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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# To fitting the given SBP data with the following beta model:
# s = s0 * pow((1.0+(r/rc)^2), 0.5-3*beta) + c
# And this tool supports the following two requirements for the fitting:
# (1) ignore the specified number of inner-most data points;
# (2) ignore the data points whose radius value less than the given value.
#
# Aaron LI
# 2015/05/29
#
# Changelogs:
# 2015/05/30:
# * Added option '-n' / '--no-radius' to ignore radius less than the
# given value.
# * Support read model initial parameter values from input file.
#
from __future__ import print_function, division
import numpy as np
from scipy.optimize import curve_fit
import os
import sys
import getopt
import re
# modes of to cut data
CUT_POINT = 'CUT_POINT'
CUT_RADIUS = 'CUT_RADIUS'
def beta_model(r, s0, rc, beta, c):
"""
SBP beta model, with a constant background.
"""
return s0 * np.power((1.0+(r/rc)**2), 0.5-3*beta) + c
def fit_beta_model(xdata, ydata, yerrdata, p0,
cutmode=CUT_POINT, cutvalue=0):
"""
Fit the provided data with the beta model.
Arguments:
p0: initial values for the parameters of beta model
cutmode: 'point' / 'radius'; ignore data by number of data points,
or by radius value less than the given value
cutvalue: the cut limit
Return:
[fitted_par, fitted_cov, fitted_model_value]
"""
if cutmode == CUT_POINT:
xdata2 = xdata[cutvalue:]
ydata2 = ydata[cutvalue:]
yerrdata2 = yerrdata[cutvalue:]
elif cutmode == CUT_RADIUS:
ii = xdata >= cutvalue
xdata2 = xdata[ii]
ydata2 = ydata[ii]
yerrdata2 = yerrdata[ii]
else:
raise ValueError('Unknown cut mode: %s' % cutmode)
par_fit, cov_fit = curve_fit(beta_model, xdata2, ydata2,
p0=p0, sigma=yerrdata2)
y_fit = beta_model(xdata, *par_fit)
return (par_fit, cov_fit, y_fit)
def main():
# options
infile = None
outfilename= None
cutmode = CUT_POINT # ignore data by number of data points
cutvalue = 0 # do not ignore any data by default
# initial values for the four parameters of the beta model
s0_0 = 1.0e-7
rc_0 = 10.0
beta_0 = 0.6
c_0 = 0.0
# debug
verbose = False
try:
opts, args = getopt.getopt(sys.argv[1:], 'c:hi:n:o:v',
['cut-point=', 'help', 'infile=', 'no-radius=',
'outfile=', 'verbose'])
except getopt.GetoptError as e:
print(e, file=sys.stderr)
usage()
sys.exit(2)
for opt, arg in opts:
if opt in ('-h', '--help'):
usage()
sys.exit(0)
elif opt in ('-v', '--verbose'):
verbose = True
elif opt in ('-i', '--infile'):
infile = arg
elif opt in ('-o', '--outfile'):
outfilename = arg
elif opt in ('-c', '--cut-point'):
cutvalue = int(arg)
cutmode = CUT_POINT
elif opt in ('-n', '--no-radius'):
cutvalue = float(arg)
cutmode = CUT_RADIUS
else:
assert False, 'unhandled option'
if not infile:
print('ERROR: --infile required', file=sys.stderr)
sys.exit(11)
if outfilename:
outfile = open(outfilename, 'w')
else:
outfile = sys.stdout
# input data list
r_data = []
rerr_data = []
s_data = []
serr_data = []
# regex to match initial parameter names, blank line, and comment line
re_blank = re.compile(r'^\s*$')
re_comment = re.compile(r'^\s*#')
re_s0 = re.compile(r'^\s*#\s*s0_0\s*[:=]')
re_rc = re.compile(r'^\s*#\s*rc_0\s*[:=]')
re_beta = re.compile(r'^\s*#\s*beta_0\s*[:=]')
re_c = re.compile(r'^\s*#\s*c_0\s*[:=]')
for line in open(infile, 'r'):
if re_s0.match(line):
# read 's0_0': initial value for parameter 's0'
s0_0 = float(re_s0.split(line)[1])
elif re_rc.match(line):
# read 'rc_0': initial value for parameter 'rc'
rc_0 = float(re_rc.split(line)[1])
elif re_beta.match(line):
# read 'beta_0': initial value for parameter 'beta'
beta_0 = float(re_beta.split(line)[1])
elif re_c.match(line):
# read 'c_0': initial value for parameter 'c'
c_0 = float(re_c.split(line)[1])
elif re_blank.match(line):
# ignore blank line
continue
elif re_comment.match(line):
# ignore comment line
continue
else:
try:
r, rerr, s, serr = map(float, line.split())
except ValueError:
try:
r, s, serr = map(float, line.split())
rerr = 0.0
except ValueError:
print('ERROR: unsupported input data format',
file=sys.stderr)
sys.exit(21)
r_data.append(r)
rerr_data.append(rerr)
s_data.append(s)
serr_data.append(serr)
# convert to numpy array
r_data = np.array(r_data)
rerr_data = np.array(rerr_data)
s_data = np.array(s_data)
serr_data = np.array(serr_data)
if verbose:
print('DEBUG: s0_0 = %g, rc_0 = %g, beta_0 = %g, c_0 = %g' % \
(s0_0, rc_0, beta_0, c_0), file=sys.stderr)
par_0 = [s0_0, rc_0, beta_0, c_0]
par_fit, cov_fit, s_fit = fit_beta_model(r_data, s_data, serr_data,
p0=par_0, cutmode=cutmode, cutvalue=cutvalue)
print("# beta-model fitting results:", file=outfile)
print("# s(r) = s0 * pow((1.0+(r/rc)^2), 0.5-3*beta) + c", file=outfile)
print("# s0 = %g\n# rc = %g\n# beta = %g\n# c = %g" % tuple(par_fit),
file=outfile)
print("# radius(input) brightness(fitted)", file=outfile)
for i in range(len(s_fit)):
print("%g %g" % (r_data[i], s_fit[i]), file=outfile)
if outfilename:
outfile.close()
USAGE = """Usage:
%(prog)s [ -h -c -o outfile ] -i infile
Required arguments:
-i, --infile
input data file with the following *four* or *three* columns:
r, rerr, s, serr
r, s, serr
Note: the initial values for beta model paramters can also be
provided with the following syntax:
# s0_0 = ??
# rc_0 = ??
# beta_0 = ??
# c_0 = ??
-o, --outfile
output file to store the fitted data
if not provided, then print results to screen
Optional arguments:
-h, --help
print this usage
-c, --cut-point
accept an integer number (n)
ignore the inner-most n data points
-n, --no-radius
accept a float number (r)
ignore the data points whose radius is less than r
""" % { 'prog': os.path.basename(sys.argv[0]) }
def usage():
print(USAGE)
if __name__ == '__main__':
main()
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