def test_laser_pusher():
"""Tests ExB drift for particles."""
S = initial("test_current", 0, 1378, 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.velocity_push(E)
p.position_push()
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)
def test_laser_pusher():
"""Tests ExB drift for particles."""
S = initial("test_current", 0, 1378, 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.velocity_push(E)
p.position_push()
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)
def test_transversal_current(init_pos, init_vx, expected):
S = initial("test_current", 0, number_cells, 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
error = error_table(investigated_density, expected)
print(pd.DataFrame({"indices": np.arange(9, 14)-2,
"found density":investigated_density,
"target density":expected,
"error %":error}))
assert np.allclose(investigated_density, expected, rtol=1e-2, atol=1e-3)
def test_longitudinal_current(init_pos, init_vx, target_density):
S = initial("test_current", 0, number_cells, 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 * lightspeed)
if init_vx:
investigated_density /= init_vx
error = error_table(investigated_density, target_density)
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 test_longitudinal_current_multiples_as_species(paramset):
expected_density = np.zeros(4)
S = initial("test_current", 0, number_cells, 0, 0, 0)
init_pos = np.array([params[0] for params in paramset]) * S.grid.dx
init_vx = np.array([params[1] for params in paramset]) * S.grid.c
for expected, v in zip([params[2] for params in paramset], init_vx):
expected_density += expected * v # TODO figure this out
spec = Species(-electric_charge, electron_rest_mass, 2, S.grid, scaling=npic)
spec.x = init_pos
spec.v[:,0] = init_vx
S.grid.list_species = [spec]
S.grid.gather_current([spec])
investigated_density = S.grid.current_density_x[9:13] / spec.eff_q
error = error_table(investigated_density, expected_density)
print("FINISHED. PARTICLE DATA")
print(pd.DataFrame({'x/dx': spec.x/S.grid.dx,
'v/c': spec.v[:,0]/spec.c}))
print("FINISHED. GRID DATA")
print(pd.DataFrame({"indices": np.arange(9, 13)-1,
"found density":investigated_density,
"target density":expected_density,
"error %":error}))
assert np.allclose(expected_density, investigated_density, rtol=1e-2, atol = 1e-3)
# coding=utf-8
from pythonpic import plotting_parser
from pythonpic.configs.run_laser import initial, impulse_duration, n_macroparticles, number_cells
args = plotting_parser("Hydrogen shield")
perturbation_amplitude = 0
powers = [21, 22, 23]
polarizations = ["Ey", "Circular"]
for power, number_particles, n_cells, polarization in [
[21, 75000, int(number_cells), "Ey"],
[21, 75000, int(number_cells), "Circular"],
[23, 75000, int(number_cells), "Ey"],
[23, 75000, int(number_cells), "Circular"],
]:
intensity = 10**power
s = initial(f"{number_particles}_{n_cells}_run_{power}_{polarization}", number_particles, n_cells, impulse_duration,
intensity, perturbation_amplitude,
laser_polarization=polarization).lazy_run().plots_3d(*args)
del s
save_data=False,
T=T,
scaling=scaling,
c=c).lazy_run()
static_plots.publication_plots(S, str(plot_folder / "ESE_energy_plot.pdf"),
[static_plots.electrostatic_energy_time_plots])
del S
S = run_coldplasma.initial(f"energy_plot_2",
qmratio=qmratio,
plasma_frequency=plasma_frequency,
NG=NG,
N_electrons=N_electrons,
epsilon_zero=epsilon_zero,
push_mode=push_mode,
save_data=False,
T=T * 10,
scaling=scaling,
c=c).lazy_run()
static_plots.publication_plots(S,
str(plot_folder / "ESE_energy_plot_long.pdf"),
[static_plots.electrostatic_energy_time_plots])
del S
S = run_laser.initial(f"75000_1378_run_21_Circular", n_macroparticles,
number_cells, impulse_duration, 1e21,
"Circular").lazy_run()
static_plots.publication_plots(
S, str(plot_folder / "preplazma.pdf"),
[time_snapshots.SpatialDistributionPlot]) # TODO fix
# coding=utf-8
"""Laser field propagation only"""
from pythonpic import plotting_parser
from pythonpic.configs.run_laser import initial, impulse_duration, n_macroparticles, plots, number_cells
args = plotting_parser("Hydrogen shield")
perturbation_amplitude = 0
number_particles = 10000
powers = range(23, 20, -1)
power = 23
intensity = 10**power
for number_particles, n_cells in [
[0, int(number_cells)], #
