This package provides a Jupyter notebook for reducing 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/Jupyter version support: Version 0.3 and higher of
reducer works with IPython 4/Jupyter. Version 0.1 works with IPython 2, and
Version 0.2.x work with IPython 3 or IPython 4/Jupyter. No improvements to
reducer will be backported to version 0.1.x/IPython 2 or to 0.2.x/IPYthon
3. 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.
On Windows it will be easiest to install using the Anaconda Python
distribution and conda (because everything has been compiled for you).
To install using conda:
conda install -c conda-forge -c astropy reducer
If you prefer, you can install with pip in any python distribution (but may end up compiling some of the dependencies):
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.
Note
reducer comes with a small set of images; the download size is roughly 13MB. It is provided so you can try the notebook without needing your own data. If you run the notebook as-is then the sample images will get expanded to 300MB in a temporary directory.
This package doesn't magically do your reduction for you. Instead, it creates a template jupyter 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:
jupyter 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: