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# Copyright 2007 by Tiago Antao <tiagoantao@gmail.com>. All rights reserved.
# This code is part of the Biopython distribution and governed by its
# license. Please see the LICENSE file that should have been included
# as part of this package.
"""This module allows you to control fdist (DEPRECATED).
This will allow you to call fdist and associated programs (cplot,
datacal, pv) by Mark Beaumont.
http://www.rubic.rdg.ac.uk/~mab/software.html (old)
http://www.maths.bris.ac.uk/~mamab/ (new)
"""
import os
import subprocess
import sys
from random import randint
from time import strftime, clock
# from logging import debug
def my_float(f):
# Because of Jython, mostly
if f == "-nan":
f = "nan"
return float(f)
class FDistController(object):
def __init__(self, fdist_dir='', ext=None):
"""Initializes the controller.
fdist_dir is the directory where fdist2 is.
ext is the extension of binaries (.exe on windows,
none on Unix)
"""
self.tmp_idx = 0
self.fdist_dir = fdist_dir
self.os_name = os.name
if sys.platform == 'win32':
py_ext = '.exe'
else:
py_ext = ''
if ext is None:
self.ext = py_ext
else:
self.ext = ext
def _get_path(self, app):
"""Returns the path to an fdist application.
Includes Path where fdist can be found plus executable extension.
"""
if self.fdist_dir == '':
return app + self.ext
else:
return os.sep.join([self.fdist_dir, app]) + self.ext
def _get_temp_file(self):
"""Gets a temporary file name.
Returns a temporary file name, if executing inside jython
tries to replace unexisting tempfile.mkstemp().
"""
self.tmp_idx += 1
return strftime("%H%M%S") + str(int(clock() * 100)) + str(randint(0, 1000)) + str(self.tmp_idx)
def run_datacal(self, data_dir='.', version=1,
crit_freq=0.99, p=0.5, beta=(0.25, 0.25)):
"""Executes datacal.
data_dir - Where the data is found.
"""
if version == 1:
datacal_name = "datacal"
else:
datacal_name = "Ddatacal"
proc = subprocess.Popen([self._get_path(datacal_name)],
universal_newlines=True,
stdin=subprocess.PIPE,
shell=(sys.platform != "win32"),
stdout=subprocess.PIPE, cwd=data_dir)
if version == 1:
out, err = proc.communicate('a\n')
lines = out.split("\n")
fst_line = lines[0].rstrip().split(' ')
fst = my_float(fst_line[4])
sample_line = lines[1].rstrip().split(' ')
sample = int(sample_line[9])
else:
out, err = proc.communicate('%f\n%f\n%f %f\na\n' % (
crit_freq, p, beta[0], beta[1]))
lines = out.split("\n")
l = lines[0].rstrip().split(" ")
loci, pops = int(l[-5]), int(l[-2])
fst_line = lines[1].rstrip().split(' ')
fst = my_float(fst_line[4])
sample_line = lines[2].rstrip().split(' ')
sample = int(sample_line[9])
F_line = lines[3].rstrip().split(' ')
F, obs = my_float(F_line[5]), int(F_line[8])
if version == 1:
return fst, sample
else:
return fst, sample, loci, pops, F, obs
def _generate_intfile(self, data_dir):
"""Generates an INTFILE.
Parameter:
data_dir - data directory
"""
inf = open(data_dir + os.sep + 'INTFILE', 'w')
for i in range(98):
inf.write(str(randint(-2 ** 31 + 1, 2 ** 31 - 1)) + '\n')
inf.write('8\n')
inf.close()
def run_fdist(self, npops, nsamples, fst, sample_size,
mut=0, num_sims=50000, data_dir='.',
is_dominant=False, theta=0.06, beta=(0.25, 0.25),
max_freq=0.99):
"""Executes (d)fdist.
Parameters:
- npops - Number of populations
- nsamples - Number of populations sampled
- fst - expected Fst
- sample_size - Sample size per population
For dfdist: if zero a sample size file has to be provided
- mut - 1=Stepwise, 0=Infinite allele
- num_sims - number of simulations
- data_dir - Where the data is found
- is_dominant - If true executes dfdist
- theta - Theta (=2Nmu)
- beta - Parameters for the beta prior
- max_freq - Maximum allowed frequency of the commonest allele
Returns:
- fst - Average Fst
Important Note: This can take quite a while to run!
