuples:
PythonUtils.firstItemMatching(t_axisList, item)
## Loop over the variable files to get the relevant info
for j in xrange(len(t_axisList)):
f_str, vRebin, vdoNorm, vXMin, vXMax, vFit, vXValue, vYValue = t_fitList[
j]
l_files = []
f = open(self.variableList, 'r')
for file in f:
l_files.append(file.strip())
l_twoD = []
t_legend = []
PythonUtils.doesFileExist(l_files[j])
g = open(l_files[j], 'r')
for vFile in g:
PythonUtils.doesFileExist(vFile.strip())
vFileParser = ConfigParser.SafeConfigParser()
vFileParser.read(vFile.strip())
## Options
vTitle = vFileParser.get('Options', 'title')
vVariable = vFileParser.get('Options', 'variable')
vColour = vFileParser.getint('Options', 'colour')
vMarker = vFileParser.getint('Options', 'marker')
vMarkerSize = vFileParser.getfloat('Options', 'markerSize')
vFitMin = vFileParser.get('Options', 'fitMin')
vFitMax = vFileParser.get('Options', 'fitMax')
## Create l_statInfo
l_statInfo = [
t_histoList[j][1], t_histoList[j][1],
float(vRebin),
int(vdoNorm),
float(vXMin),
float(vXMax), vFitMin, vFitMax
]
getMean = 0
getRMS = 0
getRES = 0
if vXValue == 'MEAN':
getMean = 1
elif vXValue == 'RMS':
getRMS = 1
elif vXValue == 'RESOLUTION':
getRES = 1
else:
getMean = getRMS = getRES = 0
l_xOption = [getMean, getRMS, getRES]
getMean = 0
getRMS = 0
getRES = 0
if vYValue == 'MEAN':
getMean = 1
elif vYValue == 'RMS':
getRMS = 1
elif vYValue == 'RESOLUTION':
getRES = 1
else:
getMean = getRMS = getRES = 0
l_yOption = [getMean, getRMS, getRES]
## Get the list of stats
l_plot = [
ROOTUtils.retrieveHistogram(self.histFile,
t_histoList[j][1], vVariable)
]
l_xValue, l_xErr = ROOTUtils.getHistoStat(
l_plot, l_statInfo, l_xOption, vFit, vVariable)
l_yValue, l_yErr = ROOTUtils.getHistoStat(
l_plot, l_statInfo, l_yOption, vFit, vVariable)
## Get the value we want from the list so we can plot it!
xValue = -1
for stat in l_xValue:
if stat != -1:
xValue = stat
for stat in l_yValue:
if stat != -1:
yValue = stat
## Create a 2D plot and save to a list so can overlay them
twoDPlot = PlottingUtils.createTwoD(t_histoList[j], xValue,
yValue, vMarker,
vMarkerSize, vColour)
l_twoD.append(twoDPlot)
if vTitle:
l_legend = [twoDPlot, vTitle, 'p']
t_legend.append(l_legend)
## Overlay our 2D plots onto one canvas
PlottingUtils.overlayTwoD(l_twoD, t_legend, t_histoList[j],
t_legendList[j], t_textList[j],
t_axisList[j], self.saveDir, l_saveAs)
def Run(self):
## Create lists from config file options
l_saveAs = PythonUtils.makeListFromString(self.saveAs, ',')
## Check the .list files exist
l_listFile = [self.axisList, self.fitList, self.histoList, self.legendList,
self.textList, self.variableList, self.histFile]
for file in l_listFile:
PythonUtils.doesFileExist(file)
## Create the tuples from the .list files
t_axisList = PythonUtils.makeTupleFromFile(self.axisList, ',')
t_fitList = PythonUtils.makeTupleFromFile(self.fitList, ',')
t_histoList = PythonUtils.makeTupleFromFile(self.histoList, ',')
t_legendList = PythonUtils.makeTupleFromFile(self.legendList, ',')
t_textList = PythonUtils.makeTupleFromFile(self.textList, ',')
## Math the first titems
l_tuples = [t_fitList, t_histoList, t_legendList, t_textList]
for item in l_tuples:
PythonUtils.firstItemMatching(t_axisList, item)
## Loop over the variable files to get the relevant info
for j in xrange(len(t_axisList)):
f_str, vRebin, vdoNorm, vXMin, vXMax, vFit, vXValue, vYValue = t_fitList[j]
l_files = []
f = open(self.variableList, 'r')
for file in f:
l_files.append(file.strip())
l_twoD = []
t_legend = []
PythonUtils.doesFileExist(l_files[j])
g = open(l_files[j], 'r')
for vFile in g:
PythonUtils.doesFileExist(vFile.strip())
vFileParser = ConfigParser.SafeConfigParser()
vFileParser.read(vFile.strip())
## Options
vTitle = vFileParser.get('Options','title')
vVariable = vFileParser.get('Options','variable')
vColour = vFileParser.getint('Options','colour')
vMarker = vFileParser.getint('Options','marker')
vMarkerSize = vFileParser.getfloat('Options','markerSize')
vFitMin = vFileParser.get('Options','fitMin')
vFitMax = vFileParser.get('Options','fitMax')
## Create l_statInfo
l_statInfo = [t_histoList[j][1], t_histoList[j][1], float(vRebin), int(vdoNorm),
float(vXMin), float(vXMax), vFitMin, vFitMax]
getMean = 0
getRMS = 0
getRES = 0
if vXValue == 'MEAN':
getMean = 1
elif vXValue == 'RMS':
getRMS = 1
elif vXValue == 'RESOLUTION':
getRES = 1
else:
getMean = getRMS = getRES = 0
l_xOption = [getMean, getRMS, getRES]
getMean = 0
getRMS = 0
getRES = 0
if vYValue == 'MEAN':
getMean = 1
elif vYValue == 'RMS':
getRMS = 1
elif vYValue == 'RESOLUTION':
getRES = 1
else:
getMean = getRMS = getRES = 0
l_yOption = [getMean, getRMS, getRES]
## Get the list of stats
l_plot = [ROOTUtils.retrieveHistogram(self.histFile, t_histoList[j][1], vVariable)]
l_xValue, l_xErr = ROOTUtils.getHistoStat(l_plot, l_statInfo, l_xOption, vFit, vVariable)
l_yValue, l_yErr = ROOTUtils.getHistoStat(l_plot, l_statInfo, l_yOption, vFit, vVariable)
