Classes
		builtins.tuple(builtins.object) FileDatum   class FileDatum(builtins.tuple)     FileDatum(name, atomPosArr)   FileDatum(name, atomPosArr)     Method resolution order: FileDatum builtins.tuple builtins.object Methods defined here: __getnewargs__(self) Return self as a plain tuple.  Used by copy and pickle. __repr__(self) Return a nicely formatted representation string _asdict(self) Return a new dict which maps field names to their values. _replace(self, /, **kwds) Return a new FileDatum object replacing specified fields with new values Class methods defined here: _make(iterable) from builtins.type Make a new FileDatum object from a sequence or iterable Static methods defined here: __new__(_cls, name, atomPosArr) Create new instance of FileDatum(name, atomPosArr) Data descriptors defined here: name   Alias for field number 0 atomPosArr   Alias for field number 1 Data and other attributes defined here: __match_args__ = ('name', 'atomPosArr') _field_defaults = {} _fields = ('name', 'atomPosArr') Methods inherited from builtins.tuple: __add__(self, value, /) Return self+value. __contains__(self, key, /) Return key in self. __eq__(self, value, /) Return self==value. __ge__(self, value, /) Return self>=value. __getattribute__(self, name, /) Return getattr(self, name). __getitem__(self, key, /) Return self[key]. __gt__(self, value, /) Return self>value. __hash__(self, /) Return hash(self). __iter__(self, /) Implement iter(self). __le__(self, value, /) Return self<=value. __len__(self, /) Return len(self). __lt__(self, value, /) Return self<value. __mul__(self, value, /) Return self*value. __ne__(self, value, /) Return self!=value. __rmul__(self, value, /) Return value*self. count(self, value, /) Return number of occurrences of value. index(self, value, start=0, stop=9223372036854775807, /) Return first index of value.   Raises ValueError if the value is not present. Class methods inherited from builtins.tuple: __class_getitem__(...) from builtins.type See PEP 585

Functions
		activateLikelyPAs(pot, minLikelihood=0.9, maxLikelihood=100) activateNonviolatedPeakAssigns(pot, violCutoff=0.5) Given a distance violation cutoff,  activate all peakAssigns that are not currently violated and deactivate all peakAssigns that are binCenter(minVal, maxVal, nBins, whichBin) Given a range minVal .. maxVal,  divided into nBins bins  which are numbered 0 .. nBins - 1,  Return the value of the center of bin #whichBin   defend against maxVal == minVal chooseBestFraction(fileData, peaks, completenessPots=[], frac=0.1, violCutoff=0.5, inverseBound=4.0, inverseMethylCorrection=0, completenessWeight=0, useNonviolatedCount=False, verbose=False) Given a list of FileDatum,  check each one's violations of a given set of peaks and return a list of FileDatum corresponding to the top frac. correctShiftOffset(pasdPot, correctTo=True, correctFrom=False, verbose=False, binWidth=0.001, minNumSymmetricPeaks=100, minOffsetToApply=0.015) For correcting proton shifts.    Find all the symmetric, intraresidue peak pairs.    Determine the most common difference between the peak position  on the from proton dimension and the peak position   of the same SA on the to dimension.    If the offset is larger than a cutoff and the number of peaks   used in determining it is larger than a cutoff, apply it to all the   peak locations along the indicated dimension and throw an exception  (to let the calling proc know that peak locations have changed)    If the correction is smaller than the cutoff, do nothing. correctUpBoundsForMethyls(peaks) This isn't necessary.  Could just use the methyl flag on each  shiftAssignment and the methyl correction defined for the inverse restraints in MarvinNOEPotential createExplicitInverseExceptions(pasdPot, fromProtonSolventRange=[], toProtonSolventRange=[], failedFiltersCutoff=9999, diagTol=0.001) initLikelihoods(pot, maxFiltersFailed=0) set previous likelihoods to 0 or 1 based on numFilteredFailed relative to maxFiltersFailed. jointFilter(pots, selection='[protein]', minPeakScore=-1, minExpectedScore=0.08, primarySeqFilter=False, minLikelihood=0.9, maxLikelihood=2.0, writeFiles=False, assignmentThreshold=None, activePAThreshold=None, inactiveAssignmentThreshold=None, deleteNonIntraPAs=False, refStructFilename='', refPDB=None, filenamePrefix='NAME_pass2', **kwargs) Filenames are generated from filenamePrefix by substituting the PASDPot instanceName for the 'NAME' literal, and then appending .exceptions, .peaks or .shiftAssignments for the respective filenames.   