class ApplicationPopup(AnalysisPopup):
help_url = 'http://www.ccpn.ac.uk'
allowedCallbackFuncnames = ('init', 'save', 'close')
def __init__(self, root, programName='Extend-NMR Interface'):
self.font = DEFAULT_FONT
# Application object needed to store application-specific data with project
self.application = Application(name=PROGRAM_NAME)
self.versionInfo = 'Version' + VERSION
self.ariaProjectFile = None
self.doneAnalysisInfo = False
self.updateFuncs = []
self.projButtons = []
self.ariaPaths = []
self.isdPaths = []
AnalysisPopup.__init__(self, root)
self.program_name = PROGRAM_NAME
self.setTitle(PROGRAM_NAME)
def printAnalysisCommandLineInfo(self, event):
if not self.doneAnalysisInfo:
Analysis.printCommandLineInfo(self)
self.doneAnalysisInfo = True
def printCommandLineInfo(self):
print """
For program documentation see:
http://www.extend-nmr.eu
"""
def body(self, guiParent):
self.menus = {}
self.menu_items = {}
self.fixedActiveMenus = {}
self.popups = {}
self.callbacksDict = {}
self.selected_objects = []
self.menubar = menubar = Menu(guiParent)
self.font = DEFAULT_FONT
self.setProjectMenu()
#
menu = Menu(self.menubar, tearoff=0)
menu.bind('<Button>', self.printAnalysisCommandLineInfo)
self.menubar.add_cascade(label='CcpNmr Analysis',
shortcut='C',
menu=menu)
self.menubar.add_command(label='FormatConverter',
shortcut='F',
command=self.runFormatConverter)
self.menubar = menu
self.initProject()
self.setPeaksMenu()
self.setMoleculeMenu()
self.setAssignMenu()
self.setResonanceMenu()
self.setDataMenu()
self.setStructureMenu()
self.setChartMenu()
self.setMacroMenu()
self.setOtherMenu()
self.setMenuState() # need to do it again because of OtherMenu state
# Help Submenu
helpMenu = Menu(self.menubar, tearoff=0)
helpMenu.add_command(label='Version',
shortcut='V',
command=self.showVersion)
helpMenu.add_command(label='About',
shortcut='A',
command=self.showAbout)
helpMenu.add_command(label='Help', shortcut='H', command=self.showHelp)
menu.add_separator()
menu.add_command(label='CCPN Updates',
shortcut='U',
image=self.iconRefresh,
compound='left',
command=self.updateAnalysis,
tipText='Get any new patches and updates to CcpNmr')
menu.add_cascade(label='CCPN Help',
shortcut='H',
image=self.iconHelp,
compound='left',
menu=helpMenu)
self.config(menu=menubar)
# Ensure that the first row and column in popup expand
guiParent.grid_rowconfigure(0, weight=1)
guiParent.grid_columnconfigure(0, weight=1, minsize=200)
frame = Frame(guiParent) # Body widgets can be put in this frame
frame.grid()
softwareOpts = [
'Extend-NMR', 'ARIA 2', 'Auremol', 'CING', ' ECI ', 'HADDOCK',
' ISD ', 'PRODECOMP'
]
self.tabbedFrame = TabbedFrame(guiParent,
options=softwareOpts,
toggleOff=False,
selected=0,
callback=self.toggleTab)
self.tabbedFrame.grid(row=0, column=0, sticky='nsew')
frames = self.tabbedFrame.frames
# Logos
ccpnDir = getTopDirectory()
imageDir = os.path.join(ccpnDir, 'python', 'extendNmr', 'images')
imageFile = os.path.join(imageDir, 'Fp6Logo.gif')
self.fp6Logo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'CingLogo.gif')
self.cingLogo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'AriaLogo.gif')
self.ariaLogo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'IsdLogo.gif')
self.isdLogo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'HaddockLogo.gif')
self.haddockLogo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'AuremolLogo.gif')
self.auremolLogo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'CcpnLogo.gif')
self.ccpnLogo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'ProdecompLogo.gif')
self.prodecompLogo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'MddLogo.gif')
self.mddLogo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'BrukerLogo.gif')
self.brukerLogo = Tkinter.PhotoImage(file=imageFile)
imageFile = os.path.join(imageDir, 'MsdLogo.gif')
self.msdLogo = Tkinter.PhotoImage(file=imageFile)
self.initExtendNmr(frames[0])
self.initAria(frames[1])
self.initAuremol(frames[2])
self.initCing(frames[3])
self.initEci(frames[4])
self.initHaddock(frames[5])
self.initIsd(frames[6])
self.initProdecomp(frames[7])
self.initProject(self.project)
if not self.project:
for button in self.projButtons:
button.disable()
self.geometry('680x670')
def setProjectMenu(self):
ProjectMenu = 'Project'
# Imports submenu
importsMenu = Menu(self.menubar, tearoff=False)
importsMenu.add_command(label='Via Format Converter',
shortcut='F',
command=self.runFormatConverter)
importsMenu.add_command(label='NMR-STAR 2.1.1',
command=self.importNmrStar211)
importsMenu.add_command(label='NMR-STAR 3.1',
shortcut='N',
command=self.importNmrStar31)
importsMenu.add_command(label='PDB 3.20',
shortcut='P',
command=self.importPdb)
importsMenu.add_command(label='Coordinates (PDB-style)',
shortcut='C',
command=self.importCoordinates)
# Preferences submenu
fontsMenu = FontMenu(self.menubar,
self.selectFont,
sizes=(8, 10, 12),
doItalic=False,
doBoldItalic=False,
tearoff=0)
prefsMenu = Menu(self.menubar, tearoff=False)
prefsMenu.add_cascade(
label='Fonts',
shortcut='F',
image=self.iconFont,
compound='left',
menu=fontsMenu,
tipText='Select font to use in the graphical interface')
prefsMenu.add_command(label='Colour Schemes',
image=self.iconTable,
compound='left',
shortcut='C',
tipText='Edit and create colour schemes',
command=self.editColorSchemes)
prefsMenu.add_command(
label='Residue Codes',
image=self.iconTable,
compound='left',
shortcut='R',
tipText=
'User-specified codes that override the standard residue names',
command=self.editResidueCodes)
prefsMenu.add_command(label='User Options',
image=self.iconTable,
compound='left',
shortcut='U',
tipText='General options for Analysis behaviour',
command=self.editProfiles)
#
menu = Menu(self.menubar, tearoff=0)
menu.add_command(
label='New',
shortcut='N',
image=self.iconNewWindow,
compound='left',
command=self.newProject,
tipText='Create a new, blank CCPN project (closes any open project)'
)
menu.add_command(
label='Open Project',
shortcut='O',
image=self.iconOpen,
compound='left',
command=self.openProject,
tipText=
'Open a new CCPN project by selecting a project directory on disk')
menu.add_command(
label='Open Spectra',
shortcut='p',
image=self.iconOpenFile,
compound='left',
command=self.openSpectrum,
tipText=
'Open spectrum data fom disk, creating a default CCPN project if needed'
)
menu.add_command(label='Save',
shortcut='S',
image=self.iconSave,
compound='left',
command=self.saveProject,
tipText='Save the current CCPN project on disk')
menu.add_command(
label='Save As',
shortcut='A',
image=self.iconSaveAs,
compound='left',
command=self.saveAsProject,
tipText=
'Save the current CCPN project under a different name (project directory)'
)
menu.add_cascade(label='Import',
shortcut='I',
image=self.iconImport,
compound='left',
menu=importsMenu)
menu.add_command(label='Close',
shortcut='C',
image=self.iconClose,
compound='left',
command=self.closeProject,
tipText='Close the current CCPN project')
menu.add_command(
label='Quit',
shortcut='Q',
image=self.iconQuit,
compound='left',
command=self.quit,
tipText='Quit Extend-NMR, closing any open CCPN project')
menu.add_separator()
menu.add_cascade(label='Preferences',
shortcut='P',
image=self.iconPrefs,
compound='left',
menu=prefsMenu)
menu.add_command(
label='Validate',
shortcut='V',
image=self.iconTool,
compound='left',
command=self.validateProject,
tipText=
'Check the current CCPN project for data model consistency errors')
menu.add_command(
label='Backup',
shortcut='B',
image=self.iconTool,
compound='left',
command=self.backupProject,
tipText='Setup options for automated backup of CCPN project data')
menu.add_command(
label='Archive',
shortcut='r',
image=self.iconTool,
compound='left',
command=self.archiveProject,
tipText=
'Save the current CCPN project in an archived form, e.g. tar gzipped'
)
self.menubar.add_cascade(label=ProjectMenu, shortcut='j', menu=menu)
self.menus[ProjectMenu] = menu
self.menu_items[ProjectMenu] = [
'New',
'Open Project',
'Open Spectra',
'Save',
'Save As',
'Import',
'Close',
'Quit',
'Preferences',
'Validate',
'Backup',
'Archive',
]
# Menus that area ctive in absence of a project
#for ii in (0,1,2,7,13,15):
for ii in (
0,
1,
2,
7,
):
self.fixedActiveMenus[(ProjectMenu, ii)] = True
def setPopupGeometries(self):
for key in self.popups.keys():
popup = self.popups[key]
if not key.startswith(window_popup_prefix): # bit of a hack
not self.setPopupGeometry(popup, key)
def toggleTab(self, index):
if (index > 0) and not self.project:
showWarning('Warning', 'No active project', parent=self)
self.tabbedFrame.select(0)
return
frame = self.tabbedFrame.frames[index]
if hasattr(frame, 'printOutDocString'):
print frame.printOutDocString
# only print it once
del frame.printOutDocString
def initCing(self, frame):
frame.grid_columnconfigure(0, weight=1)
frame.grid_rowconfigure(1, weight=1)
canvas = Tkinter.Canvas(frame, width=702, height=77)
canvas.grid(row=0, column=0, sticky='ew')
canvas.create_image(0, 0, anchor='nw', image=self.cingLogo)
cingFrame = CingFrame(frame, self)
cingFrame.grid(row=1, column=0, sticky='nsew')
#self.projButtons.extend(cingFrame.buttonBar.buttons)
self.updateFuncs.append(cingFrame.updateAll)
def initProdecomp(self, frame):
frame.grid_columnconfigure(0, weight=1)
frame.grid_rowconfigure(1, weight=1)
frame.configure(bg='#FFFFFF')
canvas = Tkinter.Canvas(frame, width=1024, height=90, bg='#FFFFFF')
canvas.grid(row=0, column=0, sticky='ew')
canvas.create_image(0, 0, anchor='nw', image=self.prodecompLogo)
prodecompFrame = ProdecompFrame(frame,
basePopup=self,
ccpnProject=self.project)
prodecompFrame.grid(row=1, column=0, sticky='nsew')
# set printOutDocString:
frame.printOutDocString = prodecompFrame.printOutDocString
#self.projButtons.extend(isdFrame.buttons)
self.updateFuncs.append(prodecompFrame.updateAll)
def initAuremol(self, frame):
frame.expandGrid(1, 0)
refText = """Gronwald W, Brunner K, Kirchhofer R, Nasser A, Trenner J, Ganslmeier B,
Riepl H, Ried A, Scheiber J, Elsner R, Neidig K-P, Kalbitzer HR
AUREMOL, a New Program for the Automated Structure Elucidation of
Biological Macromolecules. Bruker Reports 2004; 154/155: 11-14
"""
canvas = Tkinter.Canvas(frame, width=700, height=160, bg='#FFFFFF')
canvas.grid(row=0, column=0, sticky='ew')
canvas.create_image(12, 12, anchor='nw', image=self.auremolLogo)
canvas.create_text(200, 10, anchor='nw', text=refText)
auremolFrame = AuremolFrame(frame, self.project, grid=(1, 0))
#self.projButtons.extend(isdFrame.buttons)
self.updateFuncs.append(auremolFrame.updateAll)
def initEci(self, frame):
frame.grid_columnconfigure(0, weight=1)
frame.grid_rowconfigure(1, weight=1)
frame.parent = self # For notifiers
frame.configure(bg='#FFFFFF')
canvas = Tkinter.Canvas(frame,
width=800,
height=73,
bd=3,
bg='#FFFFFF')
canvas.grid(row=0, column=0, sticky='ew')
canvas.create_image(10, 10, anchor='nw', image=self.msdLogo)
eciFrame = EntryCompletionFrame(frame, basePopup=self)
eciFrame.grid(row=1, column=0, sticky='nsew')
#self.projButtons.extend(isdFrame.buttons)
self.updateFuncs.append(eciFrame.updateAll)
def initHaddock(self, frame):
frame.grid_columnconfigure(0, weight=1)
frame.grid_rowconfigure(1, weight=1)
frame.parent = self # For notifiers
canvas = Tkinter.Canvas(frame, width=753, height=92)
canvas.grid(row=0, column=0, sticky='ew')
canvas.create_image(0, 0, anchor='nw', image=self.haddockLogo)
haddockFrame = HaddockFrame(frame, self.project)
haddockFrame.grid(row=1, column=0, sticky='nsew')
#self.projButtons.extend(isdFrame.buttons)
self.updateFuncs.append(haddockFrame.updateAll)
def initIsd(self, frame):
global isd
frame.grid_columnconfigure(0, weight=1)
frame.grid_rowconfigure(1, weight=1)
frame.configure(bg='#FFFFFF')
canvas = Tkinter.Canvas(frame,
width=800,
height=91,
bd=3,
bg='#FFFFFF')
canvas.grid(row=0, column=0, sticky='ew', padx=0)
canvas.create_image(0, 0, anchor='nw', image=self.isdLogo)
isdFrame = IsdFrame(frame, self.project)
isdFrame.grid(row=1, column=0, sticky='nsew')
self.isd = isdFrame
isd = self.isd
#self.projButtons.extend(isdFrame.buttons)
self.updateFuncs.append(isdFrame.updateAll)
def initExtendNmr(self, frame):
row = 0
frame.config(bd=5)
canvas = Tkinter.Canvas(frame,
width=640,
height=600,
bg='#FFFFFF',
bd=5)
canvas.grid(row=row, column=0, sticky='nsew')
canvas.create_image(15, 15, anchor='nw', image=self.fp6Logo)
canvas.create_image(330, 15, anchor='nw', image=self.prodecompLogo)
canvas.create_image(330, 115, anchor='nw', image=self.mddLogo)
canvas.create_image(20, 200, anchor='nw', image=self.ccpnLogo)
canvas.create_image(230, 220, anchor='nw', image=self.msdLogo)
canvas.create_image(450, 200, anchor='nw', image=self.brukerLogo)
canvas.create_image(5, 310, anchor='nw', image=self.isdLogo)
canvas.create_image(230, 300, anchor='nw', image=self.ariaLogo)
canvas.create_image(450, 290, anchor='nw', image=self.auremolLogo)
canvas.create_image(5, 420, anchor='nw', image=self.haddockLogo)
canvas.create_image(5, 520, anchor='nw', image=self.cingLogo)
#row += 1
#l1 = Label(frame, text='Welcome to the Extend NMR suite')
#l1.grid(row=row, column=0, sticky='ew')
def initAria(self, frame):
welcomeMessage = \
"""ARIA Version 2.3. Authors: Benjamin Bardiaux, Michael Habeck,
Jens Linge, Therese Malliavin, Sean O'Donoghue, Wolfgang Rieping,
and Michael Nilges.
Rieping W., Habeck M., Bardiaux B., Bernard A., Malliavin T.E.,
Nilges M.(2007) ARIA2: automated NOE assignment and data
integration in NMR structure calculation. Bioinformatics 23:381-382"""
frame.grid_columnconfigure(0, weight=1)
frame.grid_rowconfigure(1, weight=1)
canvas = Tkinter.Canvas(frame, width=700, height=114, bg='#FFFFFF')
canvas.grid(row=0, column=0, sticky='ew')
canvas.create_image(0, 0, anchor='nw', image=self.ariaLogo)
canvas.create_text(250, 10, anchor='nw', text=welcomeMessage)
ariaFrame = AriaFrame(frame, self)
ariaFrame.grid(row=1, column=0, sticky='nsew')
self.projButtons.extend(ariaFrame.buttons)
self.updateFuncs.append(ariaFrame.updateAll)
def openPopup(self, popup_name, clazz, oldStyle=False, *args, **kw):
popup = self.popups.get(popup_name)
if (popup):
popup.open()
else:
if self.project:
analysisProfile = self.analysisProfile
else:
analysisProfile = None
if analysisProfile:
if popup_name.startswith(window_popup_prefix): # bit of a hack
transient = analysisProfile.transientWindows
else:
transient = analysisProfile.transientDialogs
else:
transient = True
name = popup_name
if (oldStyle):
popup = self.popups[popup_name] = clazz(self,
transient=transient,
*args,
**kw)
else:
popup = self.popups[popup_name] = clazz(self,
project=self.project,
popup_name=name,
transient=transient,
*args,
**kw)
# above automatically opens popup
return popup
def initProject(self, project=None):
AnalysisPopup.initProject(self, project, False)
self.project = project
if project:
for i, func in enumerate(self.updateFuncs):
func(project)
for button in self.projButtons:
button.enable()
else:
for button in self.projButtons:
button.disable()
def setupSoftware(self):
return
project = self.project
methodStore = project.currentMethodStore or \
project.findFirstMethodStore() or \
project.newMethodStore(name=project.name)
software = methodStore.findFirstSoftware(name=PROGRAM_NAME,
version=VERSION)
if not software:
software = methodStore.newSoftware(name=PROGRAM_NAME,
version=VERSION)
software.task = 'data pipeline'
software.vendorName = 'The Extend-NMR Project'
#software.vendorAddress = ''
software.vendorWebAddress = 'http://www.extend-nmr.eu'
class RelaxationAnalysisPopup(BasePopup):
def __init__(self, parent, *args, **kw):
self.guiParent = parent
self.t1List = None
self.t2List = None
self.noeList = None
self.waiting = False
BasePopup.__init__(self, parent, title="Relaxation Analyses", **kw)
periodicTable = self.project.currentChemElementStore
nitrogen = periodicTable.findFirstChemElement(elementSymbol='N')
hydrogen = periodicTable.findFirstChemElement(elementSymbol='H')
def body(self, guiFrame):
self.geometry('700x840')
guiFrame.expandGrid(1,0)
# Top frame
frame = Frame(guiFrame, grid=(0,0))
frame.expandGrid(None,8)
label = Label(frame, text=u' %s List:' % T1, grid=(0,0))
self.t1Pulldown = PulldownList(frame, callback=self.selectT1List, grid=(0,1))
label = Label(frame, text=u' %s List:' % T2, grid=(0,2))
self.t2Pulldown = PulldownList(frame, callback=self.selectT2List, grid=(0,3))
label = Label(frame, text=' NOE List:', grid=(0,4))
self.noePulldown = PulldownList(frame, callback=self.selectNoeList, grid=(0,5))
label = Label(frame, text=' Spectrometer Freq (MHz):', grid=(0,6))
self.sfEntry = FloatEntry(frame, grid=(0,7), text=600.00, width=6)
UtilityButtonList(frame, grid=(0,9), sticky='e')
# Tabs
options = [u'%s vs %s Scatter' % (T1, T2),
u'%s,%s & NOE Graphs' % (T1, T2) ,
u'%s/%s Graph' % (T1, T2),
u'%s Estimate Graph' % S2,
'Options']
self.tabbedFrame = TabbedFrame(guiFrame, options=options,
callback=self.toggleTab, grid=(1,0))
frameA, frameD, frameC, frameE, frameB = self.tabbedFrame.frames
# T1 vs T2 Graph
frameA.expandGrid(0,0)
self.t1t2Graph = T1VersesT2Plot(frameA, grid=(0,0))
# T1 & T2 Graph
frameD.expandGrid(0,0)
frameD.expandGrid(1,0)
frameD.expandGrid(2,0)
self.t1Graph = MeasurementPlot(frameD, T1, grid=(0,0))
self.t2Graph = MeasurementPlot(frameD, T2, grid=(1,0))
self.noeGraph = NoePlot(frameD, 'NOE', grid=(2,0))
# T1 over T2 Graph
frameC.expandGrid(0,0)
