Skip to content
Snippets Groups Projects
Commit 599c6566 authored by Francisco Jimenez Forteza's avatar Francisco Jimenez Forteza
Browse files

cleaning

parent 85eba8c6
No related branches found
No related tags found
No related merge requests found
Hide whitespace changes
Inline Side-by-side
Showing
with 0 additions and 208 deletions
code_new/rdown.py deleted 100644 → 0
+ 0
− 208
View file @ 85eba8c6
# Copyright (C) 2021 Xisco Jimenez Forteza
#
# This program is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 3 of the License, or (at your
# option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
# Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
#
# =============================================================================
#
# Preamble
#
# =============================================================================
#
# Module to generate RD waveforms.
import numpy as np
import qnm
import os
f_fpars= [[2.95845, -2.58697, 0.0533469], [2.12539, -1.78054, 0.0865503], [1.74755, -1.44776, 0.123666], [1.78287, -1.53203, 0.129475], [2.04028, -1.83224, 0.112497]]
q_fpars=[[0.584077, 1.52053, -0.480658], [0.00561441, 0.630715, -0.432664], [-0.197965, 0.515956, -0.369706], [-0.275097, 0.455691, -0.331543], [-0.287596, 0.398514, -0.309799]]
c=2.99792458*10**8;G=6.67259*10**(-11);MS=1.9885*10**30;
class Ringdown_Spectrum:
"""RDown model generator"""
def __init__(self,mf,af,l,m,n=4,s=-2,time=[],fixed=False,qnm_model='berti'):
self.mf = mf
self.af = af
self.l = l
self.m = m
self.n = n
self.time = time
self.grav_220 = [qnm.modes_cache(s=s,l=self.l,m=self.m,n=i) for i in range (0,self.n+1)]
self.dim = self.n+1
self.fixed = fixed
self.qnm_model = qnm_model
dict_omega = {'berti': self.QNM_Berti , 'qnm': self.QNM_spectrum}
dic = {'w-tau':self.rd_model_wtau , 'w-q': self.rd_model_wq, 'w-tau-fixed':self.rd_model_wtau_fixed,'w-tau-fixed-m-af': self.rd_model_wtau_m_af}
if len(self.time)==0:
self.time = np.arange(0,100,0.1)
if self.fixed:
omegas_new=np.asarray([self.grav_220[i](a=self.af)[0] for i in range (0,self.dim)])
self.w = (np.real(omegas_new))/self.mf
self.tau=-1/(np.imag(omegas_new))*self.mf
def QNM_spectrum(self):
""" It computes the RD frequencies and damping times in NR units.
"""
omegas_new=np.asarray([self.grav_220[i](a=self.af)[0] for i in range (0,self.n+1)])
w_m_a = (np.real(omegas_new))/self.mf
tau_m_a=-1/(np.imag(omegas_new))*self.mf
return (w_m_a, tau_m_a)
def QNM_Berti(self,rdowndata):
""" It computes the RD frequencies and damping times in NR units.
"""
position=np.argmax(rdowndata[0,0] >= (self.af))
#w_m_a=f1+f2*(1-af)**f3
w_m_a=[None]*(self.n+1)
tau_ma_a=[None]*(self.n+1)
for i in range(self.n+1):
qnm=rdowndata[i,1:3,position]
w_m_a[i] = qnm[0]/self.mf
tau_ma_a[i] = -1/(qnm[1])*self.mf
return w_m_a, tau_ma_a
def w_fpars_Berti(self,n):
return f_fpars[n]
def tau_qpars_Berti(self,n):
return q_fpars[n]
def mass_from_wtau(self,n,w,tau):
f1,f2,f3 = w_fpars_Berti(n)
q1,q2,q3 = tau_qpars_Berti(n)
res=(f1 + f2*(2**(-1/q3)*((-2*q1 + w*tau)/q2)**(1/q3))**f3)/w
return res
def spin_from_wtau(self,n,w,tau):
f1,f2,f3 = w_fpars_Berti(n)
q1,q2,q3 = tau_qpars_Berti(n)
res=1 - 2**(-1/q3)*((-2*q1 + w*tau)/q2)**(1/q3)
return res
def mass_from_wtau_loop(self,w,tau,l,m):
res=[None]*dim
for n in range (0,dim):
f1,f2,f3 = w_fpars_Berti(n)
q1,q2,q3 = tau_qpars_Berti(n)
res[n]=(f1 + f2*(2**(-1/q3)*((-2*q1 + w[n]*tau[n])/q2)**(1/q3))**f3)/w[n]
return res
