jess
is Python library to analyze and remove Radio Frequency Interference (RFI) for radio search mode data.
Radio Frequency Interference are anthropomorphic signals that can corrupt radio observations. In the context of Fast Radio Burst (FRB) and Pulsar searches, RFI can significantly reduce sensitivity to the astronomical signal and increase the amount of false positives. jess aims to provide a set flexible Python filters that should work on data from a wide variety of telescopes. We use Cupy to optionally leverage Graphical Processing Units (GPUs) to greatly accelerate the filters.
jess_composite.py
A composite MAD/FFT/Highpass 2D filterjess_gauss.py
Use Kurtosis and Skew as a 2D Gaussianity filterrfi_view.py
View 2D dynamic spectra, bandpass, time series, and summery statistics.channel_mask_maker.py
Make channel makes basked on user specified statistics.jess_combine_mocks.py
A clone of the your script that applies the composite filter.
channel_masks.py
Make channel masks based on statistics and outlier algorithmsdispersion/dispersion_cupy
dispersion routines, roll and FDMTfitters/fitters_cupy
Useful curve fitting, robust spline, arPLS, interactive polynomial, etcJESS_filters/JESS_filters_cupy/JESS_filters_generic
Repository with all the filters- See the full API documentation
We have a docs website
To install directly into your current Python environment
pip install git+https://github.com/josephwkania/jess.git
If you want a local version
git clone https://github.com/josephwkania/jess.git
pip install jess
If you have a GPU to use, pip install jess[cupy]
, for tests pip install jess[tests]
, and for
doc pip install jess[docs]
See CONTRIBUTING.md