qL = numpy.array([rhoL, 0, vyL, vzL, epsL, Bx, ByL, BzL, 0, 0, 0, 0, 0])
qR = numpy.array([rhoR, 0, vyR, vzR, epsR, Bx, ByR, BzR, 0, 0, 0, 0, 0])
sigma_s = [0, 10, 10**2, 10**3, 10**6] # Can even do 10^9 now
Bys = []
for sigma in sigma_s:
model = sr_rmhd.sr_rmhd_gamma_law(initial_data=sr_rmhd.initial_riemann(
qL, qR),
gamma=gamma,
sigma=sigma)
fast_source = model.relaxation_source()
sim = simulation(model,
interval,
fvs_method(2),
imex222(fast_source),
outflow,
cfl=0.25)
sim.evolve(0.4)
print("sigma={}".format(sigma))
sim.plot_system()
pyplot.show()
Bys.append(sim.cons[6, :].copy())
fig = pyplot.figure()
ax = fig.add_subplot(111)
ax.set_prop_cycle=cycler('color', ['red','green','blue','yellow','cyan']) + \
cycler('linestyle', ['-', '--', '-.', ':', '--'])
for sigma, By in zip(sigma_s, Bys):
ax.plot(sim.coordinates, By, label=r"$\sigma={}$".format(sigma))
ax.set_xlabel(r"$x$")
ax.set_ylabel(r"$B_y$")
m_p = 1.
m_e = 1.
gamma = 4.0 / 3.0
model_mf = sr_mf.sr_mf_gamma_law(initial_data=sr_mf.initial_alfven(
gamma=gamma, Kappa_f=1e80),
gamma=gamma,
kappa_m=0.05066059182116889,
kappa_f=1.0e80,
kappa_q=1.0)
fast_source_mf = model_mf.relaxation_source()
#timestepper = rk_backward_euler_split(rk3, fast_source_mf)
#timestepper = rk_euler_split(rk3, fast_source_mf)
#timestepper = rk3
timestepper = imex222(fast_source_mf)
#timestepper = imex433(fast_source_mf)
sim_mf = simulation(model_mf,
interval,
fvs_method(2),
timestepper,
periodic,
cfl=0.25)
sim_mf.evolve(0.0025)
import numpy
De = numpy.loadtxt('test100/dens_e.x.asc')
Se_x = numpy.loadtxt('test100/scon_e[0].x.asc')
Se_y = numpy.loadtxt('test100/scon_e[1].x.asc')
Se_z = numpy.loadtxt('test100/scon_e[2].x.asc')
from models import relaxation_burgers
from bcs import outflow
from simulation import simulation
from methods import weno3_upwind, vanleer_upwind
from rk import imex222
from grid import grid
from matplotlib import pyplot
Ngz = 4
Npoints = 100
tau = 1.0
tau2 = 0.001
L = 1
interval = grid([-L, L], Npoints, Ngz)
qL = numpy.array([1.0, 0.5])
qR = numpy.array([0.0, 0.0])
model = relaxation_burgers.relaxation_burgers(
initial_data=relaxation_burgers.initial_riemann(qL, qR), a=0.9)
source = relaxation_burgers.relaxation_source(tau)
source2 = relaxation_burgers.relaxation_source(tau2)
sim = simulation(model, interval, vanleer_upwind, imex222(source), outflow)
sim.evolve(0.5)
sim.plot_system()
pyplot.show()
sim2 = simulation(model, interval, vanleer_upwind, imex222(source2), outflow)
sim2.evolve(0.5)
sim2.plot_system()
pyplot.show()
])
qR = numpy.array([
rhoR_e, 0, 0, 0, epsR, rhoR_p, 0, 0, 0, epsR, Bx, ByR, BzR, 0, 0, 0, 0, 0
])
model_mf = sr_mf.sr_mf_gamma_law(initial_data=sr_mf.initial_riemann(qL, qR),
gamma=gamma,
kappa_m=kappa_m,
kappa_f=kappa_f,
kappa_q=kappa_q)
fast_source_mf = model_mf.relaxation_source()
sim_mf = simulation(model_mf,
interval,
fvs_method(2),
imex222(fast_source_mf),
outflow,
cfl=0.25)
qL = numpy.array([rhoL, 0, 0, 0, epsL, Bx, ByL, BzL, 0, 0, 0, 0, 0])
qR = numpy.array([rhoR, 0, 0, 0, epsR, Bx, ByR, BzR, 0, 0, 0, 0, 0])
#model_rmhd = sr_rmhd.sr_rmhd_gamma_law(initial_data = sr_rmhd.initial_riemann(qL, qR),
# gamma=gamma)
#fast_source_rmhd = model_rmhd.relaxation_source()
#
#sim_rmhd = simulation(model_rmhd, interval, fvs_method(2), imex222(fast_source_rmhd),
# outflow, cfl=0.25)
sim_mf.evolve(0.4)
#