def get_stellar_mass_growth(galaxies_by_id, galaxy_num):
time = [time_slice[1]*1.e3 for time_slice in galaxies_by_id[galaxy_num]]
stellar_mass = [time_slice[3] for time_slice in galaxies_by_id[galaxy_num]]
stellar_mass_coefficients = galaxies_star_mass.get_func_coeffs(time, stellar_mass)
# print 'Stellar Mass Growth Coefficients 10**(a*t**7. + b*t**6. + c*t**5. + d*t**4. + e*t**3. + f*t**2. + g*t + h), t in Myr:'
# print stellar_mass_coefficients
stellar_mass_fitted = [10.**(galaxies_star_mass.poly_func(t, *tuple(stellar_mass_coefficients))) for t in time]
return time, stellar_mass, stellar_mass_coefficients, stellar_mass_fitted
def get_star_mass_coefficients(galaxies_by_id, galaxy_num):
#time orig. in Gyr; use Myr to not have to convert it in hermite code
time = [time_slice[1]*1.e3 for time_slice in galaxies_by_id[galaxy_num]]
stellar_mass = [time_slice[3] for time_slice in galaxies_by_id[galaxy_num]]
popt = galaxies_star_mass.get_func_coeffs(time, stellar_mass)
stellar_mass_fitted = [10.**(galaxies_star_mass.poly_func(t, *tuple(popt))) for t in time]
galaxies_star_mass.plot_stellar_mass(time, galaxy_num, stellar_mass, stellar_mass_fitted)
plt.show()
return popt
def run():
mpl.rcParams.update({'font.size': 15})
plt.rc('text', usetex=True)
plt.rc('font', family='Computer Modern Sans serif')
H0 = Constants.H0
WM = Constants.WM
WV = Constants.WV
# smbh_cluster = get_clusters.process_smbh_cluster(H0, WM, WV)
smbh_cluster = get_clusters.get_pickled_file('smbh_cluster.pkl')
smbh_by_id = analyze_clusters.get_smbh_by_id(smbh_cluster)
# galaxies_cluster = get_clusters.process_galaxies_cluster(H0, WM, WV)
galaxies_cluster_no_bad_z = get_clusters.get_pickled_file('galaxies_cluster_no_bad_z.pkl')
galaxies_by_id = analyze_clusters.get_galaxies_by_id(galaxies_cluster_no_bad_z)
galaxies_masses, final_masses = analyze_clusters.get_galaxies_masses(galaxies_by_id)
for galaxy_num in ['1', '65', '149', '187', '217']:
# galaxy_num = '187'
smbh_mass = np.array(analyze_clusters.get_cbh_accreted_plus_seed_mass(smbh_by_id, galaxy_num))
popt, smbh_mass_fitted = curve_fit_central_bh_masses(galaxy_num, smbh_mass)
smbh_mass_fitted = np.array(smbh_mass_fitted)
galaxy_mass_v_time = zip(galaxies_masses[galaxy_num][1], galaxies_masses[galaxy_num][2])
galaxy_mass_v_time = np.array(map(list, galaxy_mass_v_time))
popt_galaxy_mass = analyze_clusters.curve_fit_any_galaxy_mass(galaxies_masses, galaxy_num)
ydata_est = [analyze_clusters.poly_func(x, *tuple(popt_galaxy_mass)) for x in galaxies_masses[galaxy_num][1]]
galaxies_mass_fitted = [galaxies_masses[galaxy_num][1], [10**y for y in ydata_est]]
galaxies_mass_fitted = np.array(galaxies_mass_fitted)
stellar_mass = analyze_clusters.get_galaxy_stellar_mass(galaxies_by_id, galaxy_num)
stellar_mass_v_time = zip(galaxies_masses[galaxy_num][1], stellar_mass)
stellar_mass_v_time = np.array(map(list, stellar_mass_v_time))
# print galaxies_by_id[galaxy_num]
# print galaxy_mass_v_time, '\n'
# print stellar_mass_v_time, '\n'
# print smbh_mass
plt.figure()
