def post_processing(self):
# group the per-atom density metrics for each dataset together
txt = 'Combining density metric information for each dataset '+\
'together within the damage series'
self.logFile.writeToLog(str = txt)
txt = 'Input pkl files for post processing chosen from input file:'
for file in self.pklFiles:
txt += '\n\t{}'.format(file.replace(self.outDir,""))
self.logFile.writeToLog(str = txt)
# next read in the pdb structure file as list of atom objects
initialPDBlist = PDBtoList(pdbFileName = self.get1stDsetPDB())
# retrieve object lists of atoms for each damage set
ln = '\nReading in pkl files for higher dataset structures...'
self.logFile.writeToLog(str = ln)
dList = [] # dataset list
for pkl_filename in self.pklFiles:
ln = 'Damage file number: {}'.format(len(dList)+1)
self.logFile.writeToLog(str = ln)
PDB_ret = retrieve_objectlist(fileName = pkl_filename,
logFile = self.logFile)
# remove pkl file since no longer needed
remove(pkl_filename)
# add new retrieved damage set list to dList
dList.append(PDB_ret)
pklDir = '/'.join(pkl_filename.split('/')[:-1])+'/'
# remove directory if it is now empty
if listdir(pklDir) == []:
rmdir(pklDir)
# create a list of atom objects with attributes as lists varying over
# dose range, only including atoms present in ALL damage datasets
ln = 'New list of atoms over full dose range calculated...'
self.logFile.writeToLog(str = ln)
combinedAtoms = combinedAtomList(datasetList = dList,
numLigRegDsets = len(dList),
doseList = self.doses,
initialPDBList = initialPDBlist,
outputDir = self.outputDir,
seriesName = self.seriesName,
inclFCmetrics = self.inclFCmets)
combinedAtoms.getMultiDoseAtomList()
# calculate 'average' variant Dloss metrics
combinedAtoms.calcAdditionalMetrics(newMetric = 'average')
# calculate Calpha normalised metrics, if Calpha atoms exist
if self.checkCalphasPresent(atomObjList = combinedAtoms):
for m in ('loss','mean','gain','Bfactor'):
combinedAtoms.calcAdditionalMetrics(metric = m)
self.combinedAtoms = combinedAtoms
def post_processing(self):
self.titleCaption('Post Processing')
print 'Input pkl files for post processing chosen from input file:'
for file in self.pklFiles:
print '\t{}'.format(file)
# next read in the pdb structure file as list of atom objects
print 'Reading in initial pdb file...'
initialPDBlist = PDBtoList(self.where+self.initialPDB,[])
# retrieve object lists of atoms for each damage set
self.fillerLine()
print 'Reading in damaged pkl files...'
dList = [] # dataset list
for pkl_filename in self.pklFiles:
print 'Damage file number: {}\n'.format(len(dList)+1)
PDB_ret = retrieve_objectlist(pkl_filename)
# add new retrieved damage set list to dList
dList.append(PDB_ret)
# create a list of atom objects with attributes as lists varying over
# dose range, only including atoms present in ALL damage datasets
print 'New list of atoms over full dose range calculated...'
combinedAtoms = combinedAtomList(dList,len(dList),self.doses,initialPDBlist,
self.outputDir,True,self.seriesName)
combinedAtoms.getMultiDoseAtomList()
# calculate 'standardised' and 'average' variant Dloss metrics
combinedAtoms.calcStandardisedMetrics('loss')
combinedAtoms.calcAdditionalMetrics('loss','Standard','average')
# write atom numbers and density metrics to simple text files - one for
# each density metric separately
for densMet in combinedAtoms.getDensMetrics():
print 'Writing .txt file for per-atom density metric: {}, normalisation: {}'.format(*densMet)
combinedAtoms.writeMetric2File(self.outputDir,*densMet)
self.combinedAtoms = combinedAtoms
self.summaryStats()
def post_processing(self):
# group the per-atom density metrics for each dataset together
self.logFile.writeToLog(
str='Combining density metric information for each dataset ' +
'together within the damage series')
txt = 'Input pkl files for post processing chosen from input file:'
for file in self.pklFiles:
txt += '\n\t{}'.format(file.replace(self.outDir, ""))
self.logFile.writeToLog(str=txt)
# next read in the pdb structure file as list of atom objects
initialPDBlist = PDBtoList(pdbFileName=self.get1stDsetPDB())
# retrieve object lists of atoms for each damage set
ln = '\nReading in pkl files for higher dataset structures...'
self.logFile.writeToLog(str=ln)
dList = []
for pkl_filename in self.pklFiles:
ln = 'Damage file number: {}'.format(len(dList)+1)
self.logFile.writeToLog(str=ln)
PDB_ret = retrieve_objectlist(
fileName=pkl_filename, logFile=self.logFile)
# remove pkl file since no longer needed
remove(pkl_filename)
# add new retrieved damage set list to dList
dList.append(PDB_ret)
# create a list of atom objects with attributes as lists varying over
# dose range, only including atoms present in ALL damage datasets
self.logFile.writeToLog(
str='New list of atoms over full dose range calculated...')
combinedAtoms = combinedAtomList(
datasetList=dList, numLigRegDsets=len(dList), doseList=self.doses,
initialPDBList=initialPDBlist, outputDir=self.outputDataDir,
seriesName=self.seriesName, inclFCmetrics=self.inclFCmets)
combinedAtoms.getMultiDoseAtomList(logFile=self.logFile)
# calculate 'average' variant Dloss metrics
combinedAtoms.calcAdditionalMetrics(newMetric='average')
# calculate normalised metrics, if suitable atoms exist
if self.normSet != [[]]:
if combinedAtoms.checkSpecificAtomsExist(self.normSet):
metricsOfInterest = ['loss', 'mean', 'gain', 'Bfactor']
if self.inclFCmets:
metricsOfInterest += ['density_weighted_mean_negOnly',
'density_weighted_loss',
'density_weighted_mean']
for m in metricsOfInterest:
combinedAtoms.calcAdditionalMetrics(
metric=m, newMetric='X-normalised',
normalisationSet=self.normSet)
else:
# if there is a problem finding the set of atoms
error(text='Failed to find the specified set of ' +
'atoms to normalise metrics', log=self.logFile)
# save metric data to pkl file
pklDataFile = saveGenericObject(
obj=combinedAtoms, fileName=self.seriesName)
move(pklDataFile, self.pklFileDir + pklDataFile)
self.pklDataFile = self.pklFileDir + pklDataFile
# append the pklfile name to the input RIDL file
inputfile = open(self.RIDLinputFile, 'r')
pklFound = False
for l in inputfile.readlines():
if l.startswith('pklDataFile'):
pklFound = True
break
inputfile.close()
if not pklFound:
inputfile = open(self.RIDLinputFile, 'a')
inputfile.write('\npklDataFile ' + self.pklDataFile)
inputfile.close()
