def integrated_u_merger_graphs2():
#step, mass = 20, [1e9, 1e10, 1e11]
step, mass = 20, [1e4, 1e6, 1e8, 1e10, 1e11]
mass_ratio = [10**(i / step) for i in range(-4 * step, 0)]
legend = ['M = 10^{}'.format(str(int(math.log10(i)))) for i in mass]
for z in [0.1, 1, 2]:
mergers = []
for m in mass:
mergers.append([])
for u in mass_ratio:
mergers[-1].append(
hmc.integrated_u_merger_correction(m, u, 1, z))
graph.line(mergers,
x=mass_ratio,
info={
'xlog': True,
'ylog': True,
'ylim': [6e-4, 2e1],
'xlim': [1e-4, 1],
'xlabel': 'Min Mass Ratio',
'ylabel': 'Mergers / Gyr',
'comment': 'Z = {}'.format(z),
'legend': legend,
'legend_loc': 'upper right'
})
plt.show()
def integrated_u_merger_graphs():
step, us = 10, [4, 10, 100, 1000]
min_u = [1 / i for i in us]
legend = ['u >= 1 / {}'.format(str(i)) for i in us]
starts = [8, 8.2, 9.3, 10.3]
mass = [[10**(i / step) for i in range(int(j * step), int(12 * step))]
for j in starts]
for z in [0.1, 1, 2]:
mergers = []
for k, u in enumerate(min_u):
mergers.append([])
for i in mass[k]:
mergers[-1].append(
hmc.integrated_u_merger_correction(i, u, 1, z))
graph.line(mergers,
x=mass,
info={
'xlog': True,
'ylog': True,
'ylim': [3e-3, 2e1],
'xlim': [6e7, 2e12],
'xlabel': 'Mass',
'ylabel': 'Mergers / Gyr',
'comment': 'Z = {}'.format(z),
'legend': legend,
'legend_loc': 'upper left'
})
plt.show()
def plot_by_loc(sfh, loc, info={}):
to_plot = []
for i in range(len(sfh.names)):
if sfh.get_loc()[i] == loc or loc == 'all':
to_plot.append(sfh.mass[i])
#af1 = graph.line(to_plot, [10**i/1e9 for i in sfh.legend], dict({'title': loc}, **info))
af1 = graph.line(to_plot, [10**i/1e9 for i in sfh.legend], info)
graph.line([add_median(to_plot)], [10**i/1e9 for i in sfh.legend], params={'linewidth': 4}, af1=af1)
def plot_by_type(sfh, typ, info={}):
to_plot = []
for i in range(len(sfh.names)):
if sfh.g_type[i] == typ or typ == 'all':
to_plot.append(sfh.mass[i])
#af1 = graph.line(to_plot, [10**i/1e9 for i in sfh.legend], dict({'title': typ}, **info))
af1 = graph.line(to_plot, [10**i/1e9 for i in sfh.legend], info)
graph.line([add_median(to_plot)], [10**i/1e9 for i in sfh.legend], params={'linewidth': 4}, af1=af1)
def percent_dead(z0):
z1 = z_from_t(t_from_z(2) - 0.1)
print(z0, z1)
corr, x, uncorr = hmc.correct_smf(z0, z1)
print(corr, x, uncorr)
data = [1 - uncorr[i]/corr[i] for i in range(len(corr))]
graph.line([data], x, info={'ylog':True})
graph.line([corr, uncorr], x, info={'ylog':True})
plt.show()
def percent_dead(z0):
z1 = z_from_t(t_from_z(2) - 0.1)
print(z0, z1)
corr, x, uncorr = hmc.correct_smf(z0, z1)
print(corr, x, uncorr)
data = [1 - uncorr[i] / corr[i] for i in range(len(corr))]
graph.line([data], x, info={'ylog': True})
graph.line([corr, uncorr], x, info={'ylog': True})
plt.show()
def z_graphs():
step = 10
x = [i / step for i in range(30)]
y = [z_to_t.t_from_z(i) for i in x]
graph.line(
[y],
x=x,
info={
'ylabel': 'Time (Gyr)',
'xlabel': 'Z',
'title': 'Lookback Time vs Redshift'
})
plt.show()
def integrated_u_merger_graphs2():
#step, mass = 20, [1e9, 1e10, 1e11]
step, mass = 20, [1e4, 1e6, 1e8, 1e10, 1e11]
mass_ratio = [10**(i/step) for i in range(-4*step, 0)]
legend = ['M = 10^{}'.format(str(int(math.log10(i)))) for i in mass]
for z in [0.1, 1, 2]:
mergers = []
for m in mass:
mergers.append([])
for u in mass_ratio:
mergers[-1].append(hmc.integrated_u_merger_correction(m, u, 1, z))
graph.line(mergers, x=mass_ratio, info={'xlog': True, 'ylog': True, 'ylim': [6e-4, 2e1], 'xlim': [1e-4, 1], 'xlabel': 'Min Mass Ratio', 'ylabel': 'Mergers / Gyr', 'comment': 'Z = {}'.format(z), 'legend': legend, 'legend_loc': 'upper right'})
plt.show()
def merger_graphs():
step, us= 10, [4, 10, 100, 1000]
min_u = [1/i for i in us]
legend = ['u = 1 / {}'.format(str(i)) for i in us]
starts = [8, 8.6, 9.6, 10.6]
mass = [[10**(i/step) for i in range(int(j*step), int(12.3*step))] for j in starts]
for z in [0.1, 1, 2]:
mergers = []
for k, u in enumerate(min_u):
mergers.append([])
for i in mass[k]:
mergers[-1].append(hmc.merger_correction(i, u, z))
