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TPS.py
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# TPS: Triple population synthesis.
## computes the evolution of a population of given triples
## given any initial conditions (M, q, m, A, a, E, e, i, G, g, O, o).
## Options: --M_max upper limit for the inner primary mass [100 Msun]
## --M_min lower limit for the inner primary mass [0.1 Msun]
## --M_distr mass function option:
lib_inner_primary_mass_distr = {0: "Kroupa", #default
1: "Scalo",
2: "Miller & Scalo",
3: "Salpeter",
4: "Logarithmically flat",
5: "Eggleton",
6: "Kroupa for massive stars M>0.5 powerlaw with exp=-2.3",}
## --Q_max upper limit for the inner mass ratio [1.]
## --Q_min lower limit for the inner mass ratio [0.]
## --Q_distr inner mass ratio option:
lib_inner_mass_ratio_distr = {0: "Uniform distribution", #default
1: "Kroupa IMF", #draws from mass distribution instead of mass ratio distribution
2: "Galicher et al. 2016 powerlaw (M^-1.31)", } #draws from mass distribution instead of mass ratio distribution, appropriate for planets
## --q_max upper limit for the outer mass ratio [1.]
## --q_min lower limit for the mass of the outer star [0.]
## --q_distr outer mass ratio option:
lib_outer_mass_ratio_distr = {0: "Uniform distribution", #default
1: "Kroupa IMF", #draws from mass distribution instead of mass ratio distribution
2: "Galicher et al. 2016 powerlaw (M^-1.31)", } #draws from mass distribution instead of mass ratio distribution, appropriate for planets
## --A_max upper limit for the inner semi-major axis [5e6 RSun]
## --A_min lower limit for the inner semi-major axis [5]
## --A_distr inner semi-major axcis option:
lib_inner_semi_distr = {0: "Log Uniform distribution", #default
1: "Constant semi-major axis",
2: "Tokovinin lognormal mu = 10^5d, sigma = 2.3",
3: "Lognormal mu = 10^3.5d, sigma = 2.3",
4: "Rizzuto Lognormal mu = 10^0.95 AU, sigma = 1.35",
5: "Sana et al. 2012",
6: "flat distribution",
7: "Galicher et al. 2016 powerlaw (a^-0.61)",} #appropriate for planets
## --a_max upper limit for the outer semi-major axis [5e6 RSun]
## --a_min lower limit for the outer semi-major axis [5 RSun]
## --a_distr outer semi-major axis option:
lib_outer_semi_distr = {0: "Log Uniform distribution", #default
1: "Constant semi-major axis",
2: "Tokovinin lognormal mu = 10^5d, sigma = 2.3",
3: "Lognormal mu = 10^3.5d, sigma = 2.3",
4: "Rizzuto Lognormal mu = 10^0.95 AU, sigma = 1.35",
5: "Sana et al. 2012",
6: "flat distribution",
7: "Galicher et al. 2016 powerlaw (a^-0.61)",} #appropriate for planets
## --E_max upper limit for the inner eccentricity [0.9]
## --E_min lower limit for the inner eccentricity [0.]
## --E_distr inner eccentricity option:
lib_inner_ecc_distr = {0: "Thermal", #default
1: "Constant eccentricity",
2: "Sana et al. 2012 e^-0.45", #-> close binaries
3: "Flat distribution",
4: "Powerlaw e^0.5",
5: "Bowler et al. 2020 Beta distribution",} #appropriate for planets
## --e_max upper limit for the outer eccentricity [0.9]
## --e_min lower limit for the outer eccentricity [0.]
## --e_distr outer eccentricity option:
lib_outer_ecc_distr = {0: "Thermal", #default
1: "Constant eccentricity",
2: "Sana et al. 2012 e^-0.45", #-> close binaries
3: "Flat distribution",
4: "Powerlaw e^0.5",
5: "Bowler et al. 2020 Beta distribution",} #appropriate for planets
## --i_max upper limit for the relative inclination [pi]
## --i_min lower limit for the relative inclination [0]
## --i_distr relative inclination option:
lib_incl_distr = {0: "Circular uniform distribution", #default
1: "Constant inclination",}
## --G_max upper limit for the inner argument of pericenter [pi]
## --G_min lower limit for the inner argument of pericenter [-pi]
## --G_distr inner argument of pericenter option: r
lib_inner_aop_distr = {0: "Uniform distribution", #default
1: "Constant argument of pericenter",}
## --g_max upper limit for the outer argument of pericenter [pi]
## --g_min lower limit for the outer argument of pericenter [-pi]
## --g_distr outer argument of pericenter option:
lib_outer_aop_distr = {0: "Uniform distribution", #default
1: "Constant argument of pericenter",}
## outer longitude of ascending nodes = inner - pi
## --O_max upper limit for the inner longitude of ascending node [pi]
## --O_min lower limit for the inner longitude of ascending node [-pi]
## --O_distr inner longitude of ascending node option:
lib_inner_loan_distr = {0: "Circular niform distribution",
1: "Constant longitude of ascending nodes",} #default
## -T or -t binary end time. [13500 Myr]
## -z metallicity of stars [0.02 Solar]
## -n total number of systems to be simulated. [1]
## -N number ID of first system. [0]
## --no_stop_at_mass_transfer stopping condition at mass transfer
## --no_stop_at_init_mass_transfer stopping condition at mass transfer at initialisation
## --no_stop_at_outer_mass_transfer stopping condition at mass transfer in outer binary
## --stop_at_stable_mass_transfer stopping condition at stable mass transfer
## --stop_at_eccentric_stable_mass_transfer stopping condition at eccentric stable mass transfer
## --stop_at_unstable_mass_transfer stopping condition at unstable mass transfer
## --stop_at_eccentric_unstable_mass_transfer stopping condition at eccentric unstable mass transfer
## --stop_at_no_CHE stopping condition if no chemically homogeneous evolution
## --no_stop_at_merger stopping condition at merger
## --no_stop_at_disintegrated stopping condition at disintegration
## --no_stop_at_inner_collision stopping condition at collision in inner binary
## --no_stop_at_outer_collision stopping condition at collision involving tertiary star
## --no_stop_at_dynamical_instability stopping condition at dynamical instability
## --stop_at_semisecular_regime stopping condition at semisecular regime
## --stop_at_SN stopping condition at supernova
lib_SN_kick_distr = {0: "No kick",
