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#!/usr/bin/python3
#ADD COMMENT
#ADD COMMENT
import yt ; yt.funcs.mylog.setLevel(50)
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hilbert
import glob
import os
#Maximum acceptable error for this test
relative_error_threshold = 0.06
#Physical parameters
um = 1.e-6
fs = 1.e-15
c = 299792458
#Parameters of the gaussian beam
wavelength = 1.*um
w0 = 6.*um
tt = 10.*fs
x_c = 0.*um
t_c = 20.*fs
foc_dist = 10*um
E_max = 1e12
rot_angle = -np.pi/4.0
#Parameters of the tx grid
x_l = -12.0*um
x_r = 12.0*um
x_points = 480
t_l = 0.0*fs
t_r = 40.0*fs
t_points = 400
tcoords = np.linspace(t_l, t_r, t_points)
xcoords = np.linspace(x_l, x_r, x_points)
def gauss(T,X,Y,opt):
k0 = 2.0*np.pi/wavelength
inv_tau2 = 1./tt/tt
osc_phase = k0*c*(T-t_c)
diff_factor = 1.0 + 1.0j* foc_dist * 2/(k0*w0*w0)
inv_w_2 = 1.0/(w0*w0*diff_factor)
pre_fact = np.exp(1.0j * osc_phase)
if opt == '3d':
pre_fact = pre_fact/diff_factor
else:
pre_fact = pre_fact/np.sqrt(diff_factor)
exp_arg = - (X*X + Y*Y)*inv_w_2 - inv_tau2 * (T-t_c)*(T-t_c)
return np.real(pre_fact * np.exp(exp_arg))
# Function for the envelope
def gauss_env(T,XX,ZZ):
X = np.cos(rot_angle)*XX + np.sin(rot_angle)*ZZ
Z = -np.sin(rot_angle)*XX + np.cos(rot_angle)*ZZ
inv_tau2 = 1./tt/tt
inv_w_2 = 1.0/(w0*w0)
exp_arg = - (X*X)*inv_w_2 - inv_tau2 / c/c * (Z-T*c)*(Z-T*c)
return E_max * np.real(np.exp(exp_arg))
def write_file(fname, x, y, t, E):
with open(fname, 'wb') as file:
flag_unif = 0
file.write(flag_unif.to_bytes(1, byteorder='little'))
file.write((len(t)).to_bytes(4, byteorder='little', signed=False))
file.write((len(x)).to_bytes(4, byteorder='little', signed=False))
file.write((len(y)).to_bytes(4, byteorder='little', signed=False))
file.write(t.tobytes())
file.write(x.tobytes())
file.write(y.tobytes())
file.write(E.tobytes())
def write_file_unf(fname, x, y, t, E):
with open(fname, 'wb') as file:
flag_unif = 1
file.write(flag_unif.to_bytes(1, byteorder='little'))
file.write((len(t)).to_bytes(4, byteorder='little', signed=False))
file.write((len(x)).to_bytes(4, byteorder='little', signed=False))
file.write((len(y)).to_bytes(4, byteorder='little', signed=False))
file.write(t[0].tobytes())
file.write(t[-1].tobytes())
file.write(x[0].tobytes())
file.write(x[-1].tobytes())
file.write(y[0].tobytes())
file.write(y[-1].tobytes())
file.write(E.tobytes())
def create_gaussian_2d():
T, X, Y = np.meshgrid(tcoords, xcoords, np.array([0.0]), indexing='ij')
E_t = gauss(T,X,Y,'2d')
write_file("gauss_2d.txye", xcoords, np.array([0.0]), tcoords, E_t)
write_file_unf("gauss_2d_unf.txye", xcoords, np.array([0.0]), tcoords, E_t)
def do_analysis(fname, compname, steps):
ds = yt.load(fname)
dt = ds.current_time.to_value()/steps
# Define 2D meshes
x = np.linspace(
ds.domain_left_edge[0],
ds.domain_right_edge[0],
ds.domain_dimensions[0]).v
z = np.linspace(
ds.domain_left_edge[ds.dimensionality-1],
ds.domain_right_edge[ds.dimensionality-1],
ds.domain_dimensions[ds.dimensionality-1]).v
X, Z = np.meshgrid(x, z, sparse=False, indexing='ij')
# Compute the theory for envelope
env_theory = gauss_env(+t_c-ds.current_time.to_value(), X,Z)+gauss_env(-t_c+ds.current_time.to_value(), X,Z)
# Read laser field in PIC simulation, and compute envelope
all_data_level_0 = ds.covering_grid(level=0,left_edge=ds.domain_left_edge, dims=ds.domain_dimensions)
F_laser = all_data_level_0['boxlib', 'Ey'].v.squeeze()
env = abs(hilbert(F_laser))
extent = [ds.domain_left_edge[ds.dimensionality-1], ds.domain_right_edge[ds.dimensionality-1],
ds.domain_left_edge[0], ds.domain_right_edge[0] ]
# Plot results
plt.figure(figsize=(8,6))
plt.subplot(221)
plt.title('PIC field')
plt.imshow(F_laser, extent=extent)
plt.colorbar()
plt.subplot(222)
plt.title('PIC envelope')
plt.imshow(env, extent=extent)
plt.colorbar()
plt.subplot(223)
plt.title('Theory envelope')
plt.imshow(env_theory, extent=extent)
plt.colorbar()
plt.subplot(224)
plt.title('Difference')
plt.imshow(env-env_theory, extent=extent)
plt.colorbar()
plt.tight_layout()
plt.savefig(compname, bbox_inches='tight')
relative_error_env = np.sum(np.abs(env-env_theory)) / np.sum(np.abs(env))
print("Relative error envelope: ", relative_error_env)
assert(relative_error_env < relative_error_threshold)
fft_F_laser = np.fft.fft2(F_laser)
freq_rows = np.fft.fftfreq(F_laser.shape[0],dt)
freq_cols = np.fft.fftfreq(F_laser.shape[1],dt)
pos_max = np.unravel_index(np.abs(fft_F_laser).argmax(), fft_F_laser.shape)
freq = np.sqrt((freq_rows[pos_max[0]])**2 + (freq_cols[pos_max[1]]**2))
exp_freq = c/wavelength
relative_error_freq = np.abs(freq-exp_freq)/exp_freq
print("Relative error frequency: ", relative_error_freq)
assert(relative_error_freq < relative_error_threshold)
def launch_analysis(executable):
create_gaussian_2d()
os.system("./" + executable + " inputs.2d_test_txye")
do_analysis("diags/plotfiles/plt00250/", "comp_unf.pdf", 250)
os.system("sed 's/gauss_2d_unf.txye/gauss_2d.txye/g' inputs.2d_test_txye > inputs.2d_test_txye_non_unf")
os.system("./" + executable + " inputs.2d_test_txye_non_unf")
do_analysis("diags/plotfiles/plt00250/", "comp_non_unf.pdf", 250)
def main() :
executables = glob.glob("main2d*")
if len(executables) == 1 :
launch_analysis(executables[0])
else :
assert(False)
if __name__ == "__main__":
main()
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