HCIplot
HCIplot -- High-contrast Imaging Plotting library. The goal of this
library is to be the "Swiss army" solution for plotting and visualizing
multi-dimensional high-contrast imaging datacubes on JupyterLab.
While visualizing FITS files is straightforward with SaoImage DS9 or any
other FITS viewer, exploring the content of an HCI datacube as an
in-memory numpy array (for example when running your Jupyter
session on a remote machine) is far from easy.
HCIplot contains two functions, plot_frames and plot_cubes,
and relies on the matplotlib and HoloViews libraries and
ImageMagick. HCIplot allows to:
- Plot a single frame (2d array) or create a mosaic of frames.
-
Annotate and save publication ready frames/mosaics.
-
Visualize 2d arrays as surface plots.
-
Create interactive plots when handling 3d or 4d arrays (thanks to
HoloViews)
- Save to disk a 3d array as an animation (gif or mp4).
Installation
You can install HCIplot with pip:
pip install hciplot
JupyterLab can be installed either with pip or with conda:
conda install -c conda-forge jupyterlab
The PyViz extension must be installed to display the holoviews
widgets on JupyterLab:
jupyter labextension install @pyviz/jupyterlab_pyviz
If you want to create animations with plot_cubes you need to install
ImageMagick with your system's package manager (e.g. brew if you are
on MacOS or apt-get if you are on Ubuntu).
Release files for hciplot 0.2.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hciplot-0.2.8.tar.gz | 17.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hciplot-0.2.8-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 33.1 kB
Release files / hciplot-0.2.8.tar.gz
| Download URL | hciplot-0.2.8.tar.gz |
|---|---|
| Size | 17.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
c806d41ed6f93d54526189867f676a3b55f5caf63c89fb60f109c613cd3155da
|
|
BLAKE2b-256 checksum How to use checksums |
700b5b0846ea58998ec817700145b6422c44761cd81914590bf58b4332010dbd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.14
|
Release files / hciplot-0.2.8-py2.py3-none-any.whl
| Download URL | hciplot-0.2.8-py2.py3-none-any.whl |
|---|---|
| Size | 15.8 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
82e03aed0f6a27da70cf48be666f4dfada4b7aabb21a872f75add9721330c162
|
|
BLAKE2b-256 checksum How to use checksums |
25a8464f598c3afe3324efaacc8527fa7938d7698c299517ccdf0cba8c721ec8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.14
|
