Spectral Power Of the Reionization Epoch
This is a code to model statistical foregrounds in the Epoch of Reionization. The underlying approach is equivalent to CHIPS (the Cosmological HI Power Spectrum estimator, see Trott et al, http://iopscience.iop.org/article/10.3847/0004-637X/818/2/139/pdf). However, the philosophy behind this code is somewhat different.
The idea behind spore is to provide a set of tools which can calculate relevant statistical quantities in a plug-n-play
manner. This means that most parameters are open to the user to modify. Furthermore, it means that the included models
themselves -- such as beam models, source counts, spatial distribution etc. -- are in principle modifiable by the user,
such that the overall framework will automatically include them.
- Consistent unit definitions across quantities
- Consistent conversion of units between radio astronomy and cosmology.
- Calculate 2D power-spectrum covariance analytically for arbitrary input models and scales.
- Calculate 2D power-spectrum covariance via sampling from statistical distributions, for arbitrary input models and scales.
- Some support for working with numerical simulations (from 21cmFAST)
- Some visualisation tools (in dev.)
- Intuitive package structure, separating the ideas of "measuring", "modelling", "mocking" and "visualising" the 2D power spectrum.
Non-python-users
If you don't use python much, I suggest installing the Anaconda python distribution for your OS, and ideally creating an env for using spore:
$ conda create --name spore_env numpy scipy astropy $ activate spore_env
Once you've done this, continue to the next step...
Python users
If you already/now have a working python environment, you should just be able to do the following:
$ pip install git+git://github.com/steven-murray/spore.git
All the dependencies should be automatically installed.
See the notebook docs/examples/getting_started.ipynb.