class AssignMentTransferTab(object): '''the tab in the GUI where assignments can be transferred in bulk to the ccpn analysis project. A difference is made between two types of assignments: 1) spin systems to residues, which also implies resonanceSets to atomSets. 2) resonances to peak dimensions. The user is able to configure which assignments should be transferred to the project. Attributes: guiParent: gui object this tab is part of. frame: the frame in which this element lives. dataModel(src.cython.malandro.DataModel): dataModel object describing the assignment proposed by the algorithm. selectedSolution (int): The index of the solution/run that is used asa the template to make the assignments. resonanceToDimension (bool): True if resonances should be assigned to peak dimensions. False if not. spinSystemToResidue (bool): True if spin system to residue assignment should be carried out. minScore (float): The minimal score of a spin system assignment to a residue to be allowed to transfer this assignment to the project intra (bool): True if intra-residual peaks should be assigned. sequential (bool): True if sequential peaks should be assigned. noDiagonal (bool): If True, purely diagonal peaks are ignored during the transfer of assignments. allSpectra (bool): If True, all spectra will be assigned. If False, one specified spectrum will be assigned. spectrum (src.cython.malandro.Spectrum): The spectrum that should be assigned. ''' def __init__(self, parent, frame): '''Init. args: parent: the guiElement that this tab is part of. frame: the frame this part of the GUI lives in. ''' self.guiParent = parent self.frame = frame # Buttons and fields, # will be set in body(): self.peaksCheckButton = None self.residuesCheckButton = None self.intraCheckButton = None self.sequentialCheckButton = None self.noDiagonalCheckButton = None self.spinSystemTypeSelect = None self.minScoreEntry = None self.solutionNumberEntry = None self.spectrumSelect = None self.spectraPullDown = None self.assignedResidueStrategySelect = None self.transferButton = None # Settings that determine how assignments # are transferred to the analysis project: self.minScore = 80.0 self.dataModel = None self.spectrum = None self.selectedSolution = 1 self.body() self.resonanceToDimension = True self.spinSystemToResidue = True self.intra = True self.sequential = True self.noDiagonal = True self.allSpectra = True self.spinSystemType = 0 self.strategy = 0 def body(self): '''Describes the body of this tab. It consists out of a number of radio buttons, check buttons and number entries that allow the user to indicate which assignments should be transferred. ''' # self.frame.expandColumn(0) self.frame.expandGrid(8, 0) self.frame.expandGrid(8, 1) typeOfAssignmentFrame = LabelFrame( self.frame, text='type of assignment') typeOfAssignmentFrame.grid(row=0, column=0, sticky='nesw') # typeOfAssignmentFrame.expandGrid(0,5) peakSelectionFrame = LabelFrame( self.frame, text='which peaks to assign') peakSelectionFrame.grid(row=0, column=1, sticky='nesw', rowspan=2) spinSystemSelectionFrame = LabelFrame(self.frame, text='Which spin-systems to use') spinSystemSelectionFrame.grid(row=2, column=0, sticky='nesw') tipText = 'What to do when a residue has already a spin system assigned to it.' assignedResidueFrame = LabelFrame(self.frame, text='if residue already has spin-system', tipText=tipText) assignedResidueFrame.grid(row=2, column=1, sticky='nesw') spectrumSelectionFrame = LabelFrame(self.frame, text='spectra') spectrumSelectionFrame.grid(row=1, column=0, sticky='nesw') row = 0 Label(typeOfAssignmentFrame, text='Resonances to Peak Dimensions', grid=(row, 0)) self.peaksCheckButton = CheckButton(typeOfAssignmentFrame, selected=True, grid=(row, 1)) row += 1 Label(typeOfAssignmentFrame, text='SpinSystems to Residues', grid=(row, 0)) self.residuesCheckButton = CheckButton( typeOfAssignmentFrame, selected=True, grid=(row, 1)) row = 0 Label(peakSelectionFrame, text='Intra-Residual', grid=(row, 0)) self.intraCheckButton = CheckButton( peakSelectionFrame, selected=True, grid=(row, 1)) row += 1 Label(peakSelectionFrame, text='Sequential', grid=(row, 0)) self.sequentialCheckButton = CheckButton( peakSelectionFrame, selected=True, grid=(row, 1)) row += 1 Label(peakSelectionFrame, text='Do not assign diagonal peaks', grid=(row, 0)) self.noDiagonalCheckButton = CheckButton( peakSelectionFrame, selected=True, grid=(row, 1)) entries = ['Only assigned spin systems', 'All that have a score of at least: ', 'User Defined', 'Solution number:'] tipTexts = ['Only assign resonances of spin systems that already have a sequential assignment for the assignment of peak dimensions. Spin system to residue assignment is not relevant in this case.', 'Assign all spin systems that have a score of at least a given percentage. 50% or lower is not possible, because than spin systems might have to be assigned to more than 1 residue, which is impossible.', "As defined in the lower row of buttons in the 'results' tab.", 'One of the single solutions of the annealing.'] self.spinSystemTypeSelect = RadioButtons(spinSystemSelectionFrame, entries=entries, grid=(0, 0), select_callback=None, direction=VERTICAL, gridSpan=(4, 1), tipTexts=tipTexts) tipText = 'The minimal amount of colabelling the different nuclei should have in order to still give rise to a peak.' self.minScoreEntry = FloatEntry(spinSystemSelectionFrame, grid=(1, 1), width=7, text=str(self.minScore), returnCallback=self.changeMinScore, tipText=tipText) self.minScoreEntry.bind('<Leave>', self.changeMinScore, '+') self.solutionNumberEntry = IntEntry(spinSystemSelectionFrame, grid=(3, 1), width=7, text=1, returnCallback=self.solutionUpdate, tipText=tipText) self.solutionNumberEntry.bind('<Leave>', self.solutionUpdate, '+') #self.solutionPullDown = PulldownList(spinSystemSelectionFrame, None, grid=(3,1), sticky='w') entries = ['all spectra', 'only:'] tipTexts = ['Assign peaks in all the spectra that where selected before the annealing ran.', 'Only assign peaks in one particular spectrum. You can of course repeat this multiple times for different spectra.'] self.spectrumSelect = RadioButtons(spectrumSelectionFrame, entries=entries, grid=(0, 0), select_callback=None, direction=VERTICAL, gridSpan=(2, 1), tipTexts=tipTexts) self.spectraPullDown = PulldownList(spectrumSelectionFrame, self.changeSpectrum, grid=(1, 1), sticky='w') entries = ['skip this residue', 'de-assign old spin system from residue', 'assign, but never merge', 'warn to merge'] tipTexts = ["Don't assign the new spin system to the residue. The residue is not skipped when the old spin system does not contain any resonances", "De-assign old spin system from residue, unless the old spin system is a spin system without any resonances.", "Don't merge any spin systems, merging can be performed later if nescesary in the Resonance --> SpinSystems window.", "Ask to merge individually for each spin system, this might result in clicking on a lot of popups."] self.assignedResidueStrategySelect = RadioButtons(assignedResidueFrame, entries=entries, grid=(0, 0), select_callback=None, direction=VERTICAL, gridSpan=(2, 1), tipTexts=tipTexts) texts = ['Transfer Assignments'] commands = [self.transferAssignments] self.transferButton = ButtonList( self.frame, commands=commands, texts=texts) self.transferButton.grid(row=5, column=0, sticky='nsew', columnspan=2) def update(self): '''Update the nescesary elements in the tab. Is called when the algorithm has produced possible assignments. The only thing that has to be updated in practice in this tab is the pulldown with spectra. ''' self.dataModel = self.guiParent.connector.results self.updateSpectra() def setDataModel(self, dataModel): '''Here the dataModel, which is the dataModel containing the suggested assignments body the algorithm, can be set. ''' self.dataModel = dataModel self.update() def updateSpectra(self, *opt): '''Updates the spectra shown in the spectra pulldown. These are only the spectra that were used by the algorithm. All other spectra in the project are not relevant since for those no simulated peaks have been matched to real peaks. ''' if not self.dataModel: return spectrum = self.spectrum spectra = self.dataModel.getSpectra() if spectra: names = [spectrum.name for spectrum in spectra] index = 0 if self.spectrum not in spectra: self.spectrum = spectra[0] else: index = spectra.index(self.spectrum) self.spectraPullDown.setup(names, spectra, index) def changeSpectrum(self, spectrum): '''Select a spectum to be assigned.''' self.spectrum = spectrum def solutionUpdate(self, event=None, value=None): '''Select a solution. A solution is a one to one mapping of spin systems to residues produced by one run of the algorithm. args: event: event object, this is one of the values the number entry calls his callback function with. value: the index of the solution/run. ''' if not self.dataModel: return Nsolutions = len(self.dataModel.chain.residues[0].solutions) if value is None: value = self.solutionNumberEntry.get() if value == self.selectedSolution: return else: self.selectedSolution = value if value < 1: self.solutionNumberEntry.set(1) self.selectedSolution = 1 elif value > Nsolutions: self.selectedSolution = Nsolutions self.solutionNumberEntry.set(self.selectedSolution) else: self.solutionNumberEntry.set(self.selectedSolution) def fetchOptions(self): '''Fetches user set options from the gui in one go and stores them in their corresponding instance variables. ''' self.resonanceToDimension = self.peaksCheckButton.get() self.spinSystemToResidue = self.residuesCheckButton.get() self.intra = self.intraCheckButton.get() self.sequential = self.sequentialCheckButton.get() self.noDiagonal = self.noDiagonalCheckButton.get() self.spinSystemType = self.spinSystemTypeSelect.getIndex() self.strategy = ['skip', 'remove', 'noMerge', None][ self.assignedResidueStrategySelect.getIndex()] self.allSpectra = [True, False][self.spectrumSelect.getIndex()] def changeMinScore(self, event=None): '''Set the minimal score for which a spin system to residue assignment gets transferred to the ccpn analysis project. ''' newMinScore = self.minScoreEntry.get() if self.minScore != newMinScore: if newMinScore <= 50.0: self.minScore = 51.0 self.minScoreEntry.set(51.0) elif newMinScore > 100.0: self.minScore = 100.0 self.minScoreEntry.set(100.0) else: self.minScore = newMinScore def transferAssignments(self): '''Transfer assignments to project depending on the settings from the GUI. ''' self.fetchOptions() if not self.dataModel or (not self.resonanceToDimension and not self.spinSystemToResidue): return strategy = self.strategy lookupSpinSystem = [self.getAssignedSpinSystem, self.getBestScoringSpinSystem, self.getUserDefinedSpinSystem, self.getSelectedSolutionSpinSystem][self.spinSystemType] residues = self.dataModel.chain.residues spinSystemSequence = [lookupSpinSystem(res) for res in residues] ccpnSpinSystems = [] ccpnResidues = [] # if self.spinSystemType == 0 it means that it for sure already # assigned like this if self.spinSystemToResidue and not self.spinSystemType == 0: for spinSys, res in zip(spinSystemSequence, residues): if spinSys and res: ccpnSpinSystems.append(spinSys.getCcpnResonanceGroup()) ccpnResidues.append(res.getCcpnResidue()) assignSpinSystemstoResidues(ccpnSpinSystems, ccpnResidues, strategy=strategy, guiParent=self.guiParent) if self.resonanceToDimension: allSpectra = self.allSpectra if self.intra: for residue, spinSystem in zip(residues, spinSystemSequence): if not spinSystem: continue intraLink = residue.getIntraLink(spinSystem) for pl in intraLink.getPeakLinks(): peak = pl.getPeak() if not allSpectra and peak.getSpectrum() is not self.spectrum: continue if not peak: continue resonances = pl.getResonances() if self.noDiagonal and len(set(resonances)) < len(resonances): continue for resonance, dimension in zip(resonances, peak.getDimensions()): ccpnResonance = resonance.getCcpnResonance() ccpnDimension = dimension.getCcpnDimension() assignResToDim(ccpnDimension, ccpnResonance) if self.sequential: for residue, spinSystemA, spinSystemB in zip(residues, spinSystemSequence, spinSystemSequence[1:]): if not spinSystemA or not spinSystemB: continue link = residue.getLink(spinSystemA, spinSystemB) for pl in link.getPeakLinks(): peak = pl.getPeak() if not allSpectra and peak.getSpectrum() is not self.spectrum: continue if not peak: continue resonances = pl.getResonances() if self.noDiagonal and len(set(resonances)) < len(resonances): continue for resonance, dimension in zip(resonances, peak.getDimensions()): ccpnResonance = resonance.getCcpnResonance() ccpnDimension = dimension.getCcpnDimension() assignResToDim(ccpnDimension, ccpnResonance) self.guiParent.resultsTab.update() def getAssignedSpinSystem(self, residue): '''Get the spinSystem that is assigned in the project to a residue. args: residue (src.cython.malandro.Residue) return: spinSystem (src.cython.malandro.SpinSystem) ''' ccpCode = residue.ccpCode seqCode = residue.getSeqCode() spinSystems = self.dataModel.getSpinSystems()[ccpCode] ccpnResidue = residue.getCcpnResidue() if ccpnResidue: assignedResonanceGroups = ccpnResidue.getResonanceGroups() if len(assignedResonanceGroups) > 1: print 'There is more than one spin system assigned to residue %s, did not know which one to use to assign peaks. Therefor this residue is skipped.' % (seqCode) return assignedResonanceGroup = ccpnResidue.findFirstResonanceGroup() if assignedResonanceGroup: for spinSystem in spinSystems: if spinSystem.getSerial() == assignedResonanceGroup.serial: # Just checking to make sure, analysis project could # have changed if not self.skipResidue(residue, spinSystem): return spinSystem def getBestScoringSpinSystem(self, residue): '''Get the spinSystem that scores the highest, i.e. is assigned in most of the runs to the given residue. args: residue (src.cython.malandro.Residue) return: spinSystem (src.cython.malandro.SpinSystem) ''' solutions = residue.solutions weigth = 1.0 / len(solutions) score, bestSpinSystem = max([(solutions.count(solution) * weigth * 100.0, solution) for solution in solutions]) if score >= self.minScore and not bestSpinSystem.getIsJoker() and not self.skipResidue(residue, bestSpinSystem): return bestSpinSystem return None def getUserDefinedSpinSystem(self, residue): '''Get the spinSystem that is defined by the user (probably in the resultsTab) as the correct assignment of the given residue. args: residue (src.cython.malandro.Residue) return: spinSystem (src.cython.malandro.SpinSystem) ''' userDefinedSpinSystem = residue.userDefinedSolution if userDefinedSpinSystem and not userDefinedSpinSystem.getIsJoker() and not self.skipResidue(residue, userDefinedSpinSystem): return userDefinedSpinSystem return None def getSelectedSolutionSpinSystem(self, residue): '''I a solution corresponding to one specific run of the algorithm is defined, return which spinSystem in that run got assigned to the given residue. args: residue (src.cython.malandro.Residue) return: spinSystem (src.cython.malandro.SpinSystem) ''' solutions = residue.solutions spinSystem = solutions[self.selectedSolution - 1] if not spinSystem.getIsJoker() and not self.skipResidue(residue, spinSystem): return spinSystem return None def skipResidue(self, residue, spinSystem): '''One strategy is to skip all residues that already have a spin system assignment. If that is the case determine whether to skip the given residue. args: residue (src.cython.malandro.Residue) spinSystem (src.cython.malandro.SpinSystem) return: boolean, True if residue should be skipped. ''' if self.strategy == 0: assignedGroups = residue.getCcpnResidue().getResonanceGroups() assignedSerials = set([spinSys.serial for spinSys in assignedGroups]) if assignedSerials and spinSystem.getSerial() not in assignedSerials: return True return False
