def main(argv):
inputFile = None
if len(argv) < 1:
Usage()
exit(1)
inputFile = argv[0]
printBoundPKL = False
if len(argv) >= 2:
printBoundPKL = True
if inputFile is None:
print 'ERROR: Please provide an input file'
exit(1)
if not os.path.isfile(inputFile):
print 'ERROR: The input file does not exist: ', inputFile
exit(1)
content = DistanceUtils.LoadRawDistProbFile(inputFile)
targetName, sequence, predictedDistProbMatrix, predictedContactProbMatrix = content[:
4]
""" Skip this step since in version 3, we use an unbiased deep model
if labelWeight is not None:
fixedProb = dict()
for apt in predictedDistProb.keys():
#print 'shapes: ', predictedDistProb[apt].shape, np.array(labelWeight[apt]).shape, np.array(labelDistribution[apt]).shape
fixedProb[apt] = DistanceUtils.FixDistProb( predictedDistProb[apt], labelWeight[apt], labelDistribution[apt])
else:
## in this case, the probability values in predictedDistProb are already corrected
fixedProb = predictedDistProb
fixedProb = predictedDistProb
if printProbMatrix:
probFileName = targetName + probFileSuffix
fh = open(probFileName, 'wb')
cPickle.dump(fixedProb, fh, protocol = cPickle.HIGHEST_PROTOCOL)
fh.close()
"""
bounds = EstimateDistanceBounds(predictedDistProbMatrix)
## output Cb-Cb bound in text format
if bounds.has_key('CbCb'):
boundFileName = targetName + '.bound.txt'
boundMatrix = bounds['CbCb']
SaveBoundInListFormat(targetName, sequence, boundMatrix, boundFileName)
if not printBoundPKL:
return
boundFileName = targetName + '.bound.pkl'
with open(boundFileName, 'wb') as fh:
cPickle.dump((bounds, targetName, sequence),
fh,
protocol=cPickle.HIGHEST_PROTOCOL)
def main(argv):
inputFile = None
targetName = None
labelNames = config.allAtomPairNames + config.allOrientationNames
potentialFileSuffix = 'pkl'
minPotential = -30.0
maxPotential = 30.0
UseWeight4Orientation = True
UseWeight4Distance = True
## the largest dist cutoff
rc = 18
alpha4DFIRE = 1.61
alpha4DFIREstr = '1.61'
rgScale4DOPE = 1.
## reference
reference = 'DFIRE'
##
UseRef4Orientation = True
## refFile for SimuRW
refFile = None
#savefolder = os.getcwd()
savefile=""
if len(argv) < 1:
Usage()
exit(1)
try:
opts, args = getopt.getopt(argv,"a:w:r:l:u:f:s:o",["labelNames=", "useWeight=", "refState=", "minPotential=", "maxPotential=", "refFile=", "savefile=", "noRef4Orientation="])
#print opts, args
except getopt.GetoptError:
Usage()
exit(1)
if len(args) != 1:
Usage()
exit(1)
inputFile = args[0]
for opt, arg in opts:
if opt in ("-a", "--labelNames"):
labelNames = config.ParseLabelNames(arg)
elif opt in ("-w", "--useWeight"):
scheme = np.int32(arg)
UseWeight4Orientation = (2 & scheme)>0
UseWeight4Distance = (1 & scheme)>0
elif opt in ("-r", "--refState"):
fields = arg.split('+')
reference = fields[0].upper()
if reference not in allRefTypes:
print 'ERROR: allowed reference types: ', allRefTypes
exit(1)
if len(fields) > 1:
if fields[1].isdigit():
rc = np.int32(fields[1])
else:
rc = np.float32(fields[1])
if reference == 'DFIRE':
if len(fields) > 2:
alpha4DFIREstr = fields[2]
alpha4DFIRE = np.float32(fields[2])
elif reference == 'DOPE':
if len(fields) > 2:
rgScale4DOPE = np.float32(fields[2])
elif reference == 'SimuRW'.upper():
#rc = np.float32(fields[1])
print 'Using SimuRW potential'
else:
print 'ERROR: unsupported reference format: ', arg
exit(1)
elif opt in ("-f", "--refFile"):
refFile = arg
if not os.path.isfile(refFile):
print 'the provided file for reference state is not valid: ', refFile
exit(1)
elif opt in ("-o", "--noRef4Orientation"):
