def _create_renderer(self):
""" Creates the renderer instance if not yet available
and opens the scenes in mayavi """
if self.active:
if self.rendermanager is None:
logger.debug('Create a RenderManager instance')
self.rendermanager = RenderManager(network=self)
else:
logger.debug('RenderManager instance already running. This is an error.')
class Network(HasTraits):
""" The implementation of the Connectome Networks """
implements(INetwork)
# Network ID, from parsed GraphML the graphid
networkid = ''
# Network name
networkname = Str
# network name as seen in the TreeView
name = Str
# Is it an hierarchical network?
hierarchical = CBool(False)
# TODO: later, also Hypergraph?!
# see: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000385
hypergraph = CBool(False)
# Directionality of the Network, {True: 'directed', False: 'undirected'}
directed = CBool(False)
# metadata for the network
metadata = Dict
# NodeKeys from the parsed GraphML
# These are Dict of Dict, all having strings
nodekeys = {}
# Edgekeys, from parsed GraphML
edgekeys = {}
# A NetworkX AttrGraph containing all the information
graph = Any
# Surface containers
surfaces = List(ISurfaceContainer)
# Surface containers loaded
surfaces_loaded = List(ISurfaceContainer)
# Volume data
volumes = List(IVolume)
# Track data
tracks = List(ITrackfile)
# is this network active, and thus a render manager displayed?
active = Bool
# the render manager of this network
rendermanager = Instance(RenderManager)
# DatasourceManager Instance of this network
datasourcemanager = Instance(DatasourceManager)
# private traits
###########
# parent cfile this networks belongs to
_parentcfile = Any
# filezip of cfile
_filezip = DelegatesTo('_parentcfile')
# edge parameters for visualization
_edge_para = Instance(EdgeParameters)
# View
traits_view = View(
Item('networkname', style = 'readonly'),
Item('hierarchical', style = 'simple'),
Item('hypergraph', style = 'simple'),
Item('directed', style = 'simple'),
Item('active', style = 'simple'),
title = 'A network',
)
def __init__(self, name, src = None, directed = '0', pickled_graph = None, \
hierarchical ='0', hypergraph = '0', graph = None):
""" Initializes the network and sets the traits.
Parameters
----------
name : string
the name of the network
src : file handle or StringIO object
the source text of the network to parse
pickled_graph : NetworkX graph
reference to a graph object, src should be None
directed : bool
Is the network directed?
hierarchical : bool
Is the network hierarchical? (default: '0') Not implemented yet.
hypergraph : bool
Is the network a hypergraph? (default: '0') Not implemented yet.
"""
# initialize the traits
self.networkname = name
self.directed = int(directed)
self.hierarchical = int(hierarchical)
self.hypergraph = int(hypergraph)
if src is None and not pickled_graph is None:
self.load_pickled_graphml(pickled_graph)
else:
if not src is None:
# generates NetworkX Graph
self.graph = self.parse_network_graphml(src)
elif not graph is None:
self.graph = graph
else:
if self.directed:
from networkx import DiGraph
self.graph = DiGraph()
logger.info("Initialize with empty directed Graph")
else:
from networkx import Graph
self.graph = Graph()
logger.info("Initialize with empty undirected Graph")
# initializes the weight key of the graph
# with the first edgekey
if len(self.edgekeys) > 0:
edgk = self.edgekeys.keys()
if not 'weight' in edgk:
self.set_weight_key(edgk[0])
else:
# try grabbing first edge from the graph
if self.graph.number_of_edges() > 0:
it = self.graph.edges_iter(data=True)
edg = it.next()
if len(edg[2]) > 0:
# if it has a weigth key, just leave it
edgk = edg[2].keys()
if not 'weight' in edgk:
self.set_weight_key(edgk[0])
else:
pass
# logger.error('Cannot set weight key for network : ' + self.networkname)
def _name_default(self):
return self.networkname
def _active_default(self):
return False
def _active_changed(self , value):
if value:
n = self.name
if ' [Active]' not in n:
self.name = "%s [Active]" % n
# XXX: do refactor with threaded loading of surfaces
# and default spring force layout for graph rendering!
# see also TraitsUI Demos: Multi thread demo
# load the surface containers data
# make a deep copy of the already loaded surface containers
import copy
self.surfaces = copy.deepcopy(self.surfaces_loaded)
for surfcont in self.surfaces:
surfcont.load_surface_container()
if self.rendermanager is None:
self._create_datasourcemanager()
self._create_renderer()
# if there are no surfaces, initialize
# network rendering, but only if dn_positions are given
if len(self.surfaces) == 0:
logger.debug('No surfaces found. Try to render graph view with dn_position information.')
self.rendermanager.datasourcemanager._compute_3DLayout(-1, -1)
self.rendermanager.visualize_graph()
else:
logger.debug('SurfaceContainer found. Try to render 3D View using %s.' % self.surfaces[0].name)
if len(self.surfaces[0].surfaces) == 0:
logger.debug('Rendering not possible because SurfaceContainer contains no surfaces.')
else:
logger.debug('Using first surface for rendering.')
self.surfaces[0].surfaces[0]._layout_3DView()
if not self._parentcfile._workbenchwin is None:
#from enthought.pyface.timer.api import do_later
from enthought.pyface.api import GUI
GUI.invoke_later(self._parentcfile._workbenchwin.status_bar_manager.set, message = '')
else:
self.name = self.name.replace(' [Active]', '')
logger.debug('Close RenderManager scenes')
self.rendermanager.close_scenes()
logger.debug('All scenes closed.')
# FIXME: what is happening in the following?
# e.g. for instances. e.g. reset traits?
# XXX: this is somehow not correct. do i need to use del
# or remove/reset traits?
self.rendermanager = None
self.datasourcemanager = None
self.surfaces = []
def _de_activate(self):
""" Toggles the internal state of the activation """
if self.active:
self.active = False
else:
self._parentcfile._workbenchwin.status_bar_manager.message = 'Activating network ...'
self.active = True
def _edge_parameters(self):
""" Dialog to change edge attribute and thresholding """
if self._edge_para is None:
self._edge_para = EdgeParameters(self, self.rendermanager.attract.point_scalars_name)
self._edge_para.configure_traits()
def _create_renderer(self):
""" Creates the renderer instance if not yet available
and opens the scenes in mayavi """
if self.active:
if self.rendermanager is None:
logger.debug('Create a RenderManager instance')
self.rendermanager = RenderManager(network=self)
else:
logger.debug('RenderManager instance already running. This is an error.')
def _create_datasourcemanager(self):
""" Creates the datasource manager instance if not yet available """
if self.active:
if self.datasourcemanager is None:
logger.debug('Create a DatasourceManager instance')
self.datasourcemanager = DatasourceManager(network=self)
else:
logger.debug('DatasourceManager instance already running. This is an error.')
def _render_matrix(self):
""" Invokes the connectivity matrix viewer """
# assume the network is activated (i.e. data source generated)
# we need the edge parameter instance initialized
if self._edge_para is None:
self._edge_para = EdgeParameters(self, self.rendermanager.attract.point_scalars_name)
logger.debug('Invoke Matrix Viewer...')
self.rendermanager.invoke_matrix_viewer()
def _trackvis_launch(self):
""" Generates scene file and launch Trackvis on the selected nodes """
import tempfile
logger.debug('Starting TrackVis ...')