1: "Hobbs", #Hobbs, Lorimer, Lyne & Kramer 2005, 360, 974
2: "Arzoumanian", #Arzoumanian ea 2002, 568, 289
3: "Hansen", #Hansen & Phinney 1997, 291, 569
4: "Paczynski", #Paczynski 1990, 348, 485
5: "Verbunt", #Verbunt, Igoshev & Cator, 2017, 608, 57
} #default
lib_CE = { 0: "alpha-ce + alpha-dce",
1: "gamma-ce + alpha-dce",
2: "seba style; combination of gamma-ce, alpha-ce & alpha-dce",
}
#not implemented yet
## -s random seed
import TRES as TRES
from amuse.community.seba.interface import SeBa
from seculartriple_TPS.interface import SecularTriple
import sys
from amuse.units.optparse import OptionParser
from amuse.units import units, constants
from amuse.support.console import set_printing_strategy
import numpy as np
from scipy.interpolate import interp1d
from scipy.stats import beta as beta_distribution
from amuse.ic.kroupa import new_kroupa_mass_distribution
from amuse.ic.scalo import new_scalo_mass_distribution
from amuse.ic.millerscalo import new_miller_scalo_mass_distribution
from amuse.ic.salpeter import new_salpeter_mass_distribution
from amuse.ic.flatimf import new_flat_mass_distribution
from TRES_options import REPORT_TPS, \
REPORT_USER_WARNINGS_TPS, \
EXCLUDE_SSO, \
precision, min_mass, absolute_min_mass, absolute_max_mass
def flat_distr(lower, upper):
return np.random.uniform(lower, upper)
def log_flat_distr(lower, upper):
x= np.random.uniform(np.log10(lower), np.log10(upper))
return 10**x
def eggleton_mass_distr(lower_mass, upper_mass):
turnover_mass = 0.3|units.MSun
power = 0.85
y_max = (upper_mass/turnover_mass) **(1/power)
upper = y_max / (1+y_max)
y_min = (lower_mass/turnover_mass) **(1/power)
lower = y_min / (1+y_min)
x = np.random.uniform(lower, upper)
y=turnover_mass * (x/(1-x))**power
return turnover_mass * (x/(1-x))**power
def powerlaw_distr(m_min, m_max, slope):
if slope == -1 or slope == 0:
sys.exit('slope of powerlap distribution incorrect')
slope1 = slope + 1
factor = (pow(m_max / m_min, slope1) - 1.0 )
x = np.random.uniform(0,1)
return m_min * (1.0 + factor*x) ** (1.0 / slope1)
def beta_distr_SSOs(lower, upper, mass): # (Bowler et al. 2020)
min_mass_BD = 16 |units.MJupiter # brown dwarf boundary
if absolute_min_mass < mass <= min_mass_BD :
A, B = 30, 200 # for exoplanets
elif min_mass_BD < mass < min_mass :
A, B = 2.30, 1.65 # for brown dwarfs
else:
sys.exit('You may be using a SSOs distribution for a stellar object, exiting')
e_sample = beta_distribution.rvs( A, B)
if lower <= e_sample <= upper:
return e_sample
return beta_distr_SSOs(lower, upper, mass) # pick another sample within given bounds
class Generate_initial_triple:
#-------
#setup stellar system
def __init__(self, inner_primary_mass_max, inner_primary_mass_min,
inner_secondary_mass_max, inner_secondary_mass_min,
outer_mass_min, outer_mass_max,
inner_mass_ratio_max, inner_mass_ratio_min,
outer_mass_ratio_max, outer_mass_ratio_min,
inner_semi_max, inner_semi_min, outer_semi_max, outer_semi_min,
inner_semi_latus_rectum_min, outer_semi_latus_rectum_min,
inner_semi_latus_rectum_max, outer_semi_latus_rectum_max,
inner_ecc_max, inner_ecc_min, outer_ecc_max, outer_ecc_min,
incl_max, incl_min,
inner_aop_max, inner_aop_min, outer_aop_max, outer_aop_min,
inner_loan_max, inner_loan_min,
inner_primary_mass_distr, inner_mass_ratio_distr, outer_mass_ratio_distr,
inner_semi_distr, outer_semi_distr, inner_ecc_distr, outer_ecc_distr, incl_distr,
inner_aop_distr, outer_aop_distr, inner_loan_distr):
if inner_primary_mass_distr == 5:
mass_convergence = False
while mass_convergence == False:
mass_convergence = self.generate_mass_and_semi_eggleton(inner_primary_mass_max, inner_primary_mass_min,
inner_secondary_mass_min,outer_mass_min, outer_mass_max,
inner_semi_max, inner_semi_min, outer_semi_max, outer_semi_min)
#Does not use boolean inner/outer _semi_latus_rectum_ min/max
self.inner_ecc = self.generate_ecc_1d(inner_ecc_max, inner_ecc_min, inner_ecc_distr, self.inner_secondary_mass)
self.outer_ecc = self.generate_ecc_1d(outer_ecc_max, outer_ecc_min, outer_ecc_distr, self.outer_mass)
else:
self.generate_mass(inner_primary_mass_max, inner_primary_mass_min,
inner_secondary_mass_max,inner_secondary_mass_min,outer_mass_min,outer_mass_max,
inner_mass_ratio_max, inner_mass_ratio_min,
outer_mass_ratio_max, outer_mass_ratio_min,
inner_primary_mass_distr, inner_mass_ratio_distr, outer_mass_ratio_distr)
orbit_convergence = False
while orbit_convergence == False:
orbit_convergence = self.generate_semi_and_ecc(inner_semi_max, inner_semi_min,
outer_semi_max, outer_semi_min,
inner_semi_distr, outer_semi_distr,
inner_semi_latus_rectum_min, outer_semi_latus_rectum_min,
inner_semi_latus_rectum_max, outer_semi_latus_rectum_max,
inner_ecc_max, inner_ecc_min,
outer_ecc_max, outer_ecc_min,
inner_ecc_distr, outer_ecc_distr,
self.inner_secondary_mass, self.outer_mass)
self.generate_incl(incl_max, incl_min, incl_distr)
self.generate_aop(inner_aop_max, inner_aop_min,
outer_aop_max, outer_aop_min,
inner_aop_distr, outer_aop_distr)
self.generate_loan(inner_loan_max, inner_loan_min, inner_loan_distr)
#-------
def generate_mass(self, inner_primary_mass_max, inner_primary_mass_min,
inner_secondary_mass_max,inner_secondary_mass_min,outer_mass_min, outer_mass_max,
inner_mass_ratio_max, inner_mass_ratio_min,
outer_mass_ratio_max, outer_mass_ratio_min,
