Sionna Utils - Sionna's missing pieces, your unofficial Sionna toolkit

[mlouielu]

Repo: https://github.com/mlouielu/sionna-utils

Introduction

This package sionna_utils aim to provide some utility functions to help user to adapt and debug issues on Sionna.

Examples

Export scene to a standalone HTML file for 3D preview

import sionna.rt
import sionna_utils

scene = sionna.rt.load_scene(sionna.rt.scene.munich)

# You can pass arguments for Scene.preview(), such as paths=paths
sionna_utils.utils.scene_export_html(
    scene, "preview.html", show_orientations=True
)

Add a coordinate frame in the scene

import sionna.rt
import sionna_utils

scene = sionna.rt.load_scene(sionna.rt.scene.munich)

sionna_utils.geometry.create_coordinate_frame(
    scene, scale=100.0, position=[0, 0, 0])

sionna_utils.utils.scene_export_html(
    scene, "preview.html", show_orientations=True
)

Fine-grain mask on paths object

Let's say if you want to visualize the paths, but only want to visualize the paths that are 3-bounce path, you can combine
sionna_utils.paths.get_paths_hit_sequence() and sionna_utils.paths.get_path_depths() to get the exact paths to visualize it:

import numpy as np

import sionna.rt
import mitsuba as mi
import sionna_utils
from sionna.rt import PlanarArray, Transmitter, Receiver, PathSolver

scene = sionna.rt.load_scene(sionna.rt.scene.floor_wall)
scene.tx_array = PlanarArray(
    num_rows=1,
    num_cols=2,
    pattern="tr38901",
    polarization="V",
)

# Configure antenna array for all receivers
scene.rx_array = PlanarArray(
    num_rows=1,
    num_cols=3,
    pattern="dipole",
    polarization="cross",
)

dist = 3
d = float(dist / np.sqrt(2))
scene.add(Transmitter(name="tx", position=[-d, 0, d]))
scene.add(Receiver(name="rx", position=[d, 0, d]))


for name, obj in scene.objects.items():
    obj.radio_material.scattering_coefficient = 0.1
    print(name, obj.object_id)


sionna_utils.geometry.create_coordinate_frame(scene, position=[0, 0, 0])

p_solver = PathSolver()
paths = p_solver(
    scene,
    max_depth=3,
    los=False,
    specular_reflection=True,
    diffuse_reflection=True,
    synthetic_array=False,
    seed=42,
)


depth_mask = sionna_utils.paths.get_path_depths(paths)
seq_mask = sionna_utils.paths.get_paths_hit_sequence(paths, [1, 2, 1], "per_link")
paths._valid = mi.TensorXb(paths.valid.numpy() & seq_mask & (depth_mask == 3))

sionna_utils.utils.scene_export_html(
    scene, "preview.html", show_orientations=True, paths=paths
)