A Python-based toolkit for analyzing ensemble performance data.
To use thicket, install it with pip:
$ pip install llnl-thicket
Or, if you want to develop with this repo directly, run the install script from the
root directory, which will build the package and add the cloned directory to
your PYTHONPATH:
$ source install.sh
Thicket provides an interactive visualization which can be run inside of your Jupyter notebooks. It is dependent on different mechanism for building, which we describe here.
The software in the thicket/vis subdirectory (i.e., the thicket.vis package) requires
Node.js and the Node Package Manager (NPM) for the
development and building of JavaScript code.
If you are just using our built-in visualizations, the visualization code will be built
automatically when you access the thicket.vis module. All that users have to do is make
sure they have NPM installed. If NPM is not installed, accessing the thicket.vis module
will raise a FileNotFoundError.
If you are developing a visualization, it is recommended that you build the visualization code manually. To manually build this code, follow the instructions below.
Once you have Node and NPM installed on your system, you can install all necessary node
packages by running the following line in your terminal from the thicket/vis directory:
npm install
To build out JavaScript into the static bundles used by the Jupyter visualizations,
run the following line from the thicket/vis directory in your terminal:
npm run build
Alternatively, you can run the following line to force bundles to automatically update when you change the JavaScript source code:
npm run watch
Thicket is an open-source project. We welcome contributions via pull requests, and questions, feature requests, or bug reports via issues.
Thicket is distributed under the terms of the MIT license.
All contributions must be made under the MIT license. Copyrights in the Thicket project are retained by contributors. No copyright assignment is required to contribute to Thicket.
See LICENSE and NOTICE for details.
SPDX-License-Identifier: MIT
LLNL-CODE-834749