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electrodedisplaywidget.py
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electrodedisplaywidget.py
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#! /usr/bin/env python
# -*- coding: utf-8 -*-
#
# Widget to select and display electrode plots on a common referential/template
#
# (c) Inserm U836 2012-2014 - Manik Bhattacharjee
#
# License GNU GPL v3
#
#
from PyQt4 import QtGui, QtCore, uic
import sys, pickle, shutil, traceback, os, json, re, numpy, csv
from brainvisa import axon
from brainvisa import anatomist
from soma import aims
import registration
from locateElectrodes import createElectrode, getPlotsCenters, getPlots, getPlotsNames, createBipole
from referentialconverter import ReferentialConverter
from templatewidget import TemplateMRI, TemplateMNI
from brainvisa.data.readdiskitem import ReadDiskItem
from brainvisa.data.writediskitem import WriteDiskItem
from brainvisa.data import neuroHierarchy
from readSulcusLabelTranslationFile import *
from readFreesurferLabelFile import *
from externalprocesses import PythonExecutor
from checkSpmVersion import *
from readFunctionalTractography import *
from scipy import spatial as sc_sp
#from numpy.matlib import repmat
from collections import OrderedDict
import control_ftract
from locateElectrodes import natural_keys
from bipoleSEEGColors import bipoleSEEGColors
from control_ftract2 import *
import pdb
def loadElectrodeModels():
"""Load electrode models from the database"""
models = {}
rdiEM = ReadDiskItem('Electrode Model', 'Electrode Model format')
result = list (rdiEM._findValues( {}, None, False ) )
for e in result:
#WARNING if a model is available from multiple protocols, it will use only one
models[str(e.attributes()['model_name'])] = e
return models
class ElectrodeDisplayWidget(QtGui.QWidget):
def __init__(self, app=None, ana = None,dataSubjects = None):
QtGui.QWidget.__init__(self)
uic.loadUi("groupPlots.ui", self)
self.subjects = []
self.subjItems = []
self.implantations = {}
self.plotsData = {}
self.testDataSubjects = dataSubjects
self.taskCounter = 0
self.tasks = []
self.meshes = {}
self.bipolesmeshes = {}
self.dispMode = 'off'#'sphere'
self.dispParams = {'diameter':2.0}
self.transfoManager = registration.getTransformationManager()
# Get ReferentialConverter (for Talairach, AC-PC...)
self.refConv = ReferentialConverter()
self.electrodeModels = loadElectrodeModels()
self.addSelectionButton.clicked.connect(self.addSelection)
self.removeSelectionButton.clicked.connect(self.removeSelection)
self.removePlotsNotTRC.clicked.connect(self.removeNotTRC)
self.removePlotsLeftSide.clicked.connect(lambda :self.removePlotsLeftRight('Left'))
self.removePlotsRightSide.clicked.connect(lambda :self.removePlotsLeftRight('Right'))
self.addAroundButton.clicked.connect(self.selectAround)
#self.normalizeButton.clicked.connect(self.normalizeCoords)
#self.saveNormalizedButton.clicked.connect(self.saveNormalizedCoords)
self.selectionList.itemDoubleClicked.connect(self.updatePlotSelected)
self.generateStatsButton.clicked.connect(self.generateStatisticsContacts)
#fill the combo possibility.
loca = ['*']
parcels_namesMA= readSulcusLabelTranslationFile('parcels_label_name.txt')
loca.extend(parcels_namesMA.values())
loca.sort()
self.AddMAparcels2SelectioncomboBox.clear()
self.AddMAparcels2SelectioncomboBox.addItems(loca)
self.AddMAparcels2SelectioncomboBox.currentIndexChanged.connect(self.AddMAparcels2selection)
self.radioButtonbothHemi.toggled.connect(self.changeBothRightDisplay)
#self.radioButtonAllRight.toggled.connect(self.changeBothRightDisplay)
self.radioButtonContactDisplay.toggled.connect(self.contactSEEGDisplay)
#self.radioButtonsEEGResults.toggled.connect(self.contactSEEGDisplay)
pix = QtGui.QPixmap('/home/b67-belledone/Desktop/epilepsie-manik/Logo-F-TRACT.xpm' )
anatomist.anatomist.cpp.IconDictionary.instance().addIcon('ftract_control', pix)
ad = anatomist.anatomist.cpp.ActionDictionary.instance()
#control = ensemble d'action
ad.addAction( 'fTract_Action', StimulateResults )
cd = anatomist.anatomist.cpp.ControlDictionary.instance()
cd.addControl( 'ftract_control', ControlFtract, 25 )
cm = anatomist.anatomist.cpp.ControlManager.instance()
cm.addControl('QAGLWidget3D','','ftract_control')
# Anatomist windows and objects
if ana == None:
self.a = anatomist.Anatomist('-b' )
else:
self.a = ana
layout = QtGui.QHBoxLayout( self.viewWidget )
self.axWindow = self.a.createWindow( 'Axial' )#, no_decoration=True )
self.axWindow.setParent(self.viewWidget)
layout.addWidget( self.axWindow.getInternalRep() )
self.sagWindow = self.a.createWindow( 'Sagittal' )#, no_decoration=True )
self.sagWindow.setParent(self.viewWidget)
layout.addWidget( self.sagWindow.getInternalRep() )
self.axWindow.internalRep.otherwindow = self.sagWindow
self.windows = [self.axWindow, self.sagWindow]
#pdb.set_trace()
#self.axWindow.connect()
self.templates = {'MNI':TemplateMNI(self.a)}
#self.templateCombo.clear()
#self.templateCombo.addItems(sorted(self.templates.keys()))
self.setTemplate(self.templates['MNI'])
self.templReferential = None
#self.templateCombo.currentIndexChanged.connect(self.templateChanged)
self.subjectList.itemSelectionChanged.connect(self.subjectSelectionChanged)
self.electrodeList.itemSelectionChanged.connect(self.electrodeSelectionChanged)
self.selectionList.itemSelectionChanged.connect(self.selectedSelectionChanged)
self.addDisplayButton.clicked.connect(self.displayImage)
self.addMNIImageToDisplayList.clicked.connect(self.addMNIImagetoList)
self.addMNIMeshTextToDisplayList.clicked.connect(self.addMNIMeshTexttoList)
def setStatus(self, text):
self.statusLabel.setText(str(text))
def incTaskCounter(self):
self.taskCounter = self.taskCounter + 1
self.setStatus(u"Tasks in progress : "+str(self.taskCounter))
return self.taskCounter
def decTaskCounter(self):
self.taskCounter = self.taskCounter - 1
self.setStatus(u"Tasks in progress : "+str(self.taskCounter))
return self.taskCounter
def startTask(self, taskFunction):
pe = PythonExecutor(taskFunction)
self.tasks.append(pe)
# Remove it from the list of threads when finished
pe.finished.connect(lambda th=pe:self.taskFinished(th))
self.incTaskCounter()
pe.start()
def taskFinished(self, thread):
self.tasks.remove(thread)
self.decTaskCounter()
def setTemplate(self, templ):
"""Set the template used as a common referential"""
# Un nom, des données (IRM ?) un identifiant de référentiel pour le refconv ?
self.template = templ
if self.template.referentialAnatomist:
self.a.assignReferential(self.template.referentialAnatomist, self.windows)
if self.template.volumes:
self.displayCombo.clear()
#self.displayCombo.addItems(["Image "+str(i) for i in range(len(self.template.volumes))])
self.displayCombo.addItems([os.path.split(im.fullPath())[1] for im in self.template.volumes])
#def templateChanged(self, tpl):
#"""The combo box to select the template was changed"""
## Read combo, setTemplate, remove selection or reset display (no spheres, no images)...
#pass
def displayImage(self):
try:
#try:
#self.a.removeObjects([self.currentImage,],self.windows) #self.axWindow.removeObjects(self.currentImage)
##self.sagWindow.removeObjects(self.currentImage)
#except:
#pass
self.currentImage = self.a.loadObject(self.template.volumes[self.displayCombo.currentIndex()])
self.a.addObjects([self.currentImage], self.windows)
except:
print "Could not add selected image"
pdb.set_trace()
def subjectSelectionChanged(self):
"""Subject selection changed, update electrode list selection"""
selected = [str(item.text()) for item in self.subjectList.selectedItems()]
for i in xrange(self.electrodeList.count()):
selec = False
for s in selected:
if str(self.electrodeList.item(i).text()).startswith(s):
selec = True
break
self.electrodeList.item(i).setSelected(selec)
def electrodeSelectionChanged(self):
"""Electrode selection changed, update plot list selection"""
selected = [str(item.text()) for item in self.electrodeList.selectedItems()]
for i in xrange(self.plotList.count()):
selec = False
for s in selected:
if str(self.plotList.item(i).text()).startswith(s):
selec = True
break
self.plotList.item(i).setSelected(selec)
#def plotSelectionChanged(self):
# pass
def selectedSelectionChanged(self):
"""In the selected plots list, the selected items changed -> update the view"""
# Update Anatomist selection -> select all meshes for the selected plots
g = self.a.getDefaultWindowsGroup()
g.setSelection([self.meshes[str(item.text())] for item in self.selectionList.selectedItems()])
def plotDataFromFullName(self, name):
"""Get the data from a plot using its full name (e.g. Gre_2014_DUPj : A 2)"""
(sub, elec, plot) = self.plotNameFromFullPlotName(name)
return self.plotsData[sub][elec][plot]
def fullPlotName(self, subj, elec, plot):
"""Compute fully qualified plot name from subject, electrode, plot names"""
return subj + ' : ' + elec + ' ' + plot
def plotNameFromFullPlotName(self, name):
"""Get subject, electrode, plot names from the displayed name Subject : Electrode Plot (e.g. Gre_2014_DUPj : A 2)"""
(sub, elecplot) = name.split(' : ')
(elec, plot) = elecplot.split()
return (sub, elec, plot)
#def normalizeCoords(self):
#"""Get plot coordinates in the selected template referential and store these coordinates in self.plotData"""
#def miniFunc(myself, coordsSB, s):
#"""Internal mini function to launch in a thread"""
#refId = myself.implantations[s]['ReferentialUuid']
#normCoords = myself.template.normalizeCoordinates([coordsSB[s][el][p] for el in coordsSB[s] for p in coordsSB[s][el]], refId)
##pdb.set_trace()
#idx = 0
#if normCoords is None:
#print "normCoords is None for subject %s : could not convert coordinates to template referential"%s
#return
##import pdb; pdb.set_trace()
#for el in coordsSB[s]:
#for p in coordsSB[s][el]:
#myself.plotsData[s][el][p][myself.template.name] = normCoords[idx]
#idx = idx + 1
##fin de la fonction miniFunc
#print "go back to locateElectrode for now, we don't manage call to normalisation from locateElectrode for now"
#return
#coordsSB = {}
#for s in self.subjects:
#coordsSB[s] = {}
#for elec, plots in self.plotsData[s].iteritems():
#sb = dict([(p,plots[p]['Scanner-based']) for p in plots if self.template.name not in plots[p].keys()])
#if len(sb) > 0:
#coordsSB[s][elec] = sb
## Compute template coords for this subject
#self.startTask(lambda myself=self, cSB=coordsSB, suj=s:miniFunc(myself, cSB, suj))
#def saveNormalizedCoords(self):
#"""Should save all computed coordinates of plots in elecimplant file for all subject
#with the timestamp of the original data, to avoid recomputation"""
#for s,rdi in zip(self.subjects, self.subjItems):
#self.saveImplantation(s, rdi)
#return
def selectAround(self):
"""Find in the list of selected plots the ones near the linked cursor"""
# Get linked cursor coords (in template referential)
pTempl = self.a.linkCursorLastClickedPosition(self.template.referentialAnatomist).items()[:3]
# Get accepted radius
r2 = self.radiusSpin.value()**2
meshes = []
# Compute distance to all selected plots
pdb.set_trace() #need to check if need to take absolute value in x in mni
for i in xrange(self.selectionList.count()):
fullname = str(self.selectionList.item(i).text())
(sub, elec, plot) = self.plotNameFromFullPlotName(fullname)
coords = self.plotsData[sub][elec][plot][self.template.name][:3]
dist2 = (coords[0]-pTempl[0])**2 + (coords[1]-pTempl[1])**2 + (coords[2]-pTempl[2])**2
# Select item if in range, deselect if not
self.selectionList.item(i).setSelected(dist2 <= r2)
if fullname in self.meshes and dist2 <= r2:
meshes.append(self.meshes[fullname])
# Select them in Anatomist
g = self.a.getDefaultWindowsGroup()
g.setSelection(meshes)
def setSubjects(self, names, diskitems):
"""Sets the list of subjects (and corresponding readdiskitems in the database) for the widget"""
self.subjects = sorted(names)
self.subjItems = diskitems
self.loadImplantations()
self.plotsData = dict([(s, self.getPlotDataFromImplantation(s)) for s in self.subjects])
#remove NonType from plotsData
pat_to_remove = []
for jj,kk in self.plotsData.iteritems():
if kk is None:
#self.plotsData.pop(jj,None)
pat_to_remove.append(jj)
for ii in range(len(pat_to_remove)):
self.plotsData.pop(pat_to_remove[ii],None)
if len(self.plotsData.keys()) == 0:
print "No data to show"
return
self.updateUIplots()
def addSelection(self):
"""Add the selected plots/subjects/electrodes to the selection """
current = [str(self.selectionList.item(i).text()) for i in xrange(self.selectionList.count())] # FIXME pas juste les selected ! Tous les items
new = [str(s.text()) for s in self.plotList.selectedItems() if str(s.text()) not in current]
# Display the new ones
meshes = []
invalid = set()
for n in new:
if self.template.name in self.plotDataFromFullName(n):
mesh = self.displaySphereAt(self.plotDataFromFullName(n)[self.template.name], self.plotDiameter(), self.template.referentialAnatomist, color=(0.0,0.9,0.1,1.0),name = n)
self.meshes[n] = mesh
meshes.append(mesh)
else:
invalid.add(n) # If there, coordinates are not available in the right template referential
if len(invalid) > 0:
print "Some plots were not added to the selection, because normalized coordinates were not available for them"
new = list(set(new) - invalid)
self.selectionList.addItems(new)
self.a.addObjects(meshes, self.windows)
def plotDiameter(self):
"""Returns the diameter of the spheres used to display plots"""
return 2.0
def displaySphereAt(self, center, diameter, referential, color, name = None):
"""Returns a spherical mesh (anatomist object) with color = [1.0,0.0,0.0,1.0] for a red, not transparent sphere"""
mesh = self.a.toAObject(aims.SurfaceGenerator.sphere(aims.Point3df(center[0], center[1], center[2]), diameter, 54))
if name is not None:
mesh.setName(name)
self.a.setMaterial(mesh, diffuse=color)#[color.redF(), color.greenF(), color.blueF(), color.alphaF()] #sortir le setMaterial(diffuse=color) et le mettre à la fin de la boucle for des fonctions qui l'appelle ?
self.a.assignReferential(referential, mesh)
return mesh
def removeSelection(self):
"""Remove plots from the selected list"""
removable = [str(s.text()) for s in self.selectionList.selectedItems()]
meshes = [self.meshes[r] for r in removable if r in self.meshes]
for r in removable:
if r in self.meshes:
del self.meshes[r]
self.a.removeObjects(meshes, self.windows)
self.a.deleteObjects(meshes)
# Reverse loop to remove from the bottom (avoids messing up the index)
for idx in reversed(range(self.selectionList.count())):
if str(self.selectionList.item(idx).text()) in removable:
self.selectionList.takeItem(idx)
def removeNotTRC(self):
"""Remove plots which are not registered in the TRC"""
all_items=[str(self.selectionList.item(i).text()) for i in range(self.selectionList.count())]
#on remplace les ' par des p dans all_items
all_items = [all_items[x].replace("'","p") for x in range(len(all_items))]
full_list_trc=[]
for subj in self.subjects:
#check if exist TRC in DB for this subject
rdi = ReadDiskItem('Raw SEEG recording', 'EEG TRC format' )
di = rdi.findValue({'subject':subj})
if di is not None:
data_micromed = neo.MicromedIO(filename = str(di)).read_segment() #all data
taille=len(data_micromed.analogsignals)
##Normalisation name (between analogsignals' name and plots' name)
number=['01', '02', '03', '04', '05', '06', '07', '08', '09']
noms=[]
for i in range(taille):
name=data_micromed.analogsignals[i].name
name=name.upper()
if name[len(name)-2:] in number:
name=name[:len(name)-2]+name[len(name)-1:]
setattr(data_micromed.analogsignals[i],'name',name)
noms+=[data_micromed.analogsignals[i].name]
#re.sub(noms[16],re.findall('\d+',noms[16])[0],subj + " : " + "Plot"+re.findall('\d+',noms[16])[0])
#noms_remade= [subj + " : " + re.findall('\S+(?<![\d_])',noms[x])[0] + " Plot"+re.findall('\d+',noms[x])[0] for x in taille]
noms_remade= [subj + " : " + re.findall('\S+(?<![\d_])',noms[x])[0] + " Plot"+re.findall('\d+',noms[x])[0] for x in range(len(noms)) if len(re.findall('\d+',noms[x])) > 0]
#on remplace les ' par des p dans noms_remade
[full_list_trc.append(noms_remade[x].replace("'","p")) for x in range(len(noms_remade))]
to_keep=[all_items[x] for x in range(len(all_items)) for y in range(len(full_list_trc)) if all_items[x]==full_list_trc[y]]
to_remove=list(set(all_items)-set(to_keep))
