edges-analysis 8.3.0

Functionality for processing EDGES field data

Analysis and Calibration Code for the EDGES experiment

edges-analysis has methods for I/O, receiver calibration, averaging, filtering and calibrating EDGES (and other global 21cm experiment) data. The primary goal of the code is to allow the analysis to be fully reproducible, efficient, and clear.

Features

edges-analysis includes the following features:

• Methods for reading/writiing EDGES-specific datasets/data products.

• A full set of methods for receiver calibration, applicable to most current global 21cm experiments (based on Dicke-switch calibration + the noise-wave formalism).

• Many algorithms/routines for flagging bad data, including RFI, outliers in time/frequency, poor auxiliary data etc.

• A full-featured interface for linear modelling and fitting.

• Algorithms for consistent averaging of data over nights/times/frequencies, either in specified bins or complete averaging of the dataset.

• Works with pygsdata objects for a consistent interface all the way through an analysis pipeline, including maintenance of metadata about the operations applied to particular data (and propagation of metadata like the number of averaged samples).

• Simulation algorithms, including beam models and sky models.

Documentation

Documentation is hosted on ReadTheDocs.

Installation

This package can be installed with pip:

pip install edges-analysis

If you want all the extras (for development etc), use the [dev] extra, like so:

pip install edges-analysis[dev]

You can also install directly from github. Either cloning first:

git clone https://github.com/edges-collab/edges-analysis
cd edges-analysis
pip install [-e] .

or directly:

pip install git+git://github.com/edges-collab/edges-analysis.git