-
Notifications
You must be signed in to change notification settings - Fork 0
/
plot_spectra_new_0653.py
163 lines (138 loc) · 6.86 KB
/
plot_spectra_new_0653.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
import numpy as np
from astropy.cosmology import FlatLambdaCDM
import matplotlib as mpl
from matplotlib import pyplot as plt
from matplotlib.ticker import AutoMinorLocator
from astropy.io import fits
import sys
sys.path.append('/Users/suksientie/Research/data_redux')
import mutils
import argparse
import mask_cgm_pdf
import mutils
### Figure settings
font = {'family' : 'serif', 'weight' : 'normal'}#, 'size': 11}
plt.rc('font', **font)
mpl.rcParams['axes.linewidth'] = 1.5
mpl.rcParams['xtick.major.width'] = 1.5
mpl.rcParams['ytick.major.width'] = 1.5
mpl.rcParams['xtick.minor.width'] = 1.5
mpl.rcParams['ytick.minor.width'] = 1.5
mpl.rcParams['xtick.major.size'] = 7
mpl.rcParams['xtick.minor.size'] = 4
mpl.rcParams['ytick.major.size'] = 7
mpl.rcParams['ytick.minor.size'] = 4
xytick_size = 16
xylabel_fontsize = 20
legend_fontsize = 16
datapath = '/Users/suksientie/Research/MgII_forest/rebinned_spectra2/'
qso_namelist = ['J0411-0907', 'J0319-1008', 'J0410-0139', 'J0038-0653', 'J0313-1806', 'J0038-1527', 'J0252-0503', 'J1342+0928', 'J1007+2115', 'J1120+0641']
qso_zlist = [6.826, 6.8275, 7.0, 7.1, 7.642, 7.034, 7.001, 7.541, 7.515, 7.085]
exclude_restwave = 1216 - 1185
nqso_to_plot = len(qso_namelist)
redshift_bin = 'all'
savefig = True #True
# CGM masks
good_vel_data_all, good_wave_all, norm_good_flux_all, norm_good_std_all, norm_good_ivar_all, noise_all, pz_masks_all, other_masks_all = \
mask_cgm_pdf.init(redshift_bin=redshift_bin, do_not_apply_any_mask=True, datapath=datapath)
mgii_tot_all = mask_cgm_pdf.chi_pdf(good_vel_data_all, norm_good_flux_all, norm_good_ivar_all, noise_all, plot=False, savefig=None)
#mgii_tot_all = mask_cgm_pdf.chi_pdf2(good_vel_data_all, norm_good_flux_all, norm_good_ivar_all, noise_all, pz_masks_all, other_masks_all, plot=False, savefig=None)
ymin = -0.05
ymax_ls = [0.8, 0.48, 0.4, 0.6, 0.45, 0.65, 0.5, 0.6, 0.6, 0.7]
ymin_norm, ymax_norm = -0.05, 2.3
good_zpix_all = []
dx_all = []
dz_all = []
for i in [3]:
print("====== %s ======" % qso_namelist[i])
raw_data_out, masked_data_out, all_masks_out = mutils.init_onespec(i, redshift_bin, datapath=datapath)
wave, flux, ivar, mask, std, tell, fluxfit = raw_data_out
strong_abs_gpm, redshift_mask, pz_mask, obs_wave_max, zbin_mask, telluric_mask, master_mask = all_masks_out
mgii_tot = mgii_tot_all[i]
# J1120+0641
if i == 9:
print("masking absorbers from Bosman et al. 2017")
_, abs_mask_gpm = mask_cgm_pdf.bosman_J1120([4, 4, 3.5])
fs_mask = mgii_tot.fit_gpm[0] * abs_mask_gpm
else:
fs_mask = mgii_tot.fit_gpm[0]
all_masks = master_mask * fs_mask
print("masked fraction", 1 - np.sum(all_masks) / len(all_masks))
median_snr = np.nanmedian((flux / std)[all_masks])
print("median snr", median_snr)
good_zpix = wave[all_masks] / 2800 - 1
good_zpix_all.extend(good_zpix)
zlow, zhigh = good_zpix.min(), good_zpix.max()
dx = mutils.abspath(zhigh, zlow)
dx_all.append(dx)
dz_all.append(zhigh-zlow)
print("zlow, zhigh, zhigh-zlow, dx", zlow, zhigh, zhigh-zlow, dx)
ymax = ymax_ls[i]
xmin = wave[zbin_mask].min() #19500
xmax = wave[zbin_mask].max() #wave.max()
fig, ax2 = plt.subplots(1, figsize=(16, 5), sharex=True)
#fig.subplots_adjust(left=0.085, bottom=0.11, right=0.95, top=0.89, wspace=0, hspace=0.)
fig.subplots_adjust(left=0.085, bottom=0.15, right=0.95, top=0.85, wspace=0, hspace=0.)
# xy=(xmin + 100, ymax * 0.88)
ax2.annotate(qso_namelist[i], xy=(xmin + 90, ymax_norm * 0.83), fontsize=legend_fontsize+5, bbox=dict(boxstyle='round', ec="k", fc="white"))
# ax1.plot(wave, flux, c='k', drawstyle='steps-mid')
# ax1.plot(wave, fluxfit, c='r', drawstyle='steps-mid') #, label='continuum fit')
# ax1.plot(wave, std, c='k', alpha=0.5, drawstyle='steps-mid')#, label='sigma')
#
# ind_masked = np.where(mask * strong_abs_gpm == False)[0]
# for j in range(len(ind_masked)): # bad way to plot masked pixels
# ax1.axvline(wave[ind_masked[j]], color='k', alpha=0.15, lw=1)
#
# ax1.xaxis.set_minor_locator(AutoMinorLocator())
# ax1.yaxis.set_minor_locator(AutoMinorLocator())
# ax1.tick_params(top=True, right=True, which='both', labelsize=xytick_size)
# ax1.axvline((qso_zlist[i] + 1) * 2800, ls='--', c='k', lw=3)
# ax1.set_xlim([xmin, xmax])
# ax1.set_ylim([ymin, ymax])
# ax1.set_ylabel(r'Flux' + '\n $(10^{-17}$ erg s$^{-1}$ cm$^{-2}$ $\mathrm{{\AA}}^{-1})$', fontsize=xylabel_fontsize)
ax2.plot(wave, flux / fluxfit, c='k', drawstyle='steps-mid')
ax2.plot(wave, std / fluxfit, c='k', alpha=0.5, drawstyle='steps-mid')
ax2.plot(wave, tell * 2, alpha=0.5, drawstyle='steps-mid') # telluric
# plotting the various masks individually
plot_masks = [mask, pz_mask, telluric_mask, fs_mask]
plot_masks_color = ['g', 'k', 'b', 'r']
for im in range(len(plot_masks)):
if im == len(plot_masks) - 1: # only plot masked absorbers outside of PZ region
ind_masked = np.where(plot_masks[im][pz_mask] == False)[0]
else:
ind_masked = np.where(plot_masks[im] == False)[0]
if im == len(plot_masks) - 1:
telluric_bpm = np.invert(telluric_mask)
mask_bpm = np.invert(mask)
for j in range(len(ind_masked)):
# don't plot cgm masks within the telluric bpm
if (wave[ind_masked[j]] not in wave[telluric_bpm]) and \
(wave[ind_masked[j]] not in wave[mask_bpm]):
ax2.axvline(wave[ind_masked[j]], c=plot_masks_color[im], alpha=0.15, lw=1, drawstyle='steps-mid')
else:
for j in range(len(ind_masked)): # bad way to plot masked pixels
ax2.axvline(wave[ind_masked[j]], c=plot_masks_color[im], alpha=0.15, lw=1, drawstyle='steps-mid')
ax2.axvline((qso_zlist[i] + 1) * 2800, ls='--', c='k', lw=3)
ax2.xaxis.set_minor_locator(AutoMinorLocator())
ax2.yaxis.set_minor_locator(AutoMinorLocator())
ax2.tick_params(top=True, right=True, which='both', labelsize=xytick_size)
ax2.set_xlim([xmin, xmax])
ax2.set_ylim([ymin_norm, ymax_norm])
ax2.set_xlabel(r'obs wavelength ($\mathrm{{\AA}}$)', fontsize=xylabel_fontsize)
ax2.set_ylabel(r'$F_{\mathrm{norm}}$', fontsize=xylabel_fontsize+5)
atwin = ax2.twiny()
atwin.set_xlabel('redshift', fontsize=xylabel_fontsize)
zmin, zmax = xmin / 2800 - 1, xmax / 2800 - 1
atwin.axis([zmin, zmax, ymin, ymax_norm])
atwin.tick_params(top=True, axis="x", labelsize=xytick_size)
atwin.xaxis.set_minor_locator(AutoMinorLocator())
if savefig:
plt.savefig('paper_plots/10qso_revision_2/spec_%s.pdf' % qso_namelist[i])
plt.close()
else:
plt.show()
plt.close()
print("##############")
print("good zpix = median: %0.3f, min: %0.3f, max: %0.3f" % (np.median(good_zpix_all), np.min(good_zpix_all), np.max(good_zpix_all)))
print("dx total", np.sum(dx_all))
print("dz total", np.sum(dz_all))