inner_primary_mass_distr, inner_mass_ratio_distr, outer_mass_ratio_distr):
if REPORT_TPS:
print('generate_mass')
if inner_primary_mass_max == inner_primary_mass_min:
self.inner_primary_mass = inner_primary_mass_min
else:
if inner_primary_mass_distr == 1: #Scalo 1986
self.inner_primary_mass= new_scalo_mass_distribution(1, inner_primary_mass_max)[0]
while self.inner_primary_mass < inner_primary_mass_min:
self.inner_primary_mass = new_scalo_mass_distribution(1, inner_primary_mass_max)[0]
elif inner_primary_mass_distr == 2:#Miller & Scale 1979
self.inner_primary_mass= new_miller_scalo_mass_distribution(1, inner_primary_mass_max)[0]
while self.inner_primary_mass < inner_primary_mass_min:
self.inner_primary_mass = new_miller_scalo_mass_distribution(1, inner_primary_mass_max)[0]
elif inner_primary_mass_distr == 3: #Salpeter with slope 2.35
self.inner_primary_mass= new_salpeter_mass_distribution(1, inner_primary_mass_min, inner_primary_mass_max)[0]
elif inner_primary_mass_distr == 4: # Flat in log space
self.inner_primary_mass= new_flat_mass_distribution(1, inner_primary_mass_min, inner_primary_mass_max)[0]
elif inner_primary_mass_distr == 5: # Eggleton 2009, 399, 1471, Salpeter-like with turnover at low masses
self.inner_primary_mass= eggleton_mass_distr(inner_primary_mass_min, inner_primary_mass_max)
elif inner_primary_mass_distr == 6: #Salpeter with slope 2.3 -> Kroupa for M>0.5
self.inner_primary_mass = powerlaw_distr(inner_primary_mass_min, inner_primary_mass_max, -2.3)
else: #Kroupa 2001
self.inner_primary_mass = new_kroupa_mass_distribution(1, mass_min = inner_primary_mass_min, mass_max = inner_primary_mass_max)[0]
if inner_mass_ratio_max == inner_mass_ratio_min:
inner_mass_ratio = inner_mass_ratio_min
self.inner_secondary_mass = inner_mass_ratio * self.inner_primary_mass
else:
if inner_mass_ratio_distr == 1:# Kroupa 2001
self.inner_secondary_mass = new_kroupa_mass_distribution(1, mass_min=inner_secondary_mass_min, mass_max=inner_secondary_mass_max)[0]
# self.inner_secondary_mass = new_kroupa_mass_distribution(1, mass_min=inner_secondary_mass_min, mass_max=inner_primary_mass_max)[0]
# self.inner_secondary_mass = new_kroupa_mass_distribution(1, mass_min=inner_secondary_mass_min, mass_max=inner_primary_mass)[0]
elif inner_mass_ratio_distr == 2: # Galicher et al 2016
self.inner_secondary_mass = powerlaw_distr( m_min= inner_secondary_mass_min, m_max= inner_secondary_mass_max, slope= -1.31)
else: # flat distribution
inner_mass_ratio = flat_distr(max(inner_mass_ratio_min, inner_secondary_mass_min/self.inner_primary_mass), min(inner_mass_ratio_max, inner_secondary_mass_max/self.inner_primary_mass))
self.inner_secondary_mass = inner_mass_ratio * self.inner_primary_mass
if outer_mass_ratio_max == outer_mass_ratio_min:
outer_mass_ratio = outer_mass_ratio_min
self.outer_mass = outer_mass_ratio * (self.inner_primary_mass + self.inner_secondary_mass)
else:
if outer_mass_ratio_distr == 1:# Kroupa 2001
self.outer_mass = new_kroupa_mass_distribution(1, mass_min=outer_mass_min, mass_max=outer_mass_max)[0]
elif outer_mass_ratio_distr == 2: # Galicher et al 2016
self.outer_mass = powerlaw_distr( m_min= outer_mass_min, m_max= outer_mass_max, slope= -1.31)
else: # flat distribution
inner_mass_tot = self.inner_primary_mass + self.inner_secondary_mass
outer_mass_ratio = flat_distr(max(outer_mass_ratio_min,outer_mass_min/inner_mass_tot), min(outer_mass_ratio_max, outer_mass_max/inner_mass_tot))
self.outer_mass = outer_mass_ratio * inner_mass_tot
def generate_semi_and_ecc(self,
inner_semi_max_orig, inner_semi_min_orig,
outer_semi_max_orig, outer_semi_min_orig,
inner_semi_distr, outer_semi_distr,
inner_semi_latus_rectum_min, outer_semi_latus_rectum_min,
inner_semi_latus_rectum_max, outer_semi_latus_rectum_max,
inner_ecc_max, inner_ecc_min,
outer_ecc_max, outer_ecc_min,
inner_ecc_distr, outer_ecc_distr,
inner_secondary_mass, outer_mass):
if REPORT_TPS:
print('generate_semi_and_ecc')
self.inner_ecc = self.generate_ecc_1d(inner_ecc_max, inner_ecc_min, inner_ecc_distr, inner_secondary_mass)
self.outer_ecc = self.generate_ecc_1d(outer_ecc_max, outer_ecc_min, outer_ecc_distr, outer_mass)
inner_semi_min = inner_semi_min_orig
if inner_semi_latus_rectum_min:
inner_semi_min = inner_semi_min_orig /(1-self.inner_ecc**2)
outer_semi_min = outer_semi_min_orig
if outer_semi_latus_rectum_min:
outer_semi_min = outer_semi_min_orig /(1-self.outer_ecc**2)
inner_semi_max = inner_semi_max_orig
if inner_semi_latus_rectum_max:
inner_semi_max = inner_semi_max_orig /(1-self.inner_ecc**2)
outer_semi_max = outer_semi_max_orig
if outer_semi_latus_rectum_max:
outer_semi_max = outer_semi_max_orig /(1-self.outer_ecc**2)
if inner_semi_max == inner_semi_min:
self.inner_semi = inner_semi_min
else:
if inner_semi_distr == 1: #Constant
if REPORT_USER_WARNINGS_TPS:
print('TPS::generate_semi: unambiguous choice of constant semi-major axis')
print('--A_min option to set the value of the semi-major axis in the inner binary')
self.inner_semi = inner_semi_min
elif inner_semi_distr == 2: #Tokovinin Lognormal mu=10^5d, sigma=2.3
self.inner_semi = 0.|units.RSun
while (self.inner_semi < inner_semi_min or self.inner_semi > inner_semi_max):
self.inner_ecc = self.generate_ecc_1d(inner_ecc_max, inner_ecc_min, inner_ecc_distr, inner_secondary_mass)
inner_semi_min = inner_semi_min_orig
if inner_semi_latus_rectum_min:
inner_semi_min = inner_semi_min_orig /(1-self.inner_ecc**2)
logP = np.random.normal(5, 2.3, 1)
P = (10**logP[0])|units.day
self.inner_semi = ((P/2./np.pi)**2 * constants.G* (self.inner_primary_mass + self.inner_secondary_mass))**(1./3.)