self.t1t2GraphB = T1OverT2Plot(frameC, grid=(0,0))
# Order params graph
frameE.expandGrid(0,0)
frameE.expandGrid(1,0)
frameE.expandGrid(2,0)
self.s2Graph = ScrolledGraph(frameE, title=u'%s vs Residue Sequence' % S2,
xLabel='Residue number', yLabel=S2,
width=500, height=150, graphType='histogram',
xGrid=True, yGrid=False, grid=(0,0),
dataColors=['#0000A0','#808000'],
dataNames=['Isotropic',])
self.teGraph = ScrolledGraph(frameE, title=u'%s vs Residue Sequence' % Te,
xLabel='Residue number', yLabel=u'%s (ps)' % Te,
width=500, height=150, graphType='histogram',
xGrid=True, yGrid=False, grid=(1,0),
dataColors=['#008000',])
self.rexGraph = ScrolledGraph(frameE, title=u'%s vs Residue Sequence' % 'Rex',
xLabel='Residue number', yLabel='Rex',
width=500, height=150, graphType='histogram',
xGrid=True, yGrid=False, grid=(2,0),
dataColors=['#900000',])
# Options
frameB.expandGrid(4,2)
frame = LabelFrame(frameB, text='Physical Params', grid=(0,0))
frame.expandGrid(None,3)
label = Label(frame, text=u'N-H bond length (\u00C5)', grid=(0,0))
self.lenNhEntry = FloatEntry(frame, text=1.015, grid=(0,1), width=8)
label = Label(frame, text=u'Internal correlation\ntime, \u03C4e (ps)', grid=(1,0))
self.ictEntry = FloatEntry(frame, text=50.0, grid=(1,1), width=8)
label = Label(frame, text=u'15N Chemical Shift\nAnisotopy,\u0394N (ppm)',
grid=(2,0))
self.csaNEntry = FloatEntry(frame, text=-160.0, grid=(2,1), width=8)
frame = LabelFrame(frameB, text=u'%s vs %s Scatter' % (T1, T2), grid=(1,0))
label = Label(frame, text='Max cluster difference (ms):', grid=(0,0))
self.clusterDictEntry = FloatEntry(frame, text=20.0, grid=(0,1), width=8)
label = Label(frame, text='Min cluster size:', grid=(1,0))
self.clusterSizeEntry = FloatEntry(frame, text=5, grid=(1,1), width=8)
label = Label(frame, text=u'Min graph %s (ms):' % T1, grid=(2,0))
self.minT1Entry = FloatEntry(frame, text=300.0, grid=(2,1), width=8)
label = Label(frame, text=u'Max graph %s (ms):' % T1, grid=(3,0))
self.maxT1Entry = FloatEntry(frame, text=1000.0, grid=(3,1), width=8)
label = Label(frame, text=u'Min graph %s (ms):' % T2, grid=(4,0))
self.minT2Entry = FloatEntry(frame, text=0.0, grid=(4,1), width=8)
label = Label(frame, text=u'Max graph %s (ms):' % T2, grid=(5,0))
self.maxT2Entry = FloatEntry(frame, text=600.0, grid=(5,1), width=8)
frame = LabelFrame(frameB, text=u'%s Contours' % S2, grid=(0,1))
frame.expandGrid(4,3)
label = Label(frame, text='(Order Parameter Lines)',
grid=(0,0), gridSpan=(1,2))
label = Label(frame, text='Min value:', grid=(1,0))
self.minS2Entry = FloatEntry(frame, text=0.3, grid=(1,1), width=8)
label = Label(frame, text='Max value:', grid=(2,0))
self.maxS2Entry = FloatEntry(frame, text=1.0, grid=(2,1), width=8)
label = Label(frame, text='Step:', grid=(3,0))
self.stepS2Entry = FloatEntry(frame, text=0.1, grid=(3,1), width=8)
frame = LabelFrame(frameB, text=u'\u03C4m Contours', grid=(1,1))
frame.expandGrid(4,3)
label = Label(frame, text='(Rotational Correlation Time Lines)',
grid=(0,0), gridSpan=(1,2))
label = Label(frame, text='Min value (ns):', grid=(1,0))
self.minRctEntry = FloatEntry(frame, text=5.0, grid=(1,1), width=8)
label = Label(frame, text='Max value (ns):', grid=(2,0))
self.maxRctEntry = FloatEntry(frame, text=14.0, grid=(2,1), width=8)
label = Label(frame, text='Step (ns):', grid=(3,0))
self.stepRctEntry = FloatEntry(frame, text=1.0, grid=(3,1), width=8)
# Bottom frame
texts = [u'Show %s Table' % T1,u'Show %s Table' % T2, u'Estimate %s' % S2]
commands = [self.showT1List, self.showT2List, self.mc]
buttonList = ButtonList(guiFrame, grid=(2,0), texts=texts, commands=commands)
# Update
self.updateRelaxationLists()
self.drawAfter()
self.administerNotifiers(self.registerNotify)
def open(self):
self.updateRelaxationLists()
self.drawAfter()
BasePopup.open(self)
def destroy(self):
self.administerNotifiers(self.unregisterNotify)
BasePopup.destroy(self)
def getSanitisedParams(self):
cDist = self.clusterDictEntry.get() or 0.0
lenNh = max(min(self.lenNhEntry.get() or 1.015, 1.2), 0.8)
ict = self.ictEntry.get() or 0.0
