def test_construct_from_another_with_simple_annotations(self):
t1 = Taxon("a")
t1.annotations.add_new("a", 0)
t1.annotations.add_new("b", 1)
t1.annotations.add_new("c", 3)
for t2 in (Taxon(t1), copy.deepcopy(t1), t1.clone(2)):
self.assertIsNot(t1, t2)
self.assertNotEqual(t1, t2)
self.assertEqual(t1.label, t2.label)
self.assertTrue(hasattr(t1, "annotations"))
self.assertTrue(hasattr(t2, "annotations"))
self.assertEqual(len(t1.annotations), len(t2.annotations))
self.compare_distinct_annotables(t1, t2)
def simulateTreeTopology(n):
# simulate a binary tree of n leaves
leaves = [Node()]
nodeOrder = []
myTree = Tree(seed_node = leaves[0])
for i in range(n-1):
r = randint(0,i)
a = Node()
b = Node()
p = leaves[r]
p.add_child(a)
p.add_child(b)
leaves[r] = a
leaves.append(b)
nodeOrder.append(p)
IDs = list(range(1,n+1))
i = 0
shuffle(IDs)
for leaf in leaves:
leaf.taxon = Taxon(label=str(IDs[i]))
leaf.time = 0
i += 1
return myTree,nodeOrder
def test_basic_adding(self):
tns = TaxonNamespace()
self.assertEqual(len(tns), 0)
for idx, label in enumerate(self.str_labels):
tns.add_taxon(Taxon(label=label))
self.assertEqual(len(tns), idx+1)
self.validate_taxon_concepts(tns, self.str_labels)
def test_basic_adding_to_immutable(self):
tns = TaxonNamespace()
self.assertEqual(len(tns), 0)
tns.is_mutable = False
for idx, label in enumerate(self.str_labels):
with self.assertRaises(TypeError):
tns.add_taxon(Taxon(label=label))
self.assertEqual(len(tns), 0)
def leave_only(self, to_keep_dict):
'''
Removes terminal nodes associated with Taxon objects whose labels are
not a key in to_keep_dict. For each item in to_keep_dict that matches,
increment its value by 1 (allows tracking how many we have)
We have to be careful with non-branching twigs (a series of unifurcations)
because we want the tip to be left, and the rest pruned (so that a
single species is left on the tree)
'''
to_keep = self.taxon_namespace.get_taxa(labels=to_keep_dict.keys())
#flag up the routes to keep
for nd in self.postorder_node_iter():
if hasattr(nd, 'keep') or (nd.taxon and nd.taxon in to_keep):
if (nd.parent_node):
nd.parent_node.keep = True
to_prune = set([t for t in self.taxon_namespace if t not in to_keep])
for lf in self.leaf_node_iter(lambda n: n.taxon in to_prune):
lf.spp = 1
for nd in self.postorder_node_iter():
if (hasattr(nd, 'spp')):
if (nd.parent_node and not hasattr(nd.parent_node, 'keep')):
if (hasattr(nd.parent_node, 'spp')):
nd.parent_node.spp += nd.spp
else:
nd.parent_node.spp = nd.spp
else:
if (nd.spp > 1):
if (nd.taxon):
nd.taxon.label += '#%d' % (nd.spp)
else:
if (nd.label):
nd.taxon = Taxon(label=nd.label + '#%d' % (nd.spp))
else:
warn(
"Couldn't find a label for a node with multiple descendants. Using label 'unknown'."
