-
Notifications
You must be signed in to change notification settings - Fork 3
/
PlotFermipy.py
199 lines (175 loc) · 8.81 KB
/
PlotFermipy.py
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
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
#!/usr/bin/env python
import sys
import os
import numpy as np
#from fermipy.gtanalysis import GTAnalysis
import matplotlib as mpl
import matplotlib.pyplot as plt
import math
from math import cos, sin, tan, acos, asin, atan, radians, degrees, pi, log10, sqrt, ceil, isnan
import click
import ROOT
from ROOT import gROOT, gDirectory, gPad, gSystem, gStyle, kTRUE, kFALSE
ROOT.gROOT.SetBatch()
from pColor import *
from pMETandMJD import *
MEV2ERG = 1.6021766208e-6
class Datum:
def __init__(self, time=None, enr_cfg=None, enr_sed=None, pl_index=None, flux=None, eflux=None, model_dnde=None):
self.time = time # min, max
self.enr_cfg = enr_cfg # min, max
self.enr_sed = enr_sed # ref, min, max
self.pl_index = pl_index # value, error
self.flux = flux # value, lower error, higher error
self.eflux = eflux # value, lower error, higher error
self.model_dnde = model_dnde
def get_model_e2dnde_lowest_energy():
NLOWEST = 0
elowest = self.model_dnde['energies'][NLOWEST]
e2dnde = self.model_dnde['dnde'][NLOWEST] * elowest * elowest
e2dnde_lo = self.model_dnde['dnde_lo'][NLOWEST] * elowest * elowest
e2dnde_hi = self.model_dnde['dnde_hi'][NLOWEST] * elowest * elowest
return [elowest, e2dnde, e2dnde_lo, e2dnde_hi]
def PlotFermipy(name_src, lst_np_input_pairs, t0=0): # pair of output.npy and sed.npy
# LC
lst_enr = []
lst_time = []
lst_data = []
for np_input_pair in lst_np_input_pairs:
npi = np.load(np_input_pair[0]).flat[0]
np_cfg = npi['config']
np_src = npi['sources'][name_src]
np_sed = np.load(np_input_pair[1]).flat[0]
lst_time.append([np_cfg['selection']['tmin']-t0, np_cfg['selection']['tmax']-t0])
lst_enr.append([np_cfg['selection']['emin'], np_cfg['selection']['emax']])
lst_data.append(Datum(time=lst_time[-1], enr_cfg=lst_enr[-1], enr_sed=[np_sed['e_ref'], np_sed['e_min'], np_sed['e_max']], flux=[np_sed['flux'], np_sed['flux_err_lo'], np_sed['flux_err_hi'], np_sed['flux_ul95']], eflux=[np_sed['eflux'], np_sed['eflux_err_lo'], np_sed['eflux_err_hi'], np_sed['eflux_ul95']], model_dnde=np_sed['model_flux']))
for (ipar, par) in enumerate(np_src['param_names']):
if par=='Index':
lst_data[-1].pl_index = [np_src['param_values'][ipar], np_src['param_errors'][ipar]]
lst_enr_irr = []
for e in lst_enr:
if not e in lst_enr_irr:
lst_enr_irr.append(e)
lst_enr_irr.sort()
nenr = len(lst_enr_irr)
print nenr, 'energy bins.'
lst_time_irr = []
for t in lst_time:
if not t in lst_time_irr:
lst_time_irr.append(t)
lst_time_irr.sort()
ntime = len(lst_time_irr)
print ntime, 'time bins.'
# LC
nrows_enr = int(sqrt(nenr))
print '#row:', nrows_enr
ncols_enr = int(ceil(nenr/nrows_enr))
print '#cols:', ncols_enr
fig_lc_flux, axes_lc_flux = plt.subplots(nrows=nrows_enr, ncols=ncols_enr, squeeze=False)
fig_lc_eflux, axes_lc_eflux = plt.subplots(nrows=nrows_enr, ncols=ncols_enr, squeeze=False)
fig_lc_index, axes_lc_index = plt.subplots(nrows=nrows_enr, ncols=ncols_enr, squeeze=False)
lst_key_spec = ['Best', 'Softer', 'Harder']
for (ienr, enr) in enumerate(lst_enr_irr):
print 'Light curve for', enr, 'sec'
xtime = []
xtime_err = []
yflux = []
yflux_err_lo = []
yflux_err_hi = []
yflux_ul = []
yeflux = []
yeflux_err_lo = []
yeflux_err_hi = []
yeflux_ul = []
yindex = []
yindex_err = []
ye2dnde = {}
ye2dnde_lo = {}
ye2dnde_hi = {}
ye2dnde = []
ye2dnde_lo = []
ye2dnde_hi = []
for datum in lst_data:
if datum.enr_cfg==enr:
# Time
xtime.append((datum.time[1]+datum.time[0])/2.)
xtime_err.append((datum.time[1]-datum.time[0])/2.)
# flux
if not isnan(datum.flux[2]):
yflux.append(datum.flux[0])
yflux_err_hi.append(datum.flux[1])
yflux_err_lo.append(datum.flux[2])
yflux_ul.append(datum.flux[3]) #-datum.flux[0])
else:
yflux.append(datum.flux[0])
yflux_err_lo.append(0)
yflux_err_hi.append(0)
yflux_ul.append(datum.flux[3]) #-datum.flux[0])
# Energy flux
if not isnan(datum.eflux[2]):
yeflux.append(datum.eflux[0])
yeflux_err_hi.append(datum.eflux[1])
yeflux_err_lo.append(datum.eflux[2])
yeflux_ul.append(datum.eflux[3]) #-datum.eflux[0])
else:
yeflux.append(datum.flux[0])
yeflux_err_lo.append(0)
yeflux_err_hi.append(0)
yeflux_ul.append(datum.flux[3]) #-datum.flux[0])
# Power-law index
yindex.append(datum.pl_index[0])
yindex_err.append(datum.pl_index[1])
# Model e2dnde
lst_e2dnde = datum.get_model_e2dnde_lowest_energy()
ye2dnde.append(lst_e2dnde[1])
ye2dnde_lo.append(lst_e2dnde[2])
ye2dnde_hi.append(lst_e2dnde[3])
print 'Time:', xtime
print 'Time Error', xtime_err
print 'Flux', yflux
print 'Flux Error higher', yflux_err_hi
print 'Flux Error lower', yflux_err_lo
print 'Eflux', yeflux
print 'Eflux Error higher', yeflux_err_hi
print 'Eflux Error lower', yeflux_err_lo
print 'Index', yindex
print 'Index Error', yindex_err
axes_lc_flux[ienr/ncols_enr,ienr%ncols_enr].set_xscale("log", nonposy='clip')
axes_lc_flux[ienr/ncols_enr,ienr%ncols_enr].set_yscale("log", nonposy='clip')
axes_lc_flux[ienr/ncols_enr,ienr%ncols_enr].errorbar(np.array(xtime), np.array(yflux), xerr=np.array(xtime_err), yerr=[np.array(yflux_err_lo), np.array(yflux_err_hi)], ls='')
axes_lc_flux[ienr/ncols_enr,ienr%ncols_enr].errorbar(np.array(xtime), np.array(yflux_ul), xerr=np.array(xtime_err), yerr=np.array(yflux)*0.1, uplims=True, ls='')
# axes_lc_flux[ienr/ncols_enr,ienr%ncols_enr].errorbar(np.array(xtime), np.array(yflux_ul), xerr=np.array(xtime_err), ls='')
axes_lc_flux[ienr/ncols_enr,ienr%ncols_enr].set_title('{0:d} - {1:d} MeV'.format(int(enr[0]), int(enr[1])))
axes_lc_flux[ienr/ncols_enr,ienr%ncols_enr].set_ylim([5e-9, 5e-3])
axes_lc_flux[ienr/ncols_enr,ienr%ncols_enr].set_xlabel('t - {0} [s]'.format(t0))
axes_lc_flux[ienr/ncols_enr,ienr%ncols_enr].set_ylabel('Photon flux [cm^-2 s^-1]')
axes_lc_eflux[ienr/ncols_enr,ienr%ncols_enr].set_xscale("log", nonposy='clip')
axes_lc_eflux[ienr/ncols_enr,ienr%ncols_enr].set_yscale("log", nonposy='clip')
axes_lc_eflux[ienr/ncols_enr,ienr%ncols_enr].errorbar(np.array(xtime), np.array(yeflux)*MEV2ERG, xerr=np.array(xtime_err), yerr=[np.array(yeflux_err_lo)*MEV2ERG, np.array(yeflux_err_hi)*MEV2ERG], ls='')
axes_lc_eflux[ienr/ncols_enr,ienr%ncols_enr].errorbar(np.array(xtime), np.array(yeflux_ul)*MEV2ERG, xerr=np.array(xtime_err), yerr=np.array(yeflux)*MEV2ERG*0.1, uplims=True, ls='')
axes_lc_eflux[ienr/ncols_enr,ienr%ncols_enr].set_title('{0:d} - {1:d} MeV'.format(int(enr[0]), int(enr[1])))
axes_lc_eflux[ienr/ncols_enr,ienr%ncols_enr].set_ylim([5e-12, 1e-7])
axes_lc_eflux[ienr/ncols_enr,ienr%ncols_enr].set_xlabel('t - {0} [s]'.format(t0))
axes_lc_eflux[ienr/ncols_enr,ienr%ncols_enr].set_ylabel('Energy flux [erg cm^-2 s^-1]')
axes_lc_index[ienr/ncols_enr,ienr%ncols_enr].set_xscale("log", nonposy='clip')
axes_lc_index[ienr/ncols_enr,ienr%ncols_enr].errorbar(np.array(xtime), np.array(yindex), xerr=np.array(xtime_err), yerr=np.array(yindex_err), ls='')
axes_lc_index[ienr/ncols_enr,ienr%ncols_enr].set_title('{0:d} - {1:d} MeV'.format(int(enr[0]), int(enr[1])))
axes_lc_index[ienr/ncols_enr,ienr%ncols_enr].set_xlabel('t - {0} [s]'.format(t0))
axes_lc_index[ienr/ncols_enr,ienr%ncols_enr].set_ylabel('Photon index')
#plt.show()
fig_lc_flux.tight_layout()
fig_lc_eflux.tight_layout()
fig_lc_index.tight_layout()
fig_lc_flux.savefig('{0}_LightCurve_flux.png'.format(name_src))
fig_lc_eflux.savefig('{0}_LightCurve_eflux.png'.format(name_src))
fig_lc_index.savefig('{0}_LightCurve_index.png'.format(name_src))
# @click.command()
# @click.argument('srcname', type=str)
# @click.argument('inputfile', type=str)
# @click.option('--suffix', type=str, default='')
# def main(srcname, inputfile):
# npi = np.load(inputfile).flat[0]
# np_src = np['sources'][grbname]
# PlotSED(np_src)
# if __name__ == '__main__':
# main()