def test_get_score(self):
aln = AlignIO.read('TreeConstruction/msa.phy', 'phylip')
tree = Phylo.read('./TreeConstruction/upgma.tre', 'newick')
scorer = ParsimonyScorer()
score = scorer.get_score(tree, aln)
self.assertEqual(score, 2 + 1 + 2 + 2 + 1 + 1 + 1 + 3)
alphabet = ['A', 'T', 'C', 'G']
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3.5 + 2.5 + 3.5 + 3.5 + 2.5 + 1 + 2.5 + 4.5)
alphabet = [
'A', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'K', 'L', 'M', 'N', 'P',
'Q', 'R', '1', '2', 'T', 'V', 'W', 'Y', '*', '-'
]
step_matrix = [
[0], [2, 0], [1, 2,
0],
[1, 2, 1, 0],
[2, 1, 2, 2, 0],
[1, 1, 1, 1, 2,
0], [2, 2, 1, 2, 2, 2,
0],
[2, 2, 2, 2, 1, 2,
2, 0], [2, 2, 2, 1, 2, 2, 2, 1,
0], [2, 2, 2, 2, 1, 2, 1, 1, 2,
0],
[2, 2, 2, 2, 2, 2, 2, 1, 1, 1,
0], [2, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2,
0],
[1, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2,
2, 0], [2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 2, 1,
0], [2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1,
0], [1, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 2, 1,
2, 2, 1, 2, 0],
[1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 0],
[1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 3, 2, 2, 1, 1, 2, 2, 2, 0],
[2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 2, 0],
[2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 0],
[
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 0
]
]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3 + 1 + 3 + 3 + 2 + 1 + 2 + 5)
def _build_protein_matrix(self, subsmat):
"""Convert matrix from SubsMat format to _Matrix object (PRIVATE)."""
protein_matrix = _Matrix(self.protein_alphabet)
for k, v in subsmat.items():
aa1, aa2 = k
protein_matrix[aa1, aa2] = v
return protein_matrix
def main(argv):
# Test table data and corresponding labels
M_labels = [
'Wuttagoonaspis', 'Romundina', 'Brindabellaspis', 'Eurycaraspis',
'Entelognathus'
]
print(M_labels) #A through G
M = np.loadtxt(open(argv[1], "rb"), delimiter=",")
l = np.tril(M)
temp = np.ones((5, 5))
u = np.triu(temp)
l += u
np.fill_diagonal(l, 0)
M = l.tolist()
for j in range(0, 5):
for i in range(0, 5):
M[i] = list(filter(lambda a: a != 1, M[i]))
m = _Matrix(M_labels, M)
print(type(m))
constructor = DistanceTreeConstructor()
tree = constructor.upgma(m)
Phylo.draw(tree)
def test_get_score(self):
aln = AlignIO.read('TreeConstruction/msa.phy', 'phylip')
tree = Phylo.read('./TreeConstruction/upgma.tre', 'newick')
scorer = ParsimonyScorer()
score = scorer.get_score(tree, aln)
self.assertEqual(score, 2 + 1 + 2 + 2 + 1 + 1 + 1 + 3)
alphabet = ['A', 'T', 'C', 'G']
step_matrix = [[0],
[2.5, 0],
[2.5, 1, 0],
[1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3.5 + 2.5 + 3.5 + 3.5 + 2.5 + 1 + 2.5 + 4.5)
alphabet = ['A', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'K', 'L', 'M', 'N',
'P', 'Q', 'R', '1', '2', 'T', 'V', 'W', 'Y', '*', '-']
step_matrix = [[0],
[2, 0],
[1, 2, 0],
[1, 2, 1, 0],
[2, 1, 2, 2, 0],
[1, 1, 1, 1, 2, 0],
[2, 2, 1, 2, 2, 2, 0],
[2, 2, 2, 2, 1, 2, 2, 0],
[2, 2, 2, 1, 2, 2, 2, 1, 0],
[2, 2, 2, 2, 1, 2, 1, 1, 2, 0],
[2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 0],
[2, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 0],
[1, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 0],
[2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 2, 1, 0],
[2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 0],
[1, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 0],
[1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 0],
[1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 3, 2, 2, 1, 1, 2, 2, 2, 0],
[2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 2, 0],
[2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 0],
[3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3 + 1 + 3 + 3 + 2 + 1 + 2 + 5)
def test_get_neighbors(self):
tree = Phylo.read('./TreeConstruction/upgma.tre', 'newick')
alphabet = ['A', 'T', 'C', 'G']
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
searcher = NNITreeSearcher(scorer)
trees = searcher._get_neighbors(tree)
self.assertEqual(len(trees), 2 * (5 - 3))
Phylo.write(trees, './TreeConstruction/neighbor_trees.tre', 'newick')
def test_get_neighbors(self):
tree = Phylo.read("./TreeConstruction/upgma.tre", "newick")
alphabet = ["A", "T", "C", "G"]
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
searcher = NNITreeSearcher(scorer)
trees = searcher._get_neighbors(tree)
self.assertEqual(len(trees), 2 * (5 - 3))
Phylo.write(trees, os.path.join(temp_dir, "neighbor_trees.tre"), "newick")
def test_get_neighbors(self):
tree = Phylo.read('./TreeConstruction/upgma.tre', 'newick')
alphabet = ['A', 'T', 'C', 'G']
step_matrix = [[0],