meshes = [self.meshes[r] for r in to_remove if r in self.meshes]
for r in to_remove:
if r in self.meshes:
del self.meshes[r]
self.a.removeObjects(meshes, self.windows)
self.a.deleteObjects(meshes)
# Reverse loop to remove from the bottom (avoids messing up the index)
for idx in reversed(range(self.selectionList.count())):
if str(self.selectionList.item(idx).text()) in to_remove:
self.selectionList.takeItem(idx)
def removePlotsLeftRight(self, side):
all_items=[str(self.selectionList.item(i).text()) for i in range(self.selectionList.count())]
to_remove = []
for ii in all_items:
MNI_pos = self.plotDataFromFullName(ii)['MNI']
if side == 'Left':
if MNI_pos[0] >= 0:
to_remove.append(ii)
elif side == 'Right':
if MNI_pos[0] <=0:
to_remove.append(ii)
meshes = [self.meshes[r] for r in to_remove if r in self.meshes]
for r in to_remove:
if r in self.meshes:
del self.meshes[r]
self.a.removeObjects(meshes,self.windows)
self.a.deleteObjects(meshes)
for idx in reversed(range(self.selectionList.count())):
if str(self.selectionList.item(idx).text()) in to_remove:
self.selectionList.takeItem(idx)
def updateUIplots(self):
self.subjectList.clear()
self.subjectList.addItems(self.subjects)
allElecs = sorted([s + ' : ' + el for s in self.plotsData.keys() for el in self.plotsData[s].keys()])
self.electrodeList.clear()
self.electrodeList.addItems(allElecs)
allPlots = sorted([self.fullPlotName(s, el, pl) for s in self.plotsData.keys() for el in self.plotsData[s].keys() for pl in self.plotsData[s][el].keys() ])
self.plotList.clear()
self.plotList.addItems(allPlots)
def t1pre2ScannerBased(self, subject):
""" Returns a triplet of Anatomist objects (native T1pre referential, scanner-base T1pre referential, Transformation from T1pre referential to T1pre Scanner-Based referential) """
rdi = ReadDiskItem('Transformation to Scanner Based Referential', 'Transformation matrix', exactType=True,\
requiredAttributes={'modality':'t1mri', 'subject':subject})
allTransf = list (rdi._findValues( {}, None, False ) )
for trsf in allTransf:
if trsf.attributes()['acquisition'].startswith(u'T1pre'):
print repr(trsf.attributes())
srcrDiskItem = self.transfoManager.referential( trsf.attributes()['source_referential'] )
srcr = self.a.createReferential(srcrDiskItem)
dstrDiskItem = self.transfoManager.referential(trsf.attributes()['destination_referential'])
self.t1pre2ScannerBasedId = trsf.attributes()['destination_referential']
dstr = self.a.createReferential(dstrDiskItem)
return (srcr, dstr, self.a.loadTransformation(trsf.fullPath(), srcr, dstr))
return None
def loadImplantations(self):
self.implantations = dict([(s,self.loadImplantation(rdi)) for s,rdi in zip(self.subjects, self.subjItems)])
def loadImplantation(self, rdiSuj):
rdi = ReadDiskItem( 'Electrode implantation', 'Electrode Implantation format')
impl = rdi.findValue(rdiSuj)
if not impl:
print "Cannot find implantation for %s"%rdiSuj.attributes()['subject']
return {}
if (os.path.exists(str(impl))):
filein = open(str(impl), 'rb')
try:
dic = json.loads(filein.read())
except:
filein.close()
filein = open(str(impl), 'rb')
dic = pickle.load(filein)
filein.close()
#we load eleclabel now if exist
rdi_eleclabel = ReadDiskItem('Electrodes Labels','Electrode Label Format')
impl_label = rdi_eleclabel.findValue(rdiSuj)
if not impl_label:
print("Cannot find implantation label for %s"%rdiSuj.attributes()['subject'])
pass
else:
if (os.path.exists(str(impl_label))):
filein = open(str(impl_label),"rb")
try:
dic2 = json.loads(filein.read())
except:
filein.close()
filein.open(str(impl_label),"rb")
dic2 = pickle.load(filein)
filein.close()
dic.update({'label':dic2['plots_label']})
return dic
#print "Exception while reading implantation file for %s"%rdiSuj.attributes()['subject']
#return {}
def saveImplantation(self, subj, rdiSubj):
wdi = WriteDiskItem( 'Electrode implantation', 'Electrode Implantation format')
impl = wdi.findValue(rdiSubj)
if impl is None:
print "Could not find electrode implantation file to save to (%s) !"%subj
return
try:
#import pdb; pdb.set_trace()
fileout = open(impl.fullPath()+'.temporary', 'wb')
content = self.implantations[subj]
content['plotsData-timestamp'] = content['timestamp']
content['plotsData'] = self.plotsData[subj]
fileout.write(json.dumps(content))
#pickle.dump(content, fileout)
fileout.close()
#to modify to json
shutil.move(impl.fullPath()+'.temporary', impl.fullPath())
neuroHierarchy.databases.insertDiskItem( impl, update=True )
except:
print "Exception while writing implantation file for %s"%subj
traceback.print_exc(file=sys.stdout)
return
def getPlotDataFromImplantation(self, subj):
els = self.subjectElectrodes(subj)
#self.addElectrode(e['name'], e['model'], e['target'], e['entry'], refId)
if 'plotsData' in self.implantations[subj]:
if self.implantations[subj]['plotsData-timestamp'] == self.implantations[subj]['timestamp']:
print "Using pre-recorded plots coordinates for %s"%subj
return self.implantations[subj]['plotsData']
