wo.plot_multicolumn([target[:,:,z_layer], azimuth[:,:,z_layer]%(2*np.pi), inclination[:,:,z_layer]], origin='lower', size=5, num_col=3, titles=[f'target, z={z_layer}', 'azimuth', 'inclination'], set_title = True)
#### XZ sections
wo.plot_multicolumn([np.transpose(target[y_layer,:,:]), np.transpose(azimuth[y_layer,:,:])%(2*np.pi), np.transpose(inclination[y_layer,:,:])], origin='lower', size=5, num_col=3, titles=['retardance', 'azimuth', 'inclination'], set_title = True)
plt.show()
#### Principal retardance and 3D orientation in color
orientation_3D_image = np.transpose(np.array([azimuth%(2*np.pi)/2/np.pi, inclination, np.clip((ne_map-no_map)*psz*2*np.pi/lambda_illu/np.pi/2*lambda_illu*1e3,0, 1.5)/1.5]),(3,1,2,0))
orientation_3D_image_RGB = wo.orientation_3D_to_rgb(orientation_3D_image, interp_belt = 20/180*np.pi, sat_factor = 1)
plt.figure(figsize=(10,10))
plt.imshow(orientation_3D_image_RGB[z_layer], origin='lower')
plt.figure(figsize=(10,10))
plt.imshow(orientation_3D_image_RGB[:,y_layer], origin='lower')
plt.figure(figsize=(3,3))
wo.orientation_3D_colorwheel(wheelsize=128, circ_size=50, interp_belt=20/180*np.pi, sat_factor=1, discretize=True)
plt.show()
#### Angular histogram of 3D orientation
wo.orientation_3D_hist(azimuth.flatten(), \
inclination.flatten(), \
np.abs(target).flatten(),\
bins=36, num_col=1, size=10, contour_level = 100, hist_cmap='gnuplot2', top_hemi=True)
plt.show()
## Compute permittivity and scattering potential tensors
### assign the permittivity tensor according to the sample properties
epsilon_mean = (ne_map**2 + no_map**2)/2
epsilon_del = (ne_map**2 - no_map**2)/2
]), (3, 1, 2, 0))
orientation_3D_image_RGB = wo.orientation_3D_to_rgb(orientation_3D_image,
interp_belt=20 / 180 *
np.pi,
sat_factor=1)
plt.figure(figsize=(15, 15))
plt.imshow(orientation_3D_image_RGB[z_layer], origin='lower')
plt.figure(figsize=(15, 15))
plt.imshow(orientation_3D_image_RGB[:, y_layer],
origin='lower',
aspect=z_step / ps)
# plot the top view of 3D orientation colorsphere
plt.figure(figsize=(3, 3))
wo.orientation_3D_colorwheel(wheelsize=256,
circ_size=50,
interp_belt=20 / 180 * np.pi,
sat_factor=1)
plt.show()
# ### Render 3D orientation with 2 channels (in-plane orientation and out-of-plane tilt)
# in-plane orientation
from matplotlib.colors import hsv_to_rgb
I_hsv = np.transpose(
np.array([
(azimuth[0]) % np.pi / np.pi,
np.ones_like(retardance_pr_PT[0]),
(np.clip(np.abs(retardance_pr_PT[0]), ret_min_color, ret_max_color) -
ret_min_color) / (ret_max_color - ret_min_color)
]), (3, 1, 2, 0))
in_plane_orientation = hsv_to_rgb(I_hsv.copy())
