def predictWithRCFromPDB(pdbFile, refShifts, ringRatio, typeRCDist, atomNames, builtin):
"""
Reads an RNA molecule from PDB file and predict chemical shifts.
# Parameters:
pdbFile (str); the name of the PDB file
refShifts (dict); the reference shifts for each atom to be predicted.
ringRatio (float); A scale parameter to multiply the ring-current contributions by
typeRCDist (String): Type of analysis to perform, 'rc' (ring current) or 'dist' (distances)
# Returns:
shifts (dict) the chemical shifts that were predicted. The reference ppm
value of each atom is also updated with shift
"""
Molecule.removeAll()
pdb = PDBFile()
mol = molio.readPDB(pdbFile)
#pdb.readCoordinates(pdbFile,-1,False, False)
activeStructures = mol.getActiveStructures()
avgOverStructures = False
if not avgOverStructures:
if len(activeStructures) > 0:
repI = super.findRepresentative(mol)
iStruct = repI[0]
else:
iStruct=0
structList=[iStruct]
else:
if len(activeStructures) > 0:
structList = list(activeStructures)
else:
structList=[0]
if builtin:
shifts = rnapred.predictBuiltIn(mol, atomNames, typeRCDist, structList)
else:
if typeRCDist.lower() == 'rc':
shifts = rnapred.predictRCShifts(mol, structList, refShifts, ringRatio, ringTypes)
elif typeRCDist.lower() == 'dist':
alphas = ringRatio
shifts = rnapred.predictDistShifts(mol, rmax, structList, refShifts, alphas)
return mol, shifts
def genRCTrainingMatrix(outFileName, pdbFiles, shiftSources, atomNames, ringMode, typeRCDist):
"""
Generate the training data from a list of pdbFiles and dotBracket values.
Each file is predicted using the attribute method based on a specified
dot-bracket string and the output is appended to the training matrix
# Parameters:
outFileName (str); The output file name. File is deleted if present already.
pdbFiles (list); list of PDB Files to use
shiftSources (list); list of sources for shifts. Either dot-bracket values (vienna string) or bmrb id to use for each pdb file
atomNames (list): list of atom names
ringMode
typeRCDist (String): Type of analysis to perform, 'rc' (ring current) or 'dist' (distances)
# Returns:
_ (None); Training data is written to specified file
"""
try:
os.remove(outFileName)
except:
pass
with open(outFileName,'a') as f1:
for pdbID,shiftSource in zip(pdbFiles,shiftSources):
Molecule.removeAll()
pdbFile = 'pdbfiles/'+pdbID+'.pdb'
if not getPDBFile(pdbID):
print 'skip',pdbFile
continue
print 'train',pdbFile
pdb = PDBFile()
mol = molio.readPDB(pdbFile)
if shiftSource[0]=="." or shiftSource[0]=="(":
rnapred.predictFromSequence(mol,shiftSource)
else:
setRefShiftsFromBMRB(shiftSource, {})
genRCMat(mol,atomNames,f1, ringMode, typeRCDist)