def test_transversal_current(init_pos, init_vx, expected):
S = laser("test_current", 0, 0, 0, 0)
print(f"dx: {S.grid.dx}, dt: {S.grid.dt}, Neuler: {S.grid.NG}")
init_vy = 0.01
p = Particle(S.grid,
init_pos * S.grid.dx,
init_vx * lightspeed,
init_vy * lightspeed,
q=-electric_charge,
m=electron_rest_mass,
scaling=npic)
S.grid.list_species = [p]
S.grid.gather_current([p])
investigated_density = S.grid.current_density_yz[
9:14, 0] / p.eff_q / init_vy / lightspeed
target_density = expected
error = (investigated_density - target_density) * 100
error[investigated_density != 0] /= investigated_density[
investigated_density != 0]
print(
pd.DataFrame({
"indices": np.arange(9, 14) - 2,
"found density": investigated_density,
"target density": target_density,
"error %": error
}))
assert np.allclose(investigated_density,
target_density,
rtol=1e-2,
atol=1e-3)
def test_longitudinal_current(init_pos, init_vx, expected):
S = laser("test_current", 0, 0, 0, 0)
print(f"dx: {S.grid.dx}, dt: {S.grid.dt}, Neuler: {S.grid.NG}")
p = Particle(S.grid,
init_pos * S.grid.dx,
init_vx * lightspeed,
q=-electric_charge,
m=electron_rest_mass,
scaling=npic)
S.grid.list_species = [p]
S.grid.gather_current([p])
investigated_density = S.grid.current_density_x[9:13] / (
p.eff_q * init_vx * lightspeed)
if init_vx == 0.0:
investigated_density[...] = 0
target_density = expected
error = (investigated_density - target_density) / target_density * 100
error[(investigated_density - target_density) == 0] = 0
print(
pd.DataFrame({
"indices": np.arange(9, 13) - 1,
"found density": investigated_density,
"target density": target_density,
"error %": error
}))
assert np.allclose(target_density,
investigated_density,
rtol=1e-2,
atol=1e-3)
def run():
perturbation_amplitude = 0
number_particles = 10000
power = 21
intensity = 10**power
s = laser(f"{number_particles}_run_{power}_{perturbation_amplitude}",
number_particles, impulse_duration, intensity,
perturbation_amplitude).run()
return s
def test_laser_pusher():
S = laser("test_current", 0, 0, 0, 0)
p = Particle(S.grid,
9.45*S.grid.dx,
0,
0,
q=-electric_charge,
m=electron_rest_mass,
scaling=npic)
S.grid.list_species = [p]
Ev, Bv = (np.array([[0, 1.228e12, 0]]), np.array([[0,0,4.027e3]]))
E = lambda x: (Ev, Bv)
p.push(E)
print(p.v)
expected_u = np.array([[5.089e4, -5.5698e6, 0]]) # this is u!
expected_v = expected_u #* gamma_from_u(expected_u, S.grid.c)
print(expected_v)
print((p.v - expected_v)[0,:2] / p.v[0,:2] * 100, "%")
# print(f"vx:{a:.9e}\n"
# f"vy:{b:.9e}\n"
# f"vz:{c:.9e}\n"
# f"KE:{e:.9e}\n")
assert np.allclose(expected_v, p.v, atol=1e-1, rtol=1e-2)
# coding=utf-8
from pythonpic import plotting_parser
from pythonpic.configs.run_laser import laser, impulse_duration, n_macroparticles, plots
args = plotting_parser("Hydrogen shield")
perturbation_amplitude = 0
number_particles = 10000
powers = range(23, 20, -1)
for power in powers:
intensity = 10**power
s = laser(f"{number_particles}_run_{power}_{perturbation_amplitude}",
number_particles, impulse_duration, intensity,
perturbation_amplitude).lazy_run()
if any(args):
plots(s, *args, frames="few")
# coding=utf-8
from pythonpic import plotting_parser
from pythonpic.configs.run_laser import laser, impulse_duration, n_macroparticles, plots
args = plotting_parser("Hydrogen shield")
perturbation_amplitude = 0
number_particles = 10000
powers = range(23, 20, -1)
for power in powers:
intensity = 10**power
s = laser(f"production_run_{power}_{perturbation_amplitude}", n_macroparticles, impulse_duration, intensity, perturbation_amplitude).lazy_run()
if any(args):
plots(s, *args, frames="all")
del s
# s = laser("production_run_nolaser_e-3", n_macroparticles, impulse_duration, 0, perturbation_amplitude).lazy_run()
# plots(s, *args, frames="few")
# s = laser("field_only", 0, impulse_duration, 1e21, perturbation_amplitude).lazy_run()
# plots(s, *args, frames="few")
# coding=utf-8
from pythonpic import plotting_parser
from pythonpic.configs.run_laser import laser, impulse_duration, n_macroparticles, plots
args = plotting_parser("Hydrogen shield")
perturbation_amplitude = 0
intensities = [5e20, 1e21, 5e21, 1e21, 5e21, 1e22, 5e22, 1e23]
scalings = [0.5, 0.9, 1, 1.1, 1.5]
for intensity in intensities:
for scaling in scalings:
s = laser(f"production_run_{intensity}_{scaling}", n_macroparticles,
impulse_duration, intensity, perturbation_amplitude,
scaling).lazy_run()
if any(args):
plots(s, *args, frames="few")
del s