def show_flows(g, ngs, fgs):
p0 = gd.getpos(g)
ckw = dict([(k,
dict(facecolor='gray',
alpha=1,
linewidth=.5,
arrowstyle='-|>',
edgecolor='black',
color='gray',
shrinkA=0,
shrinkB=0)) for k in g.edges()])
skw = dict(facecolor='none', edgecolor='black', s=20)
gd.draw(g, p0, g.edges(), ckw=ckw, skw=skw, cktype='simple')
colors = mycolors.getct(len(fgs))
for i, fg in enumerate(fgs):
edges = fg.edges()
weights = [fg[e[0]][e[1]]['weight'] for e in edges]
ckw = dict([(k, dict(color=colors[i], linewidth=weights[j] / 3))
for j, k in enumerate(edges)])
gd.draw(fg, p0, edges, ckw=ckw, scatter_nodes=[], cktype='simple')
def plot_easy_inference():
dg = io.getGraph()
pos = gd.getpos(dg)
f = myplots.fignum(4, (8,8))
ax = f.add_subplot(111)
ax.set_title('putative worm chip network')
gd.easy_draw(dg, pos)
f.savefig(myplots.figpath('worm_chip_graph.pdf'))
def show_flows(g, ngs, fgs):
p0 = gd.getpos(g)
ckw = dict([(k,dict(facecolor = 'gray',
alpha = 1,
linewidth = .5,
arrowstyle = '-|>',
edgecolor = 'black',
color = 'gray',
shrinkA = 0,
shrinkB = 0))
for k in g.edges() ])
skw =dict(facecolor = 'none',
edgecolor = 'black',
s = 20)
gd.draw(g,p0,g.edges(),
ckw = ckw,
skw = skw,
cktype = 'simple')
colors = mycolors.getct(len(fgs))
for i,fg in enumerate(fgs):
edges = fg.edges()
weights = [fg[e[0]][e[1]]['weight'] for e in edges]
ckw = dict([(k, dict(color = colors[i],
linewidth = weights[j]/3))
for j, k in enumerate(edges)
])
gd.draw(fg,
p0,
edges,
ckw = ckw,
scatter_nodes = [],
cktype = 'simple')
def set_pos(**kwargs):
g = get_graph(**mem.sr(kwargs))
pos = gd.getpos(g)
return pos
