def __init__(self, fname, interactive=True):
self.fname = fname
self.graph = nx.read_gpickle(fname)
#apply_workaround(self.graph, thr=1e-3)
#remove_intersecting_edges(self.graph)
print "Number of connected components:", \
nx.number_connected_components(self.graph)
self.selected_path_verts = []
if interactive:
self.fig = plt.figure()
self.path_patch = None
G_p = nx.connected_component_subgraphs(self.graph)[0]
#G_p = nx.connected_component_subgraphs(prune_graph(self.graph))[0]
plot.draw_leaf(G_p, fixed_width=True)
plt.ion()
plt.show()
self.edit_loop()
def randomize(self):
#for n, d in self.graph.nodes_iter(data=True):
# d['x'] += 10*(numpy.random.random() - 0.5)
# d['y'] += 10*(numpy.random.random() - 0.5)
# d['x'] = 1.3*d['x'] + 0.5*d['y']
# d['y'] = 1*d['y']
for u, v, d in self.graph.edges_iter(data=True):
d['conductivity'] += 5 + 0.25*(numpy.random.random()-0.5)
plt.clf()
plot.draw_leaf(self.graph)
plt.show()
def plot_DeltaF_in_leaf(DeltaF, G_pruned, ax=None, fixed_width=False):
# plot DeltaF
cmap = plt.get_cmap('jet')
norm = colors.LogNorm(vmin=1e-8, vmax=1)
scalar_map = cmx.ScalarMappable(norm=norm, cmap=cmap)
if ax == None:
plt.figure()
ax = plt.gca()
# unweighted
scalar_map.set_array(DeltaF)
cols = list(enumerate(scalar_map.to_rgba(DeltaF)))
plot.draw_leaf(G_pruned, ax=ax, mark_edges=cols,
fixed_width=fixed_width)
ax.autoscale(tight='true')
def __init__(self, fname, interactive=True):
self.fname = fname
self.graph = nx.read_gpickle(fname)
print "Number of connected components:", \
nx.number_connected_components(self.graph)
self.selected_path_verts = []
if interactive:
self.fig = plt.figure()
self.path_patch = None
plot.draw_leaf(self.graph)
plt.ion()
plt.show()
self.edit_loop()
def remove_selection(self):
if len(self.selected_path_verts) == 0:
print "Nothing selected!"
return
path = self.points_to_path(close=True)
nodes = [n for n in self.graph.nodes_iter() if
path.contains_point((self.graph.node[n]['x'],
self.graph.node[n]['y']))]
print nodes
self.graph.remove_nodes_from(nodes)
plt.clf()
plot.draw_leaf(self.graph)
self.selected_path_verts = []
self.path_patch = None
plt.show()
def straighten_path(self):
print """Please select the edges you would like to straighten out.
Available commands:
l: Linear curve fit
p: Print edge list
x: Exit
"""
self.edges = self.graph.edges()
self.edge_paths = [[(self.graph.node[e[0]]['x'],
self.graph.node[e[0]]['y']),
(self.graph.node[e[1]]['x'],
self.graph.node[e[1]]['y'])] for e in self.edges]
self.selected_edges = []
self.drawn_edges = []
self.cid_path_click = self.fig.canvas.mpl_connect(
'button_press_event',
self.onclick_straighten_path)
while True:
cmd = raw_input("SP> ")
if cmd == 'l':
self.fit_selected_edges_linear()
print "Linear fit concluded. Exiting."
plt.clf()
plot.draw_leaf(self.graph)
self.fig.canvas.mpl_disconnect(self.cid_path_click)
return
elif cmd == 'x':
# Clean up
self.fig.canvas.mpl_disconnect(self.cid_path_click)
return
elif cmd == 'p':
print [self.edges[e] for e in self.selected_edges]
else:
print "Command not recognized."
filtration_steps=args.filtration_steps)
print "Decomp. took {}s.".format(time.time() - t0)
print "Number of loops:", dual.number_of_nodes()
print "Number of tree nodes:", tree.number_of_nodes()
if args.save != "":
print "Saving file."
SAVE_FORMAT_VERSION = 5
sav = {'version':SAVE_FORMAT_VERSION, \
'leaf':leaf, 'tree':tree, 'dual':dual, \
'filtration':filtr, 'pruned':pruned, \
'removed-edges':removed_edges}
storage.save(sav, args.save)
print "Done."
if args.plot:
plt.figure()
plot.draw_leaf(leaf, "Input leaf data")
plt.figure()
plot.draw_leaf(pruned, "Pruned leaf data and dual graph")
plot.draw_dual(dual)
plt.figure()
plot.draw_tree(tree)
plt.figure()
plot.draw_filtration(filtr)
plt.show()
print "Done."
if args.plot or args.save_plots != "":
print "Plotting/saving plots."
fname = ""
fname_no_ext = ""
fext = ".png"
if args.save_plots != "":
fname, fext = os.path.splitext(args.save_plots)
fname_no_ext = fname + "_no_ext"
print fname, fext
plt.figure()
print "Drawing leaf."
plot.draw_leaf(leaf, fname=fname, fext=fext, dpi=600)
plt.figure()
print "Drawing hierarchical trees."
plot.draw_tree(marked_tree, pos=tree_pos, fname=fname, fext=fext)
plt.figure()
if args.tree_heights:
pos = tree_pos_h
else:
pos = tree_pos
plot.draw_tree(marked_tree_no_ext, pos=pos,
fname=fname_no_ext, fext=fext)
plt.figure()