Can't run spectral_forced_turbulence due to jnp.linalg.norm error

[wagenaartje]

I have copied the code from spectral_forced_turbulence.ipynb, but it gives the following error:

---------------------------------------------------------------------------

UnfilteredStackTrace                      Traceback (most recent call last)

<timed exec> in <module>

[/usr/local/lib/python3.8/dist-packages/jax_cfd/base/initial_conditions.py](https://localhost:8080/#) in filtered_velocity_field(rng_key, grid, maximum_velocity, peak_wavenumber, iterations)
    110   # specified maximum velocity.
--> 111   return funcutils.repeated(project_and_normalize, iterations)(velocity)
    112 

28 frames

UnfilteredStackTrace: TypeError: jnp.linalg.norm requires ndarray or scalar arguments, got <class 'list'> at position 0.

The stack trace below excludes JAX-internal frames.
The preceding is the original exception that occurred, unmodified.

--------------------


The above exception was the direct cause of the following exception:

TypeError                                 Traceback (most recent call last)

<timed exec> in <module>

[/usr/local/lib/python3.8/dist-packages/jax/_src/numpy/util.py](https://localhost:8080/#) in _check_arraylike(fun_name, *args)
    343                     if not _arraylike(arg))
    344     msg = "{} requires ndarray or scalar arguments, got {} at position {}."
--> 345     raise TypeError(msg.format(fun_name, type(arg), pos))
    346 
    347 

TypeError: jnp.linalg.norm requires ndarray or scalar arguments, got <class 'list'> at position 0.

You can reproduce this with this Google Colab. It is also confusing that the Google Colab provided in the README does not install jax-cfd. What is the intended way of running them?

Edit: it seems that the jax-cfd version on PyPi is outdated. Downloading the source from the repository works.

[gideonite]

Edit: it seems that the jax-cfd version on PyPi is updated. Downloading the source from the repository works.

Does this mean that this is no longer an issue?

I dug into this a little bit and it seems that the problem lies with scaling the initial conditions to have the correct maximum velocity but if the latest code fixes this, then I would suggest closing this issue.

[wagenaartje]

Yes, the latest code fixes this but I would argue it is still an issue because it is not integrated in the version installed via pip. Especially because it was fixed about 3 months ago already (see commit a9e1c21).

[danielkelshaw]

Also ran into this issue when installing from PyPi. Had to fix the source code to make this work. Would be nice to be able to pip install a corrected version.