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#!/usr/bin/env python3
# Copyright 2021 Prabhat Kumar, Remi Lehe
#
# This file is part of WarpX.
#
# License: BSD-3-Clause-LBNL
# This file is part of the WarpX automated test suite. Its purpose is to test the
# injection of a Gaussian laser pulse from an antenna in a 1D simulation.
# The test calculates the envelope of each component of the laser pulse at the end of
# the simulation and it compares it with theory. It also checks that the
# central frequency of the Fourier transform is the expected one.
import sys
import matplotlib
import yt
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
from scipy.signal import hilbert
sys.path.insert(1, '../../../../warpx/Regression/Checksum/')
import checksumAPI
# Maximum acceptable error for this test
relative_error_threshold = 0.05
# A small number
small_num = 1.0e-8
# Physical parameters
um = 1.e-6
fs = 1.e-15
c = 299792458
# Parameters of the gaussian beam
wavelength = 1.*um
w0 = 5.*um
tt = 10.*fs
t_c = 24.*fs
E_max = 4e12
# laser direction
dir_vector = np.array([0,0,1.0])
dir_vector /= np.linalg.norm(dir_vector)
# polarization vector
pol_vector = np.array([1.0,1.0,0.0])
pol_vector /= np.linalg.norm(pol_vector)
# Calculates the envelope of a Gaussian beam
def gauss_env(T,Z):
'''Function to compute the theory for the envelope
'''
inv_tau2 = 1./tt/tt
exp_arg = - inv_tau2 / c/c * (Z-T*c)*(Z-T*c)
return E_max * np.real(np.exp(exp_arg))
# Checks envelope and central frequency for a given laser component
def check_component(data, component, t_env_theory, coeff,Z,dz):
print("*** Checking " + component + " ***")
field = data['boxlib', component].v.squeeze()
env = abs(hilbert(field))
env_theory = t_env_theory*np.abs(coeff)
# Plot results
fig = plt.figure(figsize=(12,6))
ax1 = fig.add_subplot(221)
ax1.set_title('PIC field')
ax1.plot(Z,field)
ax2 = fig.add_subplot(222)
ax2.set_title('PIC envelope')
ax2.plot(Z,env)
ax3 = fig.add_subplot(223)
ax3.set_title('Theory envelope')
ax3.plot(Z,env_theory, label="theory")
ax3.plot(Z,env, label="simulation")
ax3.legend(loc="upper right")
ax4 = fig.add_subplot(224)
ax4.set_title('Difference')
ax4.plot(Z,env-env_theory)
plt.tight_layout()
plt.savefig("plt_" + component + ".png", bbox_inches='tight')
if(np.abs(coeff) < small_num):
is_field_zero = np.sum(np.abs(env)) < small_num
if is_field_zero :
print("[OK] Field component expected to be 0 is ~ 0")
else :
print("[FAIL] Field component expected to be 0 is NOT ~ 0")
assert(is_field_zero)
print("******\n")
return
fft_field = np.fft.fft(field)
freq_cols = np.fft.fftfreq(fft_field.shape[0],dz/c)
pos_max = np.unravel_index(np.abs(fft_field).argmax(), fft_field.shape)
freq = np.abs(freq_cols[pos_max[0]])
exp_freq = c/wavelength
relative_error_freq = np.abs(freq-exp_freq)/exp_freq
is_freq_ok = relative_error_freq < relative_error_threshold
if is_freq_ok :
print("[OK] Relative error frequency: {:6.3f} %".format(relative_error_freq*100))
else :
print("[FAIL] Relative error frequency: {:6.3f} %".format(relative_error_freq*100))
assert(is_freq_ok)
print("******\n")
relative_error_env = np.sum(np.abs(env-env_theory)) / np.sum(np.abs(env_theory))
is_env_ok = relative_error_env < relative_error_threshold
if is_env_ok :
print("[OK] Relative error envelope: {:6.3f} %".format(relative_error_env*100))
else :
print("[FAIL] Relative error envelope: {:6.3f} %".format(relative_error_env*100))
assert(is_env_ok)
def check_laser(filename):
ds = yt.load(filename)
# yt 4.0+ has rounding issues with our domain data:
# RuntimeError: yt attempted to read outside the boundaries
# of a non-periodic domain along dimension 0.
if 'force_periodicity' in dir(ds): ds.force_periodicity()
z = np.linspace(
ds.domain_left_edge[0].v,
ds.domain_right_edge[0].v,
ds.domain_dimensions[0])
dz = (ds.domain_right_edge[0].v-ds.domain_left_edge[0].v)/(ds.domain_dimensions[0]-1)
# Compute the theory for envelope
env_theory = gauss_env(+t_c-ds.current_time.to_value(),z)+gauss_env(-t_c+ds.current_time.to_value(),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)
b_vector = np.cross(dir_vector, pol_vector)
components = ["Ex", "Ey", "Ez", "Bx", "By", "Bz"]
coeffs = [
pol_vector[0],
pol_vector[1],
pol_vector[2],
b_vector[0],
b_vector[1],
b_vector[2]]
field_facts = [1, 1, 1, 1/c, 1/c, 1/c]
for comp, coeff, field_fact in zip(components, coeffs, field_facts):
check_component(all_data_level_0, comp, field_fact*env_theory, coeff, z, dz)
def main():
filename_end = sys.argv[1]
check_laser(filename_end)
test_name = filename_end[:-9] # Could also be os.path.split(os.getcwd())[1]
checksumAPI.evaluate_checksum(test_name, filename_end)
if __name__ == "__main__":
main()
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