In [1]:
import numpy as np
import env
import catalog as Cat
import sham_hack as SHAM
import observables as Obvs
import AbundanceMatching as AM
In [75]:
import corner as DFM
In [2]:
import matplotlib as mpl
import matplotlib.pyplot as plt
mpl.rcParams['text.usetex'] = True
mpl.rcParams['font.family'] = 'serif'
mpl.rcParams['axes.linewidth'] = 1.5
mpl.rcParams['axes.xmargin'] = 1
mpl.rcParams['xtick.labelsize'] = 'x-large'
mpl.rcParams['xtick.major.size'] = 5
mpl.rcParams['xtick.major.width'] = 1.5
mpl.rcParams['ytick.labelsize'] = 'x-large'
mpl.rcParams['ytick.major.size'] = 5
mpl.rcParams['ytick.major.width'] = 1.5
mpl.rcParams['legend.frameon'] = False
%matplotlib inline
In [3]:
subs = Cat.SubhaloHistory(sigma_smhm=0.2, smf_source='li-march', nsnap_ancestor=15)
subcat = subs.Read()
In [106]:
mmaxlim = (subcat['snapshot15_m.max'] > 0) & (subcat['snapshot15_m.star'] > 0)
msham_z1 = subcat['snapshot15_m.star'][mmaxlim]
mhalo_z1 = subcat['snapshot15_halo.m'][mmaxlim]
mmax_z1 = subcat['snapshot15_m.max'][mmaxlim]
In [107]:
print mmax_z1.min(), mmax_z1.max()
print msham_z1.min(), msham_z1.max()
In [108]:
smhmr = Obvs.Smhmr()
mmid, _, sig_logm, cnts = smhmr.Calculate(mmax_z1, msham_z1)
In [109]:
fig = plt.figure()
sub = fig.add_subplot(111)
DFM.hist2d(mmax_z1, msham_z1, levels=[0.68, 0.95],
range=[[10., 15.],[6., 13.]], plot_datapoints=True, fill_contours=False, plot_density=True, ax=sub)
In [110]:
fig = plt.figure()
sub = fig.add_subplot(111)
sub.plot(mmid, sig_logm)
sub.set_xlim([10., mmax_z1.max()])
sub.set_ylim([0., 0.5])
Out[110]:
In [111]:
fig = plt.figure()
sub = fig.add_subplot(111)
z = 1.
MF = SHAM.SMFClass('li-march', z, 0.0, 0.7)
sub.plot(np.linspace(5., 13., 20), ([MF.numden(mm) for mm in np.linspace(6., 13., 20)]), ls='--')
sub.plot(np.linspace(5., 13., 20), ([MF.dndm(mm) for mm in np.linspace(6., 13., 20)]), ls=':')
sub.set_xlim([5., 13.])
sub.set_yscale('log')
sub.set_ylim([10**-5., 10**-1.5])
Out[111]:
In [112]:
m_arr = np.linspace(6.0, 13.0, 50)
af = AM.AbundanceFunction(m_arr, np.array([MF.dndm(mm) for mm in m_arr]), ext_range=(4., 13.), faint_end_first=True)
In [113]:
scatter = 0.2
remainder = af.deconvolute(scatter, 20)
x, nd = af.get_number_density_table()
plt.plot(x, remainder/nd)
plt.xlim([6., 13.])
plt.ylim([-0.5, 1.])
Out[113]:
In [114]:
nd_halos = AM.calc_number_densities(mmax_z1, 250./0.7)
In [115]:
catalog = af.match(nd_halos)
catalog_sc = af.match(nd_halos, 0.2)
In [116]:
mmid, _, sig_logm, cnts = smhmr.Calculate(mmax_z1, catalog)
fig = plt.figure()
sub = fig.add_subplot(111)
sub.plot(mmid, sig_logm)
sub.set_xlim([10., mmax_z1.max()])
sub.set_ylim([0., 0.5])
Out[116]:
In [117]:
fig = plt.figure()
sub = fig.add_subplot(111)
DFM.hist2d(mmax_z1, msham_z1, levels=[0.68, 0.95], color='C0',
range=[[10., 15.],[6., 13.]], plot_datapoints=True, fill_contours=False, plot_density=True, ax=sub)
DFM.hist2d(mmax_z1, catalog_sc, levels=[0.68, 0.95], color='C1',
range=[[10., 15.],[6., 13.]], plot_datapoints=True, fill_contours=False, plot_density=True, ax=sub)
In [120]:
fig = plt.figure()
sub = fig.add_subplot(111)
DFM.hist2d(mhalo_z1, msham_z1, levels=[0.68, 0.95], color='C0',
range=[[10., 15.],[6., 13.]], plot_datapoints=True, fill_contours=False, plot_density=True, ax=sub)
DFM.hist2d(mhalo_z1, catalog_sc, levels=[0.68, 0.95], color='C1',
range=[[10., 15.],[6., 13.]], plot_datapoints=True, fill_contours=False, plot_density=True, ax=sub)
In [121]:
isfin = np.isfinite(catalog_sc)
mmid, _, sig_logm, cnts = smhmr.Calculate(mmax_z1[isfin], catalog_sc[isfin])
fig = plt.figure()
sub = fig.add_subplot(111)
sub.plot(mmid, sig_logm)
sub.set_xlim([10., mmax_z1.max()])
sub.set_ylim([0., 0.5])
Out[121]:
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