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fixed conflict on spatial dimensions and filtering

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This commit is contained in:
Edoardo Vergerio
2026-10-07 14:06:30 +02:00
parent bb2544954e
commit e1703ffdf0
4 changed files with 9 additions and 25 deletions
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single_converter_symm_ego.py
+5 -20
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@@ -88,7 +88,7 @@ def setup_optical_system()->pid.Simulation:
ms_max_avail_diameter=ms_max_available_diameter,
phase_mask_init_size=output_fiber_core_diameter/3,
opt_max_eval=opt_max_eval,
conic_filter_radius=1.0,
conic_filter_radius=1.5,
results_while_solving = False,
save_results = False,
)
@@ -299,7 +299,7 @@ def run_ego(initial_dataset, surrogate_model, n_ego_iter, xlimits, simulation):
y_pred_grid = np.zeros_like(d0_grid)
for i in range(d0_grid.shape[0]):
for j in range(d0_grid.shape[1]):
y_pred_grid[i,j] = sm.predict_values(np.atleast_2d([d0_grid[i,j], d1_grid[i,j]]))
y_pred_grid[i,j] = sm.predict_values(np.atleast_2d([d0_grid[i,j], d1_grid[i,j]]))[0,0]
contour = ax.contourf(d0_grid, d1_grid, y_pred_grid, levels=50, cmap='viridis')
fig.colorbar(contour, ax=ax, label='predicted overlap')
ax.scatter(xdoe_train_loaded[:,0], xdoe_train_loaded[:,1], color='blue', label='DOE Points')
@@ -328,21 +328,6 @@ def run_ego(initial_dataset, surrogate_model, n_ego_iter, xlimits, simulation):
y_opt = y_data[ind_best]
np.savetxt(f'{surrogate_folder_name}/ego_opt_results.txt', np.hstack((x_opt,y_opt)))
ims = []
fig = plt.figure(figsize=[10, 10])
ax = plt.gca()
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
for k in range(n_ego_iter):
image_pt = mpimg.imread(f"{surrogate_folder_name}/optimisation_{k}.pdf")
im = plt.imshow(image_pt)
ims.append([im])
ani = animation.ArtistAnimation(fig, ims, interval=500)
#save the animation to a gif file
ani.save(f'{surrogate_folder_name}/ego_optimization.gif', writer='pillow')
#plot of the EI history
fig, ax = plt.subplots(figsize=(8,6))
ax.plot(range(1, n_ego_iter+1), EI_history, marker='o')
@@ -459,8 +444,8 @@ if __name__ == "__main__":
n_ego_iter = 15 #number of EGO refinement iterations
corr_function_name = 'matern32'
doe_folder_name = 'DOE'
surrogate_folder_name = corr_function_name + '_surrogate_filtered'
doe_folder_name = 'DOE_1_5'
surrogate_folder_name = corr_function_name + '_surrogate_filtered_1_5'
if not os.path.exists(doe_folder_name):
os.makedirs(doe_folder_name)
if not os.path.exists(surrogate_folder_name):
@@ -486,4 +471,4 @@ if __name__ == "__main__":
#EVALUATE THE MODEL PERFORMANCE BY RUNNING A LOO CROSS-VALIDATION
refined_dataset = pickle.load(open(f'{surrogate_folder_name}/refined_dataset.pkl', 'rb'))
leave_one_out(refined_dataset, corr_function_name)
leave_one_out(refined_dataset, corr_function_name)