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# a test example for python plugin in Anatomist (Pyanatomist module)

"""Models Fusion Method
"""

import sys, os
import PyQt4.QtCore as qt
import PyQt4.QtGui as qtui
import anatomist.cpp as anatomist
from soma import aims

an = anatomist.Anatomist()
processor = an.theProcessor()

class Configurator(object):
	def __init__(self, widget, objects):
		self._widget = widget
		self._objects = objects
		oneobj = self._objects[0]
		self._choosen_data = oneobj._choosen_data
		self._choosen_type = oneobj._choosen_type
		self._abs_enable = oneobj._abs_enable
		self._connect()	

	def _connect(self):
		clicked = qt.SIGNAL("clicked()")
		activated = qt.SIGNAL("activated(int)")
		toggled = qt.SIGNAL("toggled(bool)")
		widgets_slots = {'applyButton' : (clicked, self.applySlot),
			'dataComboBox' : (activated, self.dataSlot),
			'typeComboBox' : (activated, self.typeSlot),
			'absRadioButton' : (toggled, self.absSlot)}
		widgets = dict([(name, self._widget.child(name)) \
				for name in widgets_slots.keys()])	
		for name, (signal, slot) in widgets_slots.items():
			qt.QObject.connect(widgets[name], signal, slot)
		dataToId = {'raw' : 0, 'mean' : 1, 'good' : 2, 'bad' : 3}
		typeToId = {'vertex' : 0, 'all' : 1}
		widgets['absRadioButton'].setChecked(self._abs_enable)
		widgets['dataComboBox'].setCurrentItem(\
			dataToId[self._choosen_data])
		widgets['typeComboBox'].setCurrentItem(\
			typeToId[self._choosen_type])

	def applySlot(self):
		for o in self._objects:
			o.compute(self._abs_enable)
			o.display(self._choosen_data, self._choosen_type)
					
	def okSlot(self):
		self.applySlot()
		self._widget.close()
		
	def dataSlot(self, n):
		dataFromId = ['raw', 'mean', 'bad', 'good']
		self._choosen_data = dataFromId[n]

	def typeSlot(self, n):
		typeFromId = ['vertex', 'all']
		self._choosen_type = typeFromId[n]

	def absSlot(self, on):
		self._abs_enable = on


class ConfigureCallback(anatomist.ObjectMenuCallback):
	def __init__(self):
		anatomist.ObjectMenuCallback.__init__(self)
		self._conf = None

	def doit(self, objects):
		ui = __file__[:__file__.rfind('.') + 1] + 'ui'
		parent = an.getControlWindow()
		widget = qtui.QWidgetFactory().create(ui, None, parent)
		if widget:
			self._conf = Configurator(widget, objects)
			widget.show()
		else:	print "can't load ui file '%s'" % ui


class AModelsGraphFusionObject(anatomist.ObjectList):
	_type = anatomist.AObject.registerObjectType(\
				'AModelsGraphFusionObject')
	_menus = None
	shared_path = str( an.anatomistSharedPath() )
	icon = os.path.join( shared_path,
				'icons', 'list_afgraph.xpm')
	ot = anatomist.QObjectTree
	ot.setObjectTypeName(_type, 'GraphInteraction')
	ot.setObjectTypeIcon(_type, icon)
	_id_ = 0

	def __init__(self, amodels, agraph):
		anatomist.ObjectList.__init__(self)
		self.setType(AModelsGraphFusionObject._type)
		self._amodels = amodels
		self._agraph = agraph
		AModelsGraphFusionObject._id_ += 1
		self._id = AModelsGraphFusionObject._id_
		self._mypalette = 'AModelsGraphFusionObject_pal_%d' % self._id
		self.setReferential(self._agraph.getReferential())
		self.insert(self._agraph)
		for m in self._amodels: self.insert(m)
		self._init_labels()
		self._newpalette()
		self.compute(False)
		self.display('mean', 'vertex')
		self._init_color_mode()

	def _init_labels(self):
		model = self._amodels[0].graph()

		# translate low level names to high level labels(at model level)
		transfile = os.path.join(aims.carto.Paths.shfjShared(),
				'nomenclature', 'translation',
				'sulci_model_noroots.trl')
		import sigraph
		sigraph.si().setLabelsTranslPath(transfile)
		mf = model.modelFinder()
		mf.initCliques(self._agraph.graph(), False, True)

	def _init_color_mode(self):
		ag = self._agraph
		ag.setColorMode(ag.PropertyMap)
		ag.setColorProperty('diff')

	def _newpalette(self):
		import paletteViewer as PV
		an_shared_path = str( an.anatomistSharedPath() )
		imgfilename = os.path.join(an_shared_path,'rgb', 'Blue-Red.ima')
		r = aims.Reader()
		img = r.read(imgfilename)
		colors = PV.convertVolumeToArray(img).ravel().tolist()
		colors[-4:] = (255, 255, 255, 64)
		processor.execute('NewPalette', {'name' : self._mypalette})
		processor.execute('ChangePalette', {'name' : self._mypalette,
				'colors' : colors, 'color_mode' : 'RGBA'})

	def compute(self, abs_enable):
		import sigraph.models as SM

		models = [m.graph() for m in self._amodels]
		self._abs_enable = abs_enable
		self._md = SM.ModelDifferentiator(models, abs_enable)
		self._md.diff()

	def display(self, choosen_data, choosen_type):
		self._choosen_data = choosen_data
		self._choosen_type = choosen_type