[2.5, 0],
[2.5, 1, 0],
[ 1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
searcher = NNITreeSearcher(scorer)
trees = searcher._get_neighbors(tree)
self.assertEqual(len(trees), 2 * (5 - 3))
Phylo.write(trees, './TreeConstruction/neighbor_trees.tre', 'newick')
def test_build_tree(self):
aln = AlignIO.read('TreeConstruction/msa.phy', 'phylip')
tree1 = Phylo.read('./TreeConstruction/upgma.tre', 'newick')
tree2 = Phylo.read('./TreeConstruction/nj.tre', 'newick')
alphabet = ['A', 'T', 'C', 'G']
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
searcher = NNITreeSearcher(scorer)
constructor = ParsimonyTreeConstructor(searcher, tree1)
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, './TreeConstruction/pars1.tre', 'newick')
constructor.starting_tree = tree2
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, './TreeConstruction/pars2.tre', 'newick')
constructor.starting_tree = None
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, './TreeConstruction/pars3.tre', 'newick')
def test_build_tree(self):
aln = AlignIO.read("TreeConstruction/msa.phy", "phylip")
tree1 = Phylo.read("./TreeConstruction/upgma.tre", "newick")
tree2 = Phylo.read("./TreeConstruction/nj.tre", "newick")
alphabet = ["A", "T", "C", "G"]
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
searcher = NNITreeSearcher(scorer)
constructor = ParsimonyTreeConstructor(searcher, tree1)
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, os.path.join(temp_dir, "pars1.tre"), "newick")
constructor.starting_tree = tree2
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, os.path.join(temp_dir, "pars2.tre"), "newick")
constructor.starting_tree = None
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, os.path.join(temp_dir, "pars3.tre"), "newick")
def __init__(self, model='identity', skip_letters=None):
"""Initialize with a distance model."""
# Shim for backward compatibility (#491)
if skip_letters:
self.skip_letters = skip_letters
elif model == 'identity':
self.skip_letters = ()
else:
self.skip_letters = ('-', '*')
if model == 'identity':
self.scoring_matrix = None
elif model in self.dna_models:
self.scoring_matrix = _Matrix(self.dna_alphabet,
self.dna_matrices[model])
elif model in self.protein_models:
self.scoring_matrix = self._build_protein_matrix(
self.protein_matrices[model])
else:
raise ValueError("Model not supported. Available models: " +
", ".join(self.models))
def test_build_tree(self):
aln = AlignIO.read(open('TreeConstruction/msa.phy'), 'phylip')
tree1 = Phylo.read('./TreeConstruction/upgma.tre', 'newick')
tree2 = Phylo.read('./TreeConstruction/nj.tre', 'newick')
alphabet = ['A', 'T', 'C', 'G']
step_matrix = [[0],
[2.5, 0],
[2.5, 1, 0],
[ 1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
searcher = NNITreeSearcher(scorer)
constructor = ParsimonyTreeConstructor(searcher, tree1)
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, './TreeConstruction/pars1.tre', 'newick')
constructor.starting_tree = tree2
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, './TreeConstruction/pars2.tre', 'newick')
constructor.starting_tree = None
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, './TreeConstruction/pars3.tre', 'newick')
def test_get_score(self):
aln = AlignIO.read("TreeConstruction/msa.phy", "phylip")
tree = Phylo.read("./TreeConstruction/upgma.tre", "newick")
scorer = ParsimonyScorer()
score = scorer.get_score(tree, aln)
self.assertEqual(score, 2 + 1 + 2 + 2 + 1 + 1 + 1 + 3)
alphabet = ["A", "T", "C", "G"]
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3.5 + 2.5 + 3.5 + 3.5 + 2.5 + 1 + 2.5 + 4.5)
alphabet = [
"A",
"C",
"D",
"E",
"F",
"G",
"H",
"I",
"K",
"L",
"M",
"N",
"P",
"Q",
"R",
"1",
"2",
"T",
"V",
"W",
"Y",
"*",
"-",
]
step_matrix = [
[0],
[2, 0],
[1, 2, 0],
[1, 2, 1, 0],
[2, 1, 2, 2, 0],
[1, 1, 1, 1, 2, 0],
[2, 2, 1, 2, 2, 2, 0],
[2, 2, 2, 2, 1, 2, 2, 0],
[2, 2, 2, 1, 2, 2, 2, 1, 0],
[2, 2, 2, 2, 1, 2, 1, 1, 2, 0],
[2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 0],
[2, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 0],
[1, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 0],
[2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 2, 1, 0],
[2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 0],
[1, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 0],
[1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 0],
[1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 3, 2, 2, 1, 1, 2, 2, 2, 0],
[2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 2, 0],
[2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 0],
[
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 0
],
]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3 + 1 + 3 + 3 + 2 + 1 + 2 + 5)