# extract selected subgraph
selectionlist = self.get_selectiongraph_list()
if len(selectionlist) == 0:
# message
from enthought.traits.ui.message import message
message(message = 'No nodes selected for ROI creation!', title = 'Infomessage', buttons = [ 'OK' ], parent = None)
tmpgraph = self.graph.subgraph(selectionlist)
# extract trackfile temporarily
if len(self.tracks) == 0:
logger.info('No trackfile found to invoke Trackvis.')
return
else:
# load the first trackfile
trackfname = self.tracks[0].load_trackfile_to_file()
# find the first valid segmentation volume in the self.volumes list
for vol in self.volumes:
if vol.segmentation:
logger.debug('Found a segmentation volume file. Assume labels are corresponding.')
volumefname = vol.load_volume_to_file()
break
# generate the scene file in the temporary folder
tmpscenefile=tempfile.mkstemp(prefix='tmp', suffix='.scene')
# generate trackfile
generate_scene_file(scenefname=tmpscenefile[1], \
trackfname = trackfname, \
volumefname = volumefname, \
selectiongraph = tmpgraph)
# execute trackvis in a thread
pref = preference_manager.preferences
action = ThreadedTrackvis(tvpath = pref.get('cviewer.plugins.ui.trackvispath'), \
fname = tmpscenefile[1], \
trkfname = trackfname,\
volfname = volumefname)
action.start()
def add_surface_container(self, surfacecontainer):
""" Add a surface container to the loaded list
Parameters
----------
surfacecontainer : `ISurfaceContainer` instance
a surface container object
"""
surfacecontainer._networkref = self
self.surfaces_loaded.append(surfacecontainer)
def add_volume(self, volume):
""" Adds a volume to the volumes list
Parameters
----------
volume : `IVolume` instance
a volume object
"""
self.volumes.append(volume)
def add_trackfile(self, trackfile):
""" Adds a trackfile to the tracks list
Parameters
----------
trackfile : `ITrackfile` instance
a trackfile of type ITrackfile
"""
self.tracks.append(trackfile)
def unselect_all(self):
""" Unselects every node in the current network """
if self.datasourcemanager is None:
raise Exception('No DatasourceManager. You have to first activate the network and render it.')
from numpy import array
# get all the nodes
graphnodes = self.datasourcemanager._srcobj.relabled_graph.nodes()
# and unselect all nodes
self.rendermanager._select_nodes(selection_node_array = array(graphnodes))
def select_all(self):
""" Selects all nodes in the current network """
if self.datasourcemanager is None:
raise Exception('No DatasourceManager. You have to first activate the network and render it.')
from numpy import array
# get all the nodes
graphnodes = self.datasourcemanager._srcobj.relabled_graph.nodes()
# and select all nodes
self.rendermanager._select_nodes(selection_node_array = array(graphnodes), activate = True)
def set_selectiongraph(self, sellist, activate = False):
""" Sets the selected nodes in the network to active.
Parameters
----------
sellist : array_like
a list of nodeids conforming to the NetworkX node id
activate : boolean
set the selectionlist nodes to activated?
"""
from numpy import array, int16
graphnodes = self.graph.nodes(data=False)
if self.rendermanager is None:
raise Exception('No RenderManager. You have to first activate the network and render it.')
if len(sellist) == 0:
self.unselect_all()
return
from numpy import array, append
tmparr = array([])
for node in sellist:
# check if it is a valid graph node id
if node in graphnodes:
# get the node id as integer
j = int(node.lstrip('n'))-1
# extend empty array with node id
tmparr = append(tmparr, j)
self.rendermanager._select_nodes(selection_node_array = array(tmparr, dtype = int16), activate = activate)
def get_selectiongraph_list(self):
""" Returns a list of the node ids that were selected in
the rendered scene.
"""
if self.datasourcemanager is None:
raise Exception('No DatasourceManager. You have to first activate the network and render it.')
import numpy as np
sel_list = []
if not self.active:
return sel_list
selnodesarray = self.datasourcemanager._srcobj.selected_nodes
# array with indices where the nodes are selected (==1)
idx = np.where(selnodesarray == 1)[0]
for i in idx:
sel_list.append('n' + str(i + 1))
return sel_list
def set_weight_key(self, weight_key = None):
""" Sets the weight key in the graph representation of the network.