## Get the value we want from the list so we can plot it!
xValue = -1
for stat in l_xValue:
if stat != -1:
xValue = stat
for stat in l_yValue:
if stat != -1:
yValue = stat
## Create a 2D plot and save to a list so can overlay them
twoDPlot = PlottingUtils.createTwoD(t_histoList[j], xValue, yValue,
vMarker, vMarkerSize, vColour)
l_twoD.append(twoDPlot)
if vTitle:
l_legend = [twoDPlot, vTitle, 'p']
t_legend.append(l_legend)
## Overlay our 2D plots onto one canvas
PlottingUtils.overlayTwoD(l_twoD, t_legend, t_histoList[j], t_legendList[j],
t_textList[j], t_axisList[j], self.saveDir, l_saveAs)
def Run(self):
## Check the files in the config file exist
l_file = [self.histFile, self.correctionList,
self.histoList, self.fittingList]
for file in l_file:
PythonUtils.doesFileExist(file)
## Add the trailing slash to the end of latexDir
if not self.latexDir.endswith('/'):
latexDir = self.latexDir + '/'
PythonUtils.doesDirExist(latexDir)
else:
latexDir = self.latexDir
## Make tuples from the list files
t_histoList = PythonUtils.makeTupleFromFile(self.histoList, ',')
t_fittingList = PythonUtils.makeTupleFromFile(self.fittingList, ',')
## Loop over the files in correctionsList each one is a new run
l_cFiles = []
f = open(self.correctionList, 'r')
for file in f:
if file.startswith('#'):
continue
else:
l_cFiles.append(file.strip())
for i in xrange(len(l_cFiles)):
ld_mean = []
ld_rms = []
ld_res = []
l_getOption = [int(t_fittingList[i][2]), int(t_fittingList[i][3]), int(t_fittingList[i][4])]
## Check the file in the list exists
PythonUtils.doesFileExist(l_cFiles[i])
t_corrList = PythonUtils.makeTupleFromFile(l_cFiles[i], ',')
d_meanResRMS = {}
tagType = ''
for j in xrange(len(t_corrList)):
h_location = t_corrList[j][1] + t_histoList[i][1]
t_histoList[i].append(t_corrList[j][3])
t_histoList[i].append(t_corrList[j][4])
l_hist = [t_histoList[i][0], t_histoList[i][1], t_histoList[i][2],
t_histoList[i][3], t_histoList[i][4], t_histoList[i][5],
t_corrList[j][3], t_corrList[j][4]]
pTVBin = t_histoList[i][6]
tagType = t_histoList[i][7]
l_h = [ROOTUtils.retrieveHistogram(self.histFile,
h_location, t_corrList[j][2])]
d_meanResRMS[t_corrList[j][0]] = ROOTUtils.getHistoStat(l_h, l_hist, l_getOption,
t_fittingList[i][5], t_corrList[j][0])
## We now have all the info to calculate the stats from the plots!
d_mean = {}
d_RMS = {}
d_res = {}
getMean, getRMS, getResolution = l_getOption
compareTo = t_fittingList[i][1]
fit = t_fittingList[i][5]
l_corrName = []
for k, v in d_meanResRMS.iteritems():
l_corrName.append(k)
if getMean:
d_mean[k] = [v[0][0], v[1][0]]
if getRMS:
d_RMS[k] = [v[0][1], v[1][1]]
if getResolution:
d_res[k] = [v[0][2], v[1][2]]
ld_mean.append([t_histoList[i][0], d_mean])
ld_rms.append([t_histoList[i][0], d_RMS])
ld_res.append([t_histoList[i][0], d_res])
t_mRr = []
if getMean:
t_mRr.append(PythonUtils.rankByValue(ld_mean, compareTo,
fit + ' Mean'))
if getRMS:
t_mRr.append(PythonUtils.rankByValue(ld_rms, compareTo,
fit + ' RMS'))
if getResolution:
t_mRr.append(PythonUtils.rankByValue(ld_res, compareTo,
fit + ' Resolution'))
if self.doLatex:
latex = self.writeLatex(t_mRr, l_corrName, pTVBin, t_histoList[i][0], latexDir, getMean, getRMS, getResolution)
PythonUtils.runLatex(latex, latexDir)