if logP < -0.3 or logP > 10:#truncation of Gaussian wings
self.inner_semi = 0.|units.RSun
elif inner_semi_distr == 3: #Lognormal mu=10^3.5d, sigma=2.3
self.inner_semi = 0.|units.RSun
while (self.inner_semi < inner_semi_min or self.inner_semi > inner_semi_max):
self.inner_ecc = self.generate_ecc_1d(inner_ecc_max, inner_ecc_min, inner_ecc_distr, inner_secondary_mass)
inner_semi_min = inner_semi_min_orig
if inner_semi_latus_rectum_min:
inner_semi_min = inner_semi_min_orig /(1-self.inner_ecc**2)
inner_semi_max = inner_semi_max_orig
if inner_semi_latus_rectum_max:
inner_semi_max = inner_semi_max_orig /(1-self.inner_ecc**2)
logP = np.random.normal(3.5, 2.3, 1)
P = (10**logP[0])|units.day
self.inner_semi = ((P/2./np.pi)**2 * constants.G* (self.inner_primary_mass + self.inner_secondary_mass))**(1./3.)
if logP < -0.3 or logP > 10:#truncation of Gaussian wings
self.inner_semi = 0.|units.RSun
elif inner_semi_distr == 4: #Rizzuto et al 2013, 436, 1694, Lognormal mu=10^0.95AU, sigma=1.35
self.inner_semi = 0.|units.RSun
while (self.inner_semi < inner_semi_min or self.inner_semi > inner_semi_max):
self.inner_ecc = self.generate_ecc_1d(inner_ecc_max, inner_ecc_min, inner_ecc_distr, inner_secondary_mass)
inner_semi_min = inner_semi_min_orig
if inner_semi_latus_rectum_min:
inner_semi_min = inner_semi_min_orig /(1-self.inner_ecc**2)
inner_semi_max = inner_semi_max_orig
if inner_semi_latus_rectum_max:
inner_semi_max = inner_semi_max_orig /(1-self.inner_ecc**2)
logAU = np.random.normal(0.95, 1.35, 1)
self.inner_semi = (10**logAU[0])|units.AU
if self.inner_semi < 0.5|units.RSun or self.inner_semi > 5e8|units.RSun:#truncation of Gaussian wings
self.inner_semi = 0.|units.RSun
elif inner_semi_distr == 5: #Sana
self.inner_semi = 0.|units.RSun
# (logP)^-0.55
while (self.inner_semi < inner_semi_min or self.inner_semi > inner_semi_max):
self.inner_ecc = self.generate_ecc_1d(inner_ecc_max, inner_ecc_min, inner_ecc_distr, inner_secondary_mass)
inner_semi_min = inner_semi_min_orig
if inner_semi_latus_rectum_min:
inner_semi_min = inner_semi_min_orig /(1-self.inner_ecc**2)
inner_semi_max = inner_semi_max_orig
if inner_semi_latus_rectum_max:
inner_semi_max = inner_semi_max_orig /(1-self.inner_ecc**2)
random_nr = flat_distr(0, 1)
logP_min = 0.15
logP_max = 8.5
c_s = (logP_max**0.45 - logP_min**0.45)
logP = (random_nr*c_s +logP_min**0.45)**(1./0.45)
P0 = 10**logP|units.day
M_inner = self.inner_primary_mass + self.inner_secondary_mass
self.inner_semi = ((P0/2./np.pi)**2 * M_inner*constants.G ) ** (1./3.)
elif inner_semi_distr == 6: # flat distr (uniform)
self.inner_semi = flat_distr( inner_semi_min.value_in(units.RSun), inner_semi_max.value_in(units.RSun))|units.RSun
elif inner_semi_distr == 7: # Galicher 2016: powerlaw, slope -0.61
self.inner_semi = powerlaw_distr( inner_semi_min, inner_semi_max, slope= -0.61)
else: # log flat distribution
maximal_semi = min(inner_semi_max, outer_semi_max)
if inner_semi_min > maximal_semi: #possible for extreme eccentricities
return False
self.inner_semi = log_flat_distr(inner_semi_min.value_in(units.RSun), maximal_semi.value_in(units.RSun))|units.RSun
if outer_semi_max == outer_semi_min:
self.outer_semi = outer_semi_min
else:
if outer_semi_distr == 1: #Constant
if REPORT_USER_WARNINGS_TPS:
print('TPS::generate_semi: unambiguous choise of constant semi-major axis')
print('--a_min option to set the value of the semi-major axis in the outer binary')
self.outer_semi = outer_semi_min
elif outer_semi_distr == 2: #Tokovinin Lognormal mu=10^5.5d, sigma=2.3
self.outer_semi = 0.|units.RSun
while (self.outer_semi < outer_semi_min or self.outer_semi > outer_semi_max):
self.outer_ecc = self.generate_ecc_1d(outer_ecc_max, outer_ecc_min, outer_ecc_distr, outer_mass)
outer_semi_min = outer_semi_min_orig
if outer_semi_latus_rectum_min:
outer_semi_min = outer_semi_min_orig /(1-self.outer_ecc**2)
outer_semi_max = outer_semi_max_orig
if outer_semi_latus_rectum_max:
outer_semi_max = outer_semi_max_orig /(1-self.outer_ecc**2)
logP_out = np.random.normal(5, 2.3, 1)
P_out = (10**logP_out[0])|units.day
self.outer_semi = ((P_out/2./np.pi)**2 * constants.G* (self.inner_primary_mass + self.inner_secondary_mass + self.outer_mass))**(1./3.)
if logP_out < -0.3 or logP_out > 10:#truncation of Gaussian wings
self.outer_semi = 0.|units.RSun
if logP_out < 3: # no bifurcation
self.outer_semi = 0.|units.RSun
elif outer_semi_distr == 3: #Lognormal mu=10^3.5d, sigma=2.3
self.outer_semi = 0.|units.RSun
while (self.outer_semi < outer_semi_min or self.outer_semi > outer_semi_max):
self.outer_ecc = self.generate_ecc_1d(outer_ecc_max, outer_ecc_min, outer_ecc_distr, outer_mass)
outer_semi_min = outer_semi_min_orig
if outer_semi_latus_rectum_min:
outer_semi_min = outer_semi_min_orig /(1-self.outer_ecc**2)
outer_semi_max = outer_semi_max_orig
if outer_semi_latus_rectum_max:
outer_semi_max = outer_semi_max_orig /(1-self.outer_ecc**2)
logP_out = np.random.normal(5, 2.3, 1)
P_out = (10**logP_out[0])|units.day
self.outer_semi = ((P_out/2./np.pi)**2 * constants.G* (self.inner_primary_mass + self.inner_secondary_mass + self.outer_mass))**(1./3.)
