astroml / astroml.github.com

astroML web page

AstroML: Machine Learning for Astronomy

AstroML is a Python module for machine learning and data mining built on numpy, scipy, scikit-learn, and matplotlib, and distributed under the BSD license. It contains a growing library of statistical and machine learning routines for analyzing astronomical data in python, loaders for several open astronomical datasets, and a large suite of examples of analyzing and visualizing astronomical datasets.

This project was started in 2012 by Jake VanderPlas to accompany the book Statistics, Data Mining, and Machine Learning in Astronomy by Zeljko Ivezic, Andrew Connolly, Jacob VanderPlas, and Alex Gray.

Important Links

• HTML documentation: https://www.astroML.org
• Core source-code repository: https://github.com/astroML/astroML
• Figure source-code repository: https://github.com/astroML/astroML-figures
• Issue Tracker: https://github.com/astroML/astroML/issues
• Mailing List: https://groups.google.com/forum/#!forum/astroml-general

Installation

Before installation, make sure your system meets the prerequisites listed in Dependencies, listed below.

Core

To install the core astroML package in your home directory, use:

pip install astroML

A conda package for astroML is also available either on the conda-forge or on the astropy conda channels:

conda install -c astropy astroML

The core package is pure python, so installation should be straightforward on most systems. To install from source, use:

python setup.py install

You can specify an arbitrary directory for installation using:

python setup.py install --prefix='/some/path'

To install system-wide on Linux/Unix systems:

python setup.py build
sudo python setup.py install

Dependencies

There are two levels of dependencies in astroML. Core dependencies are required for the core astroML package. Optional dependencies are required to run some (but not all) of the example scripts. Individual example scripts will list their optional dependencies at the top of the file.

Core Dependencies

The core astroML package requires the following (some of the functionality might work with older versions):

• Python version 3.6+
• Numpy >= 1.13
• Scipy >= 0.19
• Scikit-learn >= 0.18
• Matplotlib >= 3.0
• AstroPy >= 3.0

Optional Dependencies

Several of the example scripts require specialized or upgraded packages. These requirements are listed at the top of the particular scripts

• HEALPy provides an interface to the HEALPix pixelization scheme, as well as fast spherical harmonic transforms.

Development

This package is designed to be a repository for well-written astronomy code, and submissions of new routines are encouraged. After installing the version-control system Git, you can check out the latest sources from GitHub using:

git clone git://github.com/astroML/astroML.git

or if you have write privileges:

git clone [email protected]:astroML/astroML.git

Contribution

We strongly encourage contributions of useful astronomy-related code: for astroML to be a relevant tool for the python/astronomy community, it will need to grow with the field of research. There are a few guidelines for contribution:

General

Any contribution should be done through the github pull request system (for more information, see the help page Code submitted to astroML should conform to a BSD-style license, and follow the PEP8 style guide.

Documentation and Examples

All submitted code should be documented following the Numpy Documentation Guide. This is a unified documentation style used by many packages in the scipy universe.

In addition, it is highly recommended to create example scripts that show the usefulness of the method on an astronomical dataset (preferably making use of the loaders in astroML.datasets). These example scripts are in the examples subdirectory of the main source repository.

Authors

Package Author

• Jake Vanderplas https://github.com/jakevdp http://jakevdp.github.com

Maintainer

• Brigitta Sipocz https://github.com/bsipocz

Contributors

• Alex Conley
• Andreas Kopecky
• Andrew Connolly
• Asif Imran
• Benjamin Alan Weaver
• Brigitta Sipőcz
• Chris Desira
• Daniel Andreasen
• Dino Bektešević
• Edward Betts
• Hans Moritz Günther
• Hugo van Kemenade
• Jake Vanderplas
• Jeremy Blow
• Jonathan Sick
• Joris van Vugt
• Juanjo Bazán
• Julian Taylor
• Lars Buitinck
• Michael Radigan
• Morgan Fouesneau
• Nicholas Hunt-Walker
• Ole Streicher
• Pey Lian Lim
• Rodrigo Nemmen
• Ross Fadely
• Vlad Skripniuk
• Zlatan Vasović
• Engineero
• stonebig

astroml.github.com's Issues

Update figures for second edition

Set up automated API documentation updates

We don't necessarily need to use readthedocs, but something similar would be nice to make sure we have a rendered, up-to-date version of the API documentation.

Add alt-text to images

To make the webpage more accessible. This is really just an umbrella issue as addressing it belongs to all the 3 repos that actually contains the elements of the website.

Some resources about alt-text:

• https://hackmd.io/2uOMXV_fT0ycLyo4uH67HQ
• https://docs.google.com/presentation/d/1PTYVwcu2U6wTY-ozrKEK981CEp79MkBtRJymr2LQgCY/edit#slide=id.gc6f9e470d_0_0

Add links over figure numbers

We have 2, and in some cases 3 versions for the figures. The book editions are available from the drop downs, but it would be best to have way to navigate between the versions on the figure level, too.

E.g. turn the figure number, at top of each page, to a menu of 3 links that points to the different versions gone into the print.

Upload v0.4 updated material

Currently it's 0.2 on the webpage. Update it to 0.3.1 0.4 once the new release is out.

Add page for first edition figures

Add new textbook to the webpage

@ivezic - I think we should update the images and mentions of the textbook on the webpage, as well as maybe some new text.

Do you have a preference for the timing? (e.g. only do after Dec 3, or now)? Any preference for new text?

Add link to point to the counterpart figure in the other edition

It maybe useful to have a link on each figure's page that points to the same figure in the other edition of the book.

Run website accessibility checks

E.g. with the chrome extension: lighthouse report, maybe there is a CI action for it, too.

Set up sphinx-gallery for binder deployment of notebooks

Scikit-learn has a rather nice way to deploy examples from the docs with binder.

I think we don't even need the gallery part of the plugin just the deployment, but in either case this needs a bit more experimenting to get it right.

Remove note from fig 8.4 page

remove text http://www.astroml.org/book_figures/chapter8/fig_rbf_ridge_mu_z.html#changes-from-published-version, as now the published version is the right version

Refactor webpage layout

Would be nice to rethink and redesign the webpage a bit to clean up the layout, etc as currently there isn't an easy way to host multiple versions of the docs, etc.

We can again follow the strategy and design of upstream packages, scikit-learn has changed their landing page since we got their layout, as well as numpy currently is undergoing a webpage redesign.

Fix dropdown CSS

There is some ugliness in the dropdown CSS (overflow at the bottom of the box, and some weirdness at the lower part of the text)

Auto build and deployment of the website

The website deployment should be triggered by changes to affected parts of the source. The challenge is that the website components are hosted in 3 separate repos while deployed into this one:

• astroML/astroML
• astroML/astroML-figures
• astroML/astroML-notebooks

The build scripts are in the library doc itself, but those can be moved over here if needed. Rendered outputs from the previous build should be used as building everything from zero takes too much time. The two possible avenues I see are:

• have one job, run from cron e.g. daily that runs in this repo, fetches the latest versions of the components and builds and deploys the website if there are any changes.
• cross trigger builds with GH actions. I have yet to find a closeby project that did this, but this discussion should be enough for a start https://github.community/t/triggering-by-other-repository/16163

Order of double figures may have been mixed up

This PR basically swaps double figures around. Fix 10.3 has been fixed, but the others may be off, too and all has to be double-checked and confirmed to be correct.

86520ea