This package provides an ipython notebook for reducing and doing stellar photometry on CCD data.

Documentation is at: https://reducer.readthedocs.org

Comments are very, very much welcome. Please comment by making a new issue on Github (if, by chance, a reasonably senior academic is using this, you can send feedback by email; anyone else should really create a github account so you can make an issue :)).

Note about IPython version support: Version 0.2 and higher of reducer works with IPython 3 and 4. Version 0.1 works with IPython 2. No improvements to reducer will be backported to version 0.1.x/IPython 2. Feel free to fork if you need that!

You need python (2.7, or 3.4 or higher) and the SciPy stack. The easiest way to the get the full stack is from a distribution like anaconda.

Then, in a terminal/command window:

pip install reducer

You can, if you want, grab the source on github (there is a "Download as ZIP" link on the right you can use if you don't want to mess git), change into the source directory, and run python setup.py install.

This package doesn't magically do your reduction for you. Instead, it creates a template ipython notebook that leads you through data reduction. When you are done you have reduced your data and you have a notebook that allows you or someone else to reproduce your work.

In a terminal, navigate to the directory where you want to keep the notebook for doing your reduction (which does not have to be the same directory where the data is, though it can be), then type:

reducer

This will create a new template notebook. To open the notebook, type in a terminal:

ipython notebook

A browser window will open; the notebook you want is named "reduction.ipynb". Click on it, then just do what it says in the notebook and reduced data (and someday photometry!) will be yours.

If you look at the source code you'll notice pretty quickly that there is no actual science code. Think of this as the glue that brings together a couple related packages:

• ccdproc for the actual data reduction.
• astropy for lots of the underlying structure .