ax = plt.subplot(111, projection=WCS(moment0.header))
im = ax.imshow(moment0_Kkm_s,
origin='lower',
interpolation='nearest',
norm=ImageNormalize(vmin=-0.001,
vmax=np.nanmax(moment0_Kkm_s),
stretch=AsinhStretch()))
ax.set_ylabel("DEC (J2000)")
ax.set_xlabel("RA (J2000)")
cbar = plt.colorbar(im)
cbar.set_label(r"Intensity (K km s$^{-1}$)")
# raw_input("?")
plt.savefig(paper1_figures_path("zeroth_moment_map_14B088.pdf"))
plt.savefig(paper1_figures_path("zeroth_moment_map_14B088.png"))
p.clf()
moment1 = fits.open(fourteenB_HI_data_path(moment1_name))[0]
ax = plt.subplot(111, projection=WCS(moment1.header))
im = ax.imshow(moment1.data / 1000.,
origin='lower', vmin=-300, vmax=-70,
interpolation='nearest', cmap='viridis')
ax.set_ylabel("DEC (J2000)")
ax.set_xlabel("RA (J2000)")
cbar = plt.colorbar(im)
rs, sd, sd_sigma = radial_profile(gal, lwidth_co, max_rad=6 * u.kpc,
dr=dr)
sd = sd.to(u.km / u.s)
sd_sigma = sd_sigma.to(u.km / u.s)
p.errorbar(rs.value, sd.value,
yerr=sd_sigma.value, fmt="-", color="b",
drawstyle='steps-mid')
p.xlabel("R (kpc)")
p.ylabel("CO Velocity Dispersion (km/s)")
p.grid()
p.draw()
p.savefig(paper1_figures_path("co_veldisp_profile_{}pc.pdf".format(dr.value)))
p.savefig(paper1_figures_path("co_veldisp_profile_{}pc.png".format(dr.value)))
p.close()
# raw_input("Next plot?")
# Create the North and South portions.
rs_n, sd_n, sd_sigma_n = \
radial_profile(gal, lwidth_co, max_rad=6 * u.kpc,
pa_bounds=Angle([0.5 * np.pi * u.rad,
-0.5 * np.pi * u.rad]))
sd_n = sd_n.to(u.km / u.s)
sd_sigma_n = sd_sigma_n.to(u.km / u.s)
rs_s, sd_s, sd_sigma_s = \
radial_profile(gal, lwidth_co, max_rad=6 * u.kpc,
pa_bounds=Angle([-0.5 * np.pi * u.rad,
# Beyond 8 kpc, noise is dominant. It may be some reflection of the
# warp, but I don't trust it right now.
rs, sd, sd_sigma = radial_profile(gal, lwidth, max_rad=8 * u.kpc)
sd = sd.to(u.km / u.s)
sd_sigma = sd_sigma.to(u.km / u.s)
p.errorbar(rs.value, sd.value,
yerr=sd_sigma.value, fmt="-", color="b",
drawstyle='steps-mid')
p.xlabel("R (kpc)")
p.ylabel("HI Velocity Dispersion (km/s)")
p.grid()
p.draw()
p.savefig(paper1_figures_path("hi_veldisp_profile.png"))
p.savefig(paper1_figures_path("hi_veldisp_profile.pdf"))
# raw_input("Next plot?")
p.clf()
# Create the North and South portions.
rs_n, sd_n, sd_sigma_n = \
radial_profile(gal, lwidth, max_rad=8 * u.kpc,
pa_bounds=Angle([0.5 * np.pi * u.rad,
-0.5 * np.pi * u.rad]))
sd_n = sd_n.to(u.km / u.s)
sd_sigma_n = sd_sigma_n.to(u.km / u.s)
rs_s, sd_s, sd_sigma_s = \
radial_profile(gal, lwidth, max_rad=8 * u.kpc,
pa_bounds=Angle([-0.5 * np.pi * u.rad,
p.ioff()
# Show the total radial profile VLA and Arecibo
p.errorbar(rs.value, sd.value / scale_factor,
yerr=sd_sigma.value / scale_factor, fmt="-", color="b",
label="VLA", drawstyle='steps-mid')
p.plot(rs_arec.value, sd_arec.value, "g--", drawstyle='steps-mid',
label="Arecibo")
# p.errorbar(rs_arec.value, sd_arec.value, yerr=sd_sigma_arec.value,
# fmt="o--", color="g", label="Arecibo", drawstyle='steps-mid')
p.ylabel(r"$\Sigma$ (M$_{\odot}$ pc$^{-2}$)")
p.xlabel(r"R (kpc)")
p.legend(loc='best')
p.grid("on")
p.savefig(paper1_figures_path("M33_Sigma_profile_w_Arecibo.pdf"))
p.savefig(paper1_figures_path("M33_Sigma_profile_w_Arecibo.png"))
p.clf()
# W/ archival VLA
p.errorbar(rs.value, sd.value / scale_factor,
yerr=sd_sigma.value / scale_factor, fmt="-", color="b",
label="VLA", drawstyle='steps-mid')
p.plot(rs_arec.value, sd_arec.value, "g--", drawstyle='steps-mid',
label="Arecibo")
p.errorbar(rs_arch.value, sd_arch.value, yerr=sd_sigma_arec.value,
color="r", fmt="-.", drawstyle='steps-mid',
label="Archival VLA")
# p.errorbar(rs_arec.value, sd_arec.value, yerr=sd_sigma_arec.value,
# fmt="o--", color="g", label="Arecibo", drawstyle='steps-mid')
p.ylabel(r"$\Sigma$ (M$_{\odot}$ pc$^{-2}$)")
pa_bounds=Angle([-0.5 * np.pi * u.rad,
0.5 * np.pi * u.rad]),
max_rad=6 * u.kpc, dr=dr)
sd_n /= beam_eff
sd_sigma_n /= beam_eff
p.ioff()
p.errorbar(rs.value, np.log10(sd.value),
yerr=0.434 * sd_sigma.value / sd.value, fmt="-", color="b",
label=r"H$_2$", drawstyle='steps-mid')
p.ylabel(r" log $\Sigma$ (M$_{\odot}$ pc$^{-2}$)")
p.xlabel(r"R (kpc)")
# p.legend(loc='best')
p.grid("on")
p.savefig(paper1_figures_path("M33_Sigma_profile_co21_dr_{}pc.pdf".format(dr.value)))
p.savefig(paper1_figures_path("M33_Sigma_profile_co21_dr_{}pc.png".format(dr.value)))
p.close()
# p.show()
# Show the north vs south profiles
p.plot(rs.value, np.log10(sd.value), "k-.", drawstyle='steps-mid',
label="Total")
p.errorbar(rs_n.value, np.log10(sd_n.value),
yerr=0.434 * sd_sigma_n.value / sd_n.value, fmt="-", color="b",
label="North", drawstyle='steps-mid')
p.errorbar(rs_s.value, np.log10(sd_s.value),
yerr=0.434 * sd_sigma_s.value / sd_s.value, fmt="--", color="g",
label="South", drawstyle='steps-mid')
# p.plot(rs_n.value, sd_n.value, "bD-", label="North")
# VLA needs to be corrected by a 1.45 factor. See arecibo_match_props.py
total_spectrum = total_spectrum * u.Jy
total_spectrum_arecibo = total_spectrum_arecibo * u.Jy
p.plot(cube.spectral_axis.to(u.km / u.s).value, total_spectrum.value, 'b-',
label="VLA", drawstyle='steps-mid')
p.plot(arecibo.spectral_axis.to(u.km / u.s).value,
total_spectrum_arecibo.value, 'g--', label='Arecibo',
drawstyle='steps-mid')
p.ylabel("Total Intensity (Jy)")
p.xlabel("Velocity (km/s)")
p.legend(loc='upper left')
p.grid()
p.savefig(paper1_figures_path("total_profile.pdf"))
p.savefig(paper1_figures_path("total_profile.png"))
p.close()
# Now we can get the total mass
# Disregard outside this velocity range
vmax = -100 * u.km / u.s
vmin = -300 * u.km / u.s
spec_axis = cube.spectral_axis.to(u.km / u.s)
good_chans = np.logical_and(spec_axis <= vmax, spec_axis >= vmin)
# Same channel width in both
chan_width = \
mom1_wcs = wcs.WCS(mom1[0].header)
scale = wcs.utils.proj_plane_pixel_scales(mom1_wcs)[0]
# Distance scaling (1" ~ 4 pc). Conversion is deg to kpc
dist_scale = (np.pi / 180.) * gal.distance.to(u.kpc).value
# Plot the rotation curves
plt.errorbar(cent_tab["r"] * scale * dist_scale, cent_tab["Vt"],
yerr=cent_tab["eVt"], markersize=7,
label='Centroid', fmt='D-', alpha=0.8)
plt.errorbar(peak_tab["r"] * scale * dist_scale, peak_tab["Vt"],
yerr=peak_tab["eVt"], markersize=7,
label='Peak Velocity', fmt='o-', alpha=0.8)
plt.errorbar(gh_tab["r"] * scale * dist_scale, gh_tab["Vt"],
yerr=gh_tab["eVt"], markersize=7,
label='Gauss-Hermite Fit', fmt='+-', alpha=0.8)
plt.legend(loc='lower right')
plt.grid()
plt.ylabel(r"V$_{\rm circ}$ (km/s)")
plt.xlabel("Radius (kpc)")
plt.savefig(paper1_figures_path("HI_rotation_curve_comparisons.png"))
plt.savefig(paper1_figures_path("HI_rotation_curve_comparisons.pdf"))
plt.close()