)
nd.taxon = Taxon(label='unknown#%d' % (nd.spp))
nd.set_child_nodes([])
self.prune_leaves_without_taxa(update_bipartitions=False,
suppress_unifurcations=False)
check_list_against_taxa(self, to_keep_dict)
def test_discard_taxon_label(self):
taxa = [Taxon(s) for s in self.str_labels]
tns = TaxonNamespace(taxa)
expected = taxa[:]
for idx, label in enumerate(set(self.str_labels)):
tns.discard_taxon_label(label)
for t in taxa:
if t.label == label and t in expected:
expected.remove(t)
self.assertEqual(len(tns), len(expected))
for t1, t2 in zip(tns, expected):
self.assertIs(t1, t2)
def test_remove_taxon(self):
taxa = [Taxon(s) for s in self.str_labels]
tns = TaxonNamespace(taxa)
expected = taxa[:]
for idx, taxon in enumerate(taxa):
tns.remove_taxon(taxon)
expected.remove(taxon)
self.assertEqual(len(tns), len(expected))
for idx2, taxon2 in enumerate(expected):
if taxon2 in expected:
self.assertIn(taxon2, tns)
elif taxon2 not in expected:
self.assertNotIn(taxon2, tns)
def test_discard_taxon_label_case_insensitive(self):
ucase_labels = [s.upper() for s in self.str_labels]
assert ucase_labels
assert ucase_labels != self.str_labels
taxa = [Taxon(s) for s in self.str_labels]
tns = TaxonNamespace(taxa)
expected = taxa[:]
# default: case-insensitive
for idx, label in enumerate(set(ucase_labels)):
tns.discard_taxon_label(label)
for t in taxa:
if t.label.upper() == label.upper() and t in expected:
expected.remove(t)
self.assertEqual(len(tns), len(expected))
for t1, t2 in zip(tns, expected):
self.assertIs(t1, t2)
def test_discard_taxon_label_case_sensitive(self):
ucase_labels = [s.upper() for s in self.str_labels]
assert ucase_labels
assert ucase_labels != self.str_labels
taxa = [Taxon(s) for s in self.str_labels]
tns = TaxonNamespace(taxa)
expected = taxa[:]
# test: case sensitive
tns.is_case_sensitive = True
for idx, label in enumerate(set(ucase_labels)):
if label != label.lower():
x1 = len(tns)
try:
tns.discard_taxon_label(label)
except LookupError:
self.fail()
else:
self.assertEqual(len(tns), x1)
def test_remove_taxon_label_case_insensitive(self):
ucase_labels = [s.upper() for s in self.str_labels]
assert ucase_labels
assert ucase_labels != self.str_labels
taxa = [Taxon(s) for s in self.str_labels]
tns = TaxonNamespace(taxa)
expected = taxa[:]
for idx, label in enumerate(set(ucase_labels)):
if label != label.lower():
with self.assertRaises(LookupError):
tns.is_case_sensitive = True
tns.remove_taxon_label(label)
tns.is_case_sensitive = False
tns.remove_taxon_label(label)
for t in taxa:
if t.label.upper() == label.upper() and t in expected:
expected.remove(t)
self.assertEqual(len(tns), len(expected))
for t1, t2 in zip(tns, expected):
self.assertIs(t1, t2)
def test_construct_from_another_with_complex_annotations(self):
t1 = Taxon("a")
t1.annotations.add_new("a", 0)
b = t1.annotations.add_new("b", (t1, "label"), is_attribute=True)
b.annotations.add_new("c", 3)
for t2 in (Taxon(t1), copy.deepcopy(t1), t1.clone(2)):
self.assertIsNot(t1, t2)
self.assertNotEqual(t1, t2)
self.assertEqual(t1.label, t2.label)
self.assertTrue(hasattr(t1, "annotations"))
self.assertTrue(hasattr(t2, "annotations"))
self.assertEqual(len(t1.annotations), len(t2.annotations))
self.compare_distinct_annotables(t1, t2)
t1.label = "x"
self.assertEqual(t1.annotations[1].value, "x")
self.assertEqual(t2.annotations[1].value, "a")
t2.label = "z"
self.assertEqual(t1.annotations[1].value, "x")
self.assertEqual(t2.annotations[1].value, "z")
t1.label = "a"
def test_no_contains_taxa(self):
tns = TaxonNamespace(self.taxa)
taxa2 = [Taxon(label=t.label) for t in self.taxa]
for taxon in taxa2:
self.assertNotIn(taxon, tns)
def test_construct_from_another(self):
t1 = Taxon("a")
for t2 in (Taxon(t1), copy.deepcopy(t1), t1.clone(2)):
self.assertIsNot(t1, t2)
self.assertNotEqual(t1, t2)
self.assertEqual(t1.label, t2.label)
def setUp(self):
self.str_labels = ["a", "a", "b", "c", "d", "e", "_", "_", "_", "z", "z", "z"]
self.taxa = [ Taxon(label) for label in self.str_labels ]
self.tns1 = TaxonNamespace(self.taxa, label="T1")
def main(args):
if len(args) < 2:
print(
'''USAGE: %s [tree_file] [outgroups] [-mrca -mrca-dummy (optional)] [output name (optional)] [-igerr (optional)]
-- tree_file: a path to the newick tree file
-- outgroups: a list of outgroups, separated by comma.