if logP_out < -0.3 or logP_out > 10:#truncation of Gaussian wings
self.outer_semi = 0.|units.RSun
if logP_out < 3: # no bifurcation
self.outer_semi = 0.|units.RSun
elif outer_semi_distr == 4: #Rizzuto et al 2013, 436, 1694, Lognormal mu=10^0.95AU, sigma=1.35
self.outer_semi = 0.|units.RSun
while (self.outer_semi < outer_semi_min or self.outer_semi > outer_semi_max):
self.outer_ecc = self.generate_ecc_1d(outer_ecc_max, outer_ecc_min, outer_ecc_distr, outer_mass)
outer_semi_min = outer_semi_min_orig
if outer_semi_latus_rectum_min:
outer_semi_min = outer_semi_min_orig /(1-self.outer_ecc**2)
outer_semi_max = outer_semi_max_orig
if outer_semi_latus_rectum_max:
outer_semi_max = outer_semi_max_orig /(1-self.outer_ecc**2)
logAU = np.random.normal(0.95, 1.35, 1)
self.outer_semi = (10**logAU[0])|units.AU
if self.outer_semi < 0.5|units.RSun or self.outer_semi > 5e8|units.RSun:#truncation of Gaussian wings
self.outer_semi = 0.|units.RSun
elif outer_semi_distr == 5: #Sana
self.outer_semi = 0.|units.RSun
# (logP)^-0.55
while (self.outer_semi < outer_semi_min or self.outer_semi > outer_semi_max):
self.outer_ecc = self.generate_ecc_1d(outer_ecc_max, outer_ecc_min, outer_ecc_distr, outer_mass)
outer_semi_min = outer_semi_min_orig
if outer_semi_latus_rectum_min:
outer_semi_min = outer_semi_min_orig /(1-self.outer_ecc**2)
outer_semi_max = outer_semi_max_orig
if outer_semi_latus_rectum_max:
outer_semi_max = outer_semi_max_orig /(1-self.outer_ecc**2)
random_nr = flat_distr(0, 1)
logP_min = 0.15
logP_max = 8.5
c_s = (logP_max**0.45 - logP_min**0.45)
logP = (random_nr*c_s +logP_min**0.45)**(1./0.45)
P0 = 10**logP|units.day
mass_tot = self.inner_primary_mass + self.inner_secondary_mass + self.outer_mass
self.outer_semi = ((P0/2./np.pi)**2 * mass_tot*constants.G) ** (1./3.)
elif outer_semi_distr == 6: # flat distr (uniform)
self.outer_semi = flat_distr( outer_semi_min.value_in(units.RSun), outer_semi_max.value_in(units.RSun))|units.RSun
elif outer_semi_distr == 7: # Galicher 2016: powerlaw, slope -0.61
self.outer_semi = powerlaw_distr( outer_semi_min, outer_semi_max, slope= -0.61)
else: # log flat distribution
if outer_semi_min > outer_semi_max: #possible for extreme eccentricities
return False
self.outer_semi = log_flat_distr(outer_semi_min.value_in(units.RSun), outer_semi_max.value_in(units.RSun))|units.RSun
if inner_semi_distr == outer_semi_distr and inner_semi_min_orig == outer_semi_min_orig and inner_semi_max == outer_semi_max and self.outer_semi < self.inner_semi and inner_ecc_distr == outer_ecc_distr and inner_ecc_min == outer_ecc_min and inner_ecc_max == outer_ecc_max:
swap = self.outer_semi
self.outer_semi = self.inner_semi
self.inner_semi = swap
swap = self.outer_ecc
self.outer_ecc = self.inner_ecc
self.inner_ecc = swap
return True
elif self.outer_semi < self.inner_semi:
return False
return True
def generate_ecc_1d(self, ecc_max, ecc_min, ecc_distr, mass):
if REPORT_TPS:
print('generate_ecc_1d')
if ecc_max == ecc_min:
return ecc_min
else:
if ecc_distr == 1: #Constant
if REPORT_USER_WARNINGS_TPS:
print('TPS::generate_ecc: unambiguous choise of constant eccentricity')
print('--E_min and --e_min option to set the value of the eccentricity')
return ecc_min
elif ecc_distr == 2: #Sana
return powerlaw_distr(ecc_min+precision, ecc_max, -0.45)
elif ecc_distr == 3: #flat distribution
return flat_distr(ecc_min, ecc_max)
elif ecc_distr == 4: #Powerlaw
return powerlaw_distr(ecc_min+precision, ecc_max, 0.5)
elif ecc_distr == 5: # Beta distribution
return beta_distr_SSOs(ecc_min, ecc_max, mass)
else: #Thermal distribution
return np.sqrt(np.random.uniform(ecc_min*ecc_min, ecc_max*ecc_max))
def generate_incl(self, incl_max, incl_min, incl_distr):
if REPORT_TPS:
print('generate_incl')
if incl_max == incl_min:
self.incl = incl_min
else:
if incl_distr == 1: #Constant
if REPORT_USER_WARNINGS_TPS:
print('TPS::generate_incl: unambiguous choise of constant relative inclination')
print('--i_min option to set the value of the relative inclination in the inner triple')
self.incl = incl_min
else: #Circular uniform distribution
self.incl = np.arccos(np.random.uniform(np.cos(incl_min), np.cos(incl_max)))
def generate_aop(self,
inner_aop_max, inner_aop_min,
outer_aop_max, outer_aop_min,
inner_aop_distr, outer_aop_distr):
if REPORT_TPS:
print('generate_aop')
if inner_aop_max == inner_aop_min:
self.inner_aop = inner_aop_min
else:
if inner_aop_distr == 1: #Constant
if REPORT_USER_WARNINGS_TPS:
print('TPS::generate_aop: unambiguous choise of constant argument of pericenter')
print('--G_min option to set the value of the argument of pericenter of the inner binary')
self.inner_aop = inner_aop_min
else: #Uniform distribution
self.inner_aop = np.random.uniform(inner_aop_min, inner_aop_max)
if outer_aop_max == outer_aop_min:
self.outer_aop = outer_aop_min
else:
if outer_aop_distr == 1: #Constant
if REPORT_USER_WARNINGS_TPS:
print('TPS::generate_aop: unambiguous choise of constant argument of pericenter')
print('--g_min option to set the value of the argument of pericenter of the outer binary')
self.outer_aop = outer_aop_min
else: #Uniform distribution
self.outer_aop = np.random.uniform(outer_aop_min, outer_aop_max)
def generate_loan(self, inner_loan_max, inner_loan_min, inner_loan_distr):
if REPORT_TPS:
print('generate_loan')
if inner_loan_max == inner_loan_min:
self.inner_loan = inner_loan_min
else:
if inner_loan_distr == 0: #Circular uniform distribution
self.inner_loan = np.arccos(np.random.uniform(np.cos(inner_loan_min), np.cos(inner_loan_max)))
else: #Constant
