A framework for data-rich, interactive, publication-quality figures. Making the most of matplotlib
, plotly
, pyvista
, pygmt
and more!
- self-consistent 2D slices through volumes, surfaces and point-clouds provided by
arrau
,- intelligent visualisation of slicing lines,
- multi-layer plots with isolines, shading and transparency,
- 3D rendering:
- by
pyvista
(vtk
-powered), - by
ipyvolume
(OpenGL
-powered),
- by
- interactive display of associated metadata using
ipywidgets
andplotly
, - geographical coordinate-systems provided by
pygmt
.
For the lastest stable version run:
conda install kmch::plotea
For the most up-to-date but potentially unstable version, run:
git clone git@github.com:kmch/ploTea.git
cd ploTea
pip install -e .
If you use any part of this repository in your research, please cite the following paper:
- Chrapkiewicz, Kajetan and Lipp, Alex and Barron, Leon Patrick and Barnes, Richard and Roberts, Gareth, Apportioning sources of chemicals of emerging concern along an urban river with inverse modelling. Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2024.172827