csaN = self.csaNEntry.get() or -180.0
if csaN > 0:
csaN *= -1.0
minS2 = max(min(self.minS2Entry.get() or 0.0, 0.9), 0.0)
maxS2 = max(min(self.maxS2Entry.get() or 1.0, 1.0), 0.1)
if minS2 > maxS2:
maxS2, minS2 = minS2, maxS2
stepS2 = max(self.stepS2Entry.get() or 0.1, (maxS2-minS2)/100)
minRct = self.minRctEntry.get()
maxRct = self.maxRctEntry.get()
if minRct > maxRct:
maxRct, minRct = minRct, maxRct
stepRct = max(self.stepRctEntry.get() or 0.1, (maxRct-minRct)/100)
cluster = max(abs(self.clusterSizeEntry.get() or 10), 1)
minT1 = self.minT1Entry.get() or 300.0
maxT1 = self.maxT1Entry.get() or 1000.0
minT2 = self.minT2Entry.get() or 0.0
maxT2 = self.maxT2Entry.get() or 600.0
if minT1 < 0:
minT1 = 0.0
if minT2 < 0:
minT2 = 0.0
if maxT1 < 0:
maxT1 = 0.0
if maxT2 < 0:
maxT2 = 0.0
if minT1 > maxT1:
minT1, maxT1 = maxT1, minT1
if minT2 > maxT2:
minT2, maxT2 = maxT2, minT2
if minT1 == maxT1:
maxT1 += 100
if minT2 == maxT2:
maxT2 += 100
self.clusterSizeEntry.set(cluster)
self.minT1Entry.set(minT1)
self.maxT1Entry.set(maxT1)
self.minT2Entry.set(minT2)
self.maxT2Entry.set(maxT2)
self.clusterDictEntry.set(cDist)
self.lenNhEntry.set(lenNh)
self.ictEntry.set(ict)
self.csaNEntry.set(csaN)
self.minS2Entry.set(minS2)
self.maxS2Entry.set(maxS2)
self.stepS2Entry.set(stepS2)
self.minRctEntry.set(minRct)
self.maxRctEntry.set(maxRct)
self.stepRctEntry.set(stepRct)
paramsS2 = (minS2, maxS2, stepS2)
paramsRct = (minRct, maxRct, stepRct)
tBounds = (minT1, maxT1, minT2, maxT2)
return cluster, cDist, lenNh, ict, csaN, paramsS2, paramsRct, tBounds
def administerNotifiers(self, notifyFunc):
for func in ('__init__', 'delete','setName'):
for clazz in ('ccp.nmr.Nmr.T1List','ccp.nmr.Nmr.T2List'):
notifyFunc(self.updateRelaxationLists,clazz, func)
for func in ('__init__', 'delete', 'setValue'):
notifyFunc(self.updateMeasurementAfter,'ccp.nmr.Nmr.T1', func)
notifyFunc(self.updateMeasurementAfter,'ccp.nmr.Nmr.T2', func)
def showT1List(self):
if self.t1List:
self.guiParent.editMeasurements(self.t1List)
def showT2List(self):
if self.t2List:
self.guiParent.editMeasurements(self.t2List)
def toggleTab(self, index):
if index == 0:
self.drawAfter()
def updateMeasurementAfter(self, measurement):
if measurement.parentList in (self.t1List, self.t2List):
self.drawAfter()
def updateRelaxationLists(self, obj=None):
mLists = self.nmrProject.sortedMeasurementLists()
# T1
t1List = self.t1List
t1Lists = [ml for ml in mLists if ml.className == 'T1List']
index = 0
names = []
if t1Lists:
if t1List not in t1Lists:
t1List = t1Lists[0]
index = t1Lists.index(t1List)
names = [ml.name or 'List %d' % ml.serial for ml in t1Lists]
else:
t1List = None
self.selectT1List(t1List)
self.t1Pulldown.setup(names, t1Lists, index)
# T2
t2List = self.t2List
t2Lists = [ml for ml in mLists if ml.className == 'T2List']
index = 0
names = []
if t2Lists:
if t2List not in t2Lists:
t2List = t2Lists[0]
index = t2Lists.index(t2List)
names = [ml.name or 'List %d' % ml.serial for ml in t2Lists]
else:
t2List = None
self.selectT2List(t2List)
self.t2Pulldown.setup(names, t2Lists, index)
# NOE
noeList = self.noeList
noeLists = [ml for ml in mLists if ml.className == 'NoeList']
index = 0
names = []
if noeLists:
if noeList not in noeLists:
noeList = noeLists[0]
index = noeLists.index(noeList)
names = [ml.name or 'List %d' % ml.serial for ml in noeLists]
else:
noeList = None
self.selectNoeList(noeList)
self.noePulldown.setup(names, noeLists, index)
def drawAfter(self):
if self.waiting:
return
self.waiting = True
self.after_idle(self.draw)
def selectT1List(self, t1List):
if t1List is not self.t1List:
self.t1List = t1List
self.sfEntry.set(t1List.sf)
values = [m.value for m in t1List.measurements]
values.sort()
minVal = self.minT1Entry.get()
maxVal = self.maxT1Entry.get()
minVal0 = values[0]*MS_UNIT_MULTIPLIERS[t1List.unit]
maxVal0 = values[-1]*MS_UNIT_MULTIPLIERS[t1List.unit]
if minVal0 < minVal:
self.minT1Entry.set(max(minVal0 - 100, 0))
if maxVal0 > maxVal:
self.maxT1Entry.set(maxVal0 + 100)
self.drawAfter()
def selectT2List(self, t2List):
if t2List is not self.t2List:
self.t2List = t2List