"""
if fst >= 0.9:
# Lets not joke
fst = 0.899
if fst <= 0.0:
# 0 will make fdist run forever
fst = 0.001
if is_dominant:
config_name = "Dfdist_params"
else:
config_name = "fdist_params2.dat"
f = open(data_dir + os.sep + config_name, 'w')
f.write(str(npops) + '\n')
f.write(str(nsamples) + '\n')
f.write(str(fst) + '\n')
f.write(str(sample_size) + '\n')
if is_dominant:
f.write(str(theta) + '\n')
else:
f.write(str(mut) + '\n')
f.write(str(num_sims) + '\n')
if is_dominant:
f.write("%f %f\n" % beta)
f.write("%f\n" % max_freq)
f.close()
self._generate_intfile(data_dir)
if is_dominant:
bin_name = "Dfdist"
else:
bin_name = "fdist2"
proc = subprocess.Popen([self._get_path(bin_name)], cwd=data_dir,
universal_newlines=True,
stdin=subprocess.PIPE, stdout=subprocess.PIPE,
shell=(sys.platform != "win32"))
out, err = proc.communicate('y\n\n')
lines = out.split("\n")
for line in lines:
if line.startswith('average Fst'):
fst = my_float(line.rstrip().split(' ')[-1])
return fst
def run_fdist_force_fst(self, npops, nsamples, fst, sample_size,
mut=0, num_sims=50000, data_dir='.',
try_runs=5000, limit=0.001, is_dominant=False,
theta=0.06, beta=(0.25, 0.25),
max_freq=0.99):
"""Executes fdist trying to force Fst.
Parameters:
- try_runs - Number of simulations on the part trying to get
Fst correct
- limit - Interval limit
Other parameters can be seen on run_fdist.
"""
max_run_fst = 1
min_run_fst = 0
current_run_fst = fst
while True:
real_fst = self.run_fdist(npops, nsamples, current_run_fst,
sample_size, mut, try_runs, data_dir,
is_dominant, theta, beta, max_freq)
if abs(real_fst - fst) < limit:
return self.run_fdist(npops, nsamples, current_run_fst,
sample_size, mut, num_sims, data_dir,
is_dominant, theta, beta, max_freq)
if real_fst > fst:
max_run_fst = current_run_fst
if current_run_fst < min_run_fst + limit:
# we can do no better
# debug('Lower limit is ' + str(min_run_fst))
return self.run_fdist(npops, nsamples, current_run_fst,
sample_size, mut, num_sims,
data_dir)
current_run_fst = (min_run_fst + current_run_fst) / 2
else:
min_run_fst = current_run_fst
if current_run_fst > max_run_fst - limit:
return self.run_fdist(npops, nsamples, current_run_fst,
sample_size, mut, num_sims,
data_dir, is_dominant, theta,
beta, max_freq)
current_run_fst = (max_run_fst + current_run_fst) / 2
def run_cplot(self, ci=0.95, data_dir='.', version=1, smooth=0.04):
"""Executes cplot.
ci - Confidence interval.
data_dir - Where the data is found.
"""
self._generate_intfile(data_dir)
if version == 1:
cplot_name = "cplot"
else:
cplot_name = "cplot2"
proc = subprocess.Popen([self._get_path(cplot_name)], cwd=data_dir,
stdin=subprocess.PIPE, stdout=subprocess.PIPE,
shell=(sys.platform != "win32"),
universal_newlines=True)
if version == 1:
proc.communicate('out.dat out.cpl\n' + str(ci) + '\n')
else:
proc.communicate("\n".join([
"data_fst_outfile out.cpl out.dat",
str(ci), str(smooth)]))
f = open(data_dir + os.sep + 'out.cpl')
conf_lines = []
l = f.readline()
try:
while l != '':
conf_lines.append(
tuple(my_float(x) for x in l.rstrip().split(' ')))
l = f.readline()
except ValueError:
f.close()
return []
f.close()
return conf_lines
def run_pv(self, out_file='probs.dat', data_dir='.',
version=1, smooth=0.04):
"""Executes pv.
out_file - Name of output file.
data_dir - Where the data is found.
"""
self._generate_intfile(data_dir)
if version == 1:
pv_name = "pv"
else:
pv_name = "pv2"
proc = subprocess.Popen([self._get_path(pv_name)], cwd=data_dir,
shell=(sys.platform != "win32"),
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
universal_newlines=True)
proc.communicate('data_fst_outfile ' + out_file +
' out.dat\n' + str(smooth) + '\n')
pvf = open(data_dir + os.sep + out_file, 'r')
result = [tuple(my_float(y) for y in x.rstrip().split(' ')) for x in pvf.readlines()]
pvf.close()
return result
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