[IPython-dev] Concise citations for the Scipy stack

[Wes Turner]

There sem to varying definitions of "Scipy Stack"

http://www.scipy.org/stackspec.html

https://registry.hub.docker.com/u/ipython/scipystack/dockerfile/

https://github.com/ipython/docker-notebook/tree/master/scipystack

http://docs.continuum.io/anaconda/pkg-docs.html

...  http://westurner.github.io/tools/#scipy-stack
On Feb 2, 2015 1:11 PM, "Mark Voorhies" <mark.voorhies at ucsf.edu> wrote:

I'm putting together a set of "software tools" references for a paper that
we are preparing to submit.
I am trying to balance acknowledging as much of our infrastructure as
possible, while minimizing the
number of references that have no direct (i.e., unambiguously obvious to
the reader) connection to the
methods section of the paper (e.g., citing Tornado, git, h5py, or MySQL is
probably going too far; likewise,
I think it's reasonable to cite R but not rpy2).

Based on http://www.scipy.org/citing.html, I think a good minimal set (for
a paper with heavy use of
IPython for matplotlib-based plotting, including KDEs from scipy.stats, and
a lot of vanilla python
sequence/expression analysis code) is:

NumPy & SciPy
Stéfan van der Walt, S. Chris Colbert and Gaël Varoquaux. The NumPy Array:
A Structure for Efficient Numerical Computation, Computing in Science &
Engineering, 13, 22-30 (2011), DOI:10.1109/MCSE.2011.37

Matplotlib
John D. Hunter. Matplotlib: A 2D Graphics Environment, Computing in Science
& Engineering, 9, 90-95 (2007), DOI:10.1109/MCSE.2007.55

IPython
Fernando Pérez and Brian E. Granger. IPython: A System for Interactive
Scientific Computing, Computing in Science & Engineering, 9, 21-29 (2007),
DOI:10.1109/MCSE.2007.53

Thoughts?

--Mark
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