class EditPeakFindParamsPopup(BasePopup): """ ** Peak Settings and Non-Interactive Peak Finding ** The purpose of this dialog is to allow the user to select settings for finding and integrating peaks, and also to be able to find peaks in an arbitrary region that is specified in a table rather than via a spectrum window. ** Find Parameters tab ** This can be used to specify how peak finding works. First of all, you can search for just positive peaks, just negative peaks or both, and the default is that it is just positive peaks. However, this is further filtered by what the contour levels are. If there are no positive contour levels for a given spectrum then positive peaks are not found even if this dialog says they can be, and similarly if there are no negative contour levels for a given spectrum then negative peaks are not found even if this dialog says they can be. The peak finding algorithm looks for local extrema (maximum for positive peaks and minima for negative peaks). But on a grid there are various ways to define what you mean by an extremum. Suppose you are trying to determine if point p is a maximum (similar considerations apply for minimum). You would want the intensity at all nearby points to be less than or equal to the intensity at p. You can just check points that are just +- one point from p in each dimension, or you can also check "diagonal" points. For example, if you are looking at point p = (x, y) in 2D, then the former would mean checking the four points (x-1, y), (x+1, y) (x, y-1) and (x, y+1), whereas for the latter you would also have to check (x-1, y-1), (x-1, y+1), (x+1, y-1) and (x+1, y+1). In N dimensions the "diagonal" method involves checking 3^N-1 points whereas the "non-diagonal" method involves checking only 2N points. In general the "non-diagonal" method is probably the one to use, and it is the default. Peaks are only found above (for positive peaks) or below (for negative peaks) some threshold. By default this is determined by the contour level for the spectrum. For positive peaks the threshold is the minimum positive contour level, and for negative peaks the threshold is the maximum negative contour level. However these levels can be scaled up (or down) using the "Scale relative to contour levels" option (default value 1). For example, if you have drawn the contour levels low to show a bit of noise, but do not want the noise picked as peaks, then you could select a scale of 2 (or whatever) to increase the threshold. The "Exclusion buffer around peaks" is so that in crowded regions you do not get too many peaks near one location. By default the exclusion buffer is 1 point in each dimension, but this can be increased to make the algorithm find fewer peaks. By default the peak finding only looks at the orthogonal region that is displayed in the given window where peak finding is taking place. Sometimes it looks like a peak should be found because in x, y you can see an extremum, but unless it is also an extremum in the orthogonal dimensions it is not picked. You can widen out the points being examined in the orthogonal dimensions by using the "Extra thickness in orthogonal dims" option, which is specified in points. The "Minimum drop factor" is by what factor the intensity needs to drop from its extreme value for there to be considered to be a peak. This could help remove sinc wiggle peaks, for example. The default is that the drop factor is 0, which in effect means that there is no condition. The "Volume method" is what is used to estimate the volume of peaks that are found. The default is "box sum", which just looks at a fixed size box around the peak centre and sums the intensities in that. The size of the box is set in the table in the Spectrum Widths tab. The "truncated box sum" is the same as "box sum" except that the summing stops in a given direction when (if) the intensities start increasing. The "parabolic" fit fits a quadratic equation in each dimension to the intensity at the peak centre and ad +- 1 points and then uses the equivalent Gaussian fit to estimate the volume. ** Spectrum Widths ** This can be used to specify minimum linewidths (in Hz) for there to be considered a peak to exist in the peak finding algorithm. It is also where the Boxwidth for each dimension in each spectrum is specified. ** Diagonal Exclusions ** This can be used to exclude peaks from being found in regions near the diagonal (so in homonuclear experiments). The exclusion region is specified in ppm and is independent of spectrum. ** Region Peak Find ** This can be used to find peaks non-interactively (so not having to control shift drag inside a spectrum window). The region being analysed is specified in the table. There are two types of conditions that can be specified, "include" for regions that should be included and "exclude" for regions that should be excluded. The regions are specified in ppm. The "Whole Region" button will set the selected row in the table to be the entire fundamental region of the spectrum. The "Add Region" button adds an extra row to the table, and the "Delete Region" button removes the selected row. The "Adjust Params" button goes to the Find Parameters tab. The "Find Peaks!" button does the peak finding. """ def __init__(self, parent, *args, **kw): self.spectrum = None BasePopup.__init__(self, parent=parent, title='Peak : Peak Finding', **kw) def body(self, guiFrame): self.geometry('600x350') guiFrame.expandGrid(0, 0) tipTexts = ['', '', '', ''] options = [ 'Find Parameters', 'Spectrum Widths', 'Diagonal Exclusions', 'Region Peak Find' ] tabbedFrame = TabbedFrame(guiFrame, options=options, grid=(0, 0)) frameA, frameB, frameC, frameD = tabbedFrame.frames self.tabbedFrame = tabbedFrame # Find Params frameA.expandGrid(2, 0) row = 0 label = LabelFrame(frameA, text='Extrema to search for:', grid=(row, 0), gridSpan=(1, 2)) label.expandGrid(0, 1) entries = ['positive and negative', 'positive only', 'negative only'] tipTexts = [ 'Sets whether peak picking within spectra find intensity maxima, minima or both maxima and minima', ] self.extrema_buttons = RadioButtons(label, entries=entries, select_callback=self.apply, direction='horizontal', grid=(0, 0), tipTexts=tipTexts) row += 1 label = LabelFrame(frameA, text='Nearby points to check:', grid=(row, 0), gridSpan=(1, 2)) label.expandGrid(None, 1) entries = ['+-1 in at most one dim', '+-1 allowed in any dim'] tipTexts = [ 'Sets how permissive the peak picking in when searching for intensity extrema; by adding extra points to the selected search region', ] self.adjacent_buttons = RadioButtons(label, entries=entries, select_callback=self.apply, direction='horizontal', grid=(0, 0), tipTexts=tipTexts) row += 1 labelFrame = LabelFrame(frameA, text='Other parameters:', grid=(row, 0), gridSpan=(1, 2)) labelFrame.expandGrid(5, 2) frow = 0 label = Label(labelFrame, text='Scale relative to contour levels:', grid=(frow, 0), sticky='e') tipText = 'Threshold above which peaks are picked, relative to the lowest displayed contour; 1.0 means picking exactly what is visible' self.scale_entry = FloatEntry(labelFrame, grid=(frow, 1), tipText=tipText, returnCallback=self.apply, width=10) self.scale_entry.bind('<Leave>', self.apply, '+') frow += 1 label = Label(labelFrame, text='Exclusion buffer around peaks (in points):', grid=(frow, 0), sticky='e') tipText = 'The size of the no-pick region, in data points, around existing picked peaks; eliminates duplicate picking' self.buffer_entry = IntEntry(labelFrame, returnCallback=self.apply, grid=(frow, 1), width=10, tipText=tipText) self.buffer_entry.bind('<Leave>', self.apply, '+') frow += 1 label = Label(labelFrame, text='Extra thickness in orthogonal dims (in points):', grid=(frow, 0), sticky='e') tipText = 'Sets whether to consider any additional planes (Z dimension) when calculating peak volume integrals' self.thickness_entry = IntEntry(labelFrame, returnCallback=self.apply, width=10, grid=(frow, 1), tipText=tipText) self.thickness_entry.bind('<Leave>', self.apply, '+') frow += 1 label = Label(labelFrame, text='Minimum drop factor (0.0-1.0):', grid=(frow, 0), sticky='e') tipText = '' self.drop_entry = FloatEntry(labelFrame, returnCallback=self.apply, width=10, grid=(frow, 1), tipText=tipText) self.drop_entry.bind('<Leave>', self.apply, '+') frow += 1 label = Label(labelFrame, text='Volume method:', grid=(frow, 0), sticky='e') tipText = 'Selects which method to use to calculate peak volume integrals when peaks are picked; box sizes are specified in "Spectrum Widths"' self.method_menu = PulldownList(labelFrame, texts=PeakBasic.PEAK_VOLUME_METHODS, grid=(frow, 1), callback=self.apply, tipText=tipText) # Spectrum widths frameB.expandGrid(1, 1) label = Label(frameB, text='Spectrum: ') label.grid(row=0, column=0, sticky='e') tipText = 'The spectrum which determines the widths being shown' self.expt_spectrum = PulldownList(frameB, tipText=tipText, callback=self.setSpectrumProperties) self.expt_spectrum.grid(row=0, column=1, sticky='w') self.editLinewidthEntry = FloatEntry(self, text='', returnCallback=self.setLinewidth, width=10) self.editBoxwidthEntry = FloatEntry(self, text='', returnCallback=self.setBoxwidth, width=10) tipTexts = [ 'The number of the spectrum dimension to which the settings apply', 'The nuclear isotope measures in the spectrum dimension', 'The smallest value for the linewidth of a peak for it to be picked', 'The size of the spectrum region to perform the volume integral over' ] headingList = [ 'Dimension', 'Isotope', 'Minimum Linewidth (Hz)', 'Boxwidth' ] editSetCallbacks = [None, None, self.setLinewidth, self.setBoxwidth] editGetCallbacks = [None, None, self.getLinewidth, self.getBoxwidth] editWidgets = [ None, None, self.editLinewidthEntry, self.editBoxwidthEntry ] self.spectrumMatrix = ScrolledMatrix(frameB, initialRows=6, editSetCallbacks=editSetCallbacks, editGetCallbacks=editGetCallbacks, editWidgets=editWidgets, headingList=headingList, callback=self.selectCell, tipTexts=tipTexts) self.spectrumMatrix.grid(row=1, column=0, columnspan=2, sticky='nsew') # Diagonal Exclusions frameC.expandGrid(0, 0) tipTexts = [ 'The isotope as measures on the axis of a spectrum window', 'The distance from the homonuclear diagonal line within which no peak picking can occur' ] self.exclusionEntry = FloatEntry(self, text='', returnCallback=self.setExclusion, width=10) headingList = ['Isotope', 'Diagonal Exclusion (ppm)'] editSetCallbacks = [None, self.setExclusion] editGetCallbacks = [None, self.getExclusion] editWidgets = [None, self.exclusionEntry] self.isotopeMatrix = ScrolledMatrix(frameC, editSetCallbacks=editSetCallbacks, editGetCallbacks=editGetCallbacks, editWidgets=editWidgets, headingList=headingList, grid=(0, 0), tipTexts=tipTexts) # Region peak find self.regionFindPeakList = None self.regionCondition = None self.regionConditions = [] self.regionCol = 1 row = 0 label = Label(frameD, text='Peak List: ', grid=(0, 0)) tipText = 'Selects which peak list to perform region-wide peak picking for' self.regionPeakListPulldown = PulldownList( frameD, callback=self.changeRegionPeakList, grid=(0, 1), tipText=tipText) row += 1 frameD.expandGrid(row, 1) self.regionEntry = FloatEntry(self, text='', returnCallback=self.setRegion, width=10) self.conditionMenu = PulldownList(self, texts=('include', 'exclude'), callback=self.setCondition) tipTexts = [ 'Whether to include or exclude the states region from region-wide peak picking', ] headingList = ['Condition'] editSetCallbacks = [None] editGetCallbacks = [None] editWidgets = [self.conditionMenu] self.regionFindMatrix = ScrolledMatrix( frameD, headingList=headingList, callback=self.selectRegionCell, editWidgets=editWidgets, editGetCallbacks=editGetCallbacks, editSetCallbacks=editSetCallbacks, grid=(row, 0), gridSpan=(1, 2)) row += 1 tipTexts = [ 'Sets the currently selected region row to cover the whole spectrum', 'Add a new region row, which may them be set for exclusion or inclusion when peak picking large areas', 'Remove the selected region specification', 'Go to the panel for setting the parameters that control how peaks extrema are picked', 'Using the stated regions and parameters, perform region-wide peak picking' ] texts = [ 'Whole Region', 'Add Region', 'Delete Region', 'Adjust Params', 'Find Peaks!' ] commands = [ self.wholeRegion, self.addCondition, self.deleteCondition, self.adjustParams, self.regionFindPeaks ] buttons = ButtonList(frameD, texts=texts, commands=commands, grid=(row, 0), gridSpan=(1, 2), tipTexts=tipTexts) buttons.buttons[4].config(bg='#B0FFB0') utilButtons = UtilityButtonList(tabbedFrame.sideFrame, grid=(0, 0), helpUrl=self.help_url, sticky='e') self.dataDim = None self.setParamsEntries() self.updateSpectrum() self.setIsotopeProperties() self.updateRegionPeakLists() self.administerNotifiers(self.registerNotify) def administerNotifiers(self, notifyFunc): # Many more needed here, esp on the AnalysisProject prams for func in ('__init__', 'delete', 'setName'): notifyFunc(self.updateRegionPeakLists, 'ccp.nmr.Nmr.DataSource', func) notifyFunc(self.updateRegionPeakLists, 'ccp.nmr.Nmr.Experiment', func) for func in ('__init__', 'delete'): notifyFunc(self.updateRegionPeakLists, 'ccp.nmr.Nmr.PeakList', func) for clazz in ('Experiment', 'DataSource'): for func in ('__init__', 'delete', 'setName'): notifyFunc(self.updateSpectrumTable, 'ccp.nmr.Nmr.