Move shell/python scripts from 'mass_profile/' to 'bin/'

1 files changed, 0 insertions, 104 deletions

diff --git a/mass_profile/calc_entropy.py b/mass_profile/calc_entropy.py
deleted file mode 100755
index 736fe7e..0000000
--- a/mass_profile/calc_entropy.py
+++ /dev/null
@@ -1,104 +0,0 @@
-#!/usr/bin/env python3
-#
-# Calculate the entropy within the specified radius.
-#
-# Junhua GU
-# Weitian LI
-# 2016-06-07
-#
-
-import argparse
-import re
-from itertools import groupby
-import numpy as np
-
-
-def isplit(iterable, splitters):
-    """
-    Credit: https://stackoverflow.com/a/4322780/4856091
-    """
-    return [list(g) for k, g in groupby(iterable,
-                                        lambda x:x in splitters) if not k]
-
-
-def get_entropy(data, r):
-    """
-    Get the entropy *at* the specified radius.
-
-    XXX: whether to interpolate first?
-    """
-    radius = data[:, 0]
-    entropy = data[:, 1]
-    s = np.min(entropy[radius > r])
-    return s
-
-
-def read_merged_qdp(infile):
-    """
-    Read merged QDP with multiple group of data separated by "no no no".
-    """
-    lines = map(lambda line: re.sub(r"^\s*no\s+no\s+no.*$", "X",
-                                    line.strip(), flags=re.I),
-                open(infile).readlines())
-    lines = isplit(lines, ("X",))
-    data_groups = []
-    for block in lines:
-        data = [list(map(float, l.split())) for l in block]
-        data.append(np.row_stack(data))
-    return data_groups
-
-
-def calc_error(center_value, mc_values, ci=0.683):
-    """
-    Calculate the uncertainties/errors.
-    """
-    data = np.concatenate([[center_value], mc_values])
-    median, q_lower, q_upper = np.percentile(data, q=(50, 50-50*ci, 50+50*ci))
-    mean = np.mean(data)
-    std = np.std(data)
-    return {
-        "mean":    mean,
-        "std":     std,
-        "median":  median,
-        "q_lower": q_lower,
-        "q_upper": q_upper,
-    }
-
-
-def main():
-    parser = argparse.ArgumentParser(
-            description="Calculate the entropy within the given radius")
-    parser.add_argument("-C", "--confidence-level", dest="ci",
-                        type=float, default=0.683,
-                        help="confidence level to estimate the errors")
-    parser.add_argument("center_data",
-                        help="calculate central entropy profile " +
-                             "(e.g., entropy_center.qdp)")
-    parser.add_argument("mc_data",
-                        help="Merged QDP file of all the Monte Carlo " +
-                             "simulated entropy profiles " +
-                             "(e.g., summary_entropy.qdp)")
-    parser.add_argument("rout", type=float, help="outer radius (kpc)")
-    args = parser.parse_args()
-
-    center_data = np.loadtxt(args.center_data)
-    center_s = get_entropy(center_data, r=args.rout)
-
-    data_groups = read_merged_qdp(args.mc_data)
-    entropy_list = []
-    for dg in data_groups:
-        s = get_entropy(dg, r=args.rout)
-        entropy_list.append(s)
-    results = calc_error(center_s, entropy_list, ci=args.ci)
-    s_err_lower = results["q_lower"] - center_s
-    s_err_upper = results["q_upper"] - center_s
-
-    print("entropy= %e %+e/%+e keV cm^2 (ci=%.1f%%)" %
-          (center_s, s_err_lower, s_err_upper, args.ci * 100))
-    print("entropy(mean)= %e" % results["mean"])
-    print("entropy(median)= %e" % results["median"])
-    print("entropy(std)= %e" % results["std"])
-
-
-if __name__ == "__main__":
-    main()