assignmentThreshold - if set, delete all peaks which have more peak                       assignments than this value.   inactiveAssignmentThreshold - if set, delete peaks with no active peaks,                               but with more assignments than this value.                                activePAThreshold   - if set, delete peaks with more active peak                       assignments than this value.   deleteNonIntraPAs   - if True, delete all non-intramolecular peak                       assignments if there is an intramolecular peak                       assignment.   minLikelihood       - passed through to saTools.analyzeShiftAssignments maxLikelihood         and peakTools.analyzePeaks.     These additional arguments are passed through to netfilter.netFilter:    knownContacts, printResiduePairScores, passFrac, numIters,    initScoresFrom, minExpectedScore   The above filters are run after the network filter. likelihoodsFromStructs(fileData, peaks, violCutoff=0.5) Given a list of <filename, atomPosArray> pairs of converged structures  and a list of peaks,  use the coords to determine the likelihood of each peakAssignment   Could be replaced with something that would calculate previous likelihood of any pair of ShiftAssignments, whether they're used in a PeakAssignment or not. markGoodPeakAssigns(peaks, cutoff=0.5) set as good all peak assignments which satisfy distance restraints to within cutoff. processStructurePass(pots, inPassName, outPassName, filenames='INPASS_[0-9]*.pdb', combinedFiles=True, aveFilename='INPASS_ave.pdb', refStructFilename=None, violCutoff=0.5, fracConverged=0.1, highLikelihoodCutoff=0.9, noeCompletenessCutoff=0.0, scatterCutoff=999.9, completenessWeight=0.0, useSingleAssignmentBehavior=False, backboneSelStr='name CA C N', heavyatomSelStr='not (PSEUDO or name H*)', outPeakFilenames=None, outSAfilenames=None, outExceptionsFilename=None, verbose=False) Given a list of input pasdPot.PASDPot terms and a list (or glob string)  of structure filenames, generate new PeakAssignment likelihoods. saLikelihoodsFromStructs(fileData, pasdPot, violCutoff, noeCompletenessCutoff, scatterCutoff, inverseBound, inverseMethylCorrection) standardInitMatch(pasdPot, fromProtonRange, toProtonRange, fromHeavyatomRange=[], toHeavyatomRange=[], basePhase=1, refStructFilename='', filenamePrefix='NAME_pass1', peakFilename=None, saFilename=None, exceptionFilename=None, writeFiles=True, writeEachStage=False, allWeakPeaks=False, fromProtonSolventRange=[], toProtonSolventRange=[], fromProtonBroadTol=0.075, toProtonBroadTol=0.075, fromHeavyBroadTol=0.75, toHeavyBroadTol=0.75, fromProtonTightTol=0.02, toProtonTightTol=0.02, fromHeavyTightTol=0.2, toHeavyTightTol=0.2, doStripeCorrection=True, useIndividualTols=False, doCorrectShiftOffset=True, saRemarks='', peakRemarks='')   This will process 2D, 3D and 4D spectra. In order to process spectra   with more than two dimensions, the appropriate from/toHeavyRange   argument must be specified.     filenamePrefix - is used to create file names for peaks, shift                    assignments and inverse exceptions with the extensions                    .peaks, .shiftAssignments, and .exceptions,                    respectively. If present, the literal NAME is replaced                    with pasdPot.instanceName(). The values can also be                    specified on an individual basis using the                    peakFilename, saFilename, or exceptionFilename                    arguments. Setting any of these to the value False                    will disable writing the corresponding file.     allWeakPeaks - if set, treat all peaks as weak - i.e. the associated                  distance range will from smallest possible (minimum                  value in pasd.distanceBins) to largest possible                  (maximum value in pasd.distanceBins).     Returns tuple of  (peakRemarks, saRemarks), strings containing info and analysis of ShiftAssignments, and Peaks, respectively.   Output is written to filenamePrefix+".pasd" if writeFiles="combined". For backwards compatibility, individual file names can be specified using the peakFilename, saFilename exceptionFilename  arguments. writeExceptions(exceptionsFilename, pasdPot, fileAccess='w', tcl=None) writePeaks(peakFilename, pasdPot=None, remarks='', fileAccess='w', tcl=None) writeShiftAssignments(saFilename, pasdPot=None, sas=[], remarks='', fileAccess='w', tcl=None)

Data
		fileSectionHeader = '!PASD section --- '