The script goes through the list of outgroups. If the outgroup is found in the tree,
the tree is rooted at that outgroup. Otherwise, the next outgroup in the list is used.
Each element in the comma-delimited list is itself a + delimited list of taxa.
By default the script makes sure that this list of taxa are monophyletic
in the tree and roots the tree at the node leading to the clade represented
by outgroups given in the + delimited list.
Alternatively, you can specify -m which will result in mid-point rooting.
Example: HUMAN,ANOCA,STRCA+TINMA first tries to root at HUMAN, if not present,
tries to use ANOCA, if not present, tries to root at parent of STRCA and TINMA
which need to be monophyletic. If not monophyletic, roots at STRCA.
-- (optional) -mrca: using this option the mono-phyletic requirement is relaxed
and always the mrca of the + delimited list of outgroups is used.
-- (optional) -mrca-dummy: is like -mrca, but also adds a dummy taxon as outgroup to the root.
''' % args[0])
sys.exit(1)
treeName = args[1]
outgroups = [x.replace("_", " ") for x in args[2].split(",")]
use_mrca = True if len(args) > 3 and (
args[3] == "-mrca" or args[3] == "-mrca-dummy") else False
add_dummy = True if len(args) > 3 and (args[3] == "-mrca-dummy") else False
resultsFile = args[4] if len(args) > 4 else (
"%s.rooted" %
treeName[:-9] if treeName.endswith("unrooted") else "%s.rooted" %
treeName)
ignore = True if len(args) > 5 and args[5] == "-igerr" else False
print("Reading input trees %s ..." % treeName, end=' ')
trees = dendropy.TreeList.get_from_path(treeName, schema='newick')
print("%d tree(s) found" % len(trees))
i = 0
outtrees = TreeList()
for tree in trees:
tree.encode_bipartitions()
i += 1
print(".")
oldroot = tree.seed_node
#print "Tree %d:" %i
sl = {}
for n in tree.internal_nodes():
sl[n.edge.bipartition.normalize(
bitmask=n.edge.bipartition._split_bitmask)] = n.label
if outgroups[0] == "-m":
print("Midpoint rooting ... ")
tree.reroot_at_midpoint(update_bipartitions=True)
else:
mrca = None
for outgroup in outgroups:
outs = outgroup.split("+")
outns = []
for out in outs:
n = tree.find_node_with_taxon_label(out)
if n is None:
print("outgroup not found %s," % out, end=' ')
continue
outns.append(n.taxon)
if len(outns) != 0:
# Find an ingroup and root the tree there
for n in tree.leaf_iter():
if n.taxon not in outns:
ingroup = n
break
#print "rerooting at ingroup %s" %ingroup.taxon.label
'''reroot at an ingroup, so that outgroups form monophyletic groups, if possible'''
if ingroup.edge.length is not None:
tree.reroot_at_edge(ingroup.edge,
update_bipartitions=True,
length1=ingroup.edge.length / 2,
length2=ingroup.edge.length / 2)
else:
tree.reroot_at_edge(ingroup.edge,
update_bipartitions=True)
mrca = tree.mrca(taxa=outns)
break
if mrca is None:
if ignore:
print("Outgroups not found: %s" % outgroups,
file=sys.stderr)
continue
else:
raise KeyError("Outgroups not found %d: %s" %
(i, outgroups))
#print mrca.leaf_nodes()
#if not mono-phyletic, then use the first
if not use_mrca and len(mrca.leaf_nodes()) != len(outns):
print("selected set is not monophyletic. Using %s instead. " %
outns[0],
file=sys.stderr)
mrca = tree.find_node_with_taxon_label(outns[0].label)
if mrca.parent_node is None:
print("Already rooted at the root.", file=sys.stderr)
#print "rerooting on %s" % [s.label for s in outns]
#tree.reroot_at_midpoint()
elif mrca.edge.length is not None:
#print "rerooting at %s" %mrca.as_newick_string()
if ingroup.edge.length is not None:
tree.reroot_at_edge(mrca.edge,