%s' % clazz, func) for func in ('setPeakFindBoxWidth', 'setPeakFindMinLineWidth'): notifyFunc(self.updateSpectrumTable, 'ccpnmr.Analysis.AnalysisDataDim', func) def destroy(self): self.administerNotifiers(self.unregisterNotify) BasePopup.destroy(self) def updateSpectrum(self, spectrum=None): if not spectrum: spectrum = self.spectrum spectra = self.parent.getSpectra() if spectra: if spectrum not in spectra: spectrum = spectra[0] index = spectra.index(spectrum) names = ['%s:%s' % (x.experiment.name, x.name) for x in spectra] else: index = 0 names = [] self.expt_spectrum.setup(names, spectra, index) self.setSpectrumProperties(spectrum) def updateNotifier(self, *extra): self.updateSpectrum() def setLinewidth(self, *event): value = self.editLinewidthEntry.get() if value is not None: PeakFindParams.setPeakFindMinLinewidth(self.dataDim, value) self.setSpectrumProperties(self.dataDim.dataSource) def getLinewidth(self, dataDim): if dataDim: self.editLinewidthEntry.set( PeakFindParams.getPeakFindMinLinewidth(self.dataDim)) def setBoxwidth(self, *event): value = self.editBoxwidthEntry.get() if value is not None: PeakFindParams.setPeakFindBoxwidth(self.dataDim, value) self.setSpectrumProperties(self.dataDim.dataSource) def getBoxwidth(self, dataDim): if dataDim: self.editBoxwidthEntry.set( PeakFindParams.getPeakFindBoxwidth(self.dataDim)) def selectCell(self, object, row, col): self.dataDim = object def setExclusion(self, *extra): isotope = self.isotopeMatrix.currentObject if not isotope: return value = self.exclusionEntry.get() if value is not None: setIsotopeExclusion(isotope, value) self.setIsotopeProperties() def getExclusion(self, isotope): value = getIsotopeExclusion(isotope) self.exclusionEntry.set(value) def setParamsEntries(self): project = self.project params = PeakFindParams.getPeakFindParams(project) self.scale_entry.set(params['scale']) self.buffer_entry.set(params['buffer']) self.thickness_entry.set(params['thickness']) self.drop_entry.set(params['drop']) volumeMethod = params['volumeMethod'] if volumeMethod == 'parabolic fit': volumeMethod = PeakBasic.PEAK_VOLUME_METHODS[0] self.method_menu.set(params['volumeMethod']) if (params['nonadjacent']): n = 1 else: n = 0 self.adjacent_buttons.setIndex(n) have_high = params['haveHigh'] have_low = params['haveLow'] if (have_high and have_low): n = 0 elif (have_high): n = 1 else: n = 2 self.extrema_buttons.setIndex(n) def apply(self, *extra): params = {} params['scale'] = self.scale_entry.get() params['buffer'] = self.buffer_entry.get() params['thickness'] = self.thickness_entry.get() params['drop'] = self.drop_entry.get() params['volumeMethod'] = self.method_menu.getText() n = self.adjacent_buttons.getIndex() if (n == 0): nonadjacent = False else: nonadjacent = True params['nonadjacent'] = nonadjacent n = self.extrema_buttons.getIndex() if (n == 0): have_high = True have_low = True elif (n == 1): have_high = True have_low = False elif (n == 2): have_high = False have_low = True params['haveHigh'] = have_high params['haveLow'] = have_low project = self.project try: PeakFindParams.setPeakFindParams(project, params) except Implementation.ApiError, e: showError('Parameter error', e.error_msg, parent=self)
class AssignMentTransferTab(object): '''the tab in the GUI where assignments can be transferred in bulk to the ccpn analysis project. A difference is made between two types of assignments: 1) spin systems to residues, which also implies resonanceSets to atomSets. 2) resonances to peak dimensions. The user is able to configure which assignments should be transferred to the project. Attributes: guiParent: gui object this tab is part of. frame: the frame in which this element lives. dataModel(src.cython.malandro.DataModel): dataModel object describing the assignment proposed by the algorithm. selectedSolution (int): The index of the solution/run that is used asa the template to make the assignments. resonanceToDimension (bool): True if resonances should be assigned to peak dimensions. False if not. spinSystemToResidue (bool): True if spin system to residue assignment should be carried out. minScore (float): The minimal score of a spin system assignment to a residue to be allowed to transfer this assignment to the project intra (bool): True if intra-residual peaks should be assigned. sequential (bool): True if sequential peaks should be assigned. noDiagonal (bool): If True, purely diagonal peaks are ignored during the transfer of assignments. allSpectra (bool): If True, all spectra will be assigned. If False, one specified spectrum will be assigned. spectrum (src.cython.malandro.Spectrum): The spectrum that should be assigned. ''' def __init__(self, parent, frame): '''Init. args: parent: the guiElement that this tab is part of. frame: the frame this part of the GUI lives in. ''' self.guiParent = parent self.frame = frame # Buttons and fields, # will be set in body(): self.peaksCheckButton = None self.residuesCheckButton = None self.intraCheckButton = None self.sequentialCheckButton = None self.noDiagonalCheckButton = None self.spinSystemTypeSelect = None self.minScoreEntry = None self.solutionNumberEntry = None self.spectrumSelect = None self.spectraPullDown = None self.assignedResidueStrategySelect = None self.transferButton = None # Settings that determine how assignments # are transferred to the analysis project: self.minScore = 80.0 self.dataModel = None self.spectrum = None self.selectedSolution = 1 self.body() self.resonanceToDimension = True self.spinSystemToResidue = True self.intra = True self.sequential = True self.noDiagonal = True self.allSpectra = True self.spinSystemType = 0 self.strategy = 0 def body(self): '''Describes the body of this tab. It consists out of a number of radio buttons, check buttons and number entries that allow the user to indicate which assignments should be transferred. ''' # self.frame.expandColumn(0) self.frame.expandGrid(8, 0) self.frame.expandGrid(8, 1) typeOfAssignmentFrame = LabelFrame(self.frame, text='type of assignment') typeOfAssignmentFrame.grid(row=0, column=0, sticky='nesw') # typeOfAssignmentFrame.expandGrid(0,5) peakSelectionFrame = LabelFrame(self.frame, text='which peaks to assign') peakSelectionFrame.grid(row=0, column=1, sticky='nesw', rowspan=2) spinSystemSelectionFrame = LabelFrame(self.frame, text='Which spin-systems to use') spinSystemSelectionFrame.grid(row=2, column=0, sticky='nesw') tipText = 'What to do when a residue has already a spin system assigned to it.' assignedResidueFrame = LabelFrame( self.frame, text='if residue already has spin-system', tipText=tipText) assignedResidueFrame.grid(row=2, column=1, sticky='nesw') spectrumSelectionFrame = LabelFrame(self.frame, text='spectra') spectrumSelectionFrame.grid(row=1, column=0, sticky='nesw') row = 0 Label(typeOfAssignmentFrame, text='Resonances to Peak Dimensions', grid=(row, 0)) self.peaksCheckButton = CheckButton(typeOfAssignmentFrame, selected=True, grid=(row, 1)) row += 1 Label(typeOfAssignmentFrame, text='SpinSystems to Residues', grid=(row, 0)) self.residuesCheckButton = CheckButton(typeOfAssignmentFrame, selected=True, grid=(row, 1)) row = 0 Label(peakSelectionFrame, text='Intra-Residual', grid=(row, 0)) self.intraCheckButton = CheckButton(peakSelectionFrame, selected=True, grid=(row, 1)) row += 1 Label(peakSelectionFrame, text='Sequential', grid=(row, 0)) self.sequentialCheckButton = CheckButton(peakSelectionFrame, selected=True, grid=(row, 1)) row += 1 Label(peakSelectionFrame, text='Do not assign diagonal peaks', grid=(row, 0)) self.noDiagonalCheckButton = CheckButton(peakSelectionFrame, selected=True, grid=(row, 1)) entries = [ 'Only assigned spin systems', 'All that have a score of at least: ', 'User Defined', 'Solution number:' ] tipTexts = [ 'Only assign resonances of spin systems that already have a sequential assignment for the assignment of peak dimensions. Spin system to residue assignment is not relevant in this case.', 'Assign all spin systems that have a score of at least a given percentage. 50% or lower is not possible, because than spin systems might have to be assigned to more than 1 residue, which is impossible.', "As defined in the lower row of buttons in the 'results' tab.", 'One of the single solutions of the annealing.' ] self.spinSystemTypeSelect = RadioButtons(spinSystemSelectionFrame, entries=entries, grid=(0, 0), select_callback=None, direction=VERTICAL, gridSpan=(4, 1), tipTexts=tipTexts) tipText = 'The minimal amount of colabelling the different nuclei should have in order to still give rise to a peak.' self.minScoreEntry = FloatEntry(spinSystemSelectionFrame, grid=(1, 1), width=7, text=str(self.minScore), returnCallback=self.changeMinScore, tipText=tipText) self.minScoreEntry.bind('<Leave>', self.changeMinScore, '+') self.solutionNumberEntry = IntEntry(spinSystemSelectionFrame, grid=(3, 1), width=7, text=1, returnCallback=self.solutionUpdate, tipText=tipText) self.solutionNumberEntry.bind('<Leave>', self.solutionUpdate, '+') #self.solutionPullDown = PulldownList(spinSystemSelectionFrame, None, grid=(3,1), sticky='w') entries = ['all spectra', 'only:'] tipTexts = [ 'Assign peaks in all the spectra that where selected before the annealing ran.', 'Only assign peaks in one particular spectrum. You can of course repeat this multiple times for different spectra.' ] self.spectrumSelect = RadioButtons(spectrumSelectionFrame, entries=entries, grid=(0, 0), select_callback=None, direction=VERTICAL, gridSpan=(2, 1), tipTexts=tipTexts) self.spectraPullDown = PulldownList(spectrumSelectionFrame, self.changeSpectrum, grid=(1, 1), sticky='w') entries = [ 'skip this residue', 'de-assign old spin system from residue', 'assign, but never merge', 'warn to merge' ] tipTexts = [ "Don't assign the new spin system to the residue. The residue is not skipped when the old spin system does not contain any resonances", "De-assign old spin system from residue, unless the old spin system is a spin system without any resonances.", "Don't merge any spin systems, merging can be performed later if nescesary in the Resonance --> SpinSystems window.", "Ask to merge individually for each spin system, this might result in clicking on a lot of popups." ] self.assignedResidueStrategySelect = RadioButtons(assignedResidueFrame, entries=entries, grid=(0, 0), select_callback=None, direction=VERTICAL, gridSpan=(2, 1), tipTexts=tipTexts) texts = ['Transfer Assignments'] commands = [self.transferAssignments] self.transferButton = ButtonList(self.frame, commands=commands, texts=texts) self.transferButton.grid(row=5, column=0, sticky='nsew', columnspan=2) def update(self): '''Update the nescesary elements in the tab. Is called when the algorithm has produced possible assignments. The only thing that has to be updated in practice in this tab is the pulldown with spectra. ''' self.dataModel = self.guiParent.connector.results self.updateSpectra() def setDataModel(self, dataModel): '''Here the dataModel, which is the dataModel containing the suggested assignments body the algorithm, can be set. ''' self.dataModel = dataModel self.update() def updateSpectra(self, *opt): '''Updates the spectra shown in the spectra pulldown. These are only the spectra that were used by the algorithm. All other spectra in the project are not relevant since for those no simulated peaks have been matched to real peaks. ''' if not self.dataModel: return spectrum = self.spectrum spectra = self.dataModel.getSpectra() if spectra: names = [spectrum.name for spectrum in spectra] index = 0 if self.spectrum not in spectra: self.spectrum = spectra[0] else: index = spectra.index(self.spectrum) self.spectraPullDown.setup(names, spectra, index) def changeSpectrum(self, spectrum): '''Select a spectum to be assigned.''' self.spectrum = spectrum def solutionUpdate(self, event=None, value=None): '''Select a solution. A solution is a one to one mapping of spin systems to residues produced by one run of the algorithm. args: event: event object, this is one of the values the number entry calls his callback function with. value: the index of the solution/run. ''' if not self.dataModel: return Nsolutions = len(self.dataModel.chain.residues[0].solutions) if value is None: value = self.solutionNumberEntry.get() if value == self.selectedSolution: return else: self.selectedSolution = value if value < 1: self.solutionNumberEntry.set(1) self.selectedSolution = 1 elif value > Nsolutions: self.selectedSolution = Nsolutions self.solutionNumberEntry.set(self.selectedSolution) else: self.solutionNumberEntry.set(self.selectedSolution) def fetchOptions(self): '''Fetches user set options from the gui in one go and stores them in their corresponding instance variables. ''' self.resonanceToDimension = self.peaksCheckButton.get() self.spinSystemToResidue = self.residuesCheckButton.get() self.intra = self.intraCheckButton.get() self.sequential = self.sequentialCheckButton.get() self.noDiagonal = self.noDiagonalCheckButton.get() self.spinSystemType = self.spinSystemTypeSelect.getIndex() self.strategy = ['skip', 'remove', 'noMerge', None][self.assignedResidueStrategySelect.getIndex()] self.allSpectra = [True, False][self.spectrumSelect.getIndex()] def changeMinScore(self, event=None): '''Set the minimal score for which a spin system to residue assignment gets transferred to the ccpn analysis project. ''' newMinScore = self.minScoreEntry.get() if self.minScore != newMinScore: if newMinScore <= 50.0: self.minScore = 51.0 self.minScoreEntry.set(51.0) elif newMinScore > 100.0: self.minScore = 100.0 self.minScoreEntry.set(100.0) else: self.minScore = newMinScore def transferAssignments(self): '''Transfer assignments to project depending on the settings from the GUI. ''' self.fetchOptions() if not self.dataModel or (not self.resonanceToDimension and not self.spinSystemToResidue): return strategy = self.strategy lookupSpinSystem = [ self.getAssignedSpinSystem, self.getBestScoringSpinSystem, self.getUserDefinedSpinSystem, self.getSelectedSolutionSpinSystem ][self.spinSystemType] residues = self.dataModel.chain.residues spinSystemSequence = [lookupSpinSystem(res) for res in residues] ccpnSpinSystems = [] ccpnResidues = [] # if self.spinSystemType == 0 it means that it for sure already # assigned like this if self.spinSystemToResidue and not self.spinSystemType == 0: for spinSys, res in zip(spinSystemSequence, residues): if spinSys and res: ccpnSpinSystems.append(spinSys.getCcpnResonanceGroup()) ccpnResidues.append(res.getCcpnResidue()) assignSpinSystemstoResidues(ccpnSpinSystems, ccpnResidues, strategy=strategy, guiParent=self.guiParent) if self.resonanceToDimension: allSpectra = self.allSpectra if self.intra: for residue, spinSystem in zip(residues, spinSystemSequence): if not spinSystem: continue intraLink = residue.getIntraLink(spinSystem) for pl in intraLink.getPeakLinks(): peak = pl.getPeak() if not allSpectra and peak.getSpectrum( ) is not self.spectrum: continue if not peak: continue resonances = pl.getResonances() if self.noDiagonal and len( set(resonances)) < len(resonances): continue for resonance, dimension in zip( resonances, peak.getDimensions()): ccpnResonance = resonance.getCcpnResonance() ccpnDimension = dimension.getCcpnDimension() assignResToDim(ccpnDimension, ccpnResonance) if self.sequential: for residue, spinSystemA, spinSystemB in zip( residues, spinSystemSequence, spinSystemSequence[1:]): if not spinSystemA or not spinSystemB: continue link = residue.getLink(spinSystemA, spinSystemB) for pl in link.getPeakLinks(): peak = pl.getPeak() if not allSpectra and peak.getSpectrum( ) is not self.spectrum: continue if not peak: continue resonances = pl.getResonances() if self.noDiagonal and len( set(resonances)) < len(resonances): continue for resonance, dimension in zip( resonances, peak.getDimensions()): ccpnResonance = resonance.getCcpnResonance() ccpnDimension = dimension.getCcpnDimension() assignResToDim(ccpnDimension, ccpnResonance) self.guiParent.resultsTab.update() def getAssignedSpinSystem(self, residue): '''Get the spinSystem that is assigned in the project to a residue. args: residue (src.cython.malandro.Residue) return: spinSystem (src.cython.malandro.SpinSystem) ''' ccpCode = residue.ccpCode seqCode = residue.getSeqCode() spinSystems = self.dataModel.getSpinSystems()[ccpCode] ccpnResidue = residue.getCcpnResidue() if ccpnResidue: assignedResonanceGroups = ccpnResidue.getResonanceGroups() if len(assignedResonanceGroups) > 1: print 'There is more than one spin system assigned to residue %s, did not know which one to use to assign peaks. Therefor this residue is skipped.' % ( seqCode) return assignedResonanceGroup = ccpnResidue.findFirstResonanceGroup() if assignedResonanceGroup: for spinSystem in spinSystems: if spinSystem.getSerial() == assignedResonanceGroup.serial: # Just checking to make sure, analysis project could # have changed if not self.skipResidue(residue, spinSystem): return spinSystem def getBestScoringSpinSystem(self, residue): '''Get the spinSystem that scores the highest, i.e. is assigned in most of the runs to the given residue. args: residue (src.cython.malandro.Residue) return: spinSystem (src.cython.malandro.SpinSystem) ''' solutions = residue.solutions weigth = 1.0 / len(solutions) score, bestSpinSystem = max([ (solutions.count(solution) * weigth * 100.0, solution) for solution in solutions ]) if score >= self.minScore and not bestSpinSystem.getIsJoker( ) and not self.skipResidue(residue, bestSpinSystem): return bestSpinSystem return None def getUserDefinedSpinSystem(self, residue): '''Get the spinSystem that is defined by the user (probably in the resultsTab) as the correct assignment of the given residue. args: residue (src.cython.malandro.Residue) return: spinSystem (src.cython.malandro.SpinSystem) ''' userDefinedSpinSystem = residue.userDefinedSolution if userDefinedSpinSystem and not userDefinedSpinSystem.getIsJoker( ) and not self.skipResidue(residue, userDefinedSpinSystem): return userDefinedSpinSystem return None def getSelectedSolutionSpinSystem(self, residue): '''I a solution corresponding to one specific run of the algorithm is defined, return which spinSystem in that run got assigned to the given residue. args: residue (src.cython.malandro.Residue) return: spinSystem (src.cython.malandro.SpinSystem) ''' solutions = residue.solutions spinSystem = solutions[self.selectedSolution - 1] if not spinSystem.getIsJoker() and not self.skipResidue( residue, spinSystem): return spinSystem return None def skipResidue(self, residue, spinSystem): '''One strategy is to skip all residues that already have a spin system assignment. If that is the case determine whether to skip the given residue. args: residue (src.cython.malandro.Residue) spinSystem (src.cython.malandro.SpinSystem) return: boolean, True if residue should be skipped. ''' if self.strategy == 0: assignedGroups = residue.getCcpnResidue().getResonanceGroups() assignedSerials = set( [spinSys.serial for spinSys in assignedGroups]) if assignedSerials and spinSystem.getSerial( ) not in assignedSerials: return True return False
class MeccanoPopup(BasePopup): def __init__(self, parent, project, *args, **kw): self.alignMedium = None self.chain = None self.constraint = None self.constraintSet = None self.molSystem = None self.project = project self.run = None self.shiftList = None self.tensor = None BasePopup.__init__(self, parent=parent, title='MECCANO', *args, **kw) self.curateNotifiers(self.registerNotify) def body(self, guiFrame): guiFrame.grid_columnconfigure(0, weight=1) guiFrame.grid_rowconfigure(0, weight=1) options = ['Parameters','Restraints','Alignment Media & Tensors','About Meccano'] tabbedFrame = TabbedFrame(guiFrame, options=options) tabbedFrame.grid(row=0, column=0, sticky='nsew') frameA, frameB, frameC, frameD = tabbedFrame.frames frameA.grid_columnconfigure(1, weight=1) frameA.grid_rowconfigure(13, weight=1) frameB.grid_columnconfigure(1, weight=1) frameB.grid_rowconfigure(1, weight=1) frameC.grid_columnconfigure(0, weight=1) frameC.grid_rowconfigure(1, weight=1) frameD.grid_columnconfigure(0, weight=1) frameD.grid_rowconfigure(0, weight=1) texts = ['Run MECCANO!'] commands = [self.runMeccano] bottomButtons = createDismissHelpButtonList(guiFrame, texts=texts, commands=commands, expands=True) bottomButtons.grid(row=1, column=0, sticky='ew') if not Meccano: bottomButtons.buttons[0].disable() # Parameters row = 0 label = Label(frameA, text='Calculation Run:') label.grid(row=row,column=0,sticky='w') self.runPulldown = PulldownList(frameA, callback=self.selectRun) self.runPulldown.grid(row=row,column=1,sticky='w') row += 1 label = Label(frameA, text='Shift List (for CO):') label.grid(row=row,column=0,sticky='w') self.shiftListPulldown = PulldownList(frameA, callback=self.selectShiftList) self.shiftListPulldown.grid(row=row,column=1,sticky='w') row += 1 label = Label(frameA, text='Keep Copy of Used Shifts:') label.grid(row=row,column=0,sticky='w') self.toggleCopyShifts = CheckButton(frameA) self.toggleCopyShifts.grid(row=row,column=1,sticky='w') self.toggleCopyShifts.set(True) row += 1 label = Label(frameA, text='Molecular System:') label.grid(row=row,column=0,sticky='w') self.molSystemPulldown = PulldownList(frameA, callback=self.selectMolSystem) self.molSystemPulldown.grid(row=row,column=1,sticky='w') row += 1 label = Label(frameA, text='Chain:') label.grid(row=row,column=0,sticky='w') self.chainPulldown = PulldownList(frameA, callback=self.selectChain) self.chainPulldown.grid(row=row,column=1,sticky='w') self.chainPulldown.bind('<Leave>', self.updateRunParams) row += 1 label = Label(frameA, text='First Peptide Plane:') label.grid(row=row,column=0,sticky='w') self.firstResEntry = IntEntry(frameA, text=None, width=8) self.firstResEntry.grid(row=row,column=1,sticky='w') self.firstResEntry.bind('<Leave>', self.updateRunParams) row += 1 label = Label(frameA, text='Last Peptide Plane:') label.grid(row=row,column=0,sticky='w') self.lastResEntry = IntEntry(frameA, text=None, width=8) self.lastResEntry.grid(row=row,column=1,sticky='w') self.lastResEntry.bind('<Leave>', self.updateRunParams) row += 1 label = Label(frameA, text='Max Num Optimisation Steps:') label.grid(row=row,column=0,sticky='w') self.maxOptStepEntry = IntEntry(frameA, text=500, width=8) self.maxOptStepEntry.grid(row=row,column=1,sticky='w') self.maxOptStepEntry.bind('<Leave>', self.updateRunParams) row += 1 label = Label(frameA, text='Num Optimisation Peptide Planes:') label.grid(row=row,column=0,sticky='w') self.numOptPlaneEntry = IntEntry(frameA, text=2, width=8) self.numOptPlaneEntry.grid(row=row,column=1,sticky='w') self.numOptPlaneEntry.bind('<Leave>', self.updateRunParams) row += 1 label = Label(frameA, text='Min Num Optimisation Hits:') label.grid(row=row,column=0,sticky='w') self.numOptHitsEntry = IntEntry(frameA, text=5, width=8) self.numOptHitsEntry.grid(row=row,column=1,sticky='w') self.numOptHitsEntry.bind('<Leave>', self.updateRunParams) row += 1 label = Label(frameA, text='File Name Prefix:') label.grid(row=row,column=0,sticky='w') self.pdbFileEntry = Entry(frameA, text='Meccano', width=8) self.pdbFileEntry.grid(row=row,column=1,sticky='w') self.pdbFileEntry.bind('<Leave>', self.updateRunParams) row += 1 label = Label(frameA, text='Write Output File (.out):') label.grid(row=row,column=0,sticky='w') self.toggleWriteOutFile = CheckButton(frameA) self.toggleWriteOutFile.grid(row=row,column=1,sticky='w') self.toggleWriteOutFile.set(False) self.toggleWriteOutFile.bind('<Leave>', self.updateRunParams) row += 1 label = Label(frameA, text='Write PDB File (.pdb):') label.grid(row=row,column=0,sticky='w') self.toggleWritePdbFile = CheckButton(frameA) self.toggleWritePdbFile.grid(row=row,column=1,sticky='w') self.toggleWritePdbFile.set(True) self.toggleWritePdbFile.bind('<Leave>', self.updateRunParams) if not Meccano: row += 1 label = Label(frameA, text='The Meccano executable is not available (it needs to be compiled)', fg='red') label.grid(row=row,column=0,columnspan=2,sticky='w') # Restraints label = Label(frameB, text='Constraint Set:') label.grid(row=0,column=0,sticky='w') self.constraintSetPulldown = PulldownList(frameB, callback=self.selectConstraintSet) self.constraintSetPulldown.grid(row=0,column=1,sticky='w') self.alignMediumPulldown= PulldownList(self, callback=self.setAlignMedium) headingList = ['#','List Type','Use?','Alignment\nMedium','Num\nRestraints'] editWidgets = [None,None,None,self.alignMediumPulldown,None] editGetCallbacks = [None,None,self.toggleUseRestraints,self.getAlignMedium,None] editSetCallbacks = [None,None,None,self.setAlignMedium,None] self.restraintMatrix = ScrolledMatrix(frameB, headingList=headingList, editSetCallbacks=editSetCallbacks, editGetCallbacks=editGetCallbacks, editWidgets=editWidgets, callback=None, multiSelect=True) self.restraintMatrix.grid(row=1,column=0,columnspan=2,sticky='nsew') # Alignment Media div = LabelDivider(frameC,text='Alignment Media') div.grid(row=0,column=0,sticky='ew') self.mediumNameEntry = Entry(self, returnCallback=self.setMediumName) self.mediumDetailsEntry = Entry(self, returnCallback=self.setMediumDetails) headingList = ['#','Name','Details','Static Tensor','Dynamic Tensor'] editWidgets = [None, self.mediumNameEntry, self.mediumDetailsEntry, None, None] editGetCallbacks = [None, self.getMediumName, self.getMediumDetails, None, None] editSetCallbacks = [None, self.setMediumName, self.setMediumDetails, None, None] self.mediaMatrix = ScrolledMatrix(frameC, headingList=headingList, editSetCallbacks=editSetCallbacks, editGetCallbacks=editGetCallbacks, editWidgets=editWidgets, callback=self.selectAlignMedium, multiSelect=True) self.mediaMatrix.grid(row=1,column=0,sticky='nsew') texts = ['Add Alignment medium','Remove Alignment Medium'] commands = [self.addAlignMedium,self.removeAlignMedium] buttonList = ButtonList(frameC, texts=texts, commands=commands, expands=True) buttonList.grid(row=2,column=0,sticky='nsew') self.editAxialEntry = FloatEntry(self, returnCallback=self.setAxial) self.editRhombicEntry = FloatEntry(self, returnCallback=self.setRhombic) self.editAlphaEulerEntry = FloatEntry(self, returnCallback=self.setEulerAlpha) self.editBetaEulerEntry = FloatEntry(self, returnCallback=self.setEulerBeta) self.editGammaEulerEntry = FloatEntry(self, returnCallback=self.setEulerGamma) div = LabelDivider(frameC,text='Alignment Tensors') div.grid(row=3,column=0,sticky='ew') headingList = ['Type', u'Axial (\u03B6)',u'Rhombic (\u03B7)', u'Euler \u03B1',u'Euler \u03B2',u'Euler \u03B3'] editWidgets = [None,self.editAxialEntry, self.editRhombicEntry,self.editAlphaEulerEntry, self.editBetaEulerEntry,self.editGammaEulerEntry] editSetCallbacks = [None,self.setAxial,self.setRhombic, self.setEulerAlpha,self.setEulerBeta,self.setEulerGamma] editGetCallbacks = [None,self.getAxial,self.getRhombic, self.getEulerAlpha,self.getEulerBeta,self.getEulerGamma] self.tensorMatrix = ScrolledMatrix(frameC, maxRows=2, headingList=headingList, editSetCallbacks=editSetCallbacks, editGetCallbacks=editGetCallbacks, editWidgets=editWidgets, callback=self.selectTensor, multiSelect=True) self.tensorMatrix.grid(row=4,column=0,sticky='nsew') texts = ['Add Static Tensor','Add Dynamic Tensor','Remove Tensor'] commands = [self.addStaticTensor,self.addDynamicTensor,self.removeTensor] buttonList = ButtonList(frameC,texts=texts, commands=commands, expands=True) buttonList.grid(row=5,column=0,sticky='ew') # About label = Label(frameD, text='About Meccano...') label.grid(row=0,column=0,sticky='w') # self.geometry('500x400') self.updateShiftLists() self.updateMolSystems() self.updateResidueRanges() self.updateConstraintSets() self.updateAlignMedia() self.updateRuns() def close(self): self.updateRunParams() BasePopup.close(self) def destroy(self): self.updateRunParams() self.curateNotifiers(self.unregisterNotify) BasePopup.destroy(self) def curateNotifiers(self, notifyFunc): for func in ('__init__', 'delete'): notifyFunc(self.updateConstraintSetsAfter, 'ccp.nmr.NmrConstraint.NmrConstraintStore', func) for func in ('__init__', 'delete','setName','setConditionState'): for clazz in ('ccp.nmr.NmrConstraint.CsaConstraintList', 'ccp.nmr.NmrConstraint.DihedralConstraintList', 'ccp.nmr.NmrConstraint.DistanceConstraintList', 'ccp.nmr.NmrConstraint.HBondConstraintList', 'ccp.nmr.NmrConstraint.JCouplingConstraintList', 