Parameters
----------
weight_key : Str
Must be a possible existing edge key
"""
if not weight_key is None:
for u,v,d in self.graph.edges(data=True):
self.graph[u][v]['weight']=d[weight_key]
return True
else:
return False
def get_matrix(self, weight_key = None):
""" Returns the connectivity matrix of the network with the nodes
ordered according to their id in the GraphML file.
Parameters
----------
weight_key : Str
Possible key value of the edges
Returns
-------
matrix : `Numpy.array` instance
The connectivity matrix
"""
nr_nodes = len(self.graph.nodes())
if not weight_key is None:
#FIXME: sanity check if weight_key exists
# thanks to Aric Hagberg
for u,v,d in self.graph.edges(data=True):
self.graph[u][v]['weight']=d[weight_key]
nodes = [(lambda nmod:'n'+str(nmod))(node) for node in range(1,nr_nodes + 1)]
from networkx import to_numpy_matrix
return to_numpy_matrix(self.graph, nodelist = nodes)
def toggle_surface(self):
""" Toggle the surface for the selected network nodes """
if self.rendermanager is None:
raise Exception('No RenderManager. You have to first activate the network and render it.')
self.rendermanager._toggle_surface()
def show_surface(self):
""" Shows the surface for the selected network nodes """
if self.rendermanager is None:
raise Exception('No RenderManager. You have to first activate the network and render it.')
self.rendermanager._show_surface()
def load_pickled_graphml(self, graph):
""" Loads a pickled GraphML file
Parameters
----------
graph : NetworkX Graph instance
A graph instance
"""
# setting the graph
self.graph = graph
if self.graph.has_node('n0'):
if self.graph.node['n0'].has_key('nodekeys'):
# extracting the node keys from the first node
self.nodekeys = self.graph.node['n0']['nodekeys']
# extracting the edge keys from the first edge (without explanation)
if self.graph.node['n0'].has_key('edgekeys'):
self.edgekeys = self.graph.node['n0']['edgekeys']
if self.graph.node['n0'].has_key('graphid'):
self.networkid = self.graph.node['n0']['graphid']
# remove node
self.graph.remove_node('n0')
def _return_default_edgevalue(self, edgekeys, key):
""" Looks up if there is a default value defined, otherwise
return zero """
if edgekeys[key].has_key('default'):
return float(edgekeys[key]['default'])
else:
return 0.0
def parse_network_graphml(self, path):
""" Read network in GraphML format from a path.
Parameters
----------
path : string
path the the GraphML file
Returns
-------
graph : NetworkX `Graph`
"""
