def __init__(self, guiParent):
'''Init. args: guiParent'''
self.chain = None
self.useAssignments = True
self.useTentative = True
self.reTypeSpinSystems = False
self.typeSpinSystems = True
self.useDimensionalAssignments = True
self.selectedSpectra = None
self.amountOfSteps = 0
self.amountOfRepeats = 0
self.minTypeScore = 0.01
self.leavePeaksOutFraction = 0.0
self.nmrProject = None
self.project = None
self.minIsoFrac = None
self.acceptanceConstantList = []
self.sourceName = None
self.ranAnnealling = False
self.ranPreCalculations = False
self.results = None
self.GUI = ViewAssignmentPopup(guiParent, self)
self.auto = Malandro()
#self.addEnergyPoint = self.GUI.annealingSettingsTab.addEnergyPoint
self.auto.registerTextObserver(self.updateInfoText)
self.auto.registerEnergyObserver(
self.GUI.annealingSettingsTab.addEnergyPoint)
class Connector(object):
'''This is just a little class that contains all
settings the user configures in the GUI.
It acts as a connector between the real logic
of the monte carlo procedure and the GUI.
'''
def __init__(self, guiParent):
'''Init. args: guiParent'''
self.chain = None
self.useAssignments = True
self.useTentative = True
self.reTypeSpinSystems = False
self.typeSpinSystems = True
self.useDimensionalAssignments = True
self.selectedSpectra = None
self.amountOfSteps = 0
self.amountOfRepeats = 0
self.minTypeScore = 0.01
self.leavePeaksOutFraction = 0.0
self.nmrProject = None
self.project = None
self.minIsoFrac = None
self.acceptanceConstantList = []
self.sourceName = None
self.ranAnnealling = False
self.ranPreCalculations = False
self.results = None
self.GUI = ViewAssignmentPopup(guiParent, self)
self.auto = Malandro()
#self.addEnergyPoint = self.GUI.annealingSettingsTab.addEnergyPoint
self.auto.registerTextObserver(self.updateInfoText)
self.auto.registerEnergyObserver(
self.GUI.annealingSettingsTab.addEnergyPoint)
def update(self):
'''Pulls all settings out of the GUI and gives
them to the assignment algorithm written in Cython.
'''
self.chain = self.GUI.annealingSettingsTab.chain
self.useAssignments = self.GUI.annealingSettingsTab.useAssignmentsCheck.get()
self.useTentative = self.GUI.annealingSettingsTab.useTentativeCheck.get()
self.reTypeSpinSystems = not self.GUI.annealingSettingsTab.useTypeCheck.get()
self.typeSpinSystems = self.GUI.annealingSettingsTab.useAlsoUntypedSpinSystemsCheck.get()
self.useDimensionalAssignments = self.GUI.annealingSettingsTab.useDimensionalAssignmentsCheck.get()
self.amountOfRepeats = self.GUI.annealingSettingsTab.amountOfRepeats
self.amountOfSteps = self.GUI.annealingSettingsTab.amountOfSteps
self.minTypeScore = self.GUI.annealingSettingsTab.minTypeScore
self.leavePeaksOutFraction = self.GUI.annealingSettingsTab.leavePeaksOutFraction
self.nmrProject = self.GUI.nmrProject
self.project = self.GUI.project
self.minIsoFrac = self.GUI.annealingSettingsTab.minIsoFrac
#self.sourceName = self.GUI.sourceName
self.selectedSpectra = []
for spec in self.GUI.spectrumSelectionTab.specConfigList:
if spec.used:
self.selectedSpectra.append(spec)
self.GUI.annealingSettingsTab.updateAcceptanceConstantList()
self.acceptanceConstantList = self.GUI.annealingSettingsTab.acceptanceConstantList
self.residuesInRange = self.GUI.annealingSettingsTab.residues
self.auto.updateSettings(self)
def runAllCalculations(self):
'''Run all calculations. This includes all
calculations that have to be carried out
before the annealing starts and the annealing
itself.
'''
if not self.ranPreCalculations:
self.update()
self.GUI.annealingSettingsTab.disableIllegalButtonsAfterPrecalculations()
self.preCalculateDataModel()
self.startAnnealing()
def preCalculateDataModel(self):
'''Run all calculations that have to be carried
out before the annealing can run. This is mainly
setting up a data model, simulating spectra and
matching those simulated spectra with the real
spectra.
'''
print 'updating'
self.update()
if self.checkPoint1():
print 'precalculate data model'
self.auto.preCalculateDataModel()
self.ranPreCalculations = True
def startAnnealing(self):
'''Run the annealing.'''
if self.checkPoint2():
self.auto.startMonteCarlo(amountOfRuns=self.amountOfRepeats,
stepsPerTemperature=self.amountOfSteps,
acceptanceConstants=self.acceptanceConstantList,
fractionOfPeaksLeftOut=self.leavePeaksOutFraction)
self.ranAnnealling = True
self.getResults()
# createBenchmark(self.results)
# TODO: this is not very nice
self.GUI.resultsTab.dataModel = self.results
self.GUI.resultsTab.update()
self.GUI.assignTab.update()
def checkPoint1(self):
'''First of two checkpoints, is run before the precalculations.
Here the labelling scheme and the chain information is checked.
