topsy

This package visualises simulations, and is an add-on to the pynbody analysis package. Its name nods to the TIPSY project. It is built using wgpu, which is a future-facing GPU standard (with thanks to the python wgpu bindings).

At the moment, topsy is a bit of a toy project, but it already works quite well with zoom (or low resolution) simulations. The future development path will depend on the level of interest from the community.

Installing

You will need python 3.8 or later, running in a UNIX variant (basically MacOS, Linux or if you're on Windows you need WSL). You can then install topsy using pip as usual:

pip install topsy

This will install topsy and its dependencies (including pynbody itself) into your current python environment. (If it fails, check that you have python 3.8 or later, and pip is itself up-to-date using pip install -U pip.)

As usual, you can also install direct from github, e.g.

pip install git+https://github.com/pynbody/topsy

Or clone the repository and install for development using

pip install -e .

from inside the cloned repository.

If you want to play with topsy without disturbing your current installation, I recommend using venv:

# create a toy environment
python -m venv visualiser-env

# activate the new environment
source visualiser-env/bin/activate 

# install
pip install topsy

... other commands ...

# get your old environment back:
deactivate 

For more information about venv, see its tutorial page.

Trying it out

Quick start: if you just want to try it out and you don't have a suitable simulation snapshot to hand, you can download some from the tangos tutorial datasets (4.8GB). You need to untar them (tar -xzf tutorial_changa.tar.gz from your command line), then you can type topsy pioneer50h128.1536gst1.bwK1.000832 to visualise that file's dark matter content.

Long version: The package provides one simple command called topsy, to be called straight from your shell. Pass topsy the path to the simulation that you wish to visualise.

You can (and probably should) also tell it what to center on using the -c flag, to which valid arguments are:

• -c none (just loads the file without changing the centering)
• -c halo-1 (uses the shrink sphere center of halo 1; or you can change 1 to any other number)
• -c zoom (uses the shrink sphere center on the highest resolution particles, without loading a halo catalogue)
• -c all (uses the shrink sphere center on all particles in the file)

By default, it will show you dark matter particles. To change this pass -p gas to show gas particles or -p star for stars.

If your particles have other quantities defined on them (such as temp for gas particles), you can view the density-weighted average quantity by passing -q temp.

By default, topsy uses matplotlib's twilight_shifted colormap. To change this pass, for example, -m viridis, or the name of any other matplotlib colormap.

Controls in the main window

If everything works, a window will pop up with a beautiful rendering of your simulation. Make sure the window is in focus (for some reason on MacOS I sometimes have to switch to another application then back to python to get this to work). Then you can use the following controls:

• To spin around the centre, drag the mouse.
• To zoom in and out, use the mouse scroll wheel.
• To rescale the colours to an appropriate range for the current view, press r(ange)
• To return the view to the original orientation and zoom, press h(ome)
• To save a snapshot of the current image as a pdf press s(ave)

Using from jupyter

Thanks to jupyter-rfb, it is possible to use topsy within a jupyter notebook. This requires a little more knowledge than the command line version, but is still fairly straight-forward if you are familiar with pynbody. To open a topsy view within your jupyter notebook, try

import pynbody
import topsy 

f = pynbody.load("/path/to/file")
f.physical_units()
h = f.halos()
pynbody.analysis.halo.center(h[1])

vis = topsy.topsy(f.dm)
vis.canvas

This loads your data into f, performs some centering, creates the topsy viewer and then the final line (vis.canvas) instructs jupyter to bring up the interactive widget.

Note that you can interact with this widget in exactly the same way as the native window produced by topsy. Additionally, you can manipulate things on the fly. For example, you can type vis.quantity_name = 'temp' to immediately switch to viewing temperature (compare with the -q flag above).