def spin_from_wtau_loop(self,w,tau,l,m):
res=[None]*dim
for n in range (0,dim):
f1,f2,f3 = w_fpars_Berti(n)
q1,q2,q3 = tau_qpars_Berti(n)
res[n]= 1 - 2**(-1/q3)*((-2*q1 + w[n]*tau[n])/q2)**(1/q3)
return res
def rd_model_wtau(self,theta):
"""RD model parametrized with the damping time tau.
"""
assert int(len(theta)/4) == self.dim, 'Please recheck your n and parameters'
wvars = theta[ : (self.dim)]
tvars = theta[(self.dim) : 2*(self.dim)]
xvars = theta[2*(self.dim) : 3*(self.dim)]
yvars = theta[3*(self.dim) : ]
ansatz = 0
for i in range (0,self.dim):
ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-self.time/tvars[i]) * (np.cos(wvars[i]*self.time)-1j*np.sin(wvars[i]*self.time))
# -1j to agree with SXS convention
return ansatz
def rd_model_wtau_m_af(theta):
"""RD model parametrized with the damping time tau and with the QNM spectrum fixd to GR. The QNM spectrum is given from the mass and spin.
"""
xvars = theta[ : (dim)]
yvars = theta[(dim) : 2*(dim)]
mass_vars = theta[index_mass]
spin_vars = theta[index_spin]
w_m_a , tau_m_a = dict_omega[self.qnm_model](mass_vars,spin_vars,2,2)
ansatz = 0
for i in range (0,dim):
ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-timesrd_final_tsh/tau_m_a[i]) * (np.cos(w_m_a[i]*timesrd_final_tsh)-1j*np.sin(w_m_a[i]*timesrd_final_tsh))
# -1j to agree with SXS convention
return ansatz
def rd_model_wtau_fixed(theta):
"""RD model parametrized with the damping time tau and with the QNM spectrum fixd to GR.
"""
xvars = theta[ : (dim)]
yvars = theta[(dim) : 2*(dim)]
ansatz = 0
for i in range (0,dim):
ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-timesrd_final_tsh/tau[i]) * (np.cos(w[i]*timesrd_final_tsh)-1j*np.sin(w[i]*timesrd_final_tsh))
# -1j to agree with SXS convention
return ansatz
def rd_model_wq(self,theta):
"""RD model parametrized with the quality factor q.
"""
assert int(len(theta)/4) == self.dim, 'Please recheck your n and parameters'
wvars = theta[ : (self.dim)]
qvars = theta[(self.dim) : 2*(self.dim)]
xvars = theta[2*(self.dim) : 3*(self.dim)]
yvars = theta[3*(self.dim) : ]
ansatz = 0
for i in range (0,self.dim):
ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-self.time*np.pi*wvars[i]/qvars[i])*(np.cos(wvars[i]*self.time)-1j*np.sin(wvars[i]*self.time))
# -1j to agree with SXS convention
return ansatz
def rd_model_wq_fixed(self,theta):
"""RD model parametrized with the damping time tau and with the QNM spectrum fixd to GR.
"""
xvars = theta[ : (self.dim)]
yvars = theta[(self.dim) : 2*(self.dim)]
ansatz = 0
for i in range (0,self.dim):
ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-self.time/self.tau[i]) * (np.cos(self.w[i]*self.time)-1j*np.sin(self.w[i]*self.time))
# -1j to agree with SXS convention
return ansatz
def rd_model_wq_m_a(self,theta):
"""RD model parametrized with the damping time tau and with the QNM spectrum fixd to GR. The QNM spectrum is given from the mass and spin.
"""
xvars = theta[ : (self.dim)]
yvars = theta[(self.dim) : 2*(self.dim)]
mass_vars = theta[-2]
spin_vars = theta[-1]
w_m_a , tau_m_a = QNM_spectrum()
ansatz = 0
for i in range (0,dim):
ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-timesrd_final_tsh/tau_m_a[i]) * (np.cos(w_m_a[i]*timesrd_final_tsh)-1j*np.sin(w_m_a[i]*timesrd_final_tsh))
# -1j to agree with SXS convention
return ansatz
\ No newline at end of file
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Please register or to comment

AEI Privacy Policy Imprint