update_bipartitions=True,
length1=mrca.edge.length / 2,
length2=mrca.edge.length / 2)
else:
tree.reroot_at_edge(mrca.edge, update_bipartitions=True)
else:
tree.reroot_at_edge(mrca.edge, update_bipartitions=True)
if add_dummy:
dummy = tree.seed_node.new_child(taxon=Taxon(label="outgroup"),
edge_length=1)
tree.reroot_at_edge(dummy.edge, update_bipartitions=True)
'''This is to fix internal node labels when treated as support values '''
for n in tree.internal_nodes():
n.label = sl.get(
n.edge.bipartition.normalize(
n.edge.bipartition._split_bitmask), '')
'''
print (oldroot.parent_node)
print (tree.seed_node)
print (oldroot)
print("relabel")
while oldroot.parent_node != tree.seed_node and oldroot.parent_node != None:
oldroot.label = oldroot.parent_node.label
oldroot = oldroot.parent_node
print ("--")
if len(oldroot.sister_nodes()) > 0:
oldroot.label = oldroot.sister_nodes()[0].label
#tree.reroot_at_midpoint(update_bipartitions=False)'''
print("writing results to %s" % resultsFile, file=sys.stderr)
trees.write(file=open(resultsFile, 'w'),
schema='newick',
suppress_internal_taxon_labels=False,
suppress_rooting=True)
def get_super_tree(self, superTree_method, **args):
def parse_trees(**args):
n_tree, n_branch = float(len(self.data['trees'])), {}
for mt_id, mt in enumerate(self.data['trees']):
w = (float(len(mt.tre.leaf_nodes())) /
len(self.data['taxa']))**2
for node in mt.tre.preorder_node_iter():
if node.barcode not in n_branch:
n_branch[node.barcode] = [[w, mt_id, node]]
else:
n_branch[node.barcode].append([w, mt_id, node])
return n_tree, n_branch
def consensus(self, **args):
n_tree, n_branch = parse_trees(**args)
n_branch = sorted([[len(v) / n_tree, k, v]
for k, v in n_branch.iteritems()],
reverse=True)
consensus_tree = []
for posterior, branch, nodes in n_branch:
for cbr, _, _ in consensus_tree:
b1, b2 = sorted([branch, cbr])
if not (((b1 & b2) == b1) or ((b1 & (~b2)) == b1)):
branch = 0
break
if branch:
consensus_tree.append([branch, posterior, nodes])
return sorted(consensus_tree, reverse=True)
def MCC(self, **args):
n_tree, n_branch = parse_trees(**args)
for mt_id, mt in enumerate(self.data['trees']):
if len(mt.tre.leaf_nodes()) == len(self.data['taxa']):
mt.score = np.sum([
len(n_branch[node.barcode])
for node in mt.tre.preorder_node_iter()
])
tre = max(self.data['trees'], key=lambda x: x.score).tre
return [[
n.barcode,
len(n_branch[n.barcode]) / n_tree, n_branch[n.barcode]
] for n in tre.preorder_node_iter()]
def load_subtree(self, treeLabel, **args):
n_tree, n_branch = parse_trees(**args)
for mt_id, mt in enumerate(self.data['trees']):
if mt.tre.label == treeLabel:
tre = mt.tre
break
return [[
n.barcode,
len(n_branch[n.barcode]) / n_tree, n_branch[n.barcode], n.age,
n.edge_length
] for n in tre.preorder_node_iter()]
#def ASTRID(self, **args) :
#from dendropy import PhylogeneticDistanceMatrix
def load_tree(self, consFile=None, **args):
n_tree, n_branch = parse_trees(**args)
with open(consFile) as fin:
schema = 'nexus' if fin.readline().upper().startswith(
'#NEXUS') else 'newick'
for tre in Tree.yield_from_files([consFile], schema=schema):
break
internal_id = n_taxa = len(self.data['taxa'])
digit_code = np.power(2, np.arange(n_taxa, dtype='object'))
for node in tre.postorder_node_iter():
if node.is_leaf():
node.id = self.data['taxa'][node.taxon.label]
node.barcode = digit_code[node.id]
else:
node.id, internal_id = internal_id, internal_id + 1
node.barcode = sum([c.barcode for c in node.child_nodes()])
tre.seed_node.age = tre.seed_node.distance_from_tip()
