Exemple #1
0
    def test_ZsGammaConversion(self):
        avars = Andoyer.from_Simulation(self.sim, 4, 1)
        Z = avars.Z
        phiZ = avars.psi1
        Zcom = avars.Zcom
        phiZcom = avars.phiZcom
        sGamma1, gamma1, sGamma2, gamma2 = avars.Zs_to_sGammas(Z, phiZ, Zcom, phiZcom)
        nZ, nphiZ, nZcom, nphiZcom = avars.sGammas_to_Zs(sGamma1, gamma1, sGamma2, gamma2)
        self.assertAlmostEqual(nZ,Z, delta=1.e-15)
        self.assertAlmostEqual(np.mod(nphiZ, 2*np.pi), np.mod(phiZ, 2*np.pi), delta=1.e-15)
        self.assertAlmostEqual(nZcom, Zcom, delta=1.e-15)
        self.assertAlmostEqual(np.mod(nphiZcom, 2*np.pi), np.mod(phiZcom, 2*np.pi), delta=1.e-15)

        # should also be equivalent for 2 massive particles to rotation
        pvars = Poincare.from_Simulation(self.sim)
        ps = pvars.particles
        p = avars.params
        f, g = p['f'], p['g']
        ff = f*np.sqrt(p['eta']/p['m1']/p['sLambda10'])
        gg = g*np.sqrt(p['eta']/p['m2']/p['sLambda20'])
        norm = np.sqrt(ff*ff + gg*gg)
        psirotmatrix = np.array([[ff,gg],[-gg,ff]]) / norm
        invpsirotmatrix = np.array([[ff,-gg],[gg,ff]]) / norm
        Psi1,psi1,Psi2,psi2 = self.rotate_actions(ps[1].Gamma/p['eta'],ps[1].gamma,ps[2].Gamma/p['eta'],ps[2].gamma, psirotmatrix)
        self.assertAlmostEqual(Psi1, avars.Psi1, delta=1.e-15)
        self.assertAlmostEqual(np.mod(psi1, 2*np.pi), np.mod(avars.psi1, 2*np.pi), delta=1.e-15)
        self.assertAlmostEqual(Psi2, avars.Psi2, delta=1.e-15)
        self.assertAlmostEqual(np.mod(psi2, 2*np.pi), np.mod(avars.psi2, 2*np.pi), delta=1.e-15)
Exemple #2
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 def setUp(self):
     self.sim = get_sim()
     self.pvars = Poincare.from_Simulation(self.sim)
     self.pham = PoincareHamiltonian(self.pvars)
     self.terms_list = SecularTermsList(4, 4)
     for i in range(1, self.pvars.N):
         for j in range(i + 1, self.pvars.N):
             for term in self.terms_list:
                 k, z = term
                 self.pham.add_monomial_term(k,
                                             z,
                                             indexIn=i,
                                             indexOut=j,
                                             update=False)
     self.pham._update()
     qpsymbols = [S('eta{}'.format(i)) for i in range(1,self.pvars.N)] +\
     [S('rho{}'.format(i)) for i in range(1,self.pvars.N)] +\
     [S('kappa{}'.format(i)) for i in range(1,self.pvars.N)] +\
     [S('sigma{}'.format(i)) for i in range(1,self.pvars.N)]
     self.secular_variable_indices = [
         self.pham.varsymbols.index(s) for s in qpsymbols
     ]
     self.secular_sim = SecularSystemSimulation(self.pvars,