	        # palette
		infomin, infomax = self._md.getMinMax(choosen_data)
		vol = self.getOrCreatePalette().refPalette().volume().get()
		size = vol.getSizeX()
		coeff = (size + 1) / float(size)
		processor.execute('SetObjectPalette',
				{'objects' : [self._agraph],
				'palette' : self._mypalette, 'min' : 0,
				'max' : (infomax - infomin) * coeff})

		# labels
		if choosen_type == 'vertex':
			self._display_vertices_info(choosen_data)
		elif choosen_type == 'all':
			self._display_all_info(choosen_data)
		#self.notifyObservers()
		self._agraph.updateColors()
		#ag = self._agraph
		#ag.setColorMode(ag.Normal)
		#ag.setColorMode(ag.PropertyMap)

	def _display_vertices_info(self, c):
		diff = {}
		for v in self._amodels[0].graph().vertices():
			name, d = self._md.getVertexValue(v, c)
			diff[name] = d
		for v in self._agraph.graph().vertices():
			name = v['label']
			try:
				v['diff'] = diff[name]
			except KeyError:
				v['diff'] = 1. #bad value

	def _display_all_info(self, c):
		vertices = {}
		for v in self._amodels[0].graph().vertices():
			name = v['label']
			vertices[name] = v
		for v in self._agraph.graph().vertices():
			name, v['diff'] = self._md.getVertexValue(v, c)
			diff = v['diff']
			try:
				edges = vertices[name].edges()
			except KeyError:
				edges = None
			if edges:
				for e in edges:
					name, d = self._md.getEdgeValue(e, c)
					diff += d
				v['diff'] = diff / (1 + len(edges))
			else:	v['diff'] = 1. #bad value
		
	def glAPI(self):
		return self._agraph.glAPI()

	def Is2DObject(self):
		return self._agraph.Is2DObject()

	def Is3DObject(self):
		return self._agraph.Is3DObject()

	def boundingBox(self, bmin, bmax):
		return self._agraph.boundingBox(bmin, bmax)

	def optionTree(self):
		_t = qt.QT_TRANSLATE_NOOP
		if AModelsGraphFusionObject._menus is None:
			m = anatomist.ObjectMenu()
			conf = ConfigureCallback()
			import paletteViewer
			showHidePalette =paletteViewer.ShowHidePaletteCallback()
			m.insertItem([], 'configure', conf)
			m.insertItem([], 'show/hide palette', showHidePalette)
			AModelsGraphFusionObject._menus = m.releaseTree()
			AModelsGraphFusionObject._nodelete = \
				[conf, showHidePalette]
		return AModelsGraphFusionObject._menus

	def update(self, observable, arg):
		self.setChanged()
		self.notifyObservers()

	def palette(self):
		return self._agraph.palette()
	
	def getOrCreatePalette(self):
		return self._agraph.getOrCreatePalette()

class ModelsFusionMethod(anatomist.FusionMethod):
	def __init__(self):
		anatomist.FusionMethod.__init__(self)

	def canFusion(self, objects):
		import sigraph
		if len(objects) not in [2, 3]: return 0
		types = []
		for o in objects:
			if not isinstance(o, anatomist.AGraph):
				return 0
			types.append(o.graph())
		nCgraph = len([t for t in types \
				if isinstance(t, sigraph.CGraph)])
		nFRGraph = len([t for t in types \
				if isinstance(t, sigraph.FRGraph)])
		if nCgraph != 1 or (nFRGraph != len(objects) - 1):
			return 0
		return 30

	def fusion(self, objects):
		import sigraph
		amodels = []
		for o in objects.list():
			g = o.graph()
			if isinstance(g, sigraph.CGraph):
				agraph = o
			elif isinstance(g, sigraph.FRGraph):
				amodels.append(o) 
		return AModelsGraphFusionObject(amodels, agraph)

	def ID(self):
		return "modelsFusionMethod"
	
	def orederingMatters():
		return True


class ModelsFusionModule(anatomist.Module):
	def name(self):
		return 'Models Fusion Method Module'

	def description(self):
		return __doc__

f = anatomist.FusionFactory.factory()
m = ModelsFusionMethod()
f.registerMethod(m)

pm = ModelsFusionModule()