Returns True if it is safe to proceed. Returns False otherwise.
'''
if self.checkSpectraAndLabelling() and self.checkChain():
return True
else:
return False
def checkPoint2(self):
'''Second of two checkpoints, is run before the annealing starts.
It is checked whether the precalculations already ran and whether
the list with acceptance constants is valid.
Returns True if it is safe to proceed. Returns False otherwise.
'''
if self.ranPreCalculations:
if self.GUI.annealingSettingsTab.updateAcceptanceConstantList():
return True
else:
string = '''Without running the pre-calculations,
the annealing can not run.
'''
showWarning('Run pre-calculations first', string, parent=self.GUI)
return False
def checkSpectraAndLabelling(self):
'''Check whether some spectra are selected by the user
and whether a reference experiment has been set
for this experiment (needed to simulate the spectra)
and if the user said the labelling scheme should
come automatically from the labelled sample,
the labelled mixture should be set.
'''
if not self.selectedSpectra:
string = 'Select one or more spectra.'
showWarning('No Spectra Selected', string, parent=self.GUI)
return False
for spec in self.selectedSpectra:
name = spec.ccpnSpectrum.experiment.name
if not spec.ccpnSpectrum.experiment.refExperiment:
string = name + (''' has no reference experiment, '''
'''go to Experiment --> Experiments --> '''
'''Experiment Types and select '''
'''a experiment type.''')
showWarning('No Reference Experiment',
string, parent=self.GUI)
return False
mixtures = spec.ccpnSpectrum.experiment.labeledMixtures
if spec.labellingScheme is True and not mixtures:
string = name + (''' is not connected to any labelled'''
''' sample.In order to determine the'''
''' labelling scheme automatically'''
''' from the experiment, this has to'''
''' be set. Go to'''
''' Menu-Modecule-Isotope Labelling'''
''' to do so.''')
showWarning('No Labelled Sample', string, parent=self.GUI)
return False
elif len(mixtures) > 1:
string = name + (''' is connected to more than one labelled'''
''' sample. This is physically impossible.'''
''' Go to Menu-Modecule-Isotope Labelling'''
''' if you want to change this.''')
showWarning('Multiple Labelled Samples for Spectrum',
string, parent=self.GUI)
return False
return True
def checkChain(self):
'''Checks whether a chain is configured
and whether this chain has residues.
'''
if not self.chain:
string = 'Setup a molecular chain in Molecule --> Molecules'
showWarning('No chain selected', string, parent=self.GUI)
return False
if not self.chain.residues:
string = '''The selected chain does not have residues,
set up the residues in
Molecule --> Molecules --> Sequences
'''
showWarning('No Residues', string, parent=self.GUI)
return False
return True
def getResults(self):
'''Gets the results from the assignment algorithm.
'''
if self.ranAnnealling:
self.results = self.auto.getResults()
def updateInfoText(self, text):
'''Update the string with information that is
displayed to the used in the GUI and the terminal.
'''
print text
self.GUI.updateInfoText(text)
def saveDataToPyc(self, fileName):
'''Pickle the data model and save it to file to
be use later. Since this storage method relies
on pickle, it is not guaranteed that the data
can be loaded in future versions of this macro.
'''
if self.results:
if not fileName[-4:] == '.pyc':
fileName = fileName + '.pyc'
if os.path.exists(fileName):
if not showYesNo('File exists',
'File "%s" exists, overwrite?' % fileName,
parent=self.GUI):
return
self.updateInfoText('Saving results...')
writeFile = open(fileName, 'wb')
cPickle.dump(self.results, writeFile, protocol=2)
writeFile.close()
self.updateInfoText('Results succesfully saved.')
else:
string = 'There are no results to save at the moment.'
showWarning('No results to save', string, parent=self.GUI)
def loadDataFromPyc(self, fileName):
'''Load previously pickled data.
args: fileName: name of the file
'''
self.updateInfoText('Loading file...')
# TODO : fix this, getting these values from the GUI is ridiculous
self.project = self.GUI.project
self.nmrProject = self.GUI.nmrProject
results = None
fileExists = False
if os.path.exists(fileName):
fileExists = True
elif os.path.exists(fileName + '.pyc'):
fileName = fileName + '.pyc'
fileExists = True
if fileExists:
try:
with open(fileName, 'rb') as readFile:
results = cPickle.load(readFile)
except:
string = ('''Something went wrong when trying to '''
'''load the previously produced results. '''
'''Probably the file you try to '''
'''open is not of the correct type.''')
print string
showWarning('Can not open file', string, parent=self.GUI)
raise
if results:
if isinstance(results, DataModel):
self.results = results
self.updateInfoText('File loaded succesfully.')
self.updateInfoText(('''Re-connecting to object in '''
'''the ccpn analysis project...'''))
self.results.connectToProject(self.project,
self.nmrProject)
# TODO: this is not very nice
self.GUI.resultsTab.dataModel = self.results
self.updateInfoText('Done')
return
else:
string = (('''You are trying to open a file that '''
'''was not created using this macro.'''))
showWarning('Can not open file', string, parent=self.GUI)
else:
string = 'The file you selected does not exist.'
showWarning('No Such File', string, parent=self.GUI)
self.updateInfoText(' ')