                                                dtFraction=1 / 50.,
                                                max_order=4)
Exemple #3
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 def test_particles(self):
     m = 1.e-5
     M = 3.
     G = 2.
     a = 7.
     e = 0.1
     pomega = 1.3
     l = 0.7
     sLambda = np.sqrt(G * M * a)
     sGamma = sLambda * (1. - np.sqrt(1. - e**2))
     Lambda = m * sLambda
     Gamma = m * sGamma
     p = PoincareParticle(m=m,
                          M=M,
                          G=G,
                          Lambda=Lambda,
                          l=l,
                          Gamma=Gamma,
                          gamma=-pomega)
     tp = PoincareParticle(m=0.,
                           M=M,
                           G=G,
                           sLambda=sLambda,
                           l=l,
                           sGamma=sGamma,
                           gamma=-pomega)
     self.assertAlmostEqual(p.a, a, delta=1.e-15)
     self.assertAlmostEqual(p.e, e, delta=1.e-15)
     self.assertAlmostEqual(p.pomega, pomega, delta=1.e-15)
     self.assertAlmostEqual(tp.a, a, delta=1.e-15)
     self.assertAlmostEqual(tp.e, e, delta=1.e-15)
     self.assertAlmostEqual(tp.pomega, pomega, delta=1.e-15)
     pvars = Poincare(G, poincareparticles=[p, tp])
     ps = pvars.particles
     self.assertAlmostEqual(ps[1].a, a, delta=1.e-15)
     self.assertAlmostEqual(ps[1].e, e, delta=1.e-15)
     self.assertAlmostEqual(ps[1].pomega, pomega, delta=1.e-15)
     self.assertAlmostEqual(ps[2].a, a, delta=1.e-15)
     self.assertAlmostEqual(ps[2].e, e, delta=1.e-15)
     self.assertAlmostEqual(ps[2].pomega, pomega, delta=1.e-15)
     pvars = Poincare(G=G)
     pvars.add(m=m, M=M, Lambda=Lambda, l=l, Gamma=Gamma, gamma=-pomega)
     pvars.add(m=0.,
               M=M,
               sLambda=sLambda,
               l=l,
               sGamma=sGamma,
               gamma=-pomega)
     ps = pvars.particles
     self.assertAlmostEqual(ps[1].a, a, delta=1.e-15)
     self.assertAlmostEqual(ps[1].e, e, delta=1.e-15)
     self.assertAlmostEqual(ps[1].pomega, pomega, delta=1.e-15)
     self.assertAlmostEqual(ps[2].a, a, delta=1.e-15)
     self.assertAlmostEqual(ps[2].e, e, delta=1.e-15)
     self.assertAlmostEqual(ps[2].pomega, pomega, delta=1.e-15)
Exemple #4
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 def test_orbelements(self):
     pvars = Poincare.from_Simulation(self.sim, average=False)
     ps = pvars.particles
     o = self.sim.calculate_orbits(jacobi_masses=True)
     for i in range(1, 4):
         self.assertAlmostEqual(o[i - 1].a, ps[i].a, delta=1.e-15)
         self.assertAlmostEqual(o[i - 1].e, ps[i].e, delta=1.e-15)
         self.assertAlmostEqual(o[i - 1].l, ps[i].l, delta=1.e-15)