UseRef4Orientation = False
elif opt in ("-s", "--savefile"):
savefile = arg
elif opt in ("-l", "--minPotential"):
minPotential = np.float32(arg)
elif opt in ("-u", "--maxPotential"):
maxPotential = np.float32(arg)
else:
Usage()
exit(1)
if inputFile is None:
print 'ERROR: Please provide an input file'
exit(1)
if not os.path.isfile(inputFile):
print 'ERROR: The input file does not exist: ', inputFile
exit(1)
if reference in allRefTypesWithFiles and refFile is None:
print 'ERROR: The file for user-sepcified reference state is empty'
exit(1)
if reference == 'DFIRE':
if alpha4DFIRE > 10:
## take a random value between 1.57 and 1.63
alpha4DFIRE=random.uniform(1.57, 1.63)
print 'alpha for DFIRE potential is ', alpha4DFIRE
if alpha4DFIRE<1.55 or alpha4DFIRE>1.75:
print 'ERROR: alpha4DFIRE shall be between 1.55 and 1.75'
exit(1)
if reference == 'DOPE':
print 'rgScale for DOPE potential is', rgScale4DOPE
if rgScale4DOPE > 1.2 or rgScale4DOPE <0.8:
print 'ERROR: rgScale4DOPE shall be between 0.8 and 1.2'
exit(1)
if UseWeight4Distance:
print 'Use weight for distance potential'
if UseWeight4Orientation:
print 'Use weight for orientation potential'
if not UseRef4Orientation:
print 'Do not use reference for orientation'
content = DistanceUtils.LoadRawDistProbFile(inputFile)
assert len(content) >=6
name, sequence, predictedProb, predictedContactProb, labelWeight, labelDistribution = content[:6]
assert labelWeight is not None, "labelWeight shall not be empty"
predData = (predictedProb, labelWeight, labelDistribution)
targetName = os.path.basename(inputFile).split('.')[0]
print 'Generating potential for ', targetName, 'with the following labels: ', labelNames
filenames = [ targetName, 'pairPotential']
if reference == 'DFIRE':
pairPotential, cutoffs, validProb, distPotential, oriPotential = CalcDistOriPotential(predData, labelNames, distPotType='DFIRE', param4Potential=alpha4DFIRE, largestDistance=rc, useWeight4Dist=UseWeight4Distance, useRef4Ori=UseRef4Orientation, useWeight4Ori=UseWeight4Orientation, minPotential=minPotential, maxPotential=maxPotential)
filenames.extend([reference, str(rc), alpha4DFIREstr])
elif reference == 'DOPE':
pairPotential, cutoffs, validProb, distPotential, oriPotential = CalcDistOriPotential(predData, labelNames, distPotType='DOPE', param4Potential=rgScale4DOPE, largestDistance=rc, useWeight4Dist=UseWeight4Distance, useRef4Ori=UseRef4Orientation, useWeight4Ori=UseWeight4Orientation, minPotential=minPotential, maxPotential=maxPotential)
filenames.extend([reference, str(rc), str(rgScale4DOPE)])
else:
print 'ERROR: unimplemented potential type: ', reference
exit(1)
if bool(oriPotential) and UseRef4Orientation:
filenames.append('Ref4O')
wStr=None
if (bool(distPotential) and UseWeight4Distance) and (bool(oriPotential) and UseWeight4Orientation):
wStr = 'Wt4OD'
elif bool(oriPotential) and UseWeight4Orientation:
wStr = 'Wt4O'
elif bool(distPotential) and UseWeight4Distance:
wStr = 'Wt4D'
if wStr is not None:
filenames.append(wStr)
filenames.append('pkl')
if savefile == "":
savefile = '.'.join(filenames)
## save the result
with open(savefile, 'wb') as fh:
cPickle.dump((name, sequence, pairPotential, cutoffs, validProb), fh, protocol=cPickle.HIGHEST_PROTOCOL)
def main(argv):
inputFile = None
targetName = None
labelNames = ['CbCb']
potentialFileSuffix = 'pkl'
minPotential = -30.0
maxPotential = 30.0
minSeqSep = 3
minSeqSepStr='3'
## the largest dist cutoff
rc = 18
alpha4DFIRE = 1.61
rgScale4DOPE = 1.
