def calcAdditionalMetrics(self,metric,normType,newMetric):
# calculate the Calpha weights for each dataset (see CalphaWeight class for details)
# for metric "metric" (loss, gain, mean etc.)
# 'newMetric' takes values ('Calpha','netChange','linreg','subtract1')
options = ['Calpha','netChange','linreg','subtract1','average']
if newMetric == 'Calpha':
print 'Calculating Calpha weights at each dataset...'
CAweights = CalphaWeight(self.atomList)
CAweights.calculateWeights(metric)
# loop over all atoms in list and calculate additional metrics for each atom in atomList
counter = 0
numAtoms = self.getNumAtoms()
for atom in self.atomList:
counter += 1
progress(counter, numAtoms, suffix='') # unessential loading bar add-in
if newMetric == 'Calpha':
atom.CalphaWeightedDensChange(CAweights,metric)
elif newMetric == 'linreg':
atom.calcLinReg(self.numLigRegDatasets,'Standard',metric)
elif newMetric == 'netChange':
atom.calcNetChangeMetric('Standard')
elif newMetric == 'subtract1':
atom.calcFirstDatasetSubtractedMetric('Standard',metric)
elif newMetric == 'average':
atom.calcAvMetric(normType,metric)
else:
print 'new metric type not recognised.. choose from: {}'.format(options)
return
def processAtomList(self): # process the input multiPDB list of atom objects to create new # list of atom objects from processedAtom class processedList = [] # calculate the Calpha weights for each dataset (see CalphaWeight class for details) print 'Calculating Calpha weights at each dataset...' CAweights = CalphaWeight(self.unprocessedAtomList) CAweights.calculateWeights() # loop over all atoms in list and determine new atom info (defined by processedAtom class) print 'Creating new list of atom objects within class processedAtom...' counter = 0 num_atoms = len(self.unprocessedAtomList) for oldAtom in self.unprocessedAtomList: counter += 1 progress(counter, num_atoms, suffix='') #unessential loading bar add-in newAtom = processedAtom() newAtom.cloneInfo(oldAtom) newAtom.CalphaWeightedDensChange(CAweights) newAtom.calculateAdditionalMetrics() newAtom.calculateLinReg(self.numDatasets,'Standard') # newAtom.calculateLinReg(self.numDatasets,'Calpha normalised') processedList.append(newAtom) self.processedAtomList = processedList
