def get_nodesheight(self):
root = Tree(self.tree)
nh_map = {}
for node in root.traverse(strategy = "preorder"):
if hasattr(node, "B"):
height = node.get_closest_leaf(topology_only=True)
#height = node.get_farthest_leaf(topology_only=True)
nh_map[node.B] = height[1] + 1
return nh_map
def get_speciation_rate_fast(self):
"""ETE2 prune() function is extremely slow on large trees, so
this function don't use it and instead just removes "redundant"
species-level nodes one-by-one"""
species = set()
root = Tree(self.tree)
name2node = {}
for node in root.traverse(strategy = "postorder"):
if node.is_leaf():
name2node[node.name] = node
#pruning the input tree such that each species only appear once
for name in self.taxonomy.keys():
ranks = self.taxonomy[name]
sp = ranks[-1]
if sp != "-":
if sp in species:
node = name2node.get(name, None)
if node:
node.delete(preserve_branch_length=True)
else:
raise ValueError("Node names not found in the tree: " + name)
else:
species.add(sp)
# traverse the pruned tree, counting the number of speciation events and
# summing up the branch lengths
sumbr = 0.0
cnt = 0
for node in root.traverse(strategy = "preorder"):
sumbr += node.dist
cnt += 1
# sp_rate = number_of_sp_events / sum_of_branch_lengts
return float(cnt) / float(sumbr)
def get_speciation_rate(self):
#pruning the input tree such that each species only appear once
species = set()
keepseqs = []
for name in self.taxonomy.keys():
ranks = self.taxonomy[name]
sp = ranks[-1]
if sp == "-":
keepseqs.append(name)
else:
if not sp in species:
keepseqs.append(name)
species.add(sp)
root = Tree(self.tree)
root.prune(keepseqs, preserve_branch_length=True)
sumbr = 0.0
cnt = 0.0
for node in root.traverse(strategy = "preorder"):
sumbr = sumbr + node.dist
cnt = cnt + 1.0
return float(cnt) / float(sumbr)
