def main(pargs):
""" Run
"""
import warnings
import numpy as np
from matplotlib import pyplot as plt
from astropy.io import fits
from astropy import units
from frb import frb
from frb.figures import galaxies as ffgal
from frb.figures import utils as ffutils
from linetools.scripts.utils import coord_arg_to_coord
# Load up
hdu = fits.open(pargs.fits_file)
icoord = coord_arg_to_coord(pargs.frb_coord)
# Parse
if pargs.vmnx is not None:
tstr = pargs.vmnx.split(',')
vmnx = (float(tstr[0]), float(tstr[1]))
else:
vmnx = (None, None)
# Dummy FRB object
FRB = frb.FRB('TMP', icoord, 0.)
FRB.set_ee(1.0, 1.0, 0., 95.)
fig = plt.figure(figsize=(7, 7))
ffutils.set_mplrc()
ffgal.sub_image(fig,
hdu,
FRB,
vmnx=vmnx,
cmap='gist_heat',
frb_clr='white',
imsize=pargs.imsize) #img_center=HG190608.coord,
# Layout and save
plt.tight_layout(pad=0.2, h_pad=0.1, w_pad=0.1)
plt.savefig(pargs.outfile, dpi=300)
plt.close()
print('Wrote {:s}'.format(pargs.outfile))
def generate(image,
wcs,
title,
flip_ra=False,
flip_dec=False,
log_stretch=False,
cutout=None,
primary_coord=None,
secondary_coord=None,
third_coord=None,
slit=None,
vmnx=None,
extra_text=None,
outfile=None):
"""
Basic method to generate a Finder chart figure
Args:
image (np.ndarray):
Image for the finder
wcs (astropy.wcs.WCS):
WCS solution
title (str):
Title; typically the name of the primary source
flip_ra (bool, default False):
Flip the RA (x-axis). Useful for southern hemisphere finders.
flip_dec (bool, default False):
Flip the Dec (y-axis). Useful for southern hemisphere finders.
log_stretch (bool, optional):
Use a log stretch for the image display
cutout (tuple, optional):
SkyCoord (center coordinate) and Quantity (image angular size)
for a cutout from the input image.
primary_coord (astropy.coordinates.SkyCoord, optional):
If provided, place a mark in red at this coordinate
secondary_coord (astropy.coordinates.SkyCoord, optional):
If provided, place a mark in cyan at this coordinate
Assume it is an offset star (i.e. calculate offsets)
third_coord (astropy.coordinates.SkyCoord, optional):
If provided, place a mark in yellow at this coordinate
slit (tuple, optional):
If provided, places a rectangular slit with specified
coordinates, width, length, and position angle on image (from North to East)
[SkyCoords('21h44m25.255s',-40d54m00.1s', frame='icrs'), 1*u.arcsec, 10*u.arcsec, 20*u.deg]
vmnx (tuple, optional):
Used for scaling the image. Otherwise, the image
is analyzed for these values.
extra_text : str
Extra text to be added at the bottom of the Figure.
e.g. `DSS r-filter`
outfile (str, optional):
Filename for the figure. File type will be according
to the extension
Returns:
matplotlib.pyplot.figure, matplotlib.pyplot.Axis
"""
utils.set_mplrc()
plt.clf()
fig = plt.figure(figsize=(7, 8.5))
# fig.set_size_inches(7.5,10.5)
# Cutout?
if cutout is not None:
cutout_img = Cutout2D(image, cutout[0], cutout[1], wcs=wcs)
# Overwrite
wcs = cutout_img.wcs
image = cutout_img.data
# Axis
ax = fig.add_axes([0.10, 0.20, 0.75, 0.5], projection=wcs)
# Show
if log_stretch:
norm = mplnorm.ImageNormalize(stretch=LogStretch())
else:
norm = None
cimg = ax.imshow(image, cmap='Greys', norm=norm)
# Flip so RA increases to the left
if flip_ra is True:
ax.invert_xaxis()
if flip_dec is True:
ax.invert_yaxis()
# N/E
overlay = ax.get_coords_overlay('icrs')
overlay['ra'].set_ticks(color='white')
overlay['dec'].set_ticks(color='white')
overlay['ra'].set_axislabel('Right Ascension')
overlay['dec'].set_axislabel('Declination')
overlay.grid(color='green', linestyle='solid', alpha=0.5)
# Contrast
if vmnx is None:
mean, median, stddev = sigma_clipped_stats(
image
) # Also set clipping level and number of iterations here if necessary
#
vmnx = (median - stddev, median + 2 * stddev
) # sky level - 1 sigma and +2 sigma above sky level
print("Using vmnx = {} based on the image stats".format(vmnx))
cimg.set_clim(vmnx[0], vmnx[1])
# Add Primary
if primary_coord is not None:
c = SphericalCircle((primary_coord.ra, primary_coord.dec),
2 * units.arcsec,
transform=ax.get_transform('icrs'),
edgecolor='red',
facecolor='none')
ax.add_patch(c)
# Text
jname = ltu.name_from_coord(primary_coord)
ax.text(0.5,
1.34,
jname,
fontsize=28,
horizontalalignment='center',
transform=ax.transAxes)
# Secondary
if secondary_coord is not None:
c_S1 = SphericalCircle((secondary_coord.ra, secondary_coord.dec),
2 * units.arcsec,
transform=ax.get_transform('icrs'),
edgecolor='cyan',
facecolor='none')
ax.add_patch(c_S1)
# Text
jname = ltu.name_from_coord(secondary_coord)
ax.text(0.5,
1.24,
jname,
fontsize=22,
color='blue',
horizontalalignment='center',
transform=ax.transAxes)
# Print offsets
if primary_coord is not None:
sep = primary_coord.separation(secondary_coord).to('arcsec')
PA = primary_coord.position_angle(secondary_coord)
# RA/DEC
dec_off = np.cos(PA) * sep # arcsec
ra_off = np.sin(PA) * sep # arcsec (East is *higher* RA)
ax.text(
0.5,
1.22,
'Offset from Ref. Star (cyan) to Target (red):\nRA(to targ) = {:.2f} DEC(to targ) = {:.2f}'
.format(-1 * ra_off.to('arcsec'), -1 * dec_off.to('arcsec')),
fontsize=15,
horizontalalignment='center',
transform=ax.transAxes,
color='blue',
va='top')
# Add tertiary
if third_coord is not None:
c = SphericalCircle((third_coord.ra, third_coord.dec),
2 * units.arcsec,
transform=ax.get_transform('icrs'),
edgecolor='yellow',
facecolor='none')
ax.add_patch(c)
# Slit
if ((slit is not None) and (flag_photu is True)):
# List of values - [coodinates, width, length, PA],
# e.g. [SkyCoords('21h44m25.255s',-40d54m00.1s', frame='icrs'), 1*u.arcsec, 10*u.arcsec, 20*u.deg]
slit_coords, width, length, pa = slit
pa_deg = pa.to('deg').value
aper = SkyRectangularAperture(
positions=slit_coords, w=length, h=width, theta=pa
) # For theta=0, width goes North-South, which is slit length
apermap = aper.to_pixel(wcs)
apermap.plot(color='purple', lw=1)
plt.text(0.5,
-0.1,
'Slit PA={} deg'.format(pa_deg),
color='purple',
fontsize=15,
ha='center',
va='top',
transform=ax.transAxes)
if ((slit is not None) and (flag_photu is False)):
raise IOError('Slit cannot be placed without photutils package')
# Title
ax.text(0.5,
1.44,
title,
fontsize=32,
horizontalalignment='center',
transform=ax.transAxes)
# Extra text
if extra_text is not None:
ax.text(-0.1,
-0.25,
extra_text,
fontsize=20,
horizontalalignment='left',
transform=ax.transAxes)
# Sources
# Labels
#ax.set_xlabel(r'\textbf{DEC (EAST direction)}')
#ax.set_ylabel(r'\textbf{RA (SOUTH direction)}')
if outfile is not None:
plt.savefig(outfile)
plt.close()
else:
plt.show()
# Return
return fig, ax
def sub_sfms(ax_M, galaxies, clrs, markers):
"""
Generate a SF vs. M* plot on top of PRIMUS galaxies
Args:
ax_M (matplotlib.axis):
galaxies (list):
List of FRB.galaxies.frbgalaxy.FRBGalaxy objects
clrs (list):
List of matplotlib colors
markers (list):
List of matplotlib marker types
"""
utils.set_mplrc()
# Load up
primus_zcat = Table.read(
os.path.join(primus_path, 'PRIMUS_2013_zcat_v1.fits.gz'))
primus_mass = Table.read(
os.path.join(primus_path, 'PRIMUS_2014_mass_v1.fits.gz'))
gdz = (primus_zcat['Z'] > 0.2) & (primus_zcat['Z'] < 0.4)
gd_mag = primus_zcat['SDSS_ABSMAG'][:, 0] != 0.
good_mass = primus_mass['ISGOOD'] == 1
# PRIMUS
# Photometry
gd_color = gdz & gd_mag
u_r = primus_zcat['SDSS_ABSMAG'][gd_color,
0] - primus_zcat['SDSS_ABSMAG'][gd_color,
2]
rmag = primus_zcat['SDSS_ABSMAG'][gd_color, 2]
# Mass/SFR
gd_msfr = good_mass & gdz
mass = primus_mass['MASS'][gd_msfr]
sfr = primus_mass['SFR'][gd_msfr]
# Plot
ms = 22.
# Histogram
xbins = 50
ybins = 50
counts, xedges, yedges = np.histogram2d(mass, sfr, bins=(xbins, ybins))
#cm = plt.get_cmap('Reds')
cm = plt.get_cmap('Greys')
# SF
mplt = ax_M.pcolormesh(xedges, yedges, counts.transpose(), cmap=cm)
# Relation
logm_star = np.linspace(8, 12)
logsfr = lambda logm_star: -0.49 + 0.65 * (logm_star - 10) + 1.07 * (0.35 -
0.1)
ax_M.plot(logm_star, logsfr(logm_star), "k--",
lw=3) #, label="Moustakas et al 2013")
# Galaxies
for kk, galaxy in enumerate(galaxies):
# M*
if 'Mstar' in galaxy.derived.keys():
logM, sig_logM = utils.log_me(galaxy.derived['Mstar'],
galaxy.derived['Mstar_err'])
elif 'Mstar_spec' in galaxy.derived.keys():
logM, sig_logM = np.log10(galaxy.derived['Mstar_spec']), 0.3
else:
continue
# SFR
if 'SFR_nebular_err' in galaxy.derived.keys():
logS, sig_logS = utils.log_me(galaxy.derived['SFR_nebular'],
galaxy.derived['SFR_nebular_err'])
else:
logS, sig_logS = utils.log_me(galaxy.derived['SFR_nebular'],
0.3 * galaxy.derived['SFR_nebular'])
# Plot
ax_M.errorbar([logM], [logS],
xerr=sig_logM,
yerr=sig_logS,
color=clrs[kk],
marker=markers[kk],
markersize="12",
capsize=3,
label=galaxy.name)
if sig_logS is None:
# Down arrow
plt.arrow(logM,
logS,
0.,
-0.2,
fc=clrs[kk],
ec=clrs[kk],
head_width=0.02 * 4,
head_length=0.05 * 2)
ax_M.annotate(r"\textbf{Star forming}", (8.5, 0.8), fontsize=13.)
ax_M.annotate(r"\textbf{Quiescent}", (11, -0.9), fontsize=13.)
ax_M.set_xlabel("$\log \, (M_*/M_\odot)$")
ax_M.set_ylabel("$\log \, SFR (M_\odot$/yr)")
ax_M.legend(loc='lower left')
ax_M.set_xlim(7.5, 11.8)
ax_M.set_ylim(-2.5, 1.2)
def generate(image,
wcs,
title,
log_stretch=False,
cutout=None,
primary_coord=None,
secondary_coord=None,
third_coord=None,
vmnx=None,
outfile=None):
"""
Basic method to generate a Finder chart figure
Args:
image (np.ndarray):
Image for the finder
wcs (astropy.wcs.WCS):
WCS solution
title (str):
TItle; typically the name of the primry source
log_stretch (bool, optional):
Use a log stretch for the image display
cutout (tuple, optional):
SkyCoord (center coordinate) and Quantity (image angular size)
for a cutout from the input image.
primary_coord (astropy.coordinates.SkyCoord, optional):
If provided, place a mark in red at this coordinate
secondary_coord (astropy.coordinates.SkyCoord, optional):
If provided, place a mark in cyan at this coordinate
Assume it is an offset star (i.e. calculate offsets)
third_coord (astropy.coordinates.SkyCoord, optional):
If provided, place a mark in yellow at this coordinate
vmnx (tuple, optional):
Used for scaling the image. Otherwise, the image
is analyzed for these values.
outfile (str, optional):
Filename for the figure. File type will be according
to the extension
Returns:
matplotlib.pyplot.figure, matplotlib.pyplot.Axis
"""
utils.set_mplrc()
plt.clf()
fig = plt.figure(dpi=600)
fig.set_size_inches(7.5, 10.5)
# Cutout?
if cutout is not None:
cutout_img = Cutout2D(image, cutout[0], cutout[1], wcs=wcs)
# Overwrite
wcs = cutout_img.wcs
image = cutout_img.data
# Axis
ax = fig.add_axes([0.10, 0.20, 0.80, 0.5], projection=wcs)
# Show
if log_stretch:
norm = mplnorm.ImageNormalize(stretch=LogStretch())
else:
norm = None
cimg = ax.imshow(image, cmap='Greys', norm=norm)
# Flip so RA increases to the left
ax.invert_xaxis()
# N/E
overlay = ax.get_coords_overlay('icrs')
overlay['ra'].set_ticks(color='white')
overlay['dec'].set_ticks(color='white')
overlay['ra'].set_axislabel('Right Ascension')
overlay['dec'].set_axislabel('Declination')
overlay.grid(color='green', linestyle='solid', alpha=0.5)
# Contrast
if vmnx is None:
mean, median, stddev = sigma_clipped_stats(
image
) # Also set clipping level and number of iterations here if necessary
#
vmnx = (median - stddev, median + 2 * stddev
) # sky level - 1 sigma and +2 sigma above sky level
print("Using vmnx = {} based on the image stats".format(vmnx))
cimg.set_clim(vmnx[0], vmnx[1])
# Add Primary
if primary_coord is not None:
c = SphericalCircle((primary_coord.ra, primary_coord.dec),
2 * units.arcsec,
transform=ax.get_transform('icrs'),
edgecolor='red',
facecolor='none')
ax.add_patch(c)
# Text
jname = ltu.name_from_coord(primary_coord)
ax.text(0.5,
1.34,
jname,
fontsize=28,
horizontalalignment='center',
transform=ax.transAxes)
# Secondary
if secondary_coord is not None:
c_S1 = SphericalCircle((secondary_coord.ra, secondary_coord.dec),
2 * units.arcsec,
transform=ax.get_transform('icrs'),
edgecolor='cyan',
facecolor='none')
ax.add_patch(c_S1)
# Text
jname = ltu.name_from_coord(secondary_coord)
ax.text(0.5,
1.24,
jname,
fontsize=22,
color='blue',
horizontalalignment='center',
transform=ax.transAxes)
# Print offsets
if primary_coord is not None:
sep = primary_coord.separation(secondary_coord).to('arcsec')
PA = primary_coord.position_angle(secondary_coord)
# RA/DEC
dec_off = np.cos(PA) * sep # arcsec
ra_off = np.sin(PA) * sep # arcsec (East is *higher* RA)
ax.text(0.5,
1.14,
'RA(to targ) = {:.2f} DEC(to targ) = {:.2f}'.format(
-1 * ra_off.to('arcsec'), -1 * dec_off.to('arcsec')),
fontsize=18,
horizontalalignment='center',
transform=ax.transAxes)
# Add tertiary
if third_coord is not None:
c = SphericalCircle((third_coord.ra, third_coord.dec),
2 * units.arcsec,
transform=ax.get_transform('icrs'),
edgecolor='yellow',
facecolor='none')
ax.add_patch(c)
# Slit?
'''
if slit is not None:
r = Rectangle((primary_coord.ra.value, primary_coord.dec.value),
slit[0]/3600., slit[1]/3600., angle=360-slit[2],
transform=ax.get_transform('icrs'),
facecolor='none', edgecolor='red')
ax.add_patch(r)
'''
# Title
ax.text(0.5,
1.44,
title,
fontsize=32,
horizontalalignment='center',
transform=ax.transAxes)
# Sources
# Labels
#ax.set_xlabel(r'\textbf{DEC (EAST direction)}')
#ax.set_ylabel(r'\textbf{RA (SOUTH direction)}')
if outfile is not None:
plt.savefig(outfile)
plt.close()
else:
plt.show()
# Return
return fig, ax
def fig_cosmic(frbs, clrs=None, outfile=None, multi_model=False, no_curves=False,
widen=False, show_nuisance=False, ax=None,
show_sigmaDM=False, cl=(16,84), beta=3., gold_only=True, gold_frbs=None):
"""
Args:
frbs (list):
list of FRB objects
clrs (list, optional):
outfile (str, optional):
multi_model (deprecated):
no_curves (bool, optional):
If True, just show the data
widen (bool, optional):
If True, make the plot wide
show_nuisance (bool, optional):
if True, add a label giving the Nuiscance value
show_sigmaDM (bool, optional):
If True, show a model estimate of the scatter in the DM relation
cl (tuple, optional):
Confidence limits for the scatter
beta (float, optional):
Parameter to the DM scatter estimation
gold_only (bool, optional):
If True, limit to the gold standard sample
gold_frbs (list, optional):
List of gold standard FRBs
ax (matplotlib.Axis, optional):
Use this axis instead of creating one
Returns:
"""
# Init
if gold_frbs is None:
gold_frbs = cosmic.gold_frbs
# Plotting
ff_utils.set_mplrc()
bias_clr = 'darkgray'
# Start the plot
if ax is None:
if widen:
fig = plt.figure(figsize=(12, 8))
else:
fig = plt.figure(figsize=(8, 8))
plt.clf()
ax = plt.gca()
# DM_cosmic from cosmology
zmax = 0.75
DM_cosmic, zeval = frb_igm.average_DM(zmax, cumul=True)
DMc_spl = IUS(zeval, DM_cosmic)
if not no_curves:
#ax.plot(zeval, DM_cosmic, 'k-', label=r'DM$_{\rm cosmic} (z) \;\; [\rm Planck15]$')
ax.plot(zeval, DM_cosmic, 'k-', label='Planck15')
if multi_model:
# Change Omega_b
cosmo_highOb = FlatLambdaCDM(Ob0=Planck15.Ob0*1.2, Om0=Planck15.Om0, H0=Planck15.H0)
DM_cosmic_high, zeval_high = frb_igm.average_DM(zmax, cumul=True, cosmo=cosmo_highOb)
ax.plot(zeval_high, DM_cosmic_high, '--', color='gray', label=r'DM$_{\rm cosmic} (z) \;\; [1.2 \times \Omega_b]$')
# Change H0
cosmo_lowH0 = FlatLambdaCDM(Ob0=Planck15.Ob0, Om0=Planck15.Om0, H0=Planck15.H0/1.2)
DM_cosmic_lowH0, zeval_lowH0 = frb_igm.average_DM(zmax, cumul=True, cosmo=cosmo_lowH0)
ax.plot(zeval_lowH0, DM_cosmic_lowH0, ':', color='gray', label=r'DM$_{\rm cosmic} (z) \;\; [H_0/1.2]$')
if show_sigmaDM:
#f_C0 = frb_cosmology.build_C0_spline()
f_C0_3 = cosmic.grab_C0_spline(beta=3.)
# Updated
F = 0.2
nstep=50
sigma_DM = F * zeval**(-0.5) #* DM_cosmic.value
sub_sigma_DM = sigma_DM[::nstep]
sub_z = zeval[::nstep]
sub_DM = DM_cosmic.value[::nstep]
# Loop me
sigmas, C0s, sigma_lo, sigma_hi = [], [], [], []
for kk, isigma in enumerate(sub_sigma_DM):
#res = frb_cosmology.minimize_scalar(frb_cosmology.deviate2, args=(f_C0, isigma))
#sigmas.append(res.x)
sigmas.append(isigma)
C0s.append(float(f_C0_3(isigma)))
# PDF
PDF = cosmic.DMcosmic_PDF(cosmic.Delta_values, C0s[-1], sigma=sigmas[-1], beta=beta)
cumsum = np.cumsum(PDF) / np.sum(PDF)
#if sub_DM[kk] > 200.:
# embed(header='131')
# DO it
DM = cosmic.Delta_values * sub_DM[kk]
sigma_lo.append(DM[np.argmin(np.abs(cumsum-cl[0]/100))])
sigma_hi.append(DM[np.argmin(np.abs(cumsum-cl[1]/100))])
# Plot
ax.fill_between(sub_z, sigma_lo, sigma_hi, # DM_cosmic.value-sigma_DM, DM_cosmic.value+sigma_DM,
color='gray', alpha=0.3)
# Do each FRB
DM_subs = []
for ifrb in frbs:
DM_sub = ifrb.DM - ifrb.DMISM
DM_subs.append(DM_sub.value)
DM_subs = np.array(DM_subs)
# chi2
DMs_MW_host = np.linspace(30., 100., 100)
zs = np.array([ifrb.z for ifrb in frbs])
DM_theory = DMc_spl(zs)
chi2 = np.zeros_like(DMs_MW_host)
for kk,DM_MW_host in enumerate(DMs_MW_host):
chi2[kk] = np.sum(((DM_subs-DM_MW_host)-DM_theory)**2)
imin = np.argmin(chi2)
DM_MW_host_chisq = DMs_MW_host[imin]
print("DM_nuisance = {}".format(DM_MW_host))
# MW + Host term
def DM_MW_host(z, min_chisq=False):
if min_chisq:
return DM_MW_host_chisq
else:
return 50. + 50./(1+z)
# Gold FRBs
for kk,ifrb in enumerate(frbs):
if ifrb.frb_name not in gold_frbs:
continue
if clrs is not None:
clr = clrs[kk]
else:
clr = None
ax.scatter([ifrb.z], [DM_subs[kk]-DM_MW_host(ifrb.z)],
label=ifrb.frb_name, marker='s', s=90, color=clr)
# ################################
# Other FRBs
s_other = 90
if not gold_only:
labeled = False
for kk, ifrb in enumerate(frbs):
if ifrb.frb_name in gold_frbs:
continue
if not labeled:
lbl = "Others"
labeled = True
else:
lbl = None
ax.scatter([ifrb.z], [ifrb.DM.value -
ifrb.DMISM.value - DM_MW_host(ifrb.z)],
label=lbl, marker='o', s=s_other, color=bias_clr)
legend = ax.legend(loc='upper left', scatterpoints=1, borderpad=0.2,
handletextpad=0.3, fontsize=19)
ax.set_xlim(0, 0.7)
ax.set_ylim(0, 1000.)
#ax.set_xlabel(r'$z_{\rm FRB}$', fontname='DejaVu Sans')
ax.set_xlabel(r'$z_{\rm FRB}$', fontname='DejaVu Sans')
ax.set_ylabel(r'$\rm DM_{cosmic} \; (pc \, cm^{-3})$', fontname='DejaVu Sans')
#
if show_nuisance:
ax.text(0.05, 0.60, r'$\rm DM_{MW,halo} + DM_{host} = $'+' {:02d} pc '.format(int(DM_MW_host))+r'cm$^{-3}$',
transform=ax.transAxes, fontsize=23, ha='left', color='black')
ff_utils.set_fontsize(ax, 23.)
# Layout and save
if outfile is not None:
plt.tight_layout(pad=0.2,h_pad=0.1,w_pad=0.1)
plt.savefig(outfile, dpi=400)
print('Wrote {:s}'.format(outfile))
plt.close()
else:
return ax