'ccp.nmr.NmrConstraint.RdcConstraintList'): notifyFunc(self.updateConstraintListsAfter, clazz, func) for func in ('__init__', 'delete',): for clazz in ('ccp.nmr.NmrConstraint.CsaConstraint', 'ccp.nmr.NmrConstraint.DihedralConstraint', 'ccp.nmr.NmrConstraint.DistanceConstraint', 'ccp.nmr.NmrConstraint.HBondConstraint', 'ccp.nmr.NmrConstraint.JCouplingConstraint', 'ccp.nmr.NmrConstraint.RdcConstraint'): notifyFunc(self.updateConstraintsAfter, clazz, func) for func in ('__init__', 'delete'): notifyFunc(self.updateShiftListsAfter,'ccp.nmr.Nmr.ShiftList', func) for func in ('__init__', 'delete'): notifyFunc(self.updateMolSystemsAfter,'ccp.molecule.MolSystem.MolSystem', func) for func in ('__init__', 'delete'): notifyFunc(self.updateChainsAfter,'ccp.molecule.MolSystem.Chain', func) for func in ('__init__', 'delete','setDynamicAlignment', 'setStaticAlignment','setName','setDetails'): notifyFunc(self.updateAlignMediaAfter,'ccp.nmr.NmrConstraint.ConditionState', func) def updateAlignMediaAfter(self, alignMedium): if alignMedium.nmrConstraintStore is self.constraintSet: self.after_idle(self.updateAlignMedia) if alignMedium is self.alignMedium: self.after_idle(self.updateTensors) def updateConstraintSetsAfter(self, constraintSet): self.after_idle(self.updateConstraintSets) def updateShiftListsAfter(self, shiftList): self.after_idle(self.updateShiftLists) def updateMolSystemsAfter(self, molSystem): self.after_idle(self.updateMolSystems) def updateChainsAfter(self, chain): self.after_idle(self.updateChains) def updateConstraintsAfter(self, constraint): if constraint.parent.parent is self.constraintSet: self.after_idle(self.updateConstraintLists) def updateConstraintListsAfter(self, constraintList): if constraintList.parent is self.constraintSet: self.after_idle(self.updateConstraintLists) def runMeccano(self): # # # Input checks first # # warning = '' if not self.molSystem: warning += 'No molecular system selected\n' if not self.chain: warning += 'No chain selected\n' if not self.constraintSet: warning += 'No selected constraint set\n' else: constraintLists = [cl for cl in self.constraintSet.constraintLists if cl.useForMeccano] if not constraintLists: warning += 'No constraint lists selected for use\n' first, last = self.updateResidueRanges() if (last-first) < 2: warning += 'Too few peptide planes selected\n' if warning: showWarning('Cannot run MECCANO','Encountered the following problems:\n' + warning) return if not self.run: self.run = self.makeSimRun() self.updateRunParams() if self.toggleCopyShifts.get() and self.shiftList: shiftList = self.run.findFirstOutputMeasurementList(className='ShiftList') if not shiftList: shiftList = self.project.currentNmrProject.newShiftList(name='Meccano Input') self.run.setOutputMeasurementLists([shiftList,]) shiftDict = {} for shift in shiftList.shifts: shiftDict[shift.resonance] = shift for shift in self.shiftList.shifts: resonance = shift.resonance resonanceSet = resonance.resonanceSet if resonanceSet: atom = resonanceSet.findFirstAtomSet().findFirstAtom() if (atom.name == 'C') and (atom.residue.molResidue.molType == 'protein'): shift2 = shiftDict.get(resonance) if shift2: shift2.value = shift.value shift2.error = shift.error else: shiftList.newShift(resonance=resonance, value=shift.value, error=shift.error) # # # Accumulate data from CCPN data model & GUI # # # Sequence residues = self.chain.sortedResidues() residueDict = {} seqData = [] for residue in residues: molResidue = residue.molResidue code1Letter = molResidue.chemComp.code1Letter if not code1Letter: msg = 'Encountered non-standard residue type: %s' showWarning('Cannot run MECCANO', msg % residue.ccpCode) return seqCode = residue.seqCode seqData.append((seqCode, code1Letter)) residueDict[seqCode] = residue.chemCompVar.chemComp.code3Letter # Media, RDCs & Dihedrals rdcLists = [] dihedralLists = [] for constraintList in constraintLists: if constraintList.className == 'RdcConsraintList': if constraintList.conditionState: rdcLists.append(constraintList) elif constraintList.className == 'DihedralConstraintList': dihedralLists.append(dihedralLists) f = PI_OVER_180 mediaData = [] for constraintList in rdcLists: medium = constraintList.conditionState dynamicTensor = medium.dynamicAlignment staticTensor = medium.staticAlignment if not (dynamicTensor or staticTensor): continue if dynamicTensor: dynamicTensorData = ['Dynamic', dynamicTensor.aAxial, dynamicTensor.aRhombic, f*dynamicTensor.alpha, f*dynamicTensor.beta, f*dynamicTensor.gamma] if staticTensor: staticTensorData = ['Static', staticTensor.aAxial, staticTensor.aRhombic, f*staticTensor.alpha, f*staticTensor.beta, f*staticTensor.gamma] if not dynamicTensor: dynamicTensorData = staticTensorData elif not staticTensor: staticTensorData = dynamicTensorData rdcData = [] for restraint in constraintList.constraints: items = list(restraint.items) if len(items) != 1: continue resonanceA, resonanceB = [fr.resonance for fr in items[0].resonances] resonanceSetA = resonanceA.resonanceSet if not resonanceSetA: continue resonanceSetB = resonanceB.resonanceSet if not resonanceSetB: continue resNameA = getResonanceName(resonanceA) resNameB = getResonanceName(resonanceB) residueA = resonanceSetA.findFirstAtomSet().findFirstAtom().residue residueB = resonanceSetB.findFirstAtomSet().findFirstAtom().residue seqA = residueA.seqCode seqB = residueB.seqCode value = restraint.targetValue error = restraint.error if error is None: key = [resNameA,resNameB] key.sort() sigma = DEFAULT_ERRORS.get(tuple(key), 1.0) rdcData.append([seqA, resNameA, seqB, resNameB, value, error]) mediaData.append((dynamicTensorData,staticTensorData,rdcData)) oneTurn = 360.0 dihedralDict = {} for constraintList in dihedralLists: for restraint in constraintList.constraints: items = list(restraint.items) if len(items) != 1: continue item = items[0] resonances = [fr.resonance for fr in item.resonances] resonanceSets = [r.resonanceSet for r in resonances] if None in resonanceSets: continue atoms = [rs.findFirstAtomSet().findFirstAtom() for rs in resonanceSets] atomNames = [a.name for a in atoms] if atomNames == PHI_ATOM_NAMES: isPhi = True elif atomNames == PSI_ATOM_NAMES: isPhi = False else: continue residue = atoms[2].residue if residue.chain is not self.chain: continue if isPhi: residuePrev = getLinkedResidue(residue, linkCode='prev') if not residuePrev: continue atomC0 = residuePrev.findFirstAtom(name='C') atomN = residue.findFirstAtom(name='N') atomCa = residue.findFirstAtom(name='CA') atomC = residue.findFirstAtom(name='C') atoms2 = [atomC0, atomN, atomCa, atomC] else: residueNext = getLinkedResidue(residue, linkCode='next') if not residueNext: continue atomN = residue.findFirstAtom(name='N') atomCa = residue.findFirstAtom(name='CA') atomC = residue.findFirstAtom(name='C') atomN2 = residueNext.findFirstAtom(name='N') atoms2 = [atomN, atomCa, atomC, atomN2] if atoms != atoms2: continue value = item.targetValue error = item.error if error is None: upper = item.upperLimit lower = item.lowerLimit if (upper is not None) and (lower is not None): dUpper = angleDifference(value, lower, oneTurn) dLower = angleDifference(upper, value, oneTurn) error = max(dUpper, dLower) elif lower is not None: error = angleDifference(value, lower, oneTurn) elif upper is not None: error = angleDifference(upper, value, oneTurn) else: error = 30.0 # Arbitrary, but sensible for TALOS, DANGLE seqCode = residue.seqCode if not dihedralDict.has_key(seqCode): dihedralDict[seqCode] = [None, None, None, None] # Phi, Psi, PhiErr, PsiErr if isPhi: dihedralDict[seqCode][0] = value dihedralDict[seqCode][2] = error else: dihedralDict[seqCode][1] = value dihedralDict[seqCode][3] = error phipsiData = [] seqCodes = dihedralDict.keys() seqCodes.sort() for seqCode in seqCodes: data = dihedralDict[seqCode] if None not in data: phi, psi, phiErr, psiErr = data phipsiData.append((seqCode, phi, psi, phiErr, psiErr)) # User options firstPPlaneFrag = self.firstResEntry.get() or 1 lastPPlaneFrag = self.lastResEntry.get() or 1 ppNbMin = self.numOptPlaneEntry.get() or 1 minValueBest = self.numOptHitsEntry.get() or 2 maxValueBest = self.maxOptStepEntry.get() or 5 strucData = Meccano.runFwd(firstPPlaneFrag, lastPPlaneFrag, ppNbMin, minValueBest, maxValueBest, RAMACHANDRAN_DATABASE, seqData, mediaData, phipsiData) if strucData: fileName = 'CcpnMeccanoPdb%f.pdb' % time.time() fileObj = open(fileName, 'w') ch = self.chain.pdbOneLetterCode.strip() if not ch: ch = self.chain.code[0].upper() i = 1 for atomType, resNb, x, y, z in strucData: resType = residueDict.get(resNb, '???') line = PDB_FORMAT % ('ATOM',i,'%-3s' % atomType,'',resType,ch,resNb,'',x,y,z,1.0,1.0) i += 1 fileObj.close() ensemble = getStructureFromFile(self.molSystem, fileName) if not self.toggleWritePdbFile.get(): os.unlink(fileName) self.run.outputEnsemble = ensemble self.run = None self.updateRuns() def getMediumName(self, alignMedium): self.mediumNameEntry.set(alignMedium.name) def getMediumDetails(self, alignMedium): self.mediumDetailsEntry.set(alignMedium.details) def setMediumName(self, event): value = self.mediumNameEntry.get() self.alignMedium.name = value or None def setMediumDetails(self, event): value = self.mediumDetailsEntry.get() self.alignMedium.details = value or None def setAlignMedium(self, alignMedium): if self.constraintSet: self.constraintSet.conditionState = alignMedium def getAlignMedium(self, constraintList): media = self.getAlignmentMedia() names = [am.name for am in media] if constraintList.conditionState in media: index = media.index(constraintList.conditionState) else: index = 0 self.alignMediumPulldown.setup(names, media, index) def toggleUseRestraints(self, constraintList): bool = constraintList.useForMeccano bool = not bool if bool and (not constraintList.conditionState) \ and (constraintList.className == 'RdcConsraintList'): msg = 'Cannot use RDC restraint list for Meccano ' msg += 'unless it is first associated with an amigment medium' showWarning('Warning', msg, parent=self) else: constraintList.useForMeccano = bool self.updateConstraintLists() def addStaticTensor(self): if self.alignMedium: tensor = Implementation.SymmTracelessMatrix(aAxial=0.0,aRhombic=0.0, alpha=0.0,beta=0.0, gamma=0.0) self.alignMedium.staticAlignment = tensor self.updateAlignMediaAfter(self.alignMedium) def addDynamicTensor(self): if self.alignMedium: tensor = Implementation.SymmTracelessMatrix(aAxial=0.0,aRhombic=0.0, alpha=0.0,beta=0.0, gamma=0.0) self.alignMedium.dynamicAlignment = tensor self.updateAlignMediaAfter(self.alignMedium) def removeTensor(self): if self.alignMedium and self.tensor: if self.tensor is self.alignMedium.dynamicAlignment: self.alignMedium.dynamicAlignment = None elif self.tensor is self.alignMedium.staticAlignment: self.alignMedium.staticAlignment = None self.updateAlignMediaAfter(self.alignMedium) def addAlignMedium(self): if self.constraintSet: medium = self.constraintSet.newConditionState() medium.name = 'Align Medium %d' % medium.serial def removeAlignMedium(self): if self.alignMedium: self.alignMedium.delete() def updateTensor(self, aAxial=None, aRhombic=None, alpha=None, beta=None, gamma=None): aAxial = aAxial or self.tensor.aAxial aRhombic = aRhombic or self.tensor.aRhombic alpha = alpha or self.tensor.alpha beta = beta or self.tensor.beta gamma = gamma or self.tensor.gamma tensor = Implementation.SymmTracelessMatrix(aAxial=aAxial, aRhombic=aRhombic, alpha=alpha,beta=beta, gamma=gamma) if self.alignMedium: if self.tensor is self.alignMedium.dynamicAlignment: self.alignMedium.dynamicAlignment = tensor elif self.tensor is self.alignMedium.staticAlignment: self.alignMedium.staticAlignment = tensor self.tensor = tensor def setAxial(self, event): value = self.editAxialEntry.get() self.updateTensor(aAxial=value) self.updateTensors() def setRhombic(self, event): value = self.editRhombicEntry.get() self.updateTensor(aRhombic=value) self.updateTensors() def setEulerAlpha(self, event): value = self.editAlphaEulerEntry.get() self.updateTensor(alpha=value) self.updateTensors() def setEulerBeta(self, event): value = self.editBetaEulerEntry.get() self.updateTensor(beta=value) self.updateTensors() def setEulerGamma(self, event): value = self.editGammaEulerEntry.get() self.updateTensor(gamma=value) self.updateTensors() def getAxial(self, tensor): value = tensor.aAxial self.editAxialEntry.set(value) def getRhombic(self, tensor): value = tensor.aRhombic self.editRhombicEntry.set(value) def getEulerAlpha(self, tensor): value = tensor.alpha self.editAlphaEulerEntry.set(value) def getEulerBeta(self, tensor): value = tensor.beta self.editBetaEulerEntry.set(value) def getEulerGamma(self, tensor): value = tensor.gamma self.editGammaEulerEntry.set(value) def selectTensor(self, tensor, row, col): self.tensor = tensor def selectAlignMedium(self, alignMedium, row, col): self.alignMedium = alignMedium self.updateTensors() def getAlignmentMedia(self): if self.constraintSet: return self.constraintSet.sortedConditionStates() else: return [] def updateAlignMedia(self): textMatrix = [] objectList = [] if self.constraintSet: objectList = self.getAlignmentMedia() for conditionState in objectList: staticTensor = None dyamicTensor = None tensor = conditionState.dynamicAlignment if tensor: vals = (tensor.aAxial, tensor.aRhombic, tensor.alpha, tensor.beta, tensor.gamma) dyamicTensor = u'\u03B6:%.3f \u03B7:%.3f \u03B1:%.3f \u03B2:%.3f \u03B3:%.3f ' % vals tensor = conditionState.staticAlignment if tensor: vals = (tensor.aAxial, tensor.aRhombic, tensor.alpha, tensor.beta, tensor.gamma) staticTensor = u'\u03B6:%.3f \u03B7:%.3f \u03B1:%.3f \u03B2:%.3f \u03B3:%.3f ' % vals datum = [conditionState.serial, conditionState.name, conditionState.details, dyamicTensor, staticTensor] textMatrix.append(datum) if dyamicTensor or staticTensor: if not self.alignMedium: self.alignMedium = conditionState self.mediaMatrix.update(textMatrix=textMatrix, objectList=objectList) if self.alignMedium: self.mediaMatrix.selectObject(self.alignMedium) def updateTensors(self): textMatrix = [] objectList = [] conditionState = self.alignMedium if conditionState: tensor = conditionState.dynamicAlignment if tensor: datum = ['Dynamic', tensor.aAxial, tensor.aRhombic, tensor.alpha, tensor.beta, tensor.gamma] textMatrix.append(datum) objectList.append(tensor) tensor = conditionState.staticAlignment if tensor: datum = ['Static', tensor.aAxial, tensor.aRhombic, tensor.alpha, tensor.beta, tensor.gamma] textMatrix.append(datum) objectList.append(tensor) self.tensorMatrix.update(textMatrix=textMatrix, objectList=objectList) def getMolSystems(self): molSystems = [] for molSystem in self.project.sortedMolSystems(): if molSystem.chains: molSystems.append(molSystem) return molSystems def updateMolSystems(self, *notifyObj): index = 0 names = [] molSystems = self.getMolSystems() molSystem = self.molSystem if molSystems: if molSystem not in molSystems: molSystem = molSystems[0] index = molSystems.index(molSystem) names = [ms.code for ms in molSystems] else: self.molSystem = None if self.molSystem is not molSystem: if self.run: self.run.molSystem = molSystem self.molSystem = molSystem self.updateChains() self.molSystemPulldown.setup(texts=names, objects=molSystems, index=index) def selectMolSystem(self, molSystem): if self.molSystem is not molSystem: if self.run: self.run.molSystem = molSystem self.molSystem = molSystem self.updateChains() def updateChains(self, *notifyObj): index = 0 names = [] chains = [] chain = self.chain if self.molSystem: chains = [c for c in self.molSystem.sortedChains() if c.residues] if chains: if chain not in chains: chain = chains[0] index = chains.index(chain) names = [c.code for c in chains] if chain is not self.chain: self.chain = chain self.updateResidueRanges() self.chainPulldown.setup(texts=names, objects=chains, index=index) def selectChain(self, chain): if chain is not self.chain: self.chain = chain self.updateResidueRanges() def updateResidueRanges(self): first = self.firstResEntry.get() last = self.lastResEntry.get() if self.chain: residues = self.chain.sortedResidues() firstSeq = residues[0].seqCode lastSeq = residues[-2].seqCode if first < firstSeq: first = firstSeq if last == first: last = lastSeq elif last > lastSeq: last = lastSeq if first > last: last, first = first, last self.firstResEntry.set(first) self.lastResEntry.set(last) return first, last def getConstraintSets(self): constraintSets = [] nmrProject = self.project.currentNmrProject for constraintSet in nmrProject.sortedNmrConstraintStores(): for constraintList in constraintSet.constraintLists: if constraintList.className not in ('ChemShiftConstraintList','somethingElse'): constraintSets.append(constraintSet) break return constraintSets def updateConstraintSets(self, *notifyObj): index = 0 names = [] constraintSets = self.getConstraintSets() constraintSet = self.constraintSet if constraintSets: if constraintSet not in constraintSets: constraintSet = constraintSets[0] index = constraintSets.index(constraintSet) names = ['%d' % cs.serial for cs in constraintSets] if constraintSet is not self.constraintSet: if self.run: self.run.inputConstraintStore = constraintSet self.constraintSet = constraintSet self.updateConstraintLists() self.constraintSetPulldown.setup(texts=names, objects=constraintSets, index=index) def selectConstraintSet(self, constraintSet): if self.constraintSet is not constraintSet: if self.run: self.run.inputConstraintStore = constraintSet self.constraintSet = constraintSet self.updateConstraintLists() def getConstraintLists(self): constraintLists = [] if self.constraintSet: for constraintList in self.constraintSet.sortedConstraintLists(): if constraintList.className not in ('ChemShiftConstraintList','somethingElse'): constraintLists.append(constraintList) return constraintLists def updateConstraintLists(self, *notifyObj): textMatrix = [] objectList = self.getConstraintLists() for constraintList in objectList: if not hasattr(constraintList, 'useForMeccano'): if constraintList.conditionState \ or (constraintList.className != 'RdcConstraintList'): bool = True else: bool = False constraintList.useForMeccano = bool if constraintList.conditionState: alignMedium = constraintList.conditionState.name else: alignMedium = None datum = [constraintList.serial, constraintList.className[:-14], constraintList.useForMeccano and 'Yes' or 'No', alignMedium, len(constraintList.constraints)] textMatrix.append(datum) self.restraintMatrix.update(textMatrix=textMatrix, objectList=objectList) def selectConstraint(self, obj, row, column): if self.constraint is not obj: self.constraint = obj def getSimStore(self): simStore = self.project.findFirstNmrSimStore(name='meccano') if not simStore: simStore = self.project.newNmrSimStore(name='meccano') return simStore def getRuns(self): runs = [None, ] if self.molSystem and self.constraintSet: simStore = self.getSimStore() runs += simStore.sortedRuns() return runs def updateRuns(self, *notifyObj): index = 0 names = ['<New>'] runs = self.getRuns() run = self.run if runs: if run not in runs: run = runs[0] index = runs.index(run) names += [r.serial for r in runs if r] if run is not self.run: self.updateConstraintSets() self.updateMolSystems() self.updateShiftLists() self.runPulldown.setup(names, runs, index) def updateRunParams(self, event=None): if self.run and self.molSystem and self.constraintSet: simRun = self.run simRun.inputConstraintStore = self.constraintSet simRun.molSystem = self.molSystem if self.shiftList: simRun.setInputMeasurementLists([self.shiftList,]) simRun.newRunParameter(code='FirstPepPlane',id=1, intValue=self.firstResEntry.get() or 0) simRun.newRunParameter(code='LastPepPlane' ,id=1, intValue=self.lastResEntry.get() or 0) simRun.newRunParameter(code='MaxOptSteps', id=1, intValue=self.maxOptStepEntry.get() or 0) simRun.newRunParameter(code='NumOptPlanes', id=1, intValue=self.numOptPlaneEntry.get() or 0) simRun.newRunParameter(code='MinOptHits', id=1, intValue=self.numOptHitsEntry.get() or 0) def makeSimRun(self, template=None): simStore = self.getSimStore() if template: molSystem = template.molSystem constraintSet = template.inputConstraintStore shiftList = template.findFirstInputMeasurementList(className='ShiftList') protocol = template.annealProtocol else: molSystem = self.molSystem constraintSet = self.constraintSet shiftList = self.shiftList protocol = self.annealProtocol simRun = simStore.newRun(annealProtocol=protocol, molSystem=molSystem, inputConstraintStore=protocol) if shiftList: simRun.addInputMeasurementList(shiftList) if template: for param in template.runParameters: simRun.newRunParameter(code=param.code, id=param.id, booleanValue=param.booleanValue, floatValue=param.floatValue, intValue=param.intValue, textValue=param.textValue) else: if self.chain: chainCode = self.chain.code else: chaincode = 'A' simRun.newRunParameter(code='FirstPepPlane',id=1, intValue=self.firstResEntry.get() or 0) simRun.newRunParameter(code='LastPepPlane' ,id=1, intValue=self.lastResEntry.get() or 0) simRun.newRunParameter(code='MaxOptSteps', id=1, intValue=self.maxOptStepEntry.get() or 0) simRun.newRunParameter(code='NumOptPlanes', id=1, intValue=self.numOptPlaneEntry.get() or 0) simRun.newRunParameter(code='MinOptHits', id=1, intValue=self.numOptHitsEntry.get() or 0) simRun.newRunParameter(code='ChainCode', id=1, textValue=chainCode) return simRun def selectRun(self, simRun): if self.run is not simRun: if simRun: if simRun.outputEnsemble: msg = 'Selected run has already been used to generate a structure.' msg += 'A new run will be setup based on the selection.' showWarning('Warning',msg) simRun = self.makeSimRun(template=simRun) molSystem = simRun.molSystem constraintSet = simRun.inputConstraintStore shiftList = simRun.findFirstInputMeasurementList(className='ShiftList') if molSystem and (self.molSystem is not molSystem): self.molSystem = molSystem self.updateMolSystems() if constraintSet and (self.constraintSet is not constraintSet): self.constraintSet = constraintSet self.updateConstraintSets() if shiftList and (self.shiftList is not shiftList): self.shiftList = shiftList self.updateShiftLists() firstPepPlane = simRun.findFirstrunParameter(code='FirstPepPlane') lastPepPlane = simRun.findFirstrunParameter(code='LastPepPlane') maxOptSteps = simRun.findFirstrunParameter(code='MaxOptSteps') numOptPlanes = simRun.findFirstrunParameter(code='NumOptPlanes') minOptHits = simRun.findFirstrunParameter(code='MinOptHits') chainCode = simRun.findFirstrunParameter(code='ChainCode') if firstPepPlane is not None: self.firstResEntry.set(firstPepPlane.intValue or 0) if lastPepPlane is not None: self.lastResEntry.set(lastPepPlane.intValue or 0) if maxOptSteps is not None: self.maxOptStepEntry.set(maxOptSteps.intValue or 0) if numOptPlanes is not None: self.numOptPlaneEntry.set(numOptPlanes.intValue or 0) if minOptHits is not None: self.numOptHitsEntry.set(minOptHits.intValue or 0) if chainCode is not None: chainCode = chainCode.textValue or 'A' if self.molSystem: chain = self.molSystem.findFirsChain(code=chainCode) if chain: self.selectChain(chain) self.run = simRun def updateShiftLists(self, *notifyObj): index = 0 names = [] nmrProject = self.project.currentNmrProject shiftLists = nmrProject.findAllMeasurementLists(className='ShiftList') shiftLists = [(sl.serial, sl) for sl in shiftLists] shiftLists.sort() shiftLists = [x[1] for x in shiftLists] shiftList = self.shiftList if shiftLists: if shiftList not in shiftLists: shiftList = shiftLists[0] index = shiftLists.index(shiftList) names = ['%d'% sl.serial for sl in shiftLists] if shiftList is not self.shiftList: if self.run: self.run.setInputMeasurementLists([shiftList]) self.shiftListPulldown.setup(texts=names, objects=shiftLists, index=index) def selectShiftList(self, shiftList): if shiftList is not self.shiftList: if self.run: self.run.setInputMeasurementLists([shiftList]) self.shiftList = shiftList
class PeakSeparatorGui(BasePopup): """ **Separate Merged Peaks Using Peak Models** The Peak Separator code uses a Markov Chain Monte Carlo search which, using idealised peak shapes, attempts to deconvolve overlapped peak regions into their separate constituent peaks. This routine is also suitable for accurately fitting model shapes to single peaks in order to calculate precise intensities. **Options Peak Separator Parameters** *Min. Number of peaks* is by default set to one, it is not possible to set this to a value less than one. *Max. Number of peaks* is by default set to one, increasing this value allows the search routine to fit more models. The best fit may be found with fewer than the maximum number models. Higher numbers slow the routine, and setting this value to 0 allows the routine to (effectively) fit unlimited peaks. *Only pick positive peaks*. If you are not interested in negative peaks, removing the possibility of fitting negative peaks can reduce search time. *Peak Model* fits the spectra with either a Gaussian peak model or a Lorentzian peak model. **Options Region** *Peak List* choose which peak list newly picked peaks should be added to. Peaks picked using this method will have their details appended with 'PeakSepartor' so you know where they came from. *Region Table* shows which area of the current spectrum is about to be searched. *Add Region*. Once an area of spectra has been highlighted clicking this button will pass it's details on to the Peak Separator. *Reset All* will reset all search parameters. *Separate Peaks* will run the Peak Separator code with your current settings. This may take a few minutes to run, depending on the size of the spectral region being searched, the number of peaks being fitted and the speed of your machine. Please wait while this completes. After a successful Peak Separation run, the found peaks will be added to the selected peak list. These peaks intensties (volume) have been found using the peak model selected. **Advanced Settings Tab** *Rate* affects the speed of the Markov Chain Monte Carlo routine. A smaller value results in longer execution, but possibly higher quality results. The default setting is deemed sensible for the majority of runs. *Line Width* offers a finer degree of control over maximum and minimum peak widths for each dimension. The default values are *very* stupid and could do with re-checking for each experiment. *Re-Pick Entire Peak List* if you would like to use the Peak Separator to repick *every* peak in your peak list, try this option - but note that this may take a very long time! """ def __init__(self, parent, programName='Peak Separator', **kw): self.parent = parent self.programName = programName self.versionInfo = 'Version 0.2' self.help_url = 'http://www.ccpn.ac.uk/' self.window = None self.waiting = False self.rootWindow = None # just used for display - PeakSeparator will not see this self._minSigmaHz = None self._maxSigmaHz = None self.customSigma = False self.rePickPeakList = False self._sampleStartPpm = None self._sampleEndPpm = None try: self.project = parent.project except: pass self.params = PeakSeparatorParams() BasePopup.