         self.assertAlmostEqual(o[i - 1].pomega, ps[i].pomega, delta=1.e-15)
 def test_particles(self):
     m=1.e-5
     M=3.
     G=2.
     a=7.
     e=0.1
     pomega = 1.3
     Omega = 2.1
     inc = 0.07
     l=0.7
     sLambda = np.sqrt(G*M*a)
     sGamma = sLambda*(1.-np.sqrt(1.-e**2))
     sQ = (sLambda-sGamma)*(1-np.cos(inc))
     Lambda = m*sLambda
     Gamma = m*sGamma
     Q = m*sQ
     p = PoincareParticle(m=m, M=M, G=G, Lambda=Lambda, l=l, Gamma=Gamma, gamma=-pomega, Q=Q, q=-Omega)
     tp = PoincareParticle(m=0., M=M, G=G, sLambda=sLambda, l=l, sGamma=sGamma, gamma=-pomega, sQ=sQ, q=-Omega)
     self.assertAlmostEqual(p.a, a, delta=1.e-15)
     self.assertAlmostEqual(p.e, e, delta=1.e-15)
     self.assertAlmostEqual(p.inc, inc, delta=1.e-15)
     self.assertAlmostEqual(p.pomega, pomega, delta=1.e-15)
     self.assertAlmostEqual(p.Omega, Omega, delta=1.e-15)
     self.assertAlmostEqual(tp.a, a, delta=1.e-15)
     self.assertAlmostEqual(tp.e, e, delta=1.e-15)
     self.assertAlmostEqual(tp.inc, inc, delta=1.e-15)
     self.assertAlmostEqual(tp.pomega, pomega, delta=1.e-15)
     self.assertAlmostEqual(tp.Omega, Omega, delta=1.e-15)
     pvars = Poincare(G, poincareparticles=[p, tp])
     ps = pvars.particles
     self.assertAlmostEqual(ps[1].a, a, delta=1.e-15)
     self.assertAlmostEqual(ps[1].e, e, delta=1.e-15)
     self.assertAlmostEqual(ps[1].inc, inc, delta=1.e-15)
     self.assertAlmostEqual(ps[1].pomega, pomega, delta=1.e-15)
     self.assertAlmostEqual(ps[1].Omega, Omega, delta=1.e-15)
     self.assertAlmostEqual(ps[2].a, a, delta=1.e-15)
     self.assertAlmostEqual(ps[2].e, e, delta=1.e-15)
     self.assertAlmostEqual(ps[2].inc, inc, delta=1.e-15)
     self.assertAlmostEqual(ps[2].pomega, pomega, delta=1.e-15)
     self.assertAlmostEqual(ps[2].Omega, Omega, delta=1.e-15)
     pvars = Poincare(G=G)
     pvars.add(m=m, M=M, Lambda=Lambda, l=l, Gamma=Gamma, gamma=-pomega, Q=Q, q=-Omega)
     pvars.add(m=0., M=M, sLambda=sLambda, l=l, sGamma=sGamma, gamma=-pomega, sQ=sQ, q=-Omega)
     ps = pvars.particles
     self.assertAlmostEqual(ps[1].a, a, delta=1.e-15)
     self.assertAlmostEqual(ps[1].e, e, delta=1.e-15)
     self.assertAlmostEqual(ps[1].inc, inc, delta=1.e-15)
     self.assertAlmostEqual(ps[1].pomega, pomega, delta=1.e-15)
     self.assertAlmostEqual(ps[1].Omega, Omega, delta=1.e-15)
     self.assertAlmostEqual(ps[2].a, a, delta=1.e-15)
     self.assertAlmostEqual(ps[2].e, e, delta=1.e-15)
     self.assertAlmostEqual(ps[2].inc, inc, delta=1.e-15)
     self.assertAlmostEqual(ps[2].pomega, pomega, delta=1.e-15)
     self.assertAlmostEqual(ps[2].Omega, Omega, delta=1.e-15)
Exemple #6
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def averaging_error(Nseed):
    sim = packed_sim(Nseed)
    ps = sim.particles