else:
print "PlotsData timestamp was invalid for %s"%subj
res = {}
for e in els:
res[e['name']] = self.getPlotsFromElectrode(e, subj)
print(subj)
if "plotsMNI" in self.implantations[subj].keys():
info_plotsMNI = dict(self.implantations[subj]['plotsMNI'])
for kk,vv in res.iteritems():
for ll,ww in res[kk].iteritems():
ww.update({"MNI":info_plotsMNI[kk+"%02d"%int(ll[4:])]})
if "label" in self.implantations[subj].keys():
try:
ww.update({"label":self.implantations[subj]["label"][kk+"%02d"%int(ll[4:])]})
except:
pdb.set_trace()
else:
print "Error MNI Coordinates"
QtGui.QMessageBox.warning(self, "Error", "MNI coordinates haven't been generated for electrode contacts of Subject: {}\nThey have to be generated using locateElectrodes".format(subj))
return
return res
def getPlotsFromElectrode(self, el, subj):
print "Creating electrode model for %s"%subj
traceback.print_exc(file=sys.stdout)
(nativeRef, sbRef, t1pre2ScannerBased) = self.t1pre2ScannerBased(subj)
(newRef, transf, elecModel) = createElectrode(el['target'], el['entry'], nativeRef, ana=self.a, model = self.electrodeModels[str(el['model'])].fullPath(), dispMode = self.dispMode, dispParams = self.dispParams)
plots = getPlots(elecModel)
pNames = getPlotsNames(elecModel)
return dict([(n, {'internal':plots[n]['center'], 'native':list(transf.transform(plots[n]['center'])), 'Scanner-based':list(t1pre2ScannerBased.transform(transf.transform(plots[n]['center'])))}) for n in pNames])
def getSubjectImplantation(self, subj):
"""Returns electrode implantation data for the subject (dictionary from the elecimplant file)"""
return self.implantations[subj]
def subjectElectrodes(self, subj):
"""Returns the list available electrodes for the subject"""
impl = self.getSubjectImplantation(subj)
if 'electrodes' in impl:
return impl['electrodes']
return []
def subjectElectrodesNames(self, subj):
"""Returns the list of names of available electrodes for the subject"""
return [el['name'] for el in self.subjectElectrodes()]
def subjectPlot(self, subj, electrode):
"""Returns the list of plots of the chosen electrode for the subject"""
impl = self.getSubjectImplantation(subj)
if 'electrodes' in impl:
els = [e for e in impl['electrodes'] if e['name'] == electrode]
if len(els) > 0:
els[0] # (e['name'], e['model'], e['target'], e['entry'], refId)
return None
def getPlotsCoordinates(self, subj, referential = None, electrode = None, plot = None):
"""Returns the coordinates of the centers of all plots of the subject, or only for the given electrodes/plots
If referential is None, coordinates are returned in the native referential (T1pre of the subject)
"""
return None
def updatePlotSelected(self, item = None):
try:
if item is not None:
xyz = self.plotDataFromFullName(str(item.text()))[self.template.name]
# setLinkedCursor uses window referential : must apply transform before setting the position
self.windows[0].moveLinkedCursor(xyz)
else:
print "Error moving the cursor to the contact2"
except Exception as e:
print "Error moving the cursor to the contact"
#pdb.set_trace()
def addMNIImagetoList(self,path_fichier = None):
if path_fichier is None or path_fichier is False:
fichier = QtGui.QFileDialog.getOpenFileName(self, "Opening file: ", "", "(*.nii *.gii *.img *.nii.gz)")
elif not os.path.isfile(path_fichier):
fichier = QtGui.QFileDialog.getOpenFileName(self, "Opening file: ", "", "(*.nii *.gii *.img *.nii.gz)")
else:
fichier = path_fichier
image_mni_ref = self.a.loadObject(self.template.volumes[0])
#image_mni_ref.loadReferentialFromHeader()
#try:
#self.a.removeObjects([self.currentImage,],self.windows)
#except:
#pass
self.currentImage = self.a.loadObject(str(fichier))
#self.currentImage.loadReferentialFromHeader()
self.a.execute('LoadReferentialFromHeader', objects=[image_mni_ref,self.currentImage])
all_trans = self.a.getTransformations()
trans_from_vols = []
tm=registration.getTransformationManager()
tm.referential(registration.talairachMNIReferentialId)
for vol in (self.currentImage, image_mni_ref):
trans_from_vol = [t for t in all_trans if t.source() == vol.referential and not t.isGenerated()]
# hope trans_from_vol1 contains just one transform
# but if there are several, try to select the one going to
# scanner-based
if len(trans_from_vol) > 1:
trans_from_vol_filt = [t for t in trans_from_vol if t.destination().header()['name'].startswith('Scanner-based anatomical coordinates')]
if len(trans_from_vol_filt) == 1:
trans_from_vol = trans_from_vol_filt
if len(trans_from_vol) == 0:
raise RuntimeError('could not find a non-ambiguous transform')
elif len(trans_from_vol) > 1:
print "There is more than one available transformation ... we take the first one and pray"
trans_from_vol[0] = trans_from_vol_filt[0]
trans_from_vols.append(trans_from_vol)
#pdb.set_traceI()
trans_from_vol1, trans_from_vol2 = trans_from_vols
self.template.volumes.append(str(fichier))
