Valerii Chirkov

Regarding the `-trans.fif` file generation [this tutorial](https://nipy.org/nibabel/coordinate_systems.html) from NiBabel was very useful to me.

> Temporary solution is to record the browser screen using e.g. https://chrome.google.com/webstore/detail/screen-recorder/hniebljpgcogalllopnjokppmgbhaden. > > But given that we use Solara now, it should be easier to capture the Matplotlib space...

> A quick hack to test the idea is to add a line after > > https://github.com/projectmesa/mesa/blob/9c9a02e25df7c83c866ae9a23416c5d32e76a48d/mesa/experimental/jupyter_viz.py#L262 > to save the plot to a file, which filename is an increasing...

Here is the implementation using `matplotlib.animation`: Show code ```python import matplotlib.animation as animation from matplotlib.figure import Figure from mesa.experimental.jupyter_viz import JupyterContainer def plot_n_steps(viz_container: JupyterContainer, n_steps: int = 10): model =...

> We could incorporate your code, but there is a possibility that we are migrating the plotting to Altair instead (see #1806). This is still up for discussion. Just let...

Thanks @danielmk, that’s super helpful! Yeah, having a `.save()` / `.load()` interface on `NeuralInference` sounds like a great idea — especially for making things more user-friendly and future-proof. Pickle works...

@manuelgloeckler @janfb

I think to reproduce this problem, one can try to simply run sampling with a very low number of samples and the uniform prior. It may just be a sampling...

> What is the speed up you notice through this change? Basically, we save the time of training a model specifically for `test_npse_map'. But now it would be much cheaper...

Hey @janfb, I think this is more or less how the final test structure should look like, so ready for review 🙃