if REPORT_USER_WARNINGS_TPS:
print('TPS::generate_loan: unambiguous choise of constant longitude of ascending nodes')
print('--O_min option to set the value of the argument of pericenter of the inner binary')
self.inner_loan = inner_loan_min
#-------
# Eggleton 2009, 399, 1471
def generate_mass_and_semi_eggleton(self, inner_primary_mass_max, inner_primary_mass_min,
inner_secondary_mass_min,outer_mass_min,outer_mass_max,
inner_semi_max, inner_semi_min, outer_semi_max, outer_semi_min):
if REPORT_TPS:
print('generate_mass_and_semi_eggleton')
U0_mass = [0., .01, .09, .32, 1., 3.2, 11, 32, np.inf]#solar mass
U0_l0 = [0.40, 0.40, 0.40, 0.40, 0.50, 0.75, 0.88, 0.94, 0.96]
U0_l1 = [0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.20, 0.60, 0.80]
U0_l2 = [0.00, 0.00, 0.00, 0.00, 0.00, 0.20, 0.33, 0.82, 0.90]
U0_l3 = [0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00]
Mt = eggleton_mass_distr(min_mass, absolute_max_mass)
U = np.random.uniform(0, 1)
f_l0 = interp1d (U0_mass, U0_l0)
U0 = f_l0(Mt.value_in(units.MSun)) #messy, but otherwise cluster crashes
while U >= U0:
U = np.random.uniform(0, 1)
f_l0 = interp1d (U0_mass, U0_l0)
U0 = f_l0(Mt.value_in(units.MSun))
if U < U0:
V = np.random.uniform(0, 1)
P0 = 1.e5 * V**2 / (1-V)**2.5 |units.day
while P0 > 1e10|units.day:
V = np.random.uniform(0, 1)
P0 = 1.e5 * V**2 / (1-V)**2.5|units.day
x_p = np.random.uniform(0, 1)
if P0 > 25|units.day or x_p > 0.25:
Q0 = ( (U0-U)/U0 )**0.8
else:
Q0 = 0.9+0.09*(U0-U)/U0
if Q0 < 0.01:
Q0 = 0.01
M1 = Mt / (1+Q0)
M2 = M1 * Q0
f_l1 = interp1d(U0_mass, U0_l1)
U1 = np.random.uniform(0, 1)
U1_0 = f_l1(M1.value_in(units.MSun))
U2 = np.random.uniform(0, 1)
U2_0 = f_l1(M2.value_in(units.MSun))
#M1 bifurcutas and M2 not
if U1< U1_0 and U2>=U2_0:
M_bin = M1
U_bin = U1
U0_bin = U1_0
M_comp = M2
#M2 bifurcutas and M1 not
elif U1>= U1_0 and U2<U2_0:
M_bin = M2
U_bin = U2
U0_bin = U2_0
M_comp = M1
else: #two bifurcations -> higher order multiplicity
# print(U1, U1_0, U2, U2_0)
# exit(1)
return False
V_bin = np.random.uniform(0, 1)
P_bin = 0.2 * P0 * 10**(-5*V_bin)
x_pb = np.random.uniform(0, 1)
if P_bin > 25|units.day or x_pb > 0.25:
Q_bin = ( (U0_bin-U_bin)/U0_bin )**0.8
else:
Q_bin = 0.9+0.09*(U0_bin-U_bin)/U0_bin
if Q_bin < 0.01:
Q_bin = 0.01
M1_bin = M_bin / (1+Q_bin)
M2_bin = M1_bin * Q_bin
self.inner_primary_mass = M1_bin
self.inner_secondary_mass = M2_bin
self.outer_mass = M_comp
self.inner_semi = ((P_bin/2./np.pi)**2 * M_bin*constants.G ) ** (1./3.)
self.outer_semi = ((P0/2./np.pi)**2 * Mt*constants.G ) ** (1./3.)
if self.inner_primary_mass < inner_primary_mass_min or self.inner_primary_mass > inner_primary_mass_max:
return False
if self.inner_secondary_mass < inner_secondary_mass_min:
return False
if self.outer_mass < outer_mass_min or self.outer_mass > outer_mass_max:
return False
if self.inner_semi < inner_semi_min or self.inner_semi > inner_semi_max:
return False
if self.outer_semi < outer_semi_min or self.outer_semi > outer_semi_max:
return False
return True
else:
sys.exit('not possible in eggleton distribution')
#-------
#-------
def print_triple(self):
print('\nTriple - ')
print('m =', self.inner_primary_mass, self.inner_secondary_mass, self.outer_mass)
print('a =', self.inner_semi, self.outer_semi)
print('e =', self.inner_ecc, self.outer_ecc)
print('i =', self.incl)
print('g =', self.inner_aop, self.outer_aop)
print('o =', self.inner_loan, self.inner_loan -np.pi)
def print_triple_short(self):
print( self.inner_primary_mass.value_in(units.MSun), self.inner_secondary_mass.value_in(units.MSun), self.outer_mass.value_in(units.MSun), end=" ")
print( self.inner_semi.value_in(units.RSun), self.outer_semi.value_in(units.RSun), end=" ")
print( self.inner_ecc, self.outer_ecc, end=" ")
print( self.incl, end=" ")
print( self.inner_aop, self.outer_aop, end=" ")
print( self.inner_loan, self.inner_loan -np.pi, end=" ")
#-------
#-------
def evolve_model(inner_primary_mass_max, inner_primary_mass_min,inner_secondary_mass_max,
inner_secondary_mass_min,outer_mass_min,outer_mass_max,
inner_mass_ratio_max, inner_mass_ratio_min,
outer_mass_ratio_max, outer_mass_ratio_min,
inner_semi_max, inner_semi_min, outer_semi_max, outer_semi_min,
inner_semi_latus_rectum_min, outer_semi_latus_rectum_min,
inner_semi_latus_rectum_max, outer_semi_latus_rectum_max,
inner_ecc_max, inner_ecc_min, outer_ecc_max, outer_ecc_min,
incl_max, incl_min,
inner_aop_max, inner_aop_min, outer_aop_max, outer_aop_min,
inner_loan_max, inner_loan_min,
inner_primary_mass_distr, inner_mass_ratio_distr, outer_mass_ratio_distr,
inner_semi_distr, outer_semi_distr, inner_ecc_distr, outer_ecc_distr, incl_distr,
inner_aop_distr, outer_aop_distr, inner_loan_distr,
metallicity, tend, number, initial_number, seed,
stop_at_mass_transfer, stop_at_init_mass_transfer, stop_at_outer_mass_transfer,
stop_at_stable_mass_transfer, stop_at_eccentric_stable_mass_transfer,
stop_at_unstable_mass_transfer, stop_at_eccentric_unstable_mass_transfer, which_common_envelope,
stop_at_no_CHE, include_CHE, include_circ,
stop_at_merger, stop_at_disintegrated, stop_at_inner_collision, stop_at_outer_collision,
stop_at_dynamical_instability, stop_at_semisecular_regime,
stop_at_SN, SN_kick_distr, impulse_kick_for_black_holes,fallback_kick_for_black_holes,
stop_at_CPU_time, max_CPU_time, file_name, file_type, dir_plots):
i_n = 0
nr_ids = 0 #number of systems that is dynamically unstable at initialisation
nr_iss = 0 #number of systems that is in the semisecular regime at initialisation