self.a.execute('LoadTransformation',origin=trans_from_vol1[0].destination(),destination=trans_from_vol2[0].destination(),matrix=[0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1])
self.a.addObjects([self.currentImage,], self.windows)
self.displayCombo.addItems([os.path.split(str(fichier))[1]])
def addMNIMeshTexttoList(self):
#fichierMesh = QtGui.QFileDialog.getOpenFileName(self, "Opening mesh (surface corresponding to the texture): ", "", "(*.gii)")
##check if the file exist
#if not os.path.isfile(fichierMesh):
#print("the file doesn't exist")
#return
#self.addMNIImagetoList(fichierMesh)
#ask for a texture gii or a functionalTractography file
texture_info = QtGui.QMessageBox(self)
texture_info.setText("Choose the type of texture format (gii or csv to generate the gii)")
texture_info.setWindowTitle("texture format")
gii_button = texture_info.addButton(QtGui.QPushButton('.gii'),QtGui.QMessageBox.AcceptRole)
csvfuncTract_button =texture_info.addButton(QtGui.QPushButton('.csv functionalTractography'),QtGui.QMessageBox.AcceptRole)
#center_seg.setWindowModality(QtCore.Qt.NonModal)
texture_info.show()
texture_info.exec_()
#reply = texture_info.buttonRole(texture_info.clickedButton())
if str(texture_info.clickedButton().text())=='.gii':
print("texture already gii generated")
fichierTexture = QtGui.QFileDialog.getOpenFileName(self, "Opening texture (corresponding to the mesh): ", "", "(*.gii)")
pdb.set_trace()
elif str(texture_info.clickedButton().text())=='.csv functionalTractography':
print("have to generate the gii texture from the csv data, functionalTractography csv model")
fichierCSV = QtGui.QFileDialog.getOpenFileName(self, "Opening functional tractography data: ", "", "(*.csv)")
if not os.path.isfile(fichierCSV):
print("the file doesn't exist")
full_data = readFunctionalTractography(fichierCSV)
#ask where to save the data
path_to_save = QtGui.QFileDialog.getExistingDirectory(self,'Directory to save the mesh')
BrodmannParcels = aims.read('MNI_Atlases/rbrodmann.nii')
BrodmannParcelsArrayData = BrodmannParcels.arraydata()
left_white = aims.read('MNI_Brainvisa/t1mri/T1pre_1900-1-3/default_analysis/segmentation/mesh/Gre_2016_MNI1_Lwhite.gii')
right_white = aims.read('MNI_Brainvisa/t1mri/T1pre_1900-1-3/default_analysis/segmentation/mesh/Gre_2016_MNI1_Rwhite.gii')
list_remove = set(['Patient', 'Atlas'])
list_condi_max = set(['ValueNb','PeakDelayMed','PeakDelaySTD','Probability'])
list_condi_present = set(full_data.keys())
#condi_intersect = list(list_condi_max & list_condi_present)
condi_intersect = sorted(list(list_condi_present-list_remove), key=lambda s: s.lower())
nb_time = len(condi_intersect)
orderTexture = dict([(i,condi_intersect[i]) for i in range(len(condi_intersect))]) #{0:'ValueNb',1:'PeakDelayMed',2:'PeakDelaySTD',3:'Probability'}
if full_data['Atlas'] == 'MarsAtlas':
#read the marsAtlas parcellation
left_MA = aims.read('MNI_Brainvisa/t1mri/T1pre_1900-1-3/default_analysis/segmentation/mesh/surface_analysis/Gre_2016_MNI1_Lwhite_parcels_marsAtlas.gii')
right_MA = aims.read('MNI_Brainvisa/t1mri/T1pre_1900-1-3/default_analysis/segmentation/mesh/surface_analysis/Gre_2016_MNI1_Rwhite_parcels_marsAtlas.gii')
#for i in range(len(condi_intersect)):
# left_white.vertex(i).assign(left_white.vertex(0))
# left_white.normal(i).assign(left_white.normal(0))
# left_white.polygon(i).assign(left_white.polygon(0))
# right_white.vertex(i).assign(right_white.vertex(0))
# right_white.normal(i).assign(right_white.normal(0))
# right_white.polygon(i).assign(right_white.polygon(0))
aims.write(left_white,str(path_to_save) + os.path.sep + 'left_white.gii')
aims.write(right_white,str(path_to_save) + os.path.sep + 'right_white.gii')
try:
os.mkdir(str(path_to_save)+os.path.sep+'Texture')
except:
pass
#faire un test si all au lieu des noms de parcels.
for i_parcels_stimulated in full_data[orderTexture[0]].keys():
if len( full_data[orderTexture[0]][i_parcels_stimulated]) > 0:
new_TimeSurfTextLeft = aims.TimeTexture('FLOAT')
new_TimeSurfTextRight = aims.TimeTexture('FLOAT')
for i in range(nb_time): #assign the value
textnowLeft = new_TimeSurfTextLeft[i]
textnowRight = new_TimeSurfTextRight[i]
textnowLeft.reserve(len(left_white.vertex(0))) #left_white.vertex(0)))
textnowRight.reserve(len(right_white.vertex(0)))
marsatlas_label = readSulcusLabelTranslationFile('parcels_label_name.txt')
#gauche #control lateral lorsqu'étude contro/ipsi
for iter_vert in range(len(left_white.vertex(0))):
#marsatlas_label[left_MA[0].arraydata()[iter_vert]]
#if isinstance(full_data[orderTexture[i]]['L_VCcm'][marsatlas_label[left_MA[0].arraydata()[iter_vert]]], (str, unicode)):
#join right and left or not
#for now we assume that we are using marsatlas
actual_marsatlas_parcels = []
if i_parcels_stimulated.startswith('L_') or i_parcels_stimulated.startswith('R_'):
try:
actual_marsatlas_parcels = [marsatlas_label[left_MA[0].arraydata()[iter_vert]]]
except:
pass #faudrait mieux mettre si c'est == 0 alors c'est un vertex qui n'a pas de correspondance marsatlas.