]:
s = initial(f"{number_particles}_{n_cells}_run_{power}_{perturbation_amplitude}", number_particles, n_cells, impulse_duration,
intensity, perturbation_amplitude).test_run()
plots(s, *args, frames="few")
del s
# coding=utf-8
from pythonpic import plotting_parser
from pythonpic.configs.run_laser import initial, impulse_duration, n_macroparticles
args = plotting_parser("Hydrogen shield")
perturbation_amplitude = 0
intensity = 1e22
ncells = [500, 1000, 1378, 1500, 1800, 2000]
scaling = 1
for n_cells in ncells:
s = initial(f"timing_run_ncells_{n_cells}", n_macroparticles, n_cells, impulse_duration, intensity, perturbation_amplitude).lazy_run().plots_3d(*args)
del s
ncells = 1378
nparticles = [0, 1000, 5000, 10000, 20000, 40000, 60000, 70000, 80000]
for n_particles in nparticles:
s = initial(f"timing_run_nparticles_{n_particles}", n_particles, ncells, impulse_duration, intensity, perturbation_amplitude).lazy_run().plots_3d(*args)
del s
# coding=utf-8
from pythonpic import plotting_parser
from pythonpic.configs.run_laser import initial, impulse_duration, n_macroparticles, number_cells
args = plotting_parser("Hydrogen shield")
perturbation_amplitude = 0
powers = [21, 22, 23]
polarizations = ["Ey", "Circular"]
for power, number_particles, n_cells, polarization in [
[21, 75000, int(number_cells), "Ey"],
[21, 75000, int(number_cells), "Circular"],
[23, 75000, int(number_cells), "Ey"],
[23, 75000, int(number_cells), "Circular"],
]:
intensity = 10**power
s = initial(f"{number_particles}_{n_cells}_run_{power}_{polarization}",
number_particles,
n_cells,
impulse_duration,
intensity,
perturbation_amplitude,
laser_polarization=polarization).lazy_run().plots_3d(*args)
del s
# coding=utf-8
from pythonpic import plotting_parser
from pythonpic.configs.run_laser import initial, impulse_duration, n_macroparticles
args = plotting_parser("Hydrogen shield")
perturbation_amplitude = 0
intensity = 1e22
ncells = [500, 1000, 1378, 1500, 1800, 2000]
scaling = 1
for n_cells in ncells:
s = initial(f"timing_run_ncells_{n_cells}", n_macroparticles, n_cells,
impulse_duration, intensity,
perturbation_amplitude).lazy_run().plots_3d(*args)
del s
ncells = 1378
nparticles = [0, 1000, 5000, 10000, 20000, 40000, 60000, 70000, 80000]
for n_particles in nparticles:
s = initial(f"timing_run_nparticles_{n_particles}", n_particles, ncells,
impulse_duration, intensity,
perturbation_amplitude).lazy_run().plots_3d(*args)
del s
# coding=utf-8
from pythonpic import plotting_parser
from pythonpic.configs.run_laser import (initial, impulse_duration,
n_macroparticles)
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 = initial(f"production_run_{intensity}_{scaling}",
n_macroparticles,
impulse_duration,
intensity,
perturbation_amplitude,
scaling).lazy_run().plots_3d(*args)
from pythonpic import plotting_parser
from pythonpic.configs import run_coldplasma, run_laser
from pythonpic.visualization import static_plots, time_snapshots
from pythonpic.configs.run_laser import initial, impulse_duration, n_macroparticles, number_cells
import pathlib
args = plotting_parser("Cold plasma oscillations")
plasma_frequency = 1
push_mode = 2
N_electrons = 1024
NG = 64
qmratio = -1
T = 10
scaling = 1
c = 10
epsilon_zero = 1
plot_folder = pathlib.Path("/home/dominik/Inzynierka/ThesisText/Images/")
S = run_coldplasma.initial(f"energy_plot", qmratio=qmratio, plasma_frequency=plasma_frequency, NG=NG,
N_electrons=N_electrons, epsilon_zero=epsilon_zero, push_mode=push_mode, save_data=False, T = T, scaling=scaling, c=c).lazy_run()
static_plots.publication_plots(S, str(plot_folder/"ESE_energy_plot.pdf"), [static_plots.electrostatic_energy_time_plots])
del S
S = run_coldplasma.initial(f"energy_plot_2", qmratio=qmratio, plasma_frequency=plasma_frequency, NG=NG,
N_electrons=N_electrons, epsilon_zero=epsilon_zero, push_mode=push_mode, save_data=False, T = T*10, scaling=scaling, c=c).lazy_run()
static_plots.publication_plots(S, str(plot_folder/"ESE_energy_plot_long.pdf"), [static_plots.electrostatic_energy_time_plots])
del S
S = run_laser.initial(f"75000_1378_run_21_Circular", n_macroparticles, number_cells, impulse_duration, 1e21, "Circular").lazy_run()
static_plots.publication_plots(S, str(plot_folder/"preplazma.pdf"), [time_snapshots.SpatialDistributionPlot]) # TODO fix