    o = sim.calculate_orbits(jacobi_masses=True)
    a10 = o[0].a
    a20 = o[1].a
    a30 = o[2].a
    tsyn = 2 * np.pi / (o[0].n - o[1].n)
    tmax = 30 * tsyn
    Nout = 100
    times = np.linspace(0, tmax, Nout)

    pvars = Poincare.from_Simulation(sim)
    Hsim = PoincareHamiltonian(pvars)

    Nsma = np.zeros((3, Nout))
    Hsma = np.zeros((3, Nout))

    for i, t in enumerate(times):
        # Store N-body data
        o = sim.calculate_orbits(jacobi_masses=True)
        Nsma[0, i] = o[0].a
        Nsma[1, i] = o[1].a
        Nsma[2, i] = o[2].a

        ps = Hsim.particles
        Hsma[0, i] = ps[1].a
        Hsma[1, i] = ps[2].a
        Hsma[2, i] = ps[3].a

        sim.integrate(t)
        Hsim.integrate(t)

    Nmad1 = mad((Nsma[0] - a10) / a10)
    Nmad2 = mad((Nsma[1] - a20) / a20)
    Nmad3 = mad((Nsma[2] - a30) / a30)

    Nmed1 = np.median((Nsma[0] - a10) / a10)
    Pmed1 = np.median((Hsma[0] - a10) / a10)
    err1 = abs(Pmed1 - Nmed1) / Nmad1

    Nmed2 = np.median((Nsma[1] - a20) / a20)
    Pmed2 = np.median((Hsma[1] - a20) / a20)
    err2 = abs(Pmed2 - Nmed2) / Nmad2

    Nmed3 = np.median((Nsma[2] - a30) / a30)
    Pmed3 = np.median((Hsma[2] - a30) / a30)
    err3 = abs(Pmed3 - Nmed3) / Nmad3

    return max(err1, err2, err3)
Exemple #7
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    def test_jacobi_masses(self):
        pvars = Poincare.from_Simulation(self.sim, average=False)

        sim = pvars.to_Simulation(average=False)
        self.compare_simulations_orb(self.sim, sim, delta=1.e-14)

        sim = pvars.to_Simulation(masses=[1., 1.e-3, 1.e-7, 1.e-5],
                                  average=False)
        self.compare_simulations_orb(self.sim, sim, delta=1.e-14)

        # use default jacobi masses but pass it an inconsistent set of jacobi masses
        pvars.particles[1].M = 1.
        pvars.particles[2].M = 1.
        pvars.particles[3].M = 1.
        sim = pvars.to_Simulation(average=False)
        with self.assertRaises(AssertionError):
            self.compare_simulations_orb(self.sim, sim, delta=1.e-14)
Exemple #8
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    def test_H(self):
        j=3
        k=1
        a10 = 1.02
        sim = rebound.Simulation()
        sim.G = 4*np.pi**2
        sim.add(m=1.)
        sim.add(m=1.e-6, e=0.01, P=1., pomega=-np.pi/2, f=np.pi, jacobi_masses=True)
        sim.add(m=3.e-6, e=0.03, pomega=np.pi/2, P=float(j)/(j-k), jacobi_masses=True)#float(j)/(j-k), theta=3.14)
        sim.move_to_com()
        avars = Andoyer.from_Simulation(sim,j,k, a10=a10, average=True) 
        p = avars.params
        pvars = Poincare.from_Simulation(sim, average=True) 
        sGamma1 = pvars.particles[1].sGamma
        sGamma2 = pvars.particles[2].sGamma
        sLambda1 = pvars.particles[1].sLambda
        sLambda2 = pvars.particles[2].sLambda
        lambda1 = pvars.particles[1].l
        lambda2 = pvars.particles[2].l
        gamma1 = pvars.particles[1].gamma
        gamma2 = pvars.particles[2].gamma
        n10 = np.sqrt(p['G']*p['M1']/p['a10']**3)
        n20 = np.sqrt(p['G']*p['M2']/p['a10']**3*p['alpha']**3)
        z1 = np.sqrt(2*sGamma1/p['sLambda10'])
        z2 = np.sqrt(2*sGamma2/p['sLambda20'])
        Hkep = -0.5*(n10*p['m1']*p['sLambda10']**3/sLambda1**2 + n20*p['m2']*p['sLambda20']**3/sLambda2**2)
        sL10 = p['sLambda10']
        sL20 = p['sLambda20']
        Hkepexpanded = -n10*p['m1']*sL10/2*(1. - 2*avars.dL1hat + 3*avars.dL1hat**2)-n20*p['m2']*sL20/2*(1. - 2*avars.dL2hat + 3*avars.dL2hat**2)
        Hresprefac = -p['G']*p['m1']*p['m2']/p['a10']*p['alpha']
        Hres = Hresprefac*(p['f']*z1*np.cos(j*lambda2 - (j-k)*lambda1 + gamma1)+p['g']*z2*np.cos(j*lambda2 - (j-k)*lambda1 + gamma2))
        H0 = -p['n0']*p['K0']/2
        H1 = p['eta']*p['n0']*avars.dK*(1-1.5*p['eta']/p['K0']*avars.dK)
        H2 = p['eta']*p['a']*avars.dP**2
        Hkeptransformed = H0 + H1 + H2
        Hrestransformed = p['eta']*p['c']*(2*avars.Psi1)**(k/2.)*np.cos(avars.theta+k*avars.psi1)