elif i_parcels_stimulated == 'All':
try:
actual_marsatlas_parcels = [marsatlas_label[left_MA[0].arraydata()[iter_vert]]]
except:
pass #faudrait mieux mettre si c'est == 0 alors c'est un vertex qui n'a pas de correspondance marsatlas.
else:
try:
actual_marsatlas_parcels = [[marsatlas_label[left_MA[0].arraydata()[iter_vert]]][0][2:]]
except:
pass
try:
if left_MA[0].arraydata()[iter_vert] == 0:
textnowLeft.append(-4)
else:
if full_data[orderTexture[i]][i_parcels_stimulated].keys()[0].startswith('i_') or full_data[orderTexture[i]][i_parcels_stimulated].keys()[0].startswith('c_'):
if full_data[orderTexture[i]][i_parcels_stimulated]['c_'+actual_marsatlas_parcels[0]] == 'NaN':
textnowLeft.append(-4)
else:
textnowLeft.append(float(full_data[orderTexture[i]][i_parcels_stimulated]['c_'+actual_marsatlas_parcels[0]]))
else:
if full_data[orderTexture[i]][i_parcels_stimulated][actual_marsatlas_parcels[0]] == 'NaN':
textnowLeft.append(-4)
else:
textnowLeft.append(float(full_data[orderTexture[i]][i_parcels_stimulated][actual_marsatlas_parcels[0]]))
except:
textnowLeft.append(-4)
#pdb.set_trace()
#puis droite #ipsi lateral lorsqu'étude contro_ipsi
for iter_vert in range(len(right_white.vertex(0))):
actual_marsatlas_parcels = []
if i_parcels_stimulated.startswith('L_') or i_parcels_stimulated.startswith('R_'):
try:
actual_marsatlas_parcels = [marsatlas_label[right_MA[0].arraydata()[iter_vert]]]
except:
pass
elif i_parcels_stimulated == 'All':
try:
actual_marsatlas_parcels = [marsatlas_label[right_MA[0].arraydata()[iter_vert]]]
except:
pass #faudrait mieux mettre si c'est == 0 alors c'est un vertex qui n'a pas de correspondance marsatlas.
else:
try:
actual_marsatlas_parcels = [[marsatlas_label[right_MA[0].arraydata()[iter_vert]]][0][2:]]
except:
pass
try:
if right_MA[0].arraydata()[iter_vert] == 0:
textnowRight.append(-4)
else:
if full_data[orderTexture[i]][i_parcels_stimulated].keys()[0].startswith('i_') or full_data[orderTexture[i]][i_parcels_stimulated].keys()[0].startswith('c_'):
if full_data[orderTexture[i]][i_parcels_stimulated]['i_'+actual_marsatlas_parcels[0]] == 'NaN':
textnowRight.append(-4)
else:
textnowRight.append(float(full_data[orderTexture[i]][i_parcels_stimulated]['i_'+actual_marsatlas_parcels[0]]))
else:
if full_data[orderTexture[i]][i_parcels_stimulated][actual_marsatlas_parcels[0]] == 'NaN':
textnowRight.append(-4)
else:
textnowRight.append(float(full_data[orderTexture[i]][i_parcels_stimulated][actual_marsatlas_parcels[0]]))
except:
textnowRight.append(-4)
#pdb.set_trace()
aims.write(new_TimeSurfTextLeft,str(path_to_save) + os.path.sep + 'Texture' + os.path.sep + ('%s_left.gii')%i_parcels_stimulated)
aims.write(new_TimeSurfTextRight,str(path_to_save) + os.path.sep + 'Texture' + os.path.sep + ('%s_right.gii')%i_parcels_stimulated)
else:
print(('No Data for %s')%i_parcels_stimulated)
obj1 = self.a.loadObject('MNI_Brainvisa/t1mri/T1pre_1900-1-3/default_analysis/segmentation/mesh/Gre_2016_MNI1_Lwhite.gii')
obj2 = self.a.loadObject('MNI_Brainvisa/t1mri/T1pre_1900-1-3/default_analysis/segmentation/mesh/surface_analysis/Gre_2016_MNI1_Lwhite_parcels_marsAtlas.gii')
obj1.loadReferentialFromHeader()
obj2.setPalette(palette = 'marsatlas')
MarsAtlas_fusion_obj = self.a.fusionObjects([obj1, obj2], method='FusionTexSurfMethod')
self.a.addObjects(MarsAtlas_fusion_obj,self.axWindow)
self.currentImage = [obj1,obj2]
if full_data['Atlas'] == 'Brodmann':
voxel_size_T1 = [BrodmannParcels.getVoxelSize()[0], BrodmannParcels.getVoxelSize()[1], BrodmannParcels.getVoxelSize()[2], 1.0]
sizeOutputnii = BrodmannParcels.getSize().list()
sizeOutputnii[-1] = len(orderTexture.keys())
for i_parcels_stimulated in full_data[orderTexture[0]].keys():
#di.setMinf('ColorPalette','Blue-Red-fusion')
volToGenerate = aims.Volume(*sizeOutputnii,dtype = 'float')
volToGenerate.header()['voxel_size']=voxel_size_T1
volToGenerate.fill(-4)
for i_texture in orderTexture.keys():
for i_parcels_result in full_data[orderTexture[i_texture]][i_parcels_stimulated].keys():
#fait chier le droite gauche
if full_data[orderTexture[0]][i_parcels_stimulated][i_parcels_result]=='NaN':
volToGenerate.arraydata()[numpy.where(BrodmannParcelsArrayData==float(i_parcels_result))]=-4
else:
volToGenerate.arraydata()[numpy.where(BrodmannParcelsArrayData==float(i_parcels_result))]=full_data[orderTexture[i_texture]][i_parcels_stimulated][i_parcels_result]
aims.write(volToGenerate,str(path_to_save)+os.path.sep+'%s.nii'%(str(int(float(i_parcels_stimulated)))))
print("done")
pdb.set_trace()
#try:
# self.a.removeObjects([self.currentImage,],self.windows)
#except:
# pass
##self.displayCombo.addItems([os.path.split(str(fichier))[1]])
#obj3 = self.a.loadObject(str(path_to_save) + os.path.sep + 'left_white_multipletime.gii')
#obj4 = self.a.loadObject(str(path_to_save) + os.path.sep + 'Texture' + os.path.sep + ('%s_left.gii')%i_parcels_stimulated)
#obj3.loadReferentialFromHeader()
#obj4.setPalette(palette = 'Blue-Red-fusion')
#FunctioTracto_fusion_obj = self.a.fusionObjects([obj3,obj4],method='FusionTexSurfMethod')
#self.a.addObjects(FunctioTracto_fusion_obj,self.sagWindow)
#pdb.set_trace()
#self.displayCombo.addItems([os.path.split(str(fichier))[1]])
#textureContacts = aims.TimeTexture()
def doubleClickedFunctionalTractography(self):
pdb.set_trace()
def generateStatisticsContacts(self):
#get selected contacts
current = [str(self.selectionList.item(i).text()) for i in xrange(self.selectionList.count())]
#il me faut un dictionnaire avec toutes les parcels mars atlas et un dictionnaire avec toutes les parcels freesurfer possible.
