Python modules and scripts useful for variable star work in astronomy.
Project description
This is a bunch of Python modules I wrote for my astronomy work with the HAT surveys, mostly focused on handling light curves and characterizing variable stars. Module functions that deal with light curves (e.g. in the modules astrobase.lcmath, astrobase.periodbase, astrobase.varbase, astrobase.plotbase, and astrobase.checkplot) usually just require three numpy ndarrays as input: times, mags, and errs, so they should work with any time-series data that can be represented in this form. If you have flux time series measurements, most functions take a magsarefluxes keyword argument that makes them handle flux light curves correctly.
Full documentation is still a work in progress (as soon as I figure out how Sphinx works), but the docstrings are fairly good and an overview is provided at https://github.com/waqasbhatti/astrobase, along with Jupyter notebooks that demonstrate some of the functionality.
Installation
This package requires the following other packages:
numpy
scipy
astropy
matplotlib
Pillow
jplephem
astroquery
tornado
pyeebls
You might need to install openssl-devel or a similar RPM/DEB package for the python-cryptography module that gets pulled in as a dependency for astroquery. For some extra functionality, you’ll need the following modules:
for astrobase.lcdb to work, you’ll also need psycopg2
First, make sure numpy and a Fortran compiler are installed
## you'll need a Fortran compiler. ## ## on Linux: dnf/yum/apt install gcc gcc-gfortran ## ## on OSX (using homebrew): brew install gcc ## ## make sure numpy is installed first! ## ## this is required for the pyeebls module installation ## (venv)$ pip install numpy # in a virtualenv # or use dnf/yum/apt install numpy to install systemwide
Next, install astrobase
(venv)$ pip install astrobase
Or if you want the latest version
$ git clone https://github.com/waqasbhatti/astrobase $ cd astrobase $ python setup.py install $ # or use pip install . to install requirements automatically $ # or use pip install -e . to install in develop mode along with requirements
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