        self.assertAlmostEqual(Hkeptransformed, Hkepexpanded, delta=1.e-15) # should be exact
        self.assertAlmostEqual(Hrestransformed, Hres, delta=1.e-15) # should be exact for first order resonance (k=1)
        self.assertAlmostEqual(Hkepexpanded, Hkep, delta=(a10-1.)**2) # should match to O(da/a)^2, atrue=1, a10=a10

        #Hfinal = -p['eta']*p['Phi0']/p['tau']*(4.*avars.Phi**2 - 3.*avars.Phiprime*avars.Phi + 9./16.*avars.Phiprime**2 + (2.*avars.Phi)**(k/2.)*np.cos(avars.phi) - p['n0']*p['tau']/p['Phi0']*avars.dK*(1.-1.5*p['eta']/p['K0']*avars.dK))+ H0
        Hfinal = -p['eta']*p['Phi0']/p['tau']*(4.*(avars.Phi-avars.B)**2 + (2.*avars.Phi)**(k/2.)*np.cos(avars.phi) - p['n0']*p['tau']/p['Phi0']*avars.dK*(1.-1.5*p['eta']/p['K0']*avars.dK))+ H0
        self.assertAlmostEqual(Hfinal, Hkepexpanded+Hres, delta=1.e-15) # should be exact
Exemple #9
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def calc_tau(sim):
    if np.isnan(
            sim.dt
    ):  # init_sim_parameters sets timestep to nan if any orbit is hyperbolic. Return tau=inf, i.e. chaotic/unstable
        tau = np.inf
        return tau
    lsys = LaplaceLagrangeSystem.from_Simulation(sim)
    pvars = Poincare.from_Simulation(sim)
    Lambda = np.array([p.Lambda for p in pvars.particles[1:]])

    tau_max = 0
    for i in range(1, sim.N_real):
        tau = 0
        if i - 1 >= 1:
            tau += calc_tau_pair(sim, lsys, Lambda, i - 1, i)
        if i + 1 < sim.N_real:
            tau += calc_tau_pair(sim, lsys, Lambda, i, i + 1)
        if tau > tau_max:
            tau_max = tau
    return tau_max
Exemple #10
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def get_resonant(seed, Nplanets=3):
    r = random.Random()
    r.seed(seed)

    Phiprimecrits = [0, 1., -2. / 3.]
    pairs = ['inner', 'outer', 'split']

    k = r.randint(1, 2)
    pairindex = r.randint(0, 2)
    pair = pairs[pairindex]
    m1 = logunif(r, 1.e-7, 1.e-4)
    m2 = logunif(r, 1.e-7, 1.e-4)
    eH = ((m1 + m2) / 3.)**(1. / 3.)
    ehillstable = 3.5 * eH
    jmax = k / (1 - 1 / (1 + 3.5 * eH)**1.5)
    if pair == 'split':
        if Nplanets == 2:
            return  # don't want 2planet systems 60 hill radii apart
        maxHillradii = 60.  # 3rd planet will go in middle so draw up to 60
    else:
        maxHillradii = 30.
    jmin = max(k + 1, k / (1 - 1 / (1 + maxHillradii * eH)**1.5))
    jmin = int(np.ceil(jmin))
    jmax = int(np.floor(jmax))
    if k == 2:  # if k = 2, want odd j so we don't get e.g. 8:6 = 4:3
        if jmin % 2 == 0:  # even
            jmin += 1
        if jmax % 2 == 0:
            jmax -= 1
    j = r.randrange(
        jmin, jmax + 1,
        k)  # choose randomly between limits in steps of k e.g. (3,5,7,9)
    a1 = 1.
    a2 = (float(j) / (j - k))**(2. / 3.)
    ecross1 = (a2 - a1) / a1
    ecross2 = (a2 - a1) / a2
    emin1 = m2 / ecross1**2
    emin2 = m1 / ecross2**2
    emin = max(
        emin1, emin2
    )  # take as min Z the larger of the kicks a planet gets at conjunction
    emin = max(
        emin, (m1 + m2)**(1. / k)
    )  # below mtot^1/k, the resonant term is smaller than the second order mass terms we ignore
    emax = min(ecross1, ecross2)

    avars = Andoyer(j=j, k=k, X=0, Y=0, m1=m1, m2=m2)
    Phiprimecrit = Phiprimecrits[k]
    Xcrit = get_Xstarres(k, Phiprimecrit)
    Phicrit = 0.5 * Xcrit**2
    emin = max(
        avars.Phi_to_Z(Phicrit), emin
    )  # first quantity is value of Z at bifurcation when res first appears

    Zstar = logunif(r, emin, emax)
    libfac = logunif(r, 3.e-3, 3)
    negative = r.randint(0, 1)
    if negative:
        libfac *= -1

    Zcom = logunif(r, emin, emax)
    avars = Andoyer.from_elements(j=j,
                                  k=k,
                                  Zstar=Zstar,
                                  libfac=libfac,
                                  m1=m1,
                                  m2=m2,
                                  Zcom=Zcom,
                                  phiZcom=r.uniform(0, 2 * np.pi),
                                  theta=r.uniform(0, 2 * np.pi),
                                  theta1=r.uniform(0, 2 * np.pi))
    tmax = r.uniform(0, 10 * avars.tlib)
    H = AndoyerHamiltonian(avars)
    H.integrate(tmax)
    pvars = avars.to_Poincare()
    ps = pvars.particles
    if Nplanets == 3:
        m3 = logunif(r, 1.e-7, 1.e-4)
        pvarssorted = Poincare(G=pvars.G)

        if pair == "inner":
            eH = ((m2 + m3) / 3.)**(1. / 3.)
            beta = r.uniform(3.5, 30)
            a3 = a2 * (1 + beta * eH)
            ecross3 = (a3 - a2) / a3
            emin3 = m2 / ecross3**2
            e3 = logunif(r, emin3, ecross3)
            pvarssorted.add(m=ps[1].m,
                            M=ps[1].M,
                            a=ps[1].a,
                            e=ps[1].e,
                            gamma=ps[1].gamma,
                            l=ps[1].l)
            pvarssorted.add(m=ps[2].m,
                            M=ps[2].M,
                            a=ps[2].a,
                            e=ps[2].e,
                            gamma=ps[2].gamma,
                            l=ps[2].l)
            pvarssorted.add(m=m3,
                            M=1,
                            a=a3,
                            e=e3,
                            gamma=r.uniform(0, 2 * np.pi),
                            l=r.uniform(0, 2 * np.pi))

        elif pair == "outer":
            eH = ((m1 + m3) / 3.)**(1. / 3.)
            beta = r.uniform(3.5, 30)
            a3 = a1 / (1 + beta * eH)
            ecross3 = (a1 - a3) / a3
            emin3 = m1 / ecross3**2
            e3 = logunif(r, emin3, ecross3)
            pvarssorted.add(m=m3,
                            M=1,
                            a=a3,
                            e=e3,
                            gamma=r.uniform(0, 2 * np.pi),
                            l=r.uniform(0, 2 * np.pi))
            pvarssorted.add(m=ps[1].m,
                            M=ps[1].M,
                            a=ps[1].a,
                            e=ps[1].e,
                            gamma=ps[1].gamma,
                            l=ps[1].l)
            pvarssorted.add(m=ps[2].m,
                            M=ps[2].M,
                            a=ps[2].a,
                            e=ps[2].e,
                            gamma=ps[2].gamma,
                            l=ps[2].l)

        elif pair == "split":
            eH1 = ((m1 + m3) / 3.)**(1. / 3.)
            eH2 = ((m2 + m3) / 3.)**(1. / 3.)
            amin = a1 * (1 + 3.5 * eH1)
            amax = min(a1 * (1 + 30 * eH1), a2 / (1 + 3.5 * eH2))
            if amin > amax:
                seed += 900000
                return get_resonant(
                    seed=seed)  # draw new sample (may not be 'split')
            a3 = r.uniform(amin, amax)
            ecross3 = min((a3 - a1) / a1, (a2 - a3) / a3)
            emin3 = max(m1 / ((a3 - a1) / a3)**2, m2 / ((a2 - a3) / a3)**2)
            e3 = logunif(r, emin3, ecross3)
            pvarssorted.add(m=ps[1].m,
                            M=ps[1].M,
                            a=ps[1].a,
                            e=ps[1].e,
                            gamma=ps[1].gamma,
                            l=ps[1].l)
            pvarssorted.add(m=m3,
                            M=1,
                            a=a3,
                            e=e3,
                            gamma=r.uniform(0, 2 * np.pi),
                            l=r.uniform(0, 2 * np.pi))
            pvarssorted.add(m=ps[2].m,
                            M=ps[2].M,
                            a=ps[2].a,
                            e=ps[2].e,
                            gamma=ps[2].gamma,
                            l=ps[2].l)

        sim = pvarssorted.to_Simulation()
    else:
        sim = avars.to_Simulation()
    # add inclinations and scale s.t. a1 = 1, Mprimary=1. and G = 4*pi**2
    ps = sim.particles

    siminc = rebound.Simulation()
    siminc.G = 4 * np.pi**2

    dscale = ps[1].a
    tscale = ps[1].P
    mscale = siminc.G * dscale**3 / tscale**2  # ps[0].m + ps[1].m

    siminc.add(m=ps[0].m / mscale,
               x=ps[0].x / dscale,
               y=ps[0].y / dscale,
               vx=ps[0].vx / dscale * tscale,
               vy=ps[0].vy / dscale * tscale)
    for p in ps[1:]:
        siminc.add(m=p.m / mscale,
                   a=p.a / dscale,
                   e=p.e,
                   inc=logunif(r, 1.e-3, 1.e-1),
                   Omega=r.uniform(0, 2 * np.pi),
                   pomega=p.pomega,
                   l=p.l)
        rH = siminc.particles[-1].a * (siminc.particles[-1].m / 3. /
                                       siminc.particles[0].m)**(1. / 3.)
        siminc.particles[-1].r = rH
    siminc.move_to_com()
    siminc.integrator = "whfast"
    siminc.dt = 2. * np.sqrt(3) / 100. * siminc.particles[1].P
    siminc.ri_whfast.safe_mode = 0
    siminc.collision = "line"
    return siminc, j, k, pairindex, Zstar, libfac, Zcom
Exemple #11
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 def test_rebound_transformations(self):
     # averaging operation is not symmetric because have to use current
     # Lambdas to calculate correction. So turn off averaging for test
     pvars = Poincare.from_Simulation(self.sim, average=False)
     sim = pvars.to_Simulation(average=False)
     self.compare_simulations_orb(self.sim, sim, delta=1.e-14)
Exemple #12
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 def test_copy(self):
     pvars = Poincare.from_Simulation(self.sim)
     pvars2 = pvars.copy()
     self.compare_poincare_particles(
         pvars.particles, pvars2.particles)  # ignore nans in particles[0]