def setUp(self):
tree_str = "[&R] ((((H**o:0.21,Pongo:0.21)N1:0.28,Macaca:0.49)N2:0.13,Ateles:0.62)N3:0.38,Galago:1.00)N4:0.0;"
data_str = """
#NEXUS
BEGIN DATA;
DIMENSIONS NTAX=5 NCHAR=2;
FORMAT DATATYPE = CONTINUOUS GAP = - MISSING = ?;
MATRIX
H**o 4.09434 4.74493
Pongo 3.61092 3.33220
Macaca 2.37024 3.36730
Ateles 2.02815 2.89037
Galago -1.46968 2.30259
;
END;
"""
taxa = dendropy.TaxonNamespace()
self.tree = dendropy.Tree.get_from_string(tree_str,
'newick',
taxon_namespace=taxa)
self.char_matrix = dendropy.ContinuousCharacterMatrix.get_from_string(
data_str, 'nexus', taxon_namespace=taxa)
self.pic = continuous.PhylogeneticIndependentConstrasts(
tree=self.tree, char_matrix=self.char_matrix)
self.expected_vals = []
self.expected_vals.append({
# state, corrected edge length, contrast, contrast_var
"N1": (3.852630000, 0.385000000, 0.483420000, 0.420000000),
"N2": (3.200378400, 0.345600000, 1.482390000, 0.875000000),
"N3": (2.780823579, 0.601905551, 1.172228400, 0.965600000),
"N4": (1.183724613, 0.375743470, 4.250503579, 1.601905551),
})
self.expected_vals.append({
# state, corrected edge length, contrast, contrast_var
"N1": (4.038565000, 0.385000000, 1.412730000, 0.420000000),
"N2": (3.743208400, 0.345600000, 0.671265000, 0.875000000),
"N3": (3.437967150, 0.601905551, 0.852838400, 0.965600000),
"N4": (3.011356599, 0.375743470, 1.135377150, 1.601905551),
})
def pic_compute(tree_sim,Z_singleset,taxa1,order_sim):
simchar_dict = {}
keys = ["B.mysticetus", "B.acutorostrata", "C.marginata", "B.borealis",
"B.physalus", "E.robustus", "B.musculus", "B.omurai",
"E.australis", "M.novaeangliae", "B.bonaerensis", "B.brydei",
"B.edeni", "E.glacialis", "E.japonica"]
for i in range(15):
simchar_dict[keys[i]] = [Z_singleset[i]]
simchars = dendropy.ContinuousCharacterMatrix.from_dict(simchar_dict, taxon_namespace=taxa1)
simpic = continuous.PhylogeneticIndependentConstrasts(tree=tree_sim, char_matrix=simchars)
sim_ctree = simpic.contrasts_tree(character_index=0,
annotate_pic_statistics=True,
state_values_as_node_labels=False,
corrected_edge_lengths=False)
sim_pic = []
sim_label = []
for nd in sim_ctree.postorder_internal_node_iter():
sim_pic.append(nd.pic_contrast_standardized)
sim_label.append(int(nd.label))
sim_pic_ordered = np.array(sim_pic)[np.argsort(sim_label)]
return sim_pic_ordered,order_sim
import dendropy
from dendropy.model import continuous
taxa = dendropy.TaxonNamespace()
tree = dendropy.Tree.get(path="primates.cc.tre",
schema="newick",
taxon_namespace=taxa)
chars = dendropy.ContinuousCharacterMatrix.get(path="primates.cc.nex",
schema="nexus",
taxon_namespace=taxa)
pic = continuous.PhylogeneticIndependentConstrasts(tree=tree,
char_matrix=chars)
ctree1 = pic.contrasts_tree(character_index=0,
annotate_pic_statistics=True,
state_values_as_node_labels=False,
corrected_edge_lengths=False)
for nd in ctree1.postorder_internal_node_iter():
row = [
nd.pic_state_value, nd.pic_state_variance, nd.pic_contrast_raw,
nd.pic_edge_length_error
]
row_str = [(("%10.8f") % i) for i in row]
row_str = " ".join(row_str)
label = nd.label.ljust(6)
print "%s %s" % (label, row_str)
def testResolve(self):
pic = continuous.PhylogeneticIndependentConstrasts(
tree=self.tree,
char_matrix=self.char_matrix,
polytomy_strategy="Resolve")
ctree = pic.contrasts_tree(1)
def testError(self):
pic = continuous.PhylogeneticIndependentConstrasts(
tree=self.tree,
char_matrix=self.char_matrix,
polytomy_strategy="error")
self.assertRaises(ValueError, pic.contrasts_tree, 1)
def testErrorOnDefault(self):
pic = continuous.PhylogeneticIndependentConstrasts(
tree=self.tree, char_matrix=self.char_matrix)
self.assertRaises(ValueError, pic.contrasts_tree, 1)
"Eubalaena_japonica"
]
obsZ_ordered_sim = length[[
np.where(sim_species_label[i] == extantlabels_array)[0][0]
for i in range(15)
]]
obsZ = obsZ_ordered_sim
meantrait = np.mean(obsZ)
# PIC calculation
taxa1 = dendropy.TaxonNamespace()
dataset_combined = dendropy.DataSet.get(path=files + "bw_char.nex",
schema="nexus")
tree_emp = dataset_combined.tree_lists[0][0]
chars_emp = dataset_combined.char_matrices[0]
pic_emp = continuous.PhylogeneticIndependentConstrasts(tree=tree_emp,
char_matrix=chars_emp)
ctree_emp = pic_emp.contrasts_tree(character_index=0,
annotate_pic_statistics=True,
state_values_as_node_labels=False,
corrected_edge_lengths=False)
emp_pic = []
label = []
for nd in ctree_emp.postorder_internal_node_iter():
emp_pic.append(nd.pic_contrast_standardized)
label.append(int(nd.label))
emp_pic_orded_node = abs(np.array(emp_pic)[np.argsort(label)])
tree_sim = dendropy.Tree.get(path=files + "bw.nex",
schema="nexus",
taxon_namespace=taxa1)