__init__(self, parent=parent, title=programName, location='+100+100', **kw) if not self.analysisProject: print '&&& init: No analysis project found ...' try: if parent.argumentServer: self.argServer = parent.argumentServer else: print '&&& init: No argument server found...' except: print '&&& init: Test' ########################################################################### def body(self, guiFrame): self.geometry('450x500') guiFrame.grid_rowconfigure(0, weight=1) guiFrame.grid_columnconfigure(0, weight=1) options = ['Peak Separator', 'Advanced Settings'] tabbedFrame = TabbedFrame(guiFrame, options=options) tabbedFrame.grid(row=0, column=0, sticky='nsew') buttons = UtilityButtonList(tabbedFrame.sideFrame, helpUrl=self.help_url) buttons.grid(row=0, column=0, sticky='e') self.tabbedFrame = tabbedFrame frameA, frameB = tabbedFrame.frames # # FrameA : Main Settings # frameA.grid_columnconfigure(1, weight=1) row = 0 # Label row row += 1 div = LabelDivider(frameA, text='Peak Separator Parameters') div.grid(row=row, column=0, columnspan=2, sticky='ew') row += 1 label = Label(frameA, text='Min. number of peaks:') label.grid(row=row, column=0, sticky='w') self.minPeaksEntry = IntEntry(frameA, returnCallback=self.applyChange, width=10, \ tipText='Minimum number of peaks to find (must be > 0)') self.minPeaksEntry.grid(row=row, column=1, sticky='n') self.minPeaksEntry.bind('<Leave>', self.applyChange, '+') row += 1 label = Label(frameA, text='Max. number of peaks:') label.grid(row=row, column=0, sticky='w') self.maxPeaksEntry = IntEntry(frameA, returnCallback=self.applyChange, width=10, \ tipText='Maximum number of peaks to find (0 is unlimited - not recommended)') self.maxPeaksEntry.grid(row=row, column=1, sticky='n') self.maxPeaksEntry.bind('<Leave>', self.applyChange, '+') row += 1 label = Label(frameA, text='Only pick positive peaks:') label.grid(row=row, column=0, sticky='w') entries = ['False', 'True'] self.posPeaksButtons = RadioButtons( frameA, entries=entries, select_callback=self.applyChange, direction='horizontal', tipTexts=[ 'Search for both positive and negative intensity peaks', 'Limit search to only positive peaks' ]) self.posPeaksButtons.grid(row=row, column=1, sticky='n') row += 1 label = Label(frameA, text='Peak Model:') label.grid(row=row, column=0, sticky='w') ### G/L Mixture works, but volume calculation involves Gamma function # entries = ['Gaussian', 'Lorentzian', 'G/L Mixture'] entries = ['Gaussian', 'Lorentzian'] self.shapeButtons = RadioButtons( frameA, entries=entries, select_callback=self.applyChange, direction='horizontal', tipTexts=[ 'Choose a Gaussian model peak shape to fit to peaks', 'Choose a Lorentzian model peak shape to fit to peaks' ]) self.shapeButtons.grid(row=row, column=1, sticky='n') row += 1 div = LabelDivider(frameA, text='Region', tipText='Region that search will limit itself to') div.grid(row=row, column=0, columnspan=2, sticky='ew') row += 1 label = Label(frameA, text='Peak List:') label.grid(row=row, column=0, sticky='nw') self.peakListPulldown = PulldownList( frameA, callback=self.setManuallyPickPeakList, tipText='Select which peak list new peaks are to be added to') self.peakListPulldown.grid(row=row, column=1, sticky='nw') # tricky scrolled matrix row += 1 self.regionTable = None frameA.grid_rowconfigure(row, weight=1) headings = ('dim.', 'start (ppm)', 'end (ppm)', 'actual size') self.editDimEntry = IntEntry(self, returnCallback=self.applyChange, width=5, tipText='Dimension number') self.editStartEntry = FloatEntry(self, returnCallback=self.applyChange, width=5, tipText='Search area lower bound') self.editEndEntry = FloatEntry(self, returnCallback=self.applyChange, width=5, tipText='Search area upper bound') editWidgets = [ self.editDimEntry, self.editStartEntry, self.editEndEntry, None ] editGetCallbacks = [None, None, None, None] editSetCallbacks = [None, None, None, None] self.regionTable = ScrolledMatrix(frameA, headingList=headings, multiSelect=False, editWidgets=editWidgets, editGetCallbacks=editGetCallbacks, editSetCallbacks=editSetCallbacks, initialRows=5) self.regionTable.grid(row=row, column=0, columnspan=2, sticky='nsew') # Run Button row += 1 texts = ['Add Region'] commands = [self.updateFromRegion] self.addResetButtons = ButtonList( frameA, texts=texts, commands=commands, tipTexts=['Add selected specrtral region']) self.addResetButtons.grid(row=row, column=0, columnspan=2, sticky='ew') row += 1 texts = ['Separate Peaks'] commands = [self.runPeakSeparator] self.runButton = ButtonList(frameA, texts=texts, commands=commands, expands=True, tipTexts=['Run peak search now']) self.runButton.grid(row=row, column=0, columnspan=2, sticky='nsew') # # FrameB : Further Settings # frameB.grid_columnconfigure(0, weight=1) row = 0 div = LabelDivider(frameB, text='Rate:') div.grid(row=row, column=0, columnspan=2, sticky='ew') row += 1 label = Label(frameB, text='Rate of MCMC step size change') label.grid(row=row, column=0, columnspan=1, sticky='w') self.rateEntry = FloatEntry(frameB, returnCallback=self.applyChange, width=10, \ tipText='Rate effects speed of run, smaller values take longer but may produce better results') self.rateEntry.grid(row=row, column=1, sticky='n') self.rateEntry.bind('<Leave>', self.applyChange, '+') self.rateEntry.set(self.params.rate) # tricky scrolled matrix for line width row += 2 div = LabelDivider(frameB, text='Line Width (Hz):') div.grid(row=row, column=0, columnspan=2, sticky='ew') row += 1 label = Label(frameB, text="Descr.") label.grid(row=row, rowspan=2, column=0, sticky='w') row += 1 self.lineWidthTable = None frameB.grid_rowconfigure(row, weight=1) lineWidthHeadings = ('dim.', 'min. σ (Hz)', 'max. σ (Hz)') self.editMinSigmaEntry = FloatEntry(self, returnCallback=self.applyChange, width=5, tipText='Minimum line width (Hz)') self.editMaxSigmaEntry = FloatEntry(self, returnCallback=self.applyChange, width=5, tipText='Maximum line width (Hz)') # self.editDimEntry is also from regionTable initialWidthRows = 4 editLineWidthWidgets = [ None, self.editMinSigmaEntry, self.editMaxSigmaEntry ] editLineWidthGetCallbacks = [None, self.getSigmaMin, self.getSigmaMax] editLineWidthSetCallbacks = [None, self.setSigmaMin, self.setSigmaMax] self.lineWidthTable = ScrolledMatrix( frameB, headingList=lineWidthHeadings, multiSelect=False, editWidgets=editLineWidthWidgets, editGetCallbacks=editLineWidthGetCallbacks, editSetCallbacks=editLineWidthSetCallbacks, initialRows=initialWidthRows) self.lineWidthTable.grid(row=row, column=0, columnspan=2, sticky='nsew') # option to 'repick' exisiting peak list row += initialWidthRows div = LabelDivider(frameB, text='(optional - repick entire peak list)') div.grid(row=row, column=0, columnspan=2, sticky='ew') row += 1 self.repickListPulldown = PulldownList( frameB, callback=self.setRePickPeakList, tipText= 'Select which peak list to repick (new peaks will be put into a new peak list)' ) self.repickListPulldown.grid(row=row, column=0, sticky='nw') texts = ['Repick Peak List'] commands = [self.runRepickPeaks] self.runButton = ButtonList( frameB, texts=texts, commands=commands, expands=True, tipTexts=['Repick selected peak list into a new peak list.']) self.runButton.grid(row=row, column=1, columnspan=1, sticky='nsew') row += 1 div = LabelDivider(frameB) row += 1 texts = ['Separate Peaks'] commands = [self.runPeakSeparator] self.runButton = ButtonList(frameB, texts=texts, commands=commands, expands=True, tipTexts=['Run peak search now']) self.runButton.grid(row=row, column=0, columnspan=2, sticky='nsew') self.setWidgetEntries() self.administerNotifiers(self.registerNotify) def administerNotifiers(self, notifyFunc): for func in ('__init__', 'delete'): notifyFunc(self.updateAfter, 'ccp.nmr.Nmr.PeakList', func) notifyFunc(self.updateAfter, 'ccp.nmr.Nmr.Experiment', 'setName') notifyFunc(self.updateAfter, 'ccp.nmr.Nmr.DataSource', 'setName') def destroy(self): self.administerNotifiers(self.unregisterNotify) BasePopup.destroy(self) ########################################################################### # update parameters from PS Region def updateFromRegion(self): if not self.params.peakList: print '&&& update from region: Need a peak list' return if (self.argServer.parent.currentRegion) == None: showError('No Region', 'Please select a peak region to be separated') return self.rePickPeakList = False getRegionParams(self.params, argServer=self.argServer) if not self.customSigma: self.initSigmaParams() self.setWidgetEntries() ########################################################################### # update parameters from PS PeakList def updateFromPeakList(self): if not self.params.peakList: print '&&& update from peakList: Need a peak list' return getPeakListParams(self.params) if not self.customSigma: self.initSigmaParams() self.setWidgetEntries() ########################################################################### # Run the C library! def runPeakSeparator(self): """ run the peak separator """ # hack for Macs - focus isn't always lost on mouse move # so bind event not always called. Shouldn't affect other OS. self.applyChange() if not self.params.peakList: print '&&& Peak list not yet set' else: # SeparatePeakRoutine(self.params, self.params.peakList, routine='pymc' ) SeparatePeakRoutine(self.params, self.params.peakList, routine='bayesys') def runRepickPeaks(self): """ Run the Peak Separator on entire chosen peak list """ # hack for Macs - focus isn't always lost on mouse move # so bind event not always called. Shouldn't affect other OS. self.applyChange() if not self.params.peakList: print '&&& Peak list not yet set' else: SeparatePeaksInPeakList(self.params) ########################################################################### def setWidgetEntries(self): ### Page One widgets self.minPeaksEntry.set(self.params.minAtoms) self.maxPeaksEntry.set(self.params.maxAtoms) if self.params.positivePeaks == 1: self.posPeaksButtons.set('True') # only pick pos peaks else: self.posPeaksButtons.set('False') # do something fancy if different shapes for each dim! n = self.params.peakShape - 3 # shape is only 3, 4, (5) self.shapeButtons.setIndex(n) if self.project is not None: self.updatePeakListList() self.updateSpectrumWindow() if self.params.sampleStart and self.params.peakList: if not self.rePickPeakList: objectList = [] textMatrix = [] if len(self.params.samplePpmStart) != self.params.Ndim: return for i in range(self.params.Ndim): dim_entry = [] dim_entry.append('%2d' % (i + 1)) dim_entry.append('%7.3f' % self.params.samplePpmStart[i]) dim_entry.append('%7.3f' % self.params.samplePpmEnd[i]) dim_entry.append('%3d' % self.params.sampleSize[i]) textMatrix.append(dim_entry) self.regionTable.update(textMatrix=textMatrix, objectList=objectList) ### Page Two widgets self.rateEntry.set(self.params.rate) if self.params.peakList and self.params.Ndim: textMatrix = [] objectList = [] for i in range(self.params.Ndim): if self.params.isFreqDim[i]: dim_entry = [] objectList.append(i) dim_entry.append('%2d' % (i + 1)) dim_entry.append('%7.3f' % self._minSigmaHz[i]) dim_entry.append('%7.3f' % self._maxSigmaHz[i]) textMatrix.append(dim_entry) self.lineWidthTable.update(textMatrix=textMatrix, objectList=objectList) def applyChange(self, *event): """ Upon change, add settings to params """ # Page One apply changes self.params.minAtoms = self.minPeaksEntry.get() self.params.maxAtoms = self.maxPeaksEntry.get() if self.posPeaksButtons.get() == 'True': # asked only pick pos peaks self.params.positivePeaks = 1 else: self.params.positivePeaks = 0 # do something fancy if different shapes for each dim! n = self.shapeButtons.getIndex() # shape is only 3, 4, (5) self.params.peakShape = n + 3 # Page Two apply changes self.params.rate = float(self.rateEntry.get()) self.updateSigmaParams() ########################################################################### # Peak list functions provide PeakSeparator some inherited params def getPeakListList(self): """ given a spectrum, get list of peak lists """ project = self.project peakLists = [] for experiment in self.nmrProject.experiments: for spectrum in experiment.dataSources: for peakList in spectrum.peakLists: peakLists.append([ '%s:%s:%d' % (experiment.name, spectrum.name, peakList.serial), peakList ]) peakLists.sort() return peakLists def updatePeakListList(self): """ set the peaklist list in the pulldown menu """ peakListData = self.getPeakListList() index = -1 names = [] peakList = self.params.peakList if peakListData: names = [x[0] for x in peakListData] peakLists = [x[1] for x in peakListData] if peakList not in peakLists: peakList = peakLists[0] index = peakLists.index(peakList) else: peakList = None peakLists = [] if peakList is not self.params.peakList: self.params.peakList = peakList self.peakListPulldown.setup(names, peakLists, index) self.repickListPulldown.setup(names, peakLists, index) def setRePickPeakList(self, peakList): """ Set the peak list to be repicked (and hit a Flag) """ self.rePickPeakList = True self.setPeakList(peakList) def setManuallyPickPeakList(self, peakList): """ Set the peak list to add new peaks to (and hit a Flag) """ self.rePickPeakList = False self.setPeakList(peakList) def setPeakList(self, peakList): """ Sets the Peak List """ if peakList is not self.params.peakList: self.params.peakList = peakList # # interrogate the peak list and get all the usefull parameters out self.updateFromPeakList() self.updateSpectrumWindow() self.setWidgetEntries() ########################################################################### # TBD I suspect this is for matching region with peak list, but may be obsolete now def getSpectrumWindowList(self): """ get list of windows which spectrum could be in """ windows = {} if self.params.peakList: views = getSpectrumViews(self.params.peakList.dataSource) for view in views: windows[view.spectrumWindowPane.spectrumWindow] = None return [[w.name, w] for w in windows.keys()] def updateSpectrumWindow(self): """ update the spectrum window """ windowData = self.getSpectrumWindowList() index = -1 names = [] window = self.rootWindow if windowData: names = [x[0] for x in windowData] windows = [x[1] for x in windowData] if window not in windows: window = windows[0] index = windows.index(window) else: window = None windows = [] if window is not self.rootWindow: self.rootWindow = window ########################################################################### # get and set sigma stuff def setSigmaMin(self, dim): value = self.editMinSigmaEntry.get() self._minSigmaHz[dim] = value # dont go and re-write users settings self.customSigma = True # make sure changes are in params object self.updateSigmaParams(dim) self.setWidgetEntries() def getSigmaMin(self, dim): if dim is not None: self.editMinSigmaEntry.set(self._minSigmaHz[dim]) def setSigmaMax(self, dim): value = self.editMaxSigmaEntry.get() self._maxSigmaHz[dim] = value # dont go and re-write users settings self.customSigma = True # make sure changes are in params object self.updateSigmaParams(dim) self.setWidgetEntries() def getSigmaMax(self, dim): if dim is not None: self.editMaxSigmaEntry.set(self._maxSigmaHz[dim]) def updateSigmaParams(self, dim=None): """ updateSigmaParams Just updates the parameters (params obj) for sigma values. If dim is None, do this for each dim """ dataDimRefs = self.params.dataDimRefs if not dataDimRefs: return if not self.params.minSigma or len( self.params.minSigma) != self.params.Ndim: self.params.minSigma = [0.] * self.params.Ndim if not self.params.maxSigma or len( self.params.maxSigma) != self.params.Ndim: self.params.maxSigma = [0.] * self.params.Ndim def updateSigmaParam(dim, dataDimRefs): """ Convert and update sigma for dim """ if self.params.isFreqDim[dim]: # note factor of two! self.params.minSigma[dim] = self.rHz2pnt( self._minSigmaHz[dim], dataDimRefs[dim]) / 2. self.params.maxSigma[dim] = self.rHz2pnt( self._maxSigmaHz[dim], dataDimRefs[dim]) / 2. else: self.params.minSigma[dim] = 1.0 self.params.maxSigma[dim] = 1.0 if dim: updateSigmaParam(dim, dataDimRefs) else: for dim in range(self.params.Ndim): updateSigmaParam(dim, dataDimRefs) # utility functions for sigma values def pnt2rHz(self, point, dataDimRef): """ Point to relative Hz frequency relative to frequency at Zeroeth point Necessary when (for example) looking for width of peak in Hz """ assert point, dataDimRef sigmaBase = pnt2hz(0, dataDimRef) sigmaHz = pnt2hz(point, dataDimRef) return abs(sigmaHz - sigmaBase) def rHz2pnt(self, freq, dataDimRef): """ Relative Hz to point frequency relative to frequency at Zeroeth point Necessary when (for example) looking for width of peak in Hz """ assert freq, dataDimRef sigmaBase = hz2pnt(0, dataDimRef) sigmaPoint = hz2pnt(freq, dataDimRef) return abs(sigmaPoint - sigmaBase) def initSigmaParams(self): """ Set some initial default values for sigma """ self._minSigmaHz = [] self._maxSigmaHz = [] if self.params.Ndim: for dim in range(self.params.Ndim): self._minSigmaHz.append(6.) self._maxSigmaHz.append(28.) ########################################################################### def updateAll(self): self.updateSpectrumWindow() self.updatePeakListList() self.waiting = False def updateAfter(self, obj=None): if self.waiting: return else: self.waiting = True self.after_idle(self.updateAll)
