1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
|
#!/usr/bin/env python
"""
Script to plot the probabilities for atmospheric neutrino oscillations. To run
it:
$ ./plot-atmospheric-oscillations nue_osc_prob.txt
"""
from __future__ import print_function, division
import numpy as np
if __name__ == '__main__':
import argparse
from os.path import split, splitext
parser = argparse.ArgumentParser("script to plot atmospheric oscillations")
parser.add_argument("filenames", nargs='+', help="oscillation probability filenames")
parser.add_argument("--save", action="store_true", default=False, help="save plots")
args = parser.parse_args()
if args.save:
# default \textwidth for a fullpage article in Latex is 16.50764 cm.
# You can figure this out by compiling the following TeX document:
#
# \documentclass{article}
# \usepackage{fullpage}
# \usepackage{layouts}
# \begin{document}
# textwidth in cm: \printinunitsof{cm}\prntlen{\textwidth}
# \end{document}
width = 16.50764
width /= 2.54 # cm -> inches
# According to this page:
# http://www-personal.umich.edu/~jpboyd/eng403_chap2_tuftegospel.pdf,
# Tufte suggests an aspect ratio of 1.5 - 1.6.
height = width/1.5
FIGSIZE = (width,height)
import matplotlib.pyplot as plt
font = {'family':'serif', 'serif': ['computer modern roman']}
plt.rc('font',**font)
plt.rc('text', usetex=True)
else:
# on retina screens, the default plots are way too small
# by using Qt5 and setting QT_AUTO_SCREEN_SCALE_FACTOR=1
# Qt5 will scale everything using the dpi in ~/.Xresources
import matplotlib
matplotlib.use("Qt5Agg")
import matplotlib.pyplot as plt
# Default figure size. Currently set to my monitor width and height so that
# things are properly formatted
FIGSIZE = (13.78,7.48)
# Make the defalt font bigger
plt.rc('font', size=22)
for filename in args.filenames:
head, tail = split(filename)
root, ext = splitext(tail)
e, z, pnue, pnum, pnut = np.genfromtxt(filename).T
shape0 = len(np.unique(e))
ee = e.reshape((shape0,-1))
zz = z.reshape((shape0,-1))
pnue = pnue.reshape((shape0,-1))
pnum = pnum.reshape((shape0,-1))
pnut = pnut.reshape((shape0,-1))
levels = np.linspace(0,1,101)
plt.figure(figsize=FIGSIZE)
plt.contourf(ee,zz,pnue,levels=levels)
plt.gca().set_xscale('log')
plt.xlabel("Energy (GeV)")
plt.ylabel("Cos(Zenith)")
plt.colorbar()
plt.tight_layout()
if args.save:
plt.savefig("%s_nue.pdf" % root)
plt.savefig("%s_nue.eps" % root)
else:
plt.title(r"Probability to oscillate to $\nu_e$")
plt.figure(figsize=FIGSIZE)
plt.contourf(ee,zz,pnum,levels=levels)
plt.gca().set_xscale('log')
plt.xlabel("Energy (GeV)")
plt.ylabel("Cos(Zenith)")
plt.colorbar()
plt.tight_layout()
if args.save:
plt.savefig("%s_num.pdf" % root)
plt.savefig("%s_num.eps" % root)
else:
plt.title(r"Probability to oscillate to $\nu_\mu$")
plt.figure(figsize=FIGSIZE)
plt.contourf(ee,zz,pnut,levels=levels)
plt.gca().set_xscale('log')
plt.xlabel("Energy (GeV)")
plt.ylabel("Cos(Zenith)")
plt.colorbar()
plt.tight_layout()
if args.save:
plt.savefig("%s_nut.pdf" % root)
plt.savefig("%s_nut.eps" % root)
else:
plt.title(r"Probability to oscillate to $\nu_\tau$")
plt.show()
|