for node in tre.preorder_node_iter():
if node.parent_node:
node.age = node.parent_node.age - node.edge_length
return [[
n.barcode,
len(n_branch.get(n.barcode, [])) / n_tree,
n_branch.get(n.barcode, []), n.age, n.edge_length
] for n in tre.preorder_node_iter()]
if superTree_method in ('MCC', 'ASTRID', 'consensus'):
branches = locals()[superTree_method](self, **args)
elif os.path.isfile(superTree_method):
branches = load_tree(self, consFile=superTree_method, **args)
else:
branches = load_subtree(self, treeLabel=superTree_method, **args)
supertree = Tree()
sn = supertree.seed_node
sn.barcode, sn.posterior = branches[0][0], branches[0][1]
sn.age = branches[0][3] if len(branches[0]) > 3 else np.sum(
[n[2].age * n[0]
for n in branches[0][2]]) / np.sum([n[0] for n in branches[0][2]])
sn.contain = [[b[0], b[1], b[2].id] for b in branches[0][2]]
for br in branches[1:]:
cbr, posterior, nodes = br[:3]
while (sn.barcode & cbr) != cbr:
sn = sn.parent_node
new_node = Node() if len(nodes) == 0 or (
not nodes[0][2].taxon) else Node(taxon=Taxon(
label=nodes[0][2].taxon.label))
sn.add_child(new_node)
sn = new_node
sn.barcode, sn.posterior = cbr, posterior
sn.contain = [[b[0], b[1], b[2].id] for b in nodes]
if len(br) <= 3:
sn.edge_length = 0.0 if len(nodes) == 0 else np.sum(
[n[2].edge_length * n[0]
for n in nodes]) / np.sum([n[0] for n in nodes])
sn.age = sn.parent_node.age if len(nodes) == 0 else np.sum(
[n[2].age * n[0]
for n in nodes]) / np.sum([n[0] for n in nodes])
else:
sn.age, sn.edge_length = br[3:]
internal_id = len(self.data['taxa'])
for node in supertree.postorder_node_iter():
if node.is_leaf():
node.id = self.data['taxa'][node.taxon.label]
else:
node.id = internal_id
internal_id += 1
return MetaTree(supertree)
def rdf2dendropyTree(file_obj=None, data=None):
'''
Parses the content (a `file_obj` file object or `data` as a) into a dendropyTree.
Uses the 'has_Parent' term in http://www.evolutionaryontology.org/cdao/1.0/cdao.owl#
to construct and return a rooted dendropy.Tree object
Relies on rdflib and dendropy.
Raises ValueError if the graph does not imply exactly 1 root node
'''
from dendropy import Node, Tree, Edge, TaxonSet, Taxon
graph = rdflib.Graph()
if file_obj:
graph.parse(file=file_obj)
else:
graph.parse(data=data, format='xml')
nd_dict = {}
has_parent_predicate = OBO_PREFIX + HAS_PARENT_PREDICATE
if _DEBUGGING:
out = open('parse_rdf.txt', 'w')
taxon_set = TaxonSet()
OBO = rdflib.Namespace(u"http://purl.obolibrary.org/obo/")
parentless = set()
for s, p, o in graph.triples((None, OBO[HAS_PARENT_PREDICATE], None)):
parent = nd_dict.get(id(o))
if parent is None:
#print 'Parent o.value = ', o.value(rdflib.RDF.nodeID)
raw_o = o
o = rdflib.resource.Resource(graph, o)
o_tu = o.value(OBO[REPRESENTS_TU_PREDICATE])
if o_tu:
o_label = o_tu.value(rdflib.RDFS.label)
t = Taxon(label=o_label)
taxon_set.append(t)
parent = Node(taxon=t)
else:
parent = Node()
nd_dict[id(raw_o)] = parent
parentless.add(parent)
child = nd_dict.get(id(s))
if child is None:
raw_s = s
s = rdflib.resource.Resource(graph, s)
s_tu = s.value(OBO[REPRESENTS_TU_PREDICATE])
if s_tu:
s_label = s_tu.value(rdflib.RDFS.label)
t = Taxon(label=s_label)
taxon_set.append(t)
child = Node(taxon=t)
else:
child = Node()
nd_dict[id(raw_s)] = child
else:
if child in parentless:
parentless.remove(child)
parent.add_child(child)
if _DEBUGGING:
out.write('%s %s %s\n' % (str(s), p, o))
out.write('%s\n' % (str(parentless)))
if _DEBUGGING:
out.close()
if len(parentless) != 1:
message = "Expecting to find exactly Node (an object of a has_Parent triple) in the graph without a parent. Found %d" % len(
parentless)
CUTOFF_FOR_LISTING_PARENTLESS_NODES = 1 + len(
parentless
) # we might want to put in a magic number here to suppress really long output
if len(parentless) > 0 and len(
parentless) < CUTOFF_FOR_LISTING_PARENTLESS_NODES:
message += ":\n "
for i in parentless:
if i.label:
message += "\n " + i.label
else:
message += "\n <unlabeled>" + str(id(i))
raise ValueError(message)
else:
return None
tree = Tree(taxon_set=taxon_set)
tree.seed_node = list(parentless)[0]
tree.is_rooted = True
return tree
def test_simple_copy(self):
t1 = Taxon("a")
with self.assertRaises(TypeError):
copy.copy(t1)
with self.assertRaises(TypeError):
t1.clone(0)
def test_taxon_namespace_scoped_copy(self):
t1 = Taxon("a")
for t2 in (t1.clone(1), t1.taxon_namespace_scoped_copy()):
self.assertIs(t2, t1)
def setUp(self):
self.str_labels = ["a", "a", "b", "c", "d", "e", "_", "_", "_", "z", "z", "z"]
self.taxa = [
Taxon("t1"), Taxon("t2"), Taxon("t3"),
]
self.taxa_labels = [t.label for t in self.taxa]
treefile = argv[1]
infofile = argv[2]
outfile = argv[3]
with open(infofile, 'r') as f:
mapping = {}
for line in f:
taxa = line.split()
mapping[taxa[0]] = taxa[1:]
myTree = Tree.get_from_path(treefile, "newick")
leaves = list(myTree.leaf_node_iter())
for node in leaves:
if node.taxon.label in mapping:
new_node = Node(edge_length=node.edge_length)
pNode = node.parent_node
pNode.remove_child(node)
pNode.add_child(new_node)
new_node.add_child(node)
pNode = new_node
for taxon_name in mapping[node.taxon.label]:
new_taxon = Taxon(label=taxon_name)
myTree.taxon_namespace.add_taxon(new_taxon)
new_node = Node(edge_length=0, taxon=new_taxon)
pNode.add_child(new_node)
myTree.write_to_path(outfile, "newick")
def setUp(self):
self.t1 = Taxon("a")
self.t2 = Taxon("a")
line = lines.readline()
results = line.strip().split(',')
tree = Tree()
root = Node()
root.__dict__['label'] = results[0].replace("\"", "")
nodes_dict[results[0].replace("\"", "")] = root
prune = ['1']
#Add root node to tree
tree.__dict__['_seed_node'].add_child(root)
for line in lines:
results = line.strip().split(',')
node = Node()
node.__dict__['label'] = results[0].replace("\"", "")
node.taxon = Taxon(results[0].replace("\"", ""))
nodes_dict[results[0].replace("\"", "")] = node
nodes_dict[results[1].replace("\"", "")].add_child(node)
if results[0].replace("\"", "") not in species:
prune.append(results[0].replace("\"", ""))
for taxa in prune:
nodes_dict[taxa].label = ''
# tree.delete_outdegree_one_nodes()
tree.suppress_unifurcations()
output = open(taxonomyTree, 'w')
output.write(str(tree) + ";")
output.close()
lines.close()
required=False,
help="Output Newick tree file")
args = parser.parse_args()
tree = Tree.get_from_path(args.i, schema="newick", rooting="force-unrooted")
namespace = tree.taxon_namespace
labels = namespace.labels()
regex = re.compile("(.+) .+ .+")
species = [
match.group(1) for label in labels for match in [regex.match(label)]
if match
]
species_set = set(species)
species = list(species_set)
newNamespace = dendropy.datamodel.taxonmodel.TaxonNamespace()
for specie in species:
regex = re.compile(specie + " .+ .+")
leaves = [
match.group(0) for label in labels for match in [regex.match(label)]
if match
]
mrca_node = tree.mrca(taxon_labels=leaves)
del mrca_node._child_nodes[:]
taxon = Taxon(specie)
mrca_node.taxon = taxon
newNamespace.add_taxon(taxon)
tree.taxon_namespace = newNamespace
tree.write(path=args.o, schema="newick", suppress_rooting=True)