nr_imt = 0 #number of systems that has mass transfer at initialisation
nr_cp = 0 #number of systems with incorrect parameters
while i_n < number:
triple_system = Generate_initial_triple(inner_primary_mass_max, inner_primary_mass_min,
inner_secondary_mass_max, inner_secondary_mass_min, outer_mass_min, outer_mass_max,
inner_mass_ratio_max, inner_mass_ratio_min,
outer_mass_ratio_max, outer_mass_ratio_min,
inner_semi_max, inner_semi_min, outer_semi_max, outer_semi_min,
inner_semi_latus_rectum_min, outer_semi_latus_rectum_min,
inner_semi_latus_rectum_max, outer_semi_latus_rectum_max,
inner_ecc_max, inner_ecc_min, outer_ecc_max, outer_ecc_min,
incl_max, incl_min,
inner_aop_max, inner_aop_min, outer_aop_max, outer_aop_min,
inner_loan_max, inner_loan_min,
inner_primary_mass_distr, inner_mass_ratio_distr, outer_mass_ratio_distr,
inner_semi_distr, outer_semi_distr, inner_ecc_distr, outer_ecc_distr, incl_distr,
inner_aop_distr, outer_aop_distr, inner_loan_distr)
if REPORT_TPS:
triple_system.print_triple()
if (min_mass > triple_system.inner_primary_mass):
if REPORT_TPS:
print('non-star primary included: ', triple_system.inner_primary_mass)
continue
if EXCLUDE_SSO:
if (min_mass > triple_system.inner_secondary_mass) or (min_mass > triple_system.outer_mass):
if REPORT_TPS:
print('non-star secondary & tertiary included: ', triple_system.inner_secondary_mass, triple_system.outer_mass)
continue
number_of_system = initial_number + i_n
if REPORT_TPS:
print('number of system = ', number_of_system)
#do not use main_developer in TPS.py
#memory of SeBa needs to be cleaned, in particular SeBa time
#otherwise use evolve_for for particles indivicually -> many calls
tr = TRES.main(inner_primary_mass = triple_system.inner_primary_mass,
inner_secondary_mass = triple_system.inner_secondary_mass,
outer_mass = triple_system.outer_mass,
inner_semimajor_axis = triple_system.inner_semi,
outer_semimajor_axis = triple_system.outer_semi,
inner_eccentricity = triple_system.inner_ecc,
outer_eccentricity = triple_system.outer_ecc,
relative_inclination = triple_system.incl, metallicity = metallicity, tend = tend, number = number_of_system,
stop_at_mass_transfer = stop_at_mass_transfer, stop_at_init_mass_transfer = stop_at_init_mass_transfer,
stop_at_outer_mass_transfer = stop_at_outer_mass_transfer,
stop_at_stable_mass_transfer = stop_at_stable_mass_transfer,
stop_at_eccentric_stable_mass_transfer = stop_at_eccentric_stable_mass_transfer,
stop_at_unstable_mass_transfer = stop_at_unstable_mass_transfer,
stop_at_eccentric_unstable_mass_transfer = stop_at_eccentric_unstable_mass_transfer,
stop_at_merger = stop_at_merger, stop_at_disintegrated = stop_at_disintegrated,
stop_at_inner_collision = stop_at_inner_collision, stop_at_outer_collision = stop_at_outer_collision,
stop_at_dynamical_instability = stop_at_dynamical_instability,
stop_at_semisecular_regime = stop_at_semisecular_regime,
stop_at_SN = stop_at_SN, SN_kick_distr = SN_kick_distr,
impulse_kick_for_black_holes = impulse_kick_for_black_holes,
fallback_kick_for_black_holes = fallback_kick_for_black_holes,
which_common_envelope = which_common_envelope,
stop_at_CPU_time = stop_at_CPU_time,
max_CPU_time = max_CPU_time, file_name = file_name, file_type = file_type, dir_plots = dir_plots)
if tr.correct_params == False:
if REPORT_TPS:
print('Incorrect parameters')
nr_cp += 1
elif tr.semisecular_regime_at_initialisation == True:
nr_iss +=1
elif tr.dynamical_instability_at_initialisation == True:
nr_ids +=1
elif tr.mass_transfer_at_initialisation == True:
if tr.has_tertiary_donor():
nr_imt +=1
elif include_CHE:
nr_imt +=1
# todo reset so that no olof
else:
nr_imt += 1
if include_circ:
i_ecc = 0
max_nr_tries_ecc = 10
while(i_ecc < max_nr_tries_ecc and tr.mass_transfer_at_initialisation):
i_ecc += 1
new_ecc = triple_system.generate_ecc_1d(triple_system.inner_ecc, inner_ecc_min, inner_ecc_distr, triple_system.inner_secondary_mass)
#resetting semi-major axis creates too many short orbit systems - for now only eccentricity is reset
# tr.triple.child2.semimajor_axis *= (1- tr.triple.child2.eccentricity**2)/(1-new_ecc**2)
# triple_system.inner_semi = tr.triple.child2.semimajor_axis
triple_system.inner_ecc = new_ecc
tr.triple.child2.eccentricity = new_ecc
tr.check_RLOF()
if not tr.has_donor():
i_ecc = max_nr_tries_ecc+1
i_n += 1
nr_imt -= 1
tr = TRES.main(inner_primary_mass = triple_system.inner_primary_mass,
inner_secondary_mass = triple_system.inner_secondary_mass,
outer_mass = triple_system.outer_mass,
inner_semimajor_axis = triple_system.inner_semi,
outer_semimajor_axis = triple_system.outer_semi,
inner_eccentricity = triple_system.inner_ecc,
outer_eccentricity = triple_system.outer_ecc,
relative_inclination = triple_system.incl, metallicity = metallicity, tend = tend, number = number_of_system,
stop_at_mass_transfer = stop_at_mass_transfer, stop_at_init_mass_transfer = stop_at_init_mass_transfer,
stop_at_outer_mass_transfer = stop_at_outer_mass_transfer,
stop_at_stable_mass_transfer = stop_at_stable_mass_transfer,
stop_at_eccentric_stable_mass_transfer = stop_at_eccentric_stable_mass_transfer,
stop_at_unstable_mass_transfer = stop_at_unstable_mass_transfer,
stop_at_eccentric_unstable_mass_transfer = stop_at_eccentric_unstable_mass_transfer,
stop_at_merger = stop_at_merger, stop_at_disintegrated = stop_at_disintegrated,
stop_at_inner_collision = stop_at_inner_collision, stop_at_outer_collision = stop_at_outer_collision,
stop_at_dynamical_instability = stop_at_dynamical_instability,
stop_at_semisecular_regime = stop_at_semisecular_regime,
stop_at_SN = stop_at_SN, SN_kick_distr = SN_kick_distr,
impulse_kick_for_black_holes = impulse_kick_for_black_holes,
fallback_kick_for_black_holes = fallback_kick_for_black_holes,
which_common_envelope = which_common_envelope,
stop_at_CPU_time = stop_at_CPU_time,
max_CPU_time = max_CPU_time, file_name = file_name, file_type = file_type, dir_plots = dir_plots)
else:
i_n += 1
del tr
if REPORT_TPS:
print(number, i_n, nr_iss, nr_ids, nr_imt, nr_cp)
def print_distr(inner_primary_mass_max, inner_primary_mass_min,
inner_secondary_mass_max, inner_secondary_mass_min, outer_mass_min, outer_mass_max,
inner_mass_ratio_max, inner_mass_ratio_min,
outer_mass_ratio_max, outer_mass_ratio_min,
inner_semi_max, inner_semi_min, outer_semi_max, outer_semi_min,
inner_semi_latus_rectum_min, outer_semi_latus_rectum_min,
inner_semi_latus_rectum_max, outer_semi_latus_rectum_max,
inner_ecc_max, inner_ecc_min, outer_ecc_max, outer_ecc_min,
incl_max, incl_min,
inner_aop_max, inner_aop_min, outer_aop_max, outer_aop_min,
inner_loan_max, inner_loan_min,
inner_primary_mass_distr, inner_mass_ratio_distr, outer_mass_ratio_distr,
inner_semi_distr, outer_semi_distr, inner_ecc_distr, outer_ecc_distr, incl_distr,
inner_aop_distr, outer_aop_distr, inner_loan_distr,
metallicity, tend, number, initial_number, seed,
stop_at_mass_transfer, stop_at_init_mass_transfer, stop_at_outer_mass_transfer,
stop_at_stable_mass_transfer, stop_at_eccentric_stable_mass_transfer,
stop_at_unstable_mass_transfer, stop_at_eccentric_unstable_mass_transfer, which_common_envelope,
stop_at_no_CHE, include_CHE, include_circ,
stop_at_merger, stop_at_disintegrated, stop_at_inner_collision, stop_at_outer_collision,
stop_at_dynamical_instability, stop_at_semisecular_regime,
stop_at_SN, SN_kick_distr, impulse_kick_for_black_holes,fallback_kick_for_black_holes,
stop_at_CPU_time, max_CPU_time, file_name, file_type, dir_plots):
print('Based on the following distributions:')
print('Primary mass: \t\t', inner_primary_mass_distr, ' ',lib_inner_primary_mass_distr[inner_primary_mass_distr] )
print('Inner mass ratio: \t', inner_mass_ratio_distr, ' ',lib_inner_mass_ratio_distr[inner_mass_ratio_distr] )
print('Outer mass ratio: \t', outer_mass_ratio_distr, ' ',lib_outer_mass_ratio_distr[outer_mass_ratio_distr] )
print('Inner semi-major axis: \t', inner_semi_distr, ' ',lib_inner_semi_distr[inner_semi_distr] )
print('Outer semi-major axis: \t', outer_semi_distr, ' ',lib_outer_semi_distr[outer_semi_distr] )
print('Inner eccentricity: \t', inner_ecc_distr, ' ',lib_inner_ecc_distr[inner_ecc_distr] )
print('Outer eccentricity: \t', outer_ecc_distr, ' ',lib_outer_ecc_distr[outer_ecc_distr] )
print('Inclination: \t\t', incl_distr, ' ',lib_incl_distr[incl_distr] )
print('Inner aop: \t\t', inner_aop_distr, ' ',lib_inner_aop_distr[inner_aop_distr] )
print('Outer aop: \t\t', outer_aop_distr, ' ',lib_outer_aop_distr[outer_aop_distr] )
print('Inner loan: \t\t', inner_loan_distr, ' ',lib_inner_loan_distr[inner_loan_distr] )
print('Common envelope model: \t', which_common_envelope, ' ', lib_CE[which_common_envelope])
print('SN kick distr: \t\t', SN_kick_distr, ' ', lib_SN_kick_distr[SN_kick_distr])
print('Metallicity: \t\t', '-', ' ', metallicity.value_in(units.none))
print('\n')
print('Based on the following assumptions:')
print('Include CHE: \t\t', include_CHE)
print('Include circularisation during pre-MS: \t\t', include_circ)
print('\n')
print('Based on the following stopping conditions:')
print(stop_at_mass_transfer, '\t Stop at mass transfer')
print(stop_at_init_mass_transfer, '\t Stop at mass transfer initially')
print(stop_at_outer_mass_transfer, '\t Stop at outer mass transfer')
print(stop_at_stable_mass_transfer, '\t Stop at stable mass transfer')
print(stop_at_eccentric_stable_mass_transfer, '\t Stop at eccentric stable mass transfer')
print(stop_at_unstable_mass_transfer, '\t Stop at unstable mass transfer')
print(stop_at_eccentric_unstable_mass_transfer, '\t Stop at eccentric unstable mass transfer')
print(stop_at_no_CHE, '\t Stop if no chemically homogeneous evolution')
print(stop_at_merger, '\t Stop at merger')
print(stop_at_disintegrated, '\t Stop at disintegration')
print(stop_at_inner_collision, '\t Stop at collision in inner binary')
print(stop_at_outer_collision, '\t Stop at collision with outer star')
print(stop_at_dynamical_instability, '\t Stop at dynamical instability')
print(stop_at_semisecular_regime, '\t Stop at semisecular regime')
print(stop_at_CPU_time, '\t Stop at maximum CPU time')
print('\n')
def test_initial_parameters(inner_primary_mass_max, inner_primary_mass_min,
inner_secondary_mass_max, inner_secondary_mass_min, outer_mass_min, outer_mass_max,
inner_mass_ratio_max, inner_mass_ratio_min,
outer_mass_ratio_max, outer_mass_ratio_min,
inner_semi_max, inner_semi_min, outer_semi_max, outer_semi_min,
inner_semi_latus_rectum_min, outer_semi_latus_rectum_min,
inner_semi_latus_rectum_max, outer_semi_latus_rectum_max,
inner_ecc_max, inner_ecc_min, outer_ecc_max, outer_ecc_min,
incl_max, incl_min,
inner_aop_max, inner_aop_min, outer_aop_max, outer_aop_min,
inner_loan_max, inner_loan_min,
inner_primary_mass_distr, inner_mass_ratio_distr, outer_mass_ratio_distr,
inner_semi_distr, outer_semi_distr, inner_ecc_distr, outer_ecc_distr, incl_distr,
inner_aop_distr, outer_aop_distr, inner_loan_distr,
metallicity, tend, number, initial_number, seed,
stop_at_mass_transfer, stop_at_init_mass_transfer, stop_at_outer_mass_transfer,
stop_at_stable_mass_transfer, stop_at_eccentric_stable_mass_transfer,