dict_marsatlas = {}
dict_freesurfer = {}
dict_dispersion_MA = {}
dict_dispersion_FS = {}
parcels_names = readSulcusLabelTranslationFile('parcels_label_name.txt')
freesurfer_parcel_names = readFreesurferLabelFile('freesurfer_label.txt')
missing_marsatlas = []
missing_freesurfer = []
all_patients = []
dict_MNI_PatientName = {}
for ii in parcels_names.values():
dict_marsatlas.update({ii:[]})
dict_dispersion_MA.update({ii:{}})
for ii in freesurfer_parcel_names.values():
dict_freesurfer.update({ii[0]:[]})
dict_dispersion_FS.update({ii[0]:{}})
#je parcours toutes les "current", je regarde leur parcels et j'ajoute la position mni à la list de cette parcels.
for ii in current:
(sub, elec, plot) = self.plotNameFromFullPlotName(ii)
dataplot = self.plotDataFromFullName(ii)
if 'MarsAtlas' in dataplot['label'].keys():
if dataplot['label']['MarsAtlas'][1] != u'not in a mars atlas parcel':
dict_marsatlas[dataplot['label']['MarsAtlas'][1]].append(dataplot['MNI'])
else:
#signaler que certains patients n'ont pas marsatlas de généré et que ça va "fausser" les résultats
#print("plot %s without marsAtlas parcellation estimated"%(ii))
if sub not in missing_marsatlas:
missing_marsatlas.append(sub)
if 'Freesurfer' in dataplot['label'].keys():
if dataplot['label']['Freesurfer'][1] != u'not in a freesurfer parcel':
try:
dict_freesurfer[dataplot['label']['Freesurfer'][1]].append(dataplot['MNI'])
except:
print sub
print "probleme avec ce patient"
pass
else:
#signaler que certains patient n'ont pas freesurfer de généré et que ça va "fausser" les résultats
#print("plot %s without FreeSurfer parcellation estimated"%(ii))
if sub not in missing_freesurfer:
missing_freesurfer.append(sub)
if sub not in all_patients:
all_patients.append(sub)
dict_MNI_PatientName.update({str(dataplot['MNI']):sub})
#now I calculate the dispersion per parcels: (and I'ld like to normalized it but don't know how)
for iter_MA in dict_marsatlas.keys():
points_array = numpy.array(dict_marsatlas[iter_MA])
#array_median = repmat(numpy.median(points_array,axis=0),len(points_array),1)
#diff = points_array - array_median
#list_dist_median = sc_sp.distance.cdist([numpy.median(points_array,axis=0)],points_array)
if len(points_array)>1:
dict_dispersion_MA[iter_MA].update({'nb contact':len(dict_marsatlas[iter_MA]),'average point':numpy.mean(points_array,axis=0),'median point':numpy.median(points_array,axis=0)})
found_outlier = self.is_outlier(points_array,thresh = 3)
pos_outlier = numpy.where(found_outlier==True)
if len(pos_outlier[0]) == 0:
dict_dispersion_MA[iter_MA].update({'outlier position':None})
else:
#[dict_MNI_PatientName[str(points_array[pos_outlier[0]][i].tolist())] for i in range(len(points_array[pos_outlier[0]]))]
dict_dispersion_MA[iter_MA].update({'outlier position':points_array[pos_outlier[0]]})
dict_dispersion_MA[iter_MA].update({'outlier name':[dict_MNI_PatientName[str(points_array[pos_outlier[0]][i].tolist())] for i in range(len(points_array[pos_outlier[0]]))]})
elif len(points_array)==1:
dict_dispersion_MA[iter_MA].update({'nb contact': 1,'average point':numpy.mean(points_array,axis=0),'median point':numpy.median(points_array,axis=0)})
else:
dict_dispersion_MA[iter_MA].update({'nb contact': 0})
for iter_FS in dict_freesurfer.keys():
points_array = numpy.array(dict_freesurfer[iter_FS])
#array_median = repmat(numpy.median(points_array,axis=0),len(points_array),1)
#diff = points_array - array_median
#list_dist_median = sc_sp.distance.cdist([numpy.median(points_array,axis=0)],points_array)
if len(points_array)>1: