plt.savefig(osjoin(fig_path, "sigma_HI_vs_H2_w_fit.png"))
plt.savefig(osjoin(fig_path, "sigma_HI_vs_H2_w_fit.pdf"))
plt.close()
# print("Slope: {0} {1}".format(slope, slope_ci))
# print("Intercept: {0} {1}".format(inter, inter_cis))
print("Ratio Slope: {0} {1}".format(slope_ratio, slope_ratio_ci))
# Ratio Slope: 0.563181915083 [ 0.5621998 0.56414808]
print("Added stddev: {0} {1}".format(add_stddev_ratio, add_stddev_ratio_ci))
# Added stddev: 520.947992994 [ 514.89901222 527.00225878]
# Make a corner plot version
twocolumn_figure()
# hist2d(tab['sigma_HI'][good_pts] / 1000.,
# np.array(tab['sigma_CO'])[good_pts] / 1000., bins=13,
# data_kwargs={"alpha": 0.5})
data = np.vstack(
[tab['sigma_HI'][good_pts] / 1000., tab['sigma_CO'][good_pts] / 1000.])
fig = corner(data.T,
bins=13,
data_kwargs={'alpha': 0.5},
labels=[r"$\sigma_{\rm HI}$ (km/s)", r"$\sigma_{\rm CO}$ (km/s)"],
quantiles=[0.15, 0.5, 0.85])
axs = fig.get_axes()
line1 = axs[2].plot([4, 12], [4. * slope_ratio, 12. * slope_ratio],
zoom_slice = (slice(140, -140), slice(160, -160))
# Convert to K km s and correct for disk inclination.
moment0_Kkm_s = beam.jtok(hi_freq).value * (moment0.data / 1000.) * cosinc
moment0_coldens = moment0_Kkm_s[zoom_slice] * hi_coldens_Kkms.value
pixscale = np.sqrt(proj_plane_pixel_area(moment0_wcs))
# Use the reprojected version
co_moment0 = fits.open(
iram_co21_14B088_data_path("m33.co21_iram.14B-088_HI.mom0.fits"))[0]
co_noise_map = fits.open(
iram_co21_14B088_data_path("m33.rms.14B-088_HI.fits"))[0]
twocolumn_figure(fig_ratio=0.95, font_scale=1.2)
ax = plt.subplot(111, projection=moment0_wcs)
im = ax.imshow(
moment0_coldens,
cmap='binary',
origin='lower',
interpolation='nearest',
alpha=0.85,
)
# norm=ImageNormalize(vmin=-0.001,
# vmax=np.nanmax(moment0_coldens),
# stretch=AsinhStretch()))
ax.set_ylabel("DEC (J2000)")
ax.set_xlabel("RA (J2000)")
lon = ax.coords[0]