def add(self, data, name=None, support=70, scaled=True,
branchlabels=False, leaflabels=True, *args, **kwargs):
"""
Add tree to existing figure
"""
root = None
if isinstance(data, tree.Node):
root = data
else:
root = tree.read(data)
if not root:
raise IOError, "cannot coerce data into tree.Node"
name = name or root.treename
self.root.append(root)
fig = self.figure
N = len(self.plot)+1
for i, p in enumerate(self.plot):
p.change_geometry(1, N, i+1)
plt = TreePlot(fig, 1, N, N, tf=self, app=self, name=name, support=support,
scaled=scaled, branchlabels=branchlabels,
leaflabels=leaflabels, *args, **kwargs)
p = fig.add_subplot(plt)
p.set_root(root)
p.plot_tree()
p.index = N-1
self.plot.append(p)
if name:
assert name not in self.name2plot
self.name2plot[name] = p
def add(self, data, name=None, support=70, scaled=True,
branchlabels=False, leaflabels=True):
root = None
if isinstance(data, tree.Node):
root = data
else:
root = tree.read(data)
if not root:
raise IOError, "cannot coerce data into tree.Node"
name = name or root.treename
self.root.append(root)
fig = self.figure
N = len(self.plots)+1
for i, p in enumerate(self.plots):
p.change_geometry(1, N, i+1)
p = fig.add_subplot(
TreePlot(fig, 1, N, N, app=self, name=name, support=support,
scaled=scaled, branchlabels=branchlabels,
leaflabels=leaflabels)
).plot_tree(self.root[-1])
p.index = N-1
self.plots.append(p)
if name:
assert name not in self.name2plot
self.name2plot[name] = p
## global IP
## if IP:
## def f(shell, s):
## self.highlight(s)
## return sorted([ x.label for x in self.highlighted ])
## IP.expose_magic("highlight", f)
## def f(shell, s):
## self.root.ladderize()
## self.redraw()
## IP.expose_magic("ladderize", f)
## def f(shell, s):
## self.show()
## IP.expose_magic("show", f)
## def f(shell, s):
## self.redraw()
## IP.expose_magic("redraw", f)
return p
def __init__(self, data, name=None, scaled=True, div=0.25,
branchlabels=True, leaflabels=True, overview=True):
self.name = name
self.div_value = div
self.scaled = scaled
self.branchlabels = branchlabels
self.leaflabels = leaflabels
self.highlighted = set()
if isinstance(data, tree.Node):
root = data
else:
root = tree.read(data)
self.root = root
if not self.root:
raise IOError, "cannot coerce data into tree.Node"
self.name = self.name or root.treename
pars = SubplotParams(
left=0, right=1, bottom=0.05, top=1, wspace=0.01
)
fig = pyplot.figure(subplotpars=pars, facecolor="white")
connect_events(fig.canvas)
self.figure = fig
tp = TreePlot(fig, 1, 2, 2, app=self, name=self.name,
scaled=self.scaled, branchlabels=self.branchlabels,
leaflabels=self.leaflabels)
ax2 = fig.add_subplot(tp)
ax2.plot_tree(self.root)
self.detail = ax2
ax1 = fig.add_subplot(
OverviewTreePlot(fig, 121, app=self, snap=False, scaled=scaled,
branchlabels=False,
leaflabels=False,
target=self.detail)
).plot_tree(self.root)
self.overview = ax1
if not overview:
self.toggle_overview(False)
self.set_positions()
if self.detail.nleaves < 50:
self.toggle_overview()
def __init__(self, data, name=None, scaled=True, div=0.25,
branchlabels=True, leaflabels=True, xoff=0, yoff=0,
mark_named=True, overview=True, interactive=True,
radial=False, leaf_fontsize=10, branch_fontsize=10,
direction="rightwards"):
self.overview = None
self.overview_width = div
self.name = name
self.scaled = scaled
self.radial = radial
if radial:
self.leaflabels = False
self.branchlabels = branchlabels
self.leaflabels = leaflabels
self.xoff = xoff
self.yoff = yoff
self.direction=direction
self.leaf_anchor = "left" if self.direction == "rightwards" else "right"
self.branch_anchor = "right" if self.direction == "rightwards" else "left"
self.mark_named=mark_named # Drawing a circle at named nodes
if isinstance(data, tree.Node):
root = data
else:
root = tree.read(data)
self.root = root
if not self.root:
raise IOError, "cannot coerce data into tree.Node"
self.name = self.name or root.treename
pars = SubplotParams(
left=0, right=1, bottom=0.05, top=1, wspace=0.01
)
fig = pyplot.figure(subplotpars=pars, facecolor="white")
events.connect_events(fig.canvas)
self.figure = fig
self.layers = OrderedDict()
self.ovlayers = OrderedDict()
self.initialize_subplots(overview, leaf_fontsize, branch_fontsize)
self.home()
for child in node.children:
_bindeltran(child, stepmatrix, node2dpv, node2deltr, s)
return node2deltr
def binary_deltran(tree, chardata, stepmatrix):
states = range(len(stepmatrix))
node2dpv = downpass(tree, states, stepmatrix, chardata)
node2deltr = _bindeltran(tree, stepmatrix, node2dpv)
return node2deltr
if __name__ == "__main__":
from pprint import pprint
from ivy import tree
root = tree.read("(a,((b,c),(d,(e,f))));")
nstates = 4
states = range(nstates)
cm = default_costmatrix(nstates)
chardata = dict(zip("abcdef", map(int, "000233")))
dp = downpass(root, states, cm, chardata)
for i, node in enumerate(root):
if not node.label:
node.label = "N%s" % i
else:
node.label = "%s (%s)" % (node.label, chardata[node.label])
print(ascii.render(root))
_bindeltran(child, stepmatrix, node2dpv, node2deltr, s)
return node2deltr
def binary_deltran(tree, chardata, stepmatrix):
states = range(len(stepmatrix))
node2dpv = downpass(tree, states, stepmatrix, chardata)
node2deltr = _bindeltran(tree, stepmatrix, node2dpv)
return node2deltr
if __name__ == "__main__":
from pprint import pprint
from ivy import tree
root = tree.read("(a,((b,c),(d,(e,f))));")
nstates = 4
states = range(nstates)
cm = default_costmatrix(nstates)
chardata = dict(zip("abcdef", map(int, "000233")))
dp = downpass(root, states, cm, chardata)
for i, node in enumerate(root):
if not node.label:
node.label = "N%s" % i
else:
node.label = "%s (%s)" % (node.label, chardata[node.label])
print(ascii.render(root))
