jsk389

InclinationAngles

A repository to contain material describing how to obtain inclination angles from asteroseismic mode profiles

IntroToPeakBagging

Can I haz peaks pls

sloscillations

Updated version of calculating artificial red giant power spectra in the time domain.

BOChaMM

Bayesian Optimisation for the Characterisation of Mixed Modes.

HierarchicalAngles

Code to infer the inclination angle of a star from asteroseismology using the Bayesian hierarchical method outlined in Kuszlewicz et al. (2019)

ptemcