# workaround for new regions API
arbitrary_wcs = wcs.WCS(
fits.getheader(
paths.Fpath(
'merge/continuum/SgrB2_selfcal_full_TCTE7m_selfcal5_ampphase_taylorterms_multiscale_deeper_mask2.5mJy.image.tt0.pbcor.fits'
)))
core_phot_tbl = Table.read(paths.tpath("continuum_photometry_withSIMBAD.ipac"),
format='ascii.ipac')
core_phot_tbl.add_column(
Column(name='radius', data=np.zeros(len(core_phot_tbl)) + np.nan))
# measured from core_flux_distributions
core_powerlaw_index = 1.94
kroupa = imf.Kroupa()
o_mmin = 8
hii_cutoff = 20
mmax = 150
over8fraction150 = (kroupa.m_integrate(o_mmin, mmax)[0] /
kroupa.m_integrate(kroupa.mmin, mmax)[0])
x = np.linspace(o_mmin, mmax, 50000)
y = kroupa(x)
over8mean150 = (x * y).sum() / y.sum()
print("150mmax, >8 fraction: {0}, mean = {1}".format(over8fraction150,
over8mean150))
mmax = 200
over8fraction = (kroupa.m_integrate(o_mmin, mmax)[0] /
pl.figure(3).clf()
pl.loglog(list(map(float, max_masses.keys())),
max_masses.values(),
'.',
alpha=0.1)
pl.xlabel("Cluster Mass")
pl.ylabel("Maximum stellar mass")
pl.savefig(f"maxmass_vs_clustermass_{stop_crit}.png",
bbox_inches='tight',
dpi=200)
pl.savefig(f"maxmass_vs_clustermass_{stop_crit}.pdf", bbox_inches='tight')
m_to_ls = []
slopes = np.linspace(1.7, 2.9, 20)
for slope in ProgressBar(slopes):
Kroupa = imf.Kroupa(p3=slope)
cluster = imf.make_cluster(1e5,
Kroupa,
mmax=120,
silent=True,
stop_criterion=stop_crit)
lum = imf.lum_of_cluster(cluster)
m_to_l = 1e5 / 10**lum
m_to_ls.append(m_to_l)
pl.figure(4).clf()
pl.plot(slopes, m_to_ls)
pl.xlabel("Upper-end power-law slope $\\alpha$")
pl.ylabel("Mass-to-light ratio [M$_\odot$/L$_\odot$]")
ax = pl.gca()
tw = ax.twinx()