## reference
reference = 'DFIRE'
## refFile
refFile = None
try:
opts, args = getopt.getopt(argv,"i:a:r:l:u:s:f:tn",["input=", "atomPairType=", "refState=", "minPotential=", "maxPotential=", "minSeqSep=", "refFile=", "textFormat=", "nonZero="])
print opts, args
except getopt.GetoptError:
Usage()
exit(1)
if len(opts) < 1:
Usage()
exit(1)
for opt, arg in opts:
if opt in ("-i", "--input"):
inputFile = arg
elif opt in ("-a", "--atomPairType"):
labelNames = config.ParseLabelNames(arg)
elif opt in ("-r", "--refState"):
fields = arg.split('+')
reference = fields[0].upper()
if reference not in allRefTypes:
print 'allowed reference types: ', allRefTypes
exit(1)
if len(fields) > 1:
if reference == 'DFIRE':
rc = np.float32(fields[1])
if len(fields) > 2:
alpha4DFIRE = np.float32(fields[2])
elif reference == 'DOPE':
rc = np.float32(fields[1])
if len(fields) > 2:
rgScale4DOPE = np.float32(fields[2])
elif reference == 'SimuRW'.upper():
rc = np.float32(fields[1])
else:
print 'WARNING: unsupported reference format: ', arg
elif opt in ("-f", "--refFile"):
refFile = arg
if not os.path.isfile(refFile):
print 'the provided file for reference state is not valid: ', refFile
exit(1)
elif opt in ("-l", "--minPotential"):
minPotential = np.float32(arg)
elif opt in ("-u", "--maxPotential"):
maxPotential = np.float32(arg)
elif opt in ("-s", "--minSeqSep"):
minSeqSep = np.int32(arg)
minSeqSepStr = arg
if minSeqSep < 1:
print 'ERROR: minSeqSep shall be at least 1'
exit(1)
elif opt in ("-t", "--textFormat"):
potentialFileSuffix = '.txt'
elif opt in ("-n", "--nonZero"):
resetFlag = False
else:
Usage()
exit(1)
if inputFile is None:
print 'Please provide an input file'
exit(1)
if not os.path.isfile(inputFile):
print 'The input file does not exist: ', inputFile
exit(1)
if reference in allRefTypesWithFiles and refFile is None:
print 'The file for user-sepcified reference state is empty'
exit(1)
targetName = os.path.basename(inputFile).split('.')[0]
content = DistanceUtils.LoadRawDistProbFile(inputFile)
assert len(content) >=6
name, sequence, predictedDistProb, predictedContactProb, labelWeight, labelDistribution = content[:6]
assert labelWeight is not None, "labelWeight shall not be empty"
## if needed, add code to here the predicted dist probability
filenames = [ targetName, 'distPotential']
if reference == 'DFIRE':
potential = CalcPotentialByDFIRE(predictedDistProb, alpha=alpha4DFIRE, largestDistance=rc, minPotential=minPotential, maxPotential=maxPotential)
filenames.extend([reference, str(rc), str(alpha4DFIRE), potentialFileSuffix])
elif reference == 'DOPE':
potential = CalcPotentialByDOPE(predictedDistProb, largestDistance=rc, rgScale=rgScale4DOPE, minPotential=minPotential, maxPotential=maxPotential)
filenames.extend([reference, str(rc), str(rgScale4DOPE), potentialFileSuffix])
elif reference == 'SimuRW'.upper():
potential = CalcPotentialBySimuRW(predictedDistProb, refFile, largestDistance=rc, minPotential=minPotential, maxPotential=maxPotential)
filenames.extend([reference, str(rc), potentialFileSuffix])
else:
print 'ERROR: unimplemented reference state: ', reference
exit(1)
potentialFileName = '.'.join(filenames)
## save to PKL file
if potentialFileName.endswith('.pkl'):
fh = open(potentialFileName, 'wb')
potential_new = dict()
distCutoffs = dict()
for response, pot in potential.iteritems():
labelName = config.Response2LabelName(response)
if labelName not in set(labelNames):
continue
potential_new[response] = pot
distCutoffs[response] = config.GetCutoffs(response)
cPickle.dump((name, sequence, potential_new, distCutoffs), fh, protocol=cPickle.HIGHEST_PROTOCOL)
fh.close()
return
## save to text file
potentialFileName = targetName + '.distPotential.s' + minSeqSepStr + potentialFileSuffix
fh = open(potentialFileName, 'w')
fh.write('#TARGET\t' + targetName + '\n')
fh.write('#SEQ\t' + sequence + '\n')
fh.write('#DistanceBinBoundaries\t' + "Please check config.py" + '\n')
for response, pot in potential.iteritems():
labelName, labelType, subType = config.ParseResponse(response)
if labelName not in set(labelNames):
continue
size = pot.shape
for i in xrange(size[0]):
rawPotStrs = []
for j in xrange(i+ minSeqSep, size[1]):
atom1, atom2 = config.SelectAtomPair(sequence, i, j, labelName)
y = pot[i, j]
rawPotStr = ' '.join(['AtomPair', atom1.upper(), str(i+1), atom2.upper(), str(j+1), subType] + [ "{:.4f}".format(e) for e in y ] )
rawPotStrs.append(rawPotStr)
if len(rawPotStrs) >0:
fh.write('\n'.join(rawPotStrs) + '\n')
fh.close()