def layout_mds(self, steps, distances, progress_callback=None, opt_from_curr=False):
"""Position the network components according to similarities among
them.
"""
nodes = self.nodes()
if distances == None or distances.dim != len(nodes):
self.information('invalid or no distance matrix')
return 1
p = self.plot()
minStressDelta = 0
mdsRefresh = int(steps / 20)
self.mdsStep = 1
self.stopMDS = False
#~ distances.matrixType = core.SymMatrix.Symmetric
mds = MDS()(distances)
mds.optimize(10, projection.mds.SgnRelStress, 0)
rect = self.data_rect()
w_fr = rect.width()
h_fr = rect.height()
d_fr = math.sqrt(w_fr ** 2 + h_fr ** 2)
x_mds, y_mds = zip(*mds.points)
w_mds = max(x_mds) - min(x_mds)
h_mds = max(y_mds) - min(y_mds)
d_mds = math.sqrt(w_mds ** 2 + h_mds ** 2)
self.set_node_coordinates(dict(
(n, (nodes[n].x() * d_mds / d_fr, nodes[n].y() * d_mds / d_fr)) for n in nodes))
p.update_graph_layout()
qApp.processEvents()
if opt_from_curr:
for i, u in enumerate(sorted(nodes.keys())):
mds.points[i][0] = nodes[u].x()
mds.points[i][1] = nodes[u].y()
else:
mds.Torgerson()
mds.optimize(steps, projection.mds.SgnRelStress, minStressDelta,
progressCallback=
lambda a,
b=None,
mds=mds,
mdsRefresh=mdsRefresh,
progress_callback=progress_callback:
self.mds_callback(a, b, mds, mdsRefresh, progress_callback))
self.mds_callback(mds.avgStress, 0, mds, mdsRefresh, progress_callback)
if progress_callback is not None:
progress_callback(mds.avgStress, self.mdsStep)
return 0
def layout_fragviz(self, steps, distances, graph, progress_callback=None, opt_from_curr=False):
"""Position the network components according to similarities among
them.
"""
if distances == None or graph == None or distances.dim != graph.number_of_nodes():
self.information('invalid or no distance matrix')
return 1
p = self.plot()
edges = self.edges()
nodes = self.nodes()
avgLinkage = True
rotationOnly = False
minStressDelta = 0
mdsRefresh = 10#int(steps / 20)
self.mdsStep = 1
self.stopMDS = False
nodes_inds = dict((n, i) for i, n in enumerate(sorted(graph.nodes_iter())))
inds_nodes = dict((i, n) for i, n in enumerate(sorted(graph.nodes_iter())))
graph_components = nx.algorithms.connected_components(graph)
matrix_components = [[nodes_inds[n] for n in c] for c in graph_components]
#~ distances.matrixType = core.SymMatrix.Symmetric
# scale net coordinates
if avgLinkage:
distances = distances.avgLinkage(matrix_components)
# if only one component
if distances.dim == 1:
return 0
mds = MDS()(distances)
rect = self.data_rect()
w_fr = rect.width()
h_fr = rect.height()
d_fr = math.sqrt(w_fr ** 2 + h_fr ** 2)
x_mds, y_mds = zip(*mds.points)
w_mds = max(x_mds) - min(x_mds)
h_mds = max(y_mds) - min(y_mds)
d_mds = math.sqrt(w_mds ** 2 + h_mds ** 2)
# if only one component
if d_mds == 0 or d_fr == 0:
d_mds = 1
d_fr = 1
self.set_node_coordinates(dict((key, (node.x() * d_mds / d_fr, node.y() * d_mds / d_fr)) \
for key, node in nodes.items()))
p.update_graph_layout()
qApp.processEvents()
if opt_from_curr:
if avgLinkage:
for u, c in enumerate(graph_components):
x = sum([nodes[n].x() for n in c]) / len(c)
y = sum([nodes[n].y() for n in c]) / len(c)
mds.points[u][0] = x
mds.points[u][1] = y
else:
for i, u in enumerate(sorted(nodes.keys())):
mds.points[i][0] = nodes[u].x()
mds.points[i][1] = nodes[u].y()
else:
mds.Torgerson()
mds.optimize(steps, projection.mds.SgnRelStress, minStressDelta,
progressCallback=
lambda a, b=None, mds=mds, mdsRefresh=mdsRefresh, graph_comp=graph_components,
matrix_comp=matrix_components, progress_callback=progress_callback:
self.fragviz_callback(a, b, mds, mdsRefresh, graph_comp, matrix_comp, progress_callback))
self.fragviz_callback(mds.avgStress, 0, mds, mdsRefresh, graph_components, matrix_components, progress_callback)
if progress_callback is not None:
progress_callback(mds.avgStress, self.mdsStep)
return 0
