Skip to main content

A Custom Jupyter Widget Library for Interactive Visualization with yt

Project description

widgyts

Documentation Status codecov status DOI

A fully client-side pan-and-zoom widget, using WebAssembly, for variable mesh datasets from yt. It runs in the browser, so once the data hits your notebook, it's super fast and responsive!

If you'd like to dig into the Rust and WebAssembly portion of the code, you can find it at https://github.com/data-exp-lab/rust-yt-tools/ and in the npm package @data-exp-lab/yt-tools.

Check out our SciPy 2018 talk and the associated slides for more info!

Documentation

Our documentation is hosted at readthedocs. Take a look here.

Installation

To install using pip from the most recent released version:

$ pip install widgyts

To install using pip from this directory:

$ git clone https://github.com/yt-project/widgyts.git
$ cd widgyts
$ pip install .

For a development installation (requires npm),

$ git clone https://github.com/yt-project/widgyts.git
$ cd widgyts
$ pip install -e .
$ jupyter serverextension enable --py --sys-prefix widgyts
$ jupyter nbextension install --py --symlink --sys-prefix widgyts
$ jupyter nbextension enable --py --sys-prefix widgyts

Note that in previous versions, serverextension was not provided and you were required to set up your own mimetype in your local configuration. This is no longer the case and you are now able to use this server extension to set up the correct wasm mimetype.

To install the jupyterlab extension, you will need to make sure you are on a recent enough version of Jupyterlab, preferably 0.35 or above. For a development installation, do:

$ jupyter labextension install js

To install the latest released version,

$ jupyter labextension install @yt-project/yt-widgets

Using

To use this, you will need to have yt installed. Importing it monkeypatches the Slice and Projection objects, so you are now able to do:

#!python
import yt
import widgyts

ds = yt.load("data/IsolatedGalaxy/galaxy0030/galaxy0030")
s = ds.r[:,:,0.5]
s.display("density")

and for a projection:

#!python
ds = yt.load("data/IsolatedGalaxy/galaxy0030/galaxy0030")
p = ds.r[:].integrate("density", axis="x")
p.display()

There are a number of traits you can set on the resultant objects, as well.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

widgyts-0.5.1.tar.gz (267.6 kB view details)

Uploaded Source

File details

Details for the file widgyts-0.5.1.tar.gz.

File metadata

  • Download URL: widgyts-0.5.1.tar.gz
  • Upload date:
  • Size: 267.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.3

File hashes

Hashes for widgyts-0.5.1.tar.gz
Algorithm Hash digest
SHA256 cd46eba40c86bae9c73786e5f468be053042fa9f339d46b7a7d623f643bf3643
MD5 c9b28cbce9975bb990f9c8d4f5dc66a8
BLAKE2b-256 f8a3030188a45f107299a54e7e349702bf90019ebb790f0b3f66b5ba8ae16ef1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page