def add_network_from_matrix_with_pos(self, name, matrix, pos, nodeinfo_like_graph = None, \
metadata = None, directed = False, hierarchical = False, hypergraph = False):
""" Add a network to the cfil based on the given connectivity matrix and
position information.
Parameters
----------
name : String
Name of the newly added network
matrix : NxN array
A NxN Numpy array with the values for the edges. N must be the same
as len(like_network.graph.nodes()). The first row of the matrix
corresponds to the `NetworkX` node with id 'n1'
pos : Nx3 array
A Nx3 array with the X,Y,Z coordinates for every row (=node) of the matrix
nodeinfo_like_graph : `NetworkX` graph
Use the node information for the new network
metadata : Dict
A dictionary of metadata
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.
Returns
-------
networkid : int
The index in the list of networks in the cfile
"""
from cviewer.plugins.cff.network import Network
# create a new network object
my_network = Network(name = name, directed = directed, hierarchical = hierarchical, \
hypergraph = hypergraph)
if not metadata is None:
my_network.metadata = metadata
# add graph
import networkx as nx
test_G = nx.from_numpy_matrix(matrix)
# relabeling function
addn = lambda nmod:'n'+str(nmod+1)
# relabel graph
test_G_corrected = nx.relabel_nodes(test_G, addn)
# update the node position
for i in range(matrix.shape[0]):
nodeid = addn(i)
if not nodeinfo_like_graph is None and nodeinfo_like_graph.has_node(nodeid):
test_G_corrected.node[nodeid] = nodeinfo_like_graph.node[nodeid]
test_G_corrected.node[nodeid]['dn_position'] = ','.join(list(map(str,pos[i, :])))
my_network.graph = test_G_corrected
# setting the correct parent cfile
my_network._parentcfile = self
# add the created network object to this cfile
self.networks.append(my_network)
# returns the id of the added network
return len(self.networks)-1