class AnnealingSettingsTab(object): '''This class describes the tab in the GUI where the user can change setting that govern the monte carlo / annleaing procedure. This also includes which information from the ccpn analysis project is used and which information is ignored. This includes: * present sequential assignments * tentative assignments * amino acid type information * whether to include untyped spin systems * assignments to peak dimensions ALso the chain can be selected here. Furthermore the user can set the temperature regime of the annealing, the amount of times the procedure is repeated to obtain statistics. The fraction of peaks that is left out in each run to diversify the results, the treshhold score for amino acid typing and the treshhold collabelling for a peak to be expected. ''' def __init__(self, parent, frame): '''Init. args: parent: the guiElement that this tab is part of. frame: the frame this part of the GUI lives in. ''' self.guiParent = parent self.frame = frame self.project = parent.project self.nmrProject = parent.nmrProject self.minIsoFrac = 0.1 self.leavePeaksOutFraction = 0.0 self.minTypeScore = 1.0 self.chain = None self.amountOfRepeats = 10 self.amountOfSteps = 10000 self.acceptanceConstantList = [0.0, 0.01, 0.015, 0.022, 0.033, 0.050, 0.075, 0.113, 0.170, 0.256, 0.384, 0.576, 0.864, 1.297, 1.946, 2.919, 4.378, 6.568, 9.852, 14.77, 22.16, 33.25] self.energyDataSets = [[]] self.residues = [] self.body() def body(self): '''describes the body of this tab. It bascically consists of some field to fill out for the user at the top and a ScrolledGraph that shows the progess of the annealing procedure a the bottom. ''' frame = self.frame # frame.expandGrid(13,0) frame.expandGrid(15, 1) row = 0 text = 'Calculate Assignment Suggestions' command = self.runCalculations self.startButton = Button(frame, command=command, text=text) self.startButton.grid(row=row, column=0, sticky='nsew', columnspan=2) row += 1 Label(frame, text='Amount of runs: ', grid=(row, 0)) tipText = 'The amount of times the whole optimization procedure is performed, each result is safed' self.repeatEntry = IntEntry(frame, grid=(row, 1), width=7, text=10, returnCallback=self.updateRepeatEntry, tipText=tipText, sticky='nsew') self.repeatEntry.bind('<Leave>', self.updateRepeatEntry, '+') row += 1 Label(frame, text='Temperature regime: ', grid=(row, 0)) tipText = 'This list of numbers govern the temperature steps during the annealing, every number represents 1/(kb*t), where kb is the Boltzmann constant and t the temperature of one step.' self.tempEntry = Entry(frame, text=map(str, self.acceptanceConstantList), width=64, grid=(row, 1), isArray=True, returnCallback=self.updateAcceptanceConstantList, tipText=tipText, sticky='nsew') row += 1 Label(frame, text='Amount of attempts per temperature:', grid=(row, 0)) tipText = 'The amount of attempts to switch the position of two spinsystems in the sequence are performed for each temperature point' self.NAStepEntry = IntEntry(frame, grid=(row, 1), width=7, text=10000, returnCallback=self.updateStepEntry, tipText=tipText, sticky='nsew') self.NAStepEntry.bind('<Leave>', self.updateStepEntry, '+') row += 1 Label(frame, text='Fraction of peaks to leave out:', grid=(row, 0)) tipText = 'In each run a fraction of the peaks can be left out of the optimization, thereby increasing the variability in the outcome and reducing false negatives. In each run this will be different randomly chosen sub-set of all peaks. 0.1 (10%) can be a good value.' self.leaveOutPeaksEntry = FloatEntry(frame, grid=(row, 1), width=7, text=0.0, returnCallback=self.updateLeavePeaksOutEntry, tipText=tipText, sticky='nsew') self.leaveOutPeaksEntry.bind( '<Leave>', self.updateLeavePeaksOutEntry, '+') row += 1 Label(frame, text='Minmal amino acid typing score:', grid=(row, 0)) tipText = 'If automatic amino acid typing is selected, a cut-off value has to set. Every amino acid type that scores higher than the cut-off is taken as a possible type. This is the same score as can be found under resonance --> spin systems --> predict type. Value should be between 0 and 100' self.minTypeScoreEntry = FloatEntry(frame, grid=(row, 1), width=7, text=1.0, returnCallback=self.updateMinTypeScoreEntry, tipText=tipText, sticky='nsew') self.minTypeScoreEntry.bind( '<Leave>', self.updateMinTypeScoreEntry, '+') row += 1 Label(frame, text='Minimal colabelling fraction:', grid=(row, 0)) tipText = 'The minimal amount of colabelling the different nuclei should have in order to still give rise to a peak.' self.minLabelEntry = FloatEntry(frame, grid=(row, 1), width=7, text=0.1, returnCallback=self.updateMinLabelEntry, tipText=tipText, sticky='nsew') self.minLabelEntry.bind('<Leave>', self.updateMinLabelEntry, '+') row += 1 Label(frame, text='Use sequential assignments:', grid=(row, 0)) tipText = 'When this option is select the present sequential assignments will be kept in place' self.useAssignmentsCheck = CheckButton( frame, selected=True, tipText=tipText, grid=(row, 1)) row += 1 Label(frame, text='Use tentative assignments:', grid=(row, 0)) tipText = 'If a spin system has tentative assignments this can be used to narrow down the amount of possible sequential assignments.' self.useTentativeCheck = CheckButton( frame, selected=True, tipText=tipText, grid=(row, 1)) row += 1 Label(frame, text='Use amino acid types:', grid=(row, 0)) tipText = 'Use amino acid types of the spin systems. If this option is not checked the spin systems are re-typed, only resonance names and frequencies are used' self.useTypeCheck = CheckButton( frame, selected=True, tipText=tipText, grid=(row, 1)) row += 1 Label(frame, text='Include untyped spin systems:', grid=(row, 0)) tipText = 'Also include spin system that have no type information. Amino acid typing will be done on the fly.' self.useAlsoUntypedSpinSystemsCheck = CheckButton( frame, selected=True, tipText=tipText, grid=(row, 1)) row += 1 Label(frame, text='Use dimensional assignments:', grid=(row, 0)) tipText = 'If one or more dimensions of a peak is already assigned, assume that this assignment is the only option. If not the check the program will consider all possibilities for the assignment of the dimension.' self.useDimensionalAssignmentsCheck = CheckButton( frame, selected=True, tipText=tipText, grid=(row, 1)) row += 1 Label(frame, text='Chain:', grid=(row, 0)) self.molPulldown = PulldownList( frame, callback=self.changeMolecule, grid=(row, 1)) self.updateChains() row += 1 Label(frame, text='Residue ranges: ', grid=(row, 0)) tipText = 'Which residues should be included. Example: "10-35, 62-100, 130".' self.residueRangeEntry = Entry(frame, text=None, width=64, grid=(row, 1), isArray=True, returnCallback=self.updateResidueRanges, tipText=tipText, sticky='nsew') self.updateResidueRanges(fromChain=True) row += 1 self.energyPlot = ScrolledGraph(frame, symbolSize=2, width=600, height=200, title='Annealing', xLabel='temperature step', yLabel='energy') self.energyPlot.grid(row=row, column=0, columnspan=2, sticky='nsew') def runCalculations(self): '''Run all calculations. Also triggers the disabling of some buttons and fields. ''' self.startButton.disable() self.disableIllegalButtonsAfterPrecalculations() self.guiParent.connector.runAllCalculations() self.startButton.configure(text='More runs') self.startButton.enable() def disableIllegalButtonsAfterPrecalculations(self): '''Disable buttons and field the user can not alter any longer after the model is set up and the 'pre-calculations' have finished. This is done because this part of the calculation should only be run once. All settings that would be changed after this point will not have any influence. ''' illegalButtons = [self.minTypeScoreEntry, self.minLabelEntry, self.useAlsoUntypedSpinSystemsCheck, self.useAssignmentsCheck, self.useTypeCheck, self.useDimensionalAssignmentsCheck, self.useTentativeCheck] for illegalButton in illegalButtons: illegalButton.configure(state='disabled') self.molPulldown.disable() def getChainName(self, chain): '''Get the name for a chain. args: chain: ccpn analysis chain object returns: chain name ''' return '%s:%s (%s)' % (chain.molSystem.code, chain.code, chain.molecule.molType) def getChains(self): '''Get all chains present in the project. returns: list of ccpn analysis chain objects ''' chains = [] if self.project: for molSystem in self.project.sortedMolSystems(): for chain in molSystem.sortedChains(): if chain.residues: chains.append(chain) return chains def updateChains(self, *opt): '''Updates the list of chains if a new one is added to or deleted from the project. Updates the pull down list where a chain can be selected. ''' index = 0 texts = [] chains = self.getChains() chain = self.chain if chains: if chain not in chains: chain = chains[0] texts = [self.getChainName(c) for c in chains] index = chains.index(chain) else: chain = None self.molPulldown.setup(texts, chains, index) if chain is not self.chain: self.chain = chain def changeMolecule(self, chain): '''Select a molecular chain.''' if chain is not self.chain: self.chain = chain self.updateResidueRanges(fromChain=True) def updateStepEntry(self, event=None): '''Update the value and entry that sets the amount of steps per temperature point. ''' value = self.NAStepEntry.get() if value == self.amountOfSteps: return if value < 1: self.NAStepEntry.set(1) self.amountOfSteps = 1 else: self.amountOfSteps = value self.NAStepEntry.set(value) def updateRepeatEntry(self, event=None): '''Update the value and entry of that sets the amount of times the whole annealing procedure is repeated in order to obtain statistics. ''' value = self.repeatEntry.get() if value == self.amountOfRepeats: return if value < 1: self.repeatEntry.set(1) self.amountOfRepeats = 1 else: self.amountOfRepeats = value self.repeatEntry.set(value) def updateMinTypeScoreEntry(self, event=None): '''Updates the value and the entry for the treshhold value for amino acid typing. ''' value = self.minTypeScoreEntry.get() if value == self.minTypeScore: return if value < 0: self.minTypeScoreEntry.set(0.0) self.minTypeScore = 0.0 elif value > 100: self.minTypeScoreEntry.set(100.0) self.minTypeScore = 100.0 else: self.minTypeScoreEntry.set(value) self.minTypeScore = value def updateMinLabelEntry(self, event=None): '''Updates the minimum colabelling fraction for which a peak is expected to be present in the spectra. ''' value = self.minLabelEntry.get() if value == self.minIsoFrac: return if value < 0: self.minIsoFrac = 0.0 self.minLabelEntry.set(0.0) elif value > 1: self.minIsoFrac = 1.0 self.minLabelEntry.set(1.0) else: self.minIsoFrac = value self.minLabelEntry.set(value) def updateLeavePeaksOutEntry(self, event=None): '''Updates the value and entry of the fraction of peaks that should be left out in each run in order to diversify the results. ''' value = self.leaveOutPeaksEntry.get() if value == self.leavePeaksOutFraction: return if value < 0: self.leavePeaksOutFraction = 0.0 self.leaveOutPeaksEntry.set(0.0) elif value > 1: self.leavePeaksOutFraction = 1.0 self.leaveOutPeaksEntry.set(1.0) else: self.leavePeaksOutFraction = value self.leaveOutPeaksEntry.set(value) def updateAcceptanceConstantList(self, event=None): '''Updates the list with constants that are used during the monte carlo procedure to decide whether a changed is accepted or not. ''' acList = self.tempEntry.get() newList = [] for constant in acList: try: number = float(constant) newList.append(number) except ValueError: string = constant + \ ' in temperature constants is not a number.' showWarning('Not A Number', string, parent=self.guiParent) return False self.acceptanceConstantList = newList return True def updateResidueRanges(self, event=None, fromChain=False): self.residues = set() subRanges = self.residueRangeEntry.get() if not subRanges or fromChain: self.residues = set(self.chain.residues) residues = self.chain.sortedResidues() text = '{}-{}'.format(residues[0].seqCode, residues[-1].seqCode) self.residueRangeEntry.set(text=text) return for subRange in subRanges: indeces = subRange.split('-') start = int(indeces[0]) stop = int(indeces[-1]) + 1 for seqCode in range(start, stop): residue = self.chain.findFirstResidue(seqCode=seqCode) if not residue: showWarning('Residue out of range.', 'There is no residue at position {}'.format(seqCode), parent=self.guiParent) self.residues = set() return self.residues.add(residue) def addEnergyPoint(self, energy, time): '''Adds a point to the graph that shows the progress of the annealling procedure. args: energy: the y-value time: the x-value ''' point = (time, energy * -1) # This means one run has finished if len(self.energyDataSets[-1]) / (len(self.acceptanceConstantList) + 1): self.energyDataSets.append([point]) else: self.energyDataSets[-1].append(point) colors = colorSeries Ncolors = len(colors) NdataSets = len(self.energyDataSets) colorList = (NdataSets / Ncolors) * colors + \ colors[:NdataSets % Ncolors] self.energyPlot.update(dataSets=self.energyDataSets, dataColors=colorList) # Forcing the graph to draw, eventhough calculations # are still running. Only do this with high numbers of # steps, otherwise drawing takes longer than annealling. if self.amountOfSteps >= 100000: self.energyPlot.draw()