self.sfEntry.set(t2List.sf)
values = [m.value for m in t2List.measurements]
values.sort()
values.sort()
minVal = self.minT2Entry.get()
maxVal = self.maxT2Entry.get()
minVal0 = values[0]*MS_UNIT_MULTIPLIERS[t2List.unit]
maxVal0 = values[-1]*MS_UNIT_MULTIPLIERS[t2List.unit]
if minVal0 < minVal:
self.minT2Entry.set(max(minVal0 - 50, 0))
if maxVal0 > maxVal:
self.maxT2Entry.set(maxVal0 + 50)
self.drawAfter()
def selectNoeList(self, noeList):
if noeList is not self.noeList:
self.noeList = noeList
self.sfEntry.set(noeList.sf)
#self.drawAfter()
def draw(self):
params = self.getSanitisedParams()
cSize, cDist, lenNh, ict, csaN, paramsS2, paramsRct, tBounds = params
sf = abs(self.sfEntry.get() or 500.010)
self.t1t2Graph.update(self.t1List, self.t2List, cSize, cDist, sf, lenNh,
ict, csaN, paramsS2, paramsRct, tBounds)
self.t1t2GraphB.update(self.t1List, self.t2List)
self.t1Graph.update(self.t1List)
self.t2Graph.update(self.t2List)
self.noeGraph.update(self.noeList)
self.waiting = False
def mc(self):
sf = abs(self.sfEntry.get() or 500.010)
if not self.t1List and self.t2List:
return
chains = set([])
t1t2Points = {}
resonancesT1 = {}
resonancesNoe = {}
residueResonances = {}
t1Unit = MS_UNIT_MULTIPLIERS[self.t1List.unit]
t2Unit = MS_UNIT_MULTIPLIERS[self.t2List.unit]
if self.noeList:
for noe in self.noeList.measurements:
for resonance in noe.resonances:
resonancesNoe[resonance] = noe
for t1 in self.t1List.measurements:
resonancesT1[t1.resonance] = t1
for t2 in self.t2List.measurements:
resonance = t2.resonance
if not resonance.resonanceSet:
continue
residue = resonance.resonanceSet.findFirstAtomSet().findFirstAtom().residue
t1 = resonancesT1.get(resonance)
noe = resonancesNoe.get(resonance)
if t1 and noe:
t1t2Points[residue] = 1e-3*t1Unit*t1.value, 1e-3*t2Unit*t2.value, noe.value
chains.add(residue.chain)
residueResonances[residue] = resonance
if t1:
t1t2Points[residue] = 1e-3*t1Unit*t1.value, 1e-3*t2Unit*t2.value, None
chains.add(residue.chain)
residueResonances[residue] = resonance
for chain in chains:
residues = chain.sortedResidues()
t1Values = []
t2Values = []
noeValues = []
n = len(residues)
n2 = n-1
jj = range(n)
s2Best = [0.0] * n
teBest = [0.0] * n
rexBest = [0.0] * n
print ''
for residue in residues:
t1,t2, noe = t1t2Points.get(residue, (None, None, None))
t1Values.append(t1)
t2Values.append(t2)
noeValues.append(noe)
t1s = [v for v in t1Values if v]
t2s = [v for v in t2Values if v]
noes = [v for v in noeValues if v]
m = len(t1s)
t1 = sum(t1s)/float(m)
t2 = sum(t2s)/float(m)
noe = sum(noes)/float(m)
t12 = [v/t2s[i] for i, v in enumerate(t1s) if v]
t12m = sum(t12)/float(len(t12))
deltas = [abs(v-t12m)/t12m for v in t12]
w = [1.0/(v*v) for v in deltas]
t1 = sum([ t1s[j]*w[j] for j in range(m)])/sum(w)
t2 = sum([ t2s[j]*w[j] for j in range(m)])/sum(w)
if noes:
noe = sum([ noes[j]*w[j] for j in range(m)])/sum(w)
else:
noe = None
i, ensemble = self.fitT1T2(t1, t2, noe, sf, tmFix=None, teFix=None, s2Fix=None,
tmMin=1e-9, tmMax=100e-9, teMin=1e-12, teMax=1e-10,
rexFix=0.0)
ensemble.sort()
score, s2, te0, tm0, rex, t1t, t2t, noet = ensemble[0]
data = (s2, te0*1e12, tm0*1e9, rex, t1, t1t, t2, t2t, noe or 0.0, noet, score, i)
print 'Mean A S2:%5.3f Te:%5.1f Tm:%5.3f Rex:%5.3f T1:%5.3f %5.3f T2:%5.3f %5.3f NOE:%5.3f %5.3f %e %6d' % data
rexCheck = 999 # 1.40 * t1/t2
# Prior is mean, then region
for j in jj:
t1 = t1Values[j]
t2 = t2Values[j]
noe = noeValues[j]
if t1 is None:
continue
residue = residues[j]
print '%3d%s' % (residue.seqCode, residue.ccpCode),
i, ensemble = self.fitT1T2(t1, t2, noe, sf, tmFix=tm0, teFix=None, s2Fix=None,
tmMin=tm0*0.1, tmMax=tm0*5, teMin=te0/100, teMax=te0*20,
rexFix=0.0, rexMax=15.0)
ensemble.sort()
score, s2, te, tm, rex, t1t, t2t, noet = ensemble[0]
if s2 > 0.995:
i, ensemble = self.fitT1T2(t1, t2, noe, sf, tmFix=tm0, teFix=None, s2Fix=None,
teMin=te/10, teMax=te*10,
rexFix=None, rexMax=15.0)
ensemble.sort()
score, s2, te, tm, rex, t1t, t2t, noet = ensemble[0]
teBest[j] = te
s2Best[j] = s2
rexBest[j] = rex
data = (s2, te*1e12, tm*1e9, rex, t1, t1t, t2, t2t, noe or 0.0, noet, score, i)
print 'S2:%5.3f Te:%5.1f Tm:%5.3f Rex:%5.3f T1:%5.3f %5.3f T2:%5.3f %5.3f NOE:%5.3f %5.3f %e %6d' % data
dataSet1 = []
dataSet2 = []
dataSet3 = []
for j in jj:
residue = residues[j]
resonance = residueResonances.get(residue)
if not resonance:
continue
dataSet1.append((residue.seqCode, s2Best[j]))
dataSet2.append((residue.seqCode, teBest[j]*1e9))
dataSet3.append((residue.seqCode, rexBest[j]))
self.s2Graph.update([dataSet1,])
self.teGraph.update([dataSet2,])
self.rexGraph.update([dataSet3,])
self.tabbedFrame.select(3)
def fitT1T2(self, t1, t2, noe, sf, tmFix=None, teFix=None, s2Fix=None,
tmMin=1e-9, tmMax=100e-9, teMin=1e-12, teMax=1e-9,
rexFix=None, rexMax=15.0, niter=10000):
# Could have multiple sf
rNH = 1.015
csaN = 160*1e-6 # 160 ppm
omegaH = sf * 2 * PI * 1e6 # Rad/s
omegaN = omegaH * GAMMA_N/GAMMA_H
gammaHN = GAMMA_H/GAMMA_N
A = REDUCED_PERM_VACUUM * REDUCED_PLANK * GAMMA_N * GAMMA_H * 1e30 # Cubic Angstrom adjust
A /= rNH**3.0
A = A*A/4.0
C = omegaN * omegaN * csaN * csaN
C /= 3.0
# Init params
if s2Fix is None:
s2Start = [x*0.05 for x in range(1,20)]
else:
s2Start = [s2Fix,]
if teFix is None:
teStart = [x*1e-12 for x in [10,30,70,100,300,700,1000]]
else:
teStart = [teFix,]
if tmFix is None:
tmStart = [x*1e-9 for x in range(1,30)]
else:
tmStart = [tmFix,]
if rexFix is None:
rexStart = [float(x) for x in range(int(rexMax))]
else:
rexStart = [rexFix,]
# Init ensemble of solutions
ensemble = []
for s2 in s2Start:
for te in teStart:
for tm in tmStart:
for rex in rexStart:
ensemble.append((None, s2, te, tm, rex))
# Init scores
for k, (score, s2, te, tm, rex) in enumerate(ensemble):
jH = getSpectralDensity(s2, tm, te, omegaH)
jN = getSpectralDensity(s2, tm, te, omegaN)
jHpN = getSpectralDensity(s2, tm, te, omegaH+omegaN)
jHmN = getSpectralDensity(s2, tm, te, omegaH-omegaN)
j0 = getSpectralDensity(s2, tm, te, 0.0)
r1 = A*( (3*jN) + (6*jHpN) + jHmN ) + C*jN
r2 = 0.5*A*( (4*j0) + (3*jN) + (6*jHpN) + (6*jH) + jHmN ) + C*( 2*j0/3.0 + 0.5*jN ) + rex
t1p = 1.0/r1
t2p = 1.0/r2
d1 = (t1p-t1)/t1
d2 = (t2p-t2)/t2
score = (d1*d1) + (d2*d2)
if noe is None:
noep = 0.0
else:
noep = 1.0 + ( A * gammaHN * t1 * ((6*jHpN)-jHmN) )
dn = (noep-noe)/2.0
score += (dn*dn)
ensemble[k] = (score, s2, te, tm, rex, t1p, t2p, noep)
# Matrix
#
# Pred Jh
# R1
# R2
# NOE
# r = 1.0/rct + 1.0/ict
# t = 1.0/r
# j = (s2*rct) / (1.0 + w*w*rct*rct)
# j += ((1.0-s2)*t) / (1.0 + w*w*t*t)
#
# return j*0.4
ensemble.sort()
ensemble = ensemble[:10]
ensembleSize = len(ensemble)
bestScore = 1e99
for i in xrange(niter):
f = i/float(niter)
f = exp(-10.0*f)
# Mutate
ensemble.sort()
prevScore, s2, te, tm, rex, t1p, t2p, noep = ensemble[-1] #Biggest is worst
if ensemble[0][0] < 1e-10:
break
if not s2Fix:
#d = ((random() + 0.618 - 1.0) * f) + 1.0
d = ((random() - 0.382) * f) + 1.0
s2 = max(0.0, min(1.0, s2*d))
if not tmFix:
d = ((random() - 0.382) * f) + 1.0
tm = max(tmMin, min(tmMax, tm*d))
if not teFix:
d = ((random() - 0.382) * f) + 1.0
te = max(teMin, min(teMax, te*d))
d = ((random() - 0.382) * f) + 1.0
rex = max(0.0, min(rexMax, rex*d))
jH = getSpectralDensity(s2, tm, te, omegaH)
jN = getSpectralDensity(s2, tm, te, omegaN)
jHpN = getSpectralDensity(s2, tm, te, omegaH+omegaN)
jHmN = getSpectralDensity(s2, tm, te, omegaH-omegaN)
j0 = getSpectralDensity(s2, tm, te, 0.0)
r1 = A*( (3*jN) + (6*jHpN) + jHmN ) + C*jN
r2 = 0.5*A*( (4*j0) + (3*jN) + (6*jHpN) + (6*jH) + jHmN ) + C*( 2*j0/3.0 + 0.5*jN ) + rex
t1p = 1.0/r1
t2p = 1.0/r2
d1 = (t1p-t1)/t1
d2 = (t2p-t2)/t2
score = (d1*d1) + (d2*d2)
if noe is None:
noep = 0.0
else:
noep = 1.0 + ( A * gammaHN * t1 * ((6*jHpN)-jHmN) )
dn = (noep-noe)/2.0
score += (dn*dn)
ratio = exp(prevScore-score)
if ratio > 1.0: # random():
ensemble[-1] = (score, s2, te, tm, rex, t1p, t2p, noep)
else:
k = randint(0,ensembleSize-1)
score, s2, te, tm, rex, t1p, t2p, noep = ensemble[k]
ensemble[-1] = (score, s2, te, tm, rex, t1p, t2p, noep)
if score < bestScore:
bestScore = score
#print bestScore, ', '.join(['%.3e' % x[0] for x in ensemble])
return i, ensemble
