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When I use the scene file I generated in blender, the color can be displayed normally using preview, but it becomes black using render. This bothers me. Do I need to add appropriate lights when generating the scene file? Thank you for your attention.

While trying to add a custom scene, I got this error:

I tried to run Learning_Materials.ipynb with Sionna 0.16.2.
And, I found the following description in NVlabs/sionna#274.

(Breaking change) Removes the flags trainable_position and trainable_orientation from Transmitter and Receiver

So, I changed Learning_Materials.ipynb for Sionna 0.16.x.

before

# Create new trainable material with some default values
new_mat = RadioMaterial(mat.name + "_train",
                        relative_permittivity=3.0,
                        conductivity=0.1,
                        trainable_relative_permittivity=True,
                        trainable_conductivity=True)

after

# Create new trainable material with some default values
new_mat = RadioMaterial(mat.name + "_train",
                        relative_permittivity=3.0,
                        conductivity=0.1)

Test

https://github.com/NVlabs/diff-rt/blob/main/Learning_Materials.ipynb has training process.
And, this notebook has the following figure.

But, I could not reproduce with Sionna 0.16.2.

Environment

I read README.md.

Running this code requires Sionna 0.15 or later. To run the notebooks on your machine, you also need Jupyter. We recommend Ubuntu 20.04, Python 3.8, and TensorFlow 2.12.

So, I used the following environment.

• Ubuntu 20.04
• Python 3.8
• sionna 0.16.2
• tensorflow 2.12.0

while ray tracing, I was trying to visualize the path. But I received the error:

hi, l meet a problem while running learning_orientation.ipynb in jupyter notebook. Here is the problem:

TypeError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_34764\3417808883.py in
24
25 # Create a transmitter and add it to the scene
---> 26 tx = Transmitter("tx", position=[-232, 130, 25.0],
27 orientation=[0.0,0.0,0.0],
28 trainable_orientation=True) # Trainable orientation

TypeError: init() got an unexpected keyword argument 'trainable_orientation'

My platform is windows and the versions:
sionna: 0.16.2
tensorflow: 2.10.1
python:3.9.13

I did not change any code from the code you provide. Do you have any idea how to solve it?
Thank you!

Hi,
in the example learning_orientation, I wanted to be able to browse the scene so I decided to use scene.preview() instead of scene.render(cam).
However, doing so is not working properly as you can see below:

File ~/miniconda3/envs/sionna/lib/python3.8/site-packages/ipykernel/jsonutil.py:131, in <listcomp>(.0)
    128     obj = list(obj)
    130 if isinstance(obj, list):
--> 131     return [json_clean(x) for x in obj]
    133 if isinstance(obj, dict):
    134     # First, validate that the dict won't lose data in conversion due to
    135     # key collisions after stringification.  This can happen with keys like
    136     # True and 'true' or 1 and '1', which collide in JSON.
    137     nkeys = len(obj)

File ~/miniconda3/envs/sionna/lib/python3.8/site-packages/ipykernel/jsonutil.py:151, in json_clean(obj)
    148     return obj.strftime(ISO8601)
    150 # we don't understand it, it's probably an unserializable object
--> 151 raise ValueError("Can't clean for JSON: %r" % obj)

ValueError: Can't clean for JSON: [0.0, 0.0, 25.0]

Any idea?