Added tool 'fit_beta_model.py'.

fit_beta_model.py
* fit provided data with beta model
* ignore the inner-most n data points for the fitting

1 files changed, 133 insertions, 0 deletions

diff --git a/astro/fitting/fit_beta_model.py b/astro/fitting/fit_beta_model.py
new file mode 100755
index 0000000..aaf5781
--- /dev/null
+++ b/astro/fitting/fit_beta_model.py
@@ -0,0 +1,133 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+#
+# Fitting data according to (SBP) beta model.
+#
+# Aaron LI
+# 2015/05/29
+
+
+import numpy as np
+from scipy.optimize import curve_fit
+
+import os
+import sys
+import getopt
+import re
+
+
+USAGE = """Usage:
+    %(prog)s [ -h -c -o outfile ] -i infile
+
+Required arguments:
+    -i, --infile
+        input data file with the following *four* columns:
+            r, rerr, s, serr
+    -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
+        accept an integer number
+        ignore the inner-most n data points
+""" % { 'prog': os.path.basename(sys.argv[0]) }
+
+
+def usage():
+    print(USAGE)
+
+
+def beta_model(r, s0, rc, beta, c):
+    """
+    SBP beta model.
+    """
+    return s0 * np.power((1.0+(r/rc)**2), 0.5-3*beta) + c
+
+
+def main():
+    infile = None
+    outfilename= None
+    cut = 0
+
+    try:
+        opts, args = getopt.getopt(sys.argv[1:], 'c:hi:o:',
+                ['cut=', 'help', 'infile=', 'outfile='])
+    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 ('-i', '--infile'):
+            infile = arg
+        elif opt in ('-o', '--outfile'):
+            outfilename = arg
+        elif opt in ('-c', '--cut'):
+            cut = int(arg)
+        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 = []
+
+    for line in open(infile, 'r'):
+        if re.match(r'^\s*#', line):
+            continue
+        if re.match(r'^\s*$', line):
+            continue
+        r, rerr, s, serr = map(float, line.split())
+        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)
+
+    # initial parameter values for beta model
+    s0_0 = 1.0e-7
+    rc_0 = 10.0
+    beta_0 = 0.6
+    c_0 = 0.0
+    par_0 = [s0_0, rc_0, beta_0, c_0]
+
+    par_fit, cov_fit = curve_fit(beta_model, r_data[cut:], s_data[cut:],
+            p0=par_0, sigma=serr_data[cut:])
+
+    s_fitted = beta_model(r_data, *par_fit)
+
+    print("# beta-model fitting results:", file=outfile)
+    print("# s0 * power((1.0+(r/rc)**2), 0.5-3*beta) + c", file=outfile)
+    print("# s0 = %g, rc = %g, beta = %g, c = %g" % tuple(par_fit),
+            file=outfile)
+    print("# radius(input)  brightness(fitted)", file=outfile)
+    for i in range(len(s_fitted)):
+        print("%g  %g" % (r_data[i], s_fitted[i]), file=outfile)
+
+    if not outfilename:
+        outfile.close()
+
+
+if __name__ == '__main__':
+    main()
+