This page includes some tips for troubleshooting issues that you might run into when using jaxoplanet. This is a work-in-progress, so if you don’t see your issue listed here, feel free to open an issue on the GitHub repository issue tracker.

NaNs and infinities#

It’s not that uncommon to hit NaNs or infinities when using jax and jaxoplanet. This is often caused by numerical precision issues, and this can be exacerbated by the fact that, by default, jax disables double precision calculations. You can enable double precision a few different ways as described in the jax docs, and the way we do it in these docs is to add the following, when necessary:

import jax

jax.config.update("jax_enable_x64", True)

If enabling double precision doesn’t do the trick, this often means that there’s an issue with the parameter or modeling choices that you’re making. jax’s “debug NaNs” mode can help diagnose issues here.

Installation issues on ARM Macs#

Follow these steps to install jax and jaxoplanet on your system, with special instructions for Mac M1 chip or newer.

Step 1: Check Your Python Architecture#

First, verify your Python architecture to determine if you’re on an ARM or Intel-based chip.

import platform
  • If the output is “arm64”, proceed with the following steps.

  • If the output is “x86-64”, you’re running an Intel emulator on an Apple silicon chip and need to switch to arm64.

For the best performance of jax, it will be better to install Python under the arm64 architecture.

Install Miniforge for ARM64.

Download Miniforge from the official Conda Forge page ( Run the installer script:


Restart the terminal.

Step 2: Install jax and jaxoplanet#

Create a New Environment (Optional) in miniforge.

It’s a good practice to create a new environment for your projects:

conda create --name jaxoplanet
conda activate jaxoplanet
conda install pip

conda install jax
# or
python -m pip install "jax[cpu]"

Then install jaxoplanet using the instructions in Installation Guide.