import networkx as nx
from networkx.utils import _get_fh
from lxml import etree
# Return a file handle for given path.
# Path can be a string or a file handle.
# Attempt to uncompress/compress files ending in .gz and .bz2.
fh=_get_fh(path,mode='r')
tree = etree.parse(fh)
# get the root node from parsed lxml
root = tree.getroot()
# Schema Validation
# http://codespeak.net/lxml/validation.html#xmlschema
# define the namespace prefixes
nsprefix = "{%s}" % root.nsmap[None]
nsxlink = "{%s}" % root.nsmap['xlink']
nodekeys = {}
edgekeys = {}
defaultDirected = [True]
# Parse the KEYs
for child in root.iterchildren():
if child.tag == (nsprefix+'key'):
attribs = child.attrib
ddkeys = {}
for mchildren in child:
if mchildren.tag == (nsprefix+'default'):
ddkeys['default'] = mchildren.text
elif mchildren.tag == (nsprefix+'desc'):
ddkeys['desc'] = mchildren.text
if child.attrib['for'] == 'node':
# Parse all the node keys
# Read in the description and the default (if existing)
# dict of dicts for nodes: key1: the id; key2: rest: attr.name, attr.type, desc, default
nodekeys[attribs['id']] = {'attr.name' : attribs['attr.name'], \
'attr.type' : attribs['attr.type']}
# add default/desc keys if existing
nodekeys[attribs['id']] = ddkeys
elif child.attrib['for'] == 'edge':
# Parse all the edge keys
# Read in the description and the default (if existing)
# dict of dicts for edges: key1: the id; key2: rest: attr.name, attr.type, desc, default
edgekeys[attribs['id']] = {'attr.name' : attribs['attr.name'], \
'attr.type' : attribs['attr.type']}
# add default/desc keys if existing
edgekeys[attribs['id']] = ddkeys
else:
logger.error("The 'for' attribute of key-tag not known, must be either node or edge")
elif child.tag == (nsprefix+'graph'):
# start parsing the graph into networkx data structure
# create graph depending on (either AttrGraph or AttrDiGraph)
# directionality: undirected/directed
# version of networkx:
# contains self-loops
# edges have dicts
# data per graph/node/edge
for attr, value in child.items():
if attr == 'edgedefault' and value == 'undirected':
defaultDirected[0] = False
elif attr == 'id':
graphid = value
if defaultDirected[0]:
G = nx.DiGraph()
else:
G = nx.Graph()
# add id, nodekeys and edkeys as traits
self.networkid = graphid
self.nodekeys = nodekeys
self.edgekeys = edgekeys
# iterate over all nodes and edges
for children in child.iterchildren():
if children.tag == (nsprefix+'node'):
# parse the node
for attr, value in children.items():
if attr == 'id':
# add the node with corresponding id
G.add_node(value)
# keep node id to store attributes
nodeid = value
elif attr == (nsxlink+'href'):
# add xlink to node dictionary
G.node[nodeid]['xlink'] = value
else:
# node attribute not known
logger.warning('The following node attribute is not known and thus discarded:'+ attr + ':' + value)
# parse node data, add to node dict
for data in children.iterchildren():
# read the keylabel, i.e. the data attribute name
keylabel = data.attrib['key']
# is the keylabel in the list of allowed keys
if nodekeys.has_key(keylabel):
if not data.text == '':
# add data to the node's dict
G.node[nodeid][keylabel] = data.text
else:
# no data available, check if default value exists
if nodekeys[keylabel].has_key('default'):
# add default data to the node's dict
G.node[nodeid][keylabel] = nodekeys[keylabel]['default']
logger.debug('Added default value '+ keylabel + ':' + nodekeys[keylabel]['default'])
else:
logger.warning('Nor data nor default value defined for ' + keylabel)
# TODO: Work with exceptions!
else:
logger.warning("Data entry with key " + keylabel + " not defined.")
elif children.tag == (nsprefix+'edge'):
# parse the edge
# parse its attributes
for attr, value in children.items():
if attr == 'id':
# no usage of edge id
# add the edge with corresponding id
src = children.attrib['source']
tar = children.attrib['target']
G.add_edge(src, tar)
# keep dest and tar id to store attributes
srcid = src
tarid = tar
elif attr == (nsxlink+'href'):
# add xlink to edge dictionary
G.edge[srcid][tarid]['xlink'] = value
# parse data, and add to the edge dict
for data in children.iterchildren():
# read the keylabel, i.e. the data attribute name
keylabel = data.attrib['key']
# is the keylabel in the list of allowed keys
if self.edgekeys.has_key(keylabel):
if not data.text == '':
# add data to the edge's dict, assume float!!
G.edge[srcid][tarid][keylabel] = float(data.text)
else:
# no data available, check if default value exists
G.edge[srcid][tarid][keylabel] = self._return_default_edgevalue(self.edgekeys, keylabel)
data_keys = G.edge[srcid][tarid].keys()
# check if we missed some edge keys that are available in the header
for k, v in self.edgekeys.items():
if not k in data_keys:
G.edge[srcid][tarid][k] = self._return_default_edgevalue(self.edgekeys, k)
# return the generated network graph
return G