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added k-fold cross validation in the EGO surrogate modeling. full_meta.ipynb implementes the full FDTD simulation domain (Tidy3D) for the device and produces some result plots in comparison to the ASM model

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Edoardo Vergerio
2026-08-28 16:10:53 +02:00
parent b9b64c05ab
commit 1e1f75c2bf
12 changed files with 12136 additions and 317 deletions
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metaprop_fibermode_doublet_sym.py
+39 -21
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@@ -1,14 +1,35 @@
import os
save_folder = "results_sym"
if not os.path.exists(save_folder):
os.makedirs(save_folder)
lock_file_path = f"{save_folder}/lock_file.lock"
if os.path.exists(lock_file_path):
with open(lock_file_path, "r") as lock_file:
lock_status = lock_file.read().strip()
if lock_status != "open":
print("A lock is preventing this script to run.")
exit(0)
elif lock_status == "open":
print("Lock is open. Continuing execution.")
else:
print("A lock file must exist before running.")
exit(0)
import time
import multiprocessing
import pyfftw
#pyFFTW setup
n_cpu = multiprocessing.cpu_count()
#n_cpu = multiprocessing.cpu_count()
n_cpu = 1
pyfftw.config.NUM_THREADS = n_cpu
pyfftw.interfaces.cache.enable()
pyfftw.config.PLANNER_EFFORT = 'FFTW_MEASURE'
pyfftw.interfaces.cache.disable()
pyfftw.config.PLANNER_EFFORT = 'FFTW_ESTIMATE'
import nlopt
nlopt.srand(42)
import numpy as np
import matplotlib.pyplot as plt
@@ -18,12 +39,6 @@ plt.rcParams.update({'font.size': 14})
from scipy.special import jv, kv
import os
save_folder = "results_sym"
if not os.path.exists(save_folder):
os.makedirs(save_folder)
##############################
#physics and simulation domain
wavelength = 1.55e-6
@@ -39,7 +54,7 @@ k0 = 2 * np.pi / lda0
k1 = 2 * np.pi / lda1
k2 = 2 * np.pi / lda2
opt_max_eval = 200
opt_max_eval = 150
unit_cell_pitch = 700e-9 #equivalent to spatial sampling
@@ -73,9 +88,9 @@ rho = np.sqrt(X**2 + Y**2)
sampling_period = xs[1] - xs[0]
d0 = 353e-6 #propagation distance: source - MS1 [m]
d0 = 476e-6 #propagation distance: source - MS1 [m]
d_source = d0 - lda0 / 2 #propagation distance: source - MS1 used for FDTD simulations [m]
d1 = 218e-6 #propagation distance: MS1 - MS2 [m]
d1 = 510e-6 #propagation distance: MS1 - MS2 [m]
d2 = d0 #propagation distance: MS2 - target [m]
phase_min = 0
@@ -89,7 +104,7 @@ beam_waist = 5.2e-6 #[um]
output_fiber_core_diameter = 19e-6 #[um]
#fibre cladding diameter
fibre_cladding_diameter = 125e-6 #[um]
max_available_diameter = 122e-6
max_available_diameter = 122e-6 #[um]
##############################
##############################
@@ -98,15 +113,18 @@ fft_input_array = pyfftw.empty_aligned((Nx, Ny), dtype='complex128', n=16)
fft_output_array = pyfftw.empty_aligned((Nx, Ny), dtype='complex128', n=16)
ifft_input_array = pyfftw.empty_aligned((Nx, Ny), dtype='complex128', n=16)
ifft_output_array = pyfftw.empty_aligned((Nx, Ny), dtype='complex128', n=16)
fft_operator = pyfftw.FFTW(fft_input_array, fft_output_array, axes=(0,1), direction='FFTW_FORWARD', threads=n_cpu, flags=('FFTW_MEASURE','FFTW_DESTROY_INPUT',))
ifft_operator = pyfftw.FFTW(ifft_input_array, ifft_output_array, axes=(0,1), direction='FFTW_BACKWARD', threads=n_cpu, flags=('FFTW_MEASURE','FFTW_DESTROY_INPUT',))
fft_input_array.fill(0)
fft_output_array.fill(0)
ifft_input_array.fill(0)
ifft_output_array.fill(0)
fft_operator = pyfftw.FFTW(fft_input_array, fft_output_array, axes=(0,1), direction='FFTW_FORWARD', threads=n_cpu, flags=('FFTW_ESTIMATE',))
ifft_operator = pyfftw.FFTW(ifft_input_array, ifft_output_array, axes=(0,1), direction='FFTW_BACKWARD', threads=n_cpu, flags=('FFTW_ESTIMATE',))
##############################
##############################
#setting up spatial frequencies
ks = 2 * np.pi / sampling_period
kappas = np.arange(-Nx//2, Nx//2) * ks / Nx
kappas = np.arange(-Nx//2+1, Nx//2+1) * ks / Nx
KX, KY = np.meshgrid(kappas, kappas)
K_parallel = np.sqrt(KX**2 + KY**2)
nu_parallel = K_parallel / (2 * np.pi)
@@ -443,13 +461,14 @@ make_2Dplot_of(source_field_2d, choose_quantity="phase", save_name="source_field
###########################
#initialize input field (propagated source field)
input_field = propagate_source(source_field)
input_field_2d = input_field.reshape((Nx, Ny)) #reshape to 2D for plotting
#save the input field to numpy array
np.save(f"{save_folder}/input_field_{d0}_{d1}.npy", input_field_2d)
#propagate the source field to the plane just before MS1 and save it to a numpy array, to be used in FDTD simulations
input_field_before_MS1 = propagate_source_before_MS1(source_field)
np.save(f"{save_folder}/input_field_before_MS1.npy", input_field_before_MS1.reshape((Nx, Ny)))
input_field_2d = input_field.reshape((Nx, Ny)) #reshape to 2D for plotting
#save the input field to numpy array
np.save(f"{save_folder}/input_field.npy", input_field_2d)
#input field integrated intensity
input_field_intensity = np.sum(np.abs(input_field)**2)
print("Input field integrated intensity: %.4e" % input_field_intensity)
@@ -475,7 +494,6 @@ make_2Dplot_of(target_Efield_2d, choose_quantity="phase", save_name="target_fiel
###########################
#initialize the normalized phase masks and global phase mask
w_norm = np.zeros((2*S)) #concatenated normalized parameters for both masks
rho = np.sqrt(X**2 + Y**2)
circular_mask_1 = np.where(rho.flatten() < output_fiber_core_diameter/3, 1, 0)
#w_norm[:S] += circular_mask_1