sunkit-image#
A toolbox of useful image processing routines applicable to solar physics data.
Mission Statement#
The goal of sunkit-image
is not to be a general purpose image processing library.
The goal of sunkit-image
is to provide access to image processing routines that are:
Focused on being applied to solar image data.
Are published in the literature or in preparation to be published. If for any reason, there is doubt to the publication status, the code will only be merged when it’s close to actual publication i.e., after approval from the referees.
Widely used throughout the solar physics community. Examples include co-alignment routines that compensate for incorrect pointing, solar feature identification algorithms, and filtering functions.
If the code is already in a released package, we will wrap calls to the existing package in a way that makes it easy to use with sunpy.map.Map
or ndcube.NDCube
objects.
Additional modifications to such packages are outside the scope of sunkit-image
.
We will not copy code from other packages into this one.
Installation#
For detailed installation instructions, see the installation guide in the sunpy
docs.
This takes you through the options for getting a virtual environment and installing sunpy
.
You will need to replace “sunpy” with “sunkit-image”.
Getting Help#
Stop by our chat room #sunpy:matrix.org if you have any questions.
Contributing#
Help is always welcome so let us know what you like to work on, or check out the issues page for the list of known outstanding items.
If you would like to get involved, please read our contributing guide, this talks about sunpy
but the same is for sunkit-image
.
If you want help develop sunkit-image
you will need to install it from GitHub.
The best way to do this is to create a new python virtual environment.
Once you have that virtual environment, you will want to fork the repo and then run:
$ git clone https://github.com/<your_username>/sunkit-image.git
$ cd sunkit-image
$ pip install -e ".[dev]"