plt.semilogy(galaxy_mass_v_time[:,0], galaxy_mass_v_time[:,1], 'b', lw=3.5, alpha=0.5, label='Galaxy Mass')
plt.semilogy(galaxies_mass_fitted[0,:], galaxies_mass_fitted[1,:], 'b--', lw=3.5, alpha=0.5)
# plt.ylabel('Mass [M$_\odot$]')
plt.ylabel(r'$M_{BH} [M_\odot]$')
plt.semilogy(stellar_mass_v_time[:,0], stellar_mass_v_time[:,1], 'g', lw=2., alpha=0.5, label='Stellar Mass')
popt_star_mass = galaxies_star_mass.get_func_coeffs(stellar_mass_v_time[:,0]*1.e3, stellar_mass_v_time[:,1])
stellar_mass_fitted = zip(stellar_mass_v_time[:,0]*1.e3,
[10.**(galaxies_star_mass.poly_func(t, *tuple(popt_star_mass))) for t in
stellar_mass_v_time[:,0]*1.e3])
stellar_mass_fitted = np.array(stellar_mass_fitted)
plt.semilogy(stellar_mass_fitted[:,0]/1.e3, stellar_mass_fitted[:,1], 'g--', lw=2., alpha=0.5)
print(galaxy_num, smbh_mass[:,1])
plt.semilogy(smbh_mass[:,0], smbh_mass[:,1], 'r', lw=0.5, alpha=1., label='Central BH Mass')
plt.semilogy(smbh_mass_fitted[0,:], smbh_mass_fitted[1,:], 'r--', lw=1., alpha=0.5)
plt.xticks(np.arange(0., math.ceil(max(galaxy_mass_v_time[:,0]))+1., 1.0))
plt.xlabel('Time [Gyr]')
plt.xticks(np.arange(0, 16, 2))
# plt.xlim([0, 14])
plt.ylim([10.**4, 10.**15])
plt.tight_layout()
plt.legend(loc='lower right')
plt.savefig(os.path.join(plots_folder, 'Masses_plot_galaxy_%s.png' % (galaxy_num)))
# plt.show()
plt.close()
# print galaxies_by_id[galaxy_num]
# galaxy_1 = [line for line in galaxies_cluster if line[2]==1]
# black_holes = [time_slice[-1] for time_slice in galaxy_1 if time_slice[0]<=0.0][0]
# print black_holes
# analyze_clusters.plot_galaxies_all_masses(galaxies_masses)
'''
top_masses = 3
galaxies_max_mass = analyze_clusters.get_most_massive_galaxies(galaxies_masses, final_masses, top_masses)
# print galaxies_max_mass
F1 = open(os.path.join(get_clusters.cluster_folder, ''.join([str(top_masses), '_max_mass_galaxies.pkl'])), 'wb')
pickle.dump(galaxies_max_mass, F1)
F1.close()
# analyze_clusters.plot_max_galaxies_masses(galaxies_max_mass)
popt_galaxies_masses, galaxies_max_mass_fitted = analyze_clusters.curve_fit_most_massive_galaxies(galaxies_max_mass)
print popt_galaxies_masses
F = open(os.path.join(get_clusters.cluster_folder,
''.join([str(top_masses), '_max_mass_galaxies_fitted.pkl'])), 'wb')
pickle.dump(galaxies_max_mass_fitted, F)
F.close()
####################################################
f = open(os.path.join(os.path.expanduser('~'), 'Dropbox', 'Columbia', 'Ostriker', 'Cannibalism', 'hermite',
'galaxy_mass.txt'), 'rb')
time_mass = f.readlines()
time = []
mass = []
for line in time_mass:
time.append(float(line.split()[0]))
mass.append(float(line.split()[1]))
time = np.array(time)
garbage = []
mass = np.array(mass)
galaxies_max_mass_fitted['65'] = [time, garbage, mass]
analyze_clusters.plot_max_masses_galaxies_orig_and_fitted(galaxies_max_mass, galaxies_max_mass_fitted, top_masses)
'''
fit_and_plot_central_bh_masses(smbh_cluster, galaxies_cluster_no_bad_z)