graph.line(mergers, x=mass, info={'xlog': True, 'ylog': True, 'ylim': [1e-2, 1e4], 'xlim': [6e7, 2e12], 'xlabel': 'Mass', 'ylabel': 'Mergers / Gyr', 'comment': 'Z = {}'.format(z), 'legend': legend, 'legend_loc': 'upper left'})
plt.show()
def z_graphs():
step = 10
x = [i/step for i in range(30)]
y = [z_to_t.t_from_z(i) for i in x]
graph.line([y], x=x, info={'ylabel': 'Time (Gyr)', 'xlabel': 'Z', 'title': 'Lookback Time vs Redshift'})
plt.show()
import sys
if __name__ == "__main__":
d, step = data.schechter(), 1
start, masses = [8 + i / step for i in range(3 * step)], []
# For a variety of start masses
# Find the number density at that mass at the highest Z (target)
# Find the masses that have the same number density at all other Z
# (binary search through all number densities until we find one that = the target. return the mass)
for start_mass in start:
masses.append([start_mass])
target = hs.param_double_schechter(start_mass,
d.double[0][-1]) # Just Z
for i in range(1, len(d.double)):
masses[-1].append(hs.binary_search(target, d.double[i][-1]))
print(masses)
print(d.z_avg)
info = {
'xlabel': r'$\mathregular{Z}$',
'ylabel': r'$\mathregular{log(M/M_\odot)}$',
'title': "Mass at constant number density over time",
'xlim': [0.35, 2.75],
'invert_xaxis': True
}
graph.line(masses, d.z_avg, info)
graph.cut_line([2.75, 9.5], [0.35, 8])
plt.show()
"""
import helpers.schechter as hs
import helpers.data as data
import helpers.graph as graph
import matplotlib.pyplot as plt
import sys
if __name__ == "__main__":
d, step = data.schechter(), 1
start, masses = [8 + i/step for i in range(3*step)], []
# For a variety of start masses
# Find the number density at that mass at the highest Z (target)
# Find the masses that have the same number density at all other Z
# (binary search through all number densities until we find one that = the target. return the mass)
for start_mass in start:
masses.append([start_mass])
target = hs.param_double_schechter(start_mass, d.double[0][-1]) # Just Z
for i in range(1, len(d.double)):
masses[-1].append(hs.binary_search(target, d.double[i][-1]))
print(masses)
print(d.z_avg)
info = {'xlabel': r'$\mathregular{Z}$', 'ylabel': r'$\mathregular{log(M/M_\odot)}$', 'title': "Mass at constant number density over time", 'xlim': [0.35, 2.75], 'invert_xaxis': True}
graph.line(masses, d.z_avg, info)
graph.cut_line([2.75, 9.5],[0.35, 8])
plt.show()
#!/usr/bin/env python3
'''
Finds the best approximation to the slow z_to_t formula
'''
from os import path
import sys
sys.path.append(path.dirname(path.dirname(path.abspath(__file__))))
import math
import helpers.z_to_t as z_to_t
import matplotlib.pyplot as plt
import helpers.graph as graph
if __name__ == '__main__':
zs = [i/10 for i in range(31)]
res = [[],[]]
for z in zs:
res[0].append(z_to_t.old_t_from_z(z))
res[1].append(z_to_t.t_from_z(z))
graph.line(res, x=zs)
ts = res[0]
res = [[], []]
for t in ts:
res[0].append(z_to_t.old_z_from_t(t))
res[1].append(z_to_t.z_from_t(t))
graph.line(res, x=ts)
plt.show()
info = {'xlabel': r'$\mathregular{log(M/M_\odot)}$', 'ylabel': r'$\mathregular{log(\phi / Mpc^3/dex)}$', 'legend': smf.z_range[-i:], 'xlim': [7.75, 12.25], 'ylim': [-5.75, -0.75]}
params = {'marker': 'x'}
graph.line(smf.smf[-i:], smf.mass, dict({'title': 'SMF'}, **info), params)
'''
# Plot raw data: total, quiescent, star forming
smf = data.smf()
info = {
'xlabel': r'$\mathregular{log(M/M_\odot)}$',
'ylabel': r'$\mathregular{log(\phi / Mpc^3/dex)}$',
'legend': smf.z_range,
'xlim': [7.75, 12.25],
'ylim': [-5.75, -0.75]
}
params = {'marker': 'x'}
graph.line(smf.smf, smf.mass, dict({'title': ''}, **info), params)
graph.line(smf.sf_smf, smf.mass, dict({'title': "Star Forming SMF"},
**info), params)
graph.line(smf.q_smf, smf.mass, dict({'title': "Quiescent SMF"}, **info),
params)
# Plot raw data: all 8 z bins on same graph
info = {
'legend': ['SMF', 'SF_SMF', 'Q_SMF'],
'xlim': [7.75, 12.25],
'ylim': [-5.75, -0.75],
'xlabel8': r'$\mathregular{log(M/M_\odot)}$',
'ylabel8': r'$\mathregular{log(\phi / Mpc^3/dex)}$'
}
params = {'marker': 'x'}
gs = graph.setup8(info)