/
20080307a.py
98 lines (91 loc) · 3.41 KB
/
20080307a.py
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"""Sample a nucleotide alignment given a tree and a mixture model.
The mixture is scaled so that the branch lengths in the newick tree
are the expected number of substitutions on the branch.
The rows and columns of the rate matrices
are ordered alphabetically by nucleotide.
"""
import numpy as np
from SnippetUtil import HandlingError
import SnippetUtil
import Newick
import PhyLikelihood
import RateMatrix
import MatrixUtil
import SubModel
import Form
import FormOut
g_nt_matrix_a = np.array([
[-3, 1, 1, 1], [1, -3, 1, 1], [1, 1, -3, 1], [1, 1, 1, -3]])
g_nt_matrix_b = np.array([
[-3, 1, 1, 1], [1, -3, 1, 1], [1, 1, -3, 1], [1, 1, 1, -3]])
g_nt_matrix_c = np.array([
[-3, 1, 1, 1], [10, -12, 1, 1], [10, 1, -12, 1], [10, 1, 1, -12]])
g_weight_a = 1
g_weight_b = 2
g_weight_c = 3
def get_form():
"""
@return: the body of a form
"""
# define the tree string
tree_string = '(((Human:0.1, Chimpanzee:0.2):0.8, Gorilla:0.3):0.7, Orangutan:0.4, Gibbon:0.5);'
tree = Newick.parse(tree_string, Newick.NewickTree)
formatted_tree_string = Newick.get_narrow_newick_string(tree, 60)
# define the form objects
form_objects = [
Form.MultiLine('tree', 'newick tree', formatted_tree_string),
Form.Integer('ncols', 'sample this many columns',
100, low=1, high=1000),
Form.Matrix('matrix_a', 'first nucleotide rate matrix',
g_nt_matrix_a),
Form.Float('weight_a', 'first mixture weight',
g_weight_a, low_inclusive=0),
Form.Matrix('matrix_b', 'second nucleotide rate matrix',
g_nt_matrix_b),
Form.Float('weight_b', 'second mixture weight',
g_weight_b, low_inclusive=0),
Form.Matrix('matrix_c', 'third nucleotide rate matrix',
g_nt_matrix_c),
Form.Float('weight_c', 'third mixture weight',
g_weight_c, low_inclusive=0)]
return form_objects
def get_form_out():
return FormOut.NucleotideFasta()
def get_response_content(fs):
# get the tree
tree = Newick.parse(fs.tree, Newick.NewickTree)
tree.assert_valid()
# get the mixture weights
weights = [fs.weight_a, fs.weight_b, fs.weight_c]
# get the matrices
matrices = [fs.matrix_a, fs.matrix_b, fs.matrix_c]
for R in matrices:
if R.shape != (4,4):
msg = 'expected each nucleotide rate matrix to be 4x4'
raise HandlingError(msg)
# create the mixture proportions
weight_sum = sum(weights)
mixture_proportions = [weight / weight_sum for weight in weights]
# create the rate matrix objects
ordered_states = list('ACGT')
rate_matrix_objects = []
for R in matrices:
rate_matrix_object = RateMatrix.RateMatrix(R.tolist(), ordered_states)
rate_matrix_objects.append(rate_matrix_object)
# create the mixture model
mixture_model = SubModel.MixtureModel(mixture_proportions,
rate_matrix_objects)
# normalize the mixture model
mixture_model.normalize()
# simulate the alignment
try:
alignment = PhyLikelihood.simulate_alignment(tree,
mixture_model, fs.ncols)
except PhyLikelihood.SimulationError as e:
raise HandlingError(e)
# get the alignment
arr = []
for node in tree.gen_tips():
arr.append(alignment.get_fasta_sequence(node.name))
# return the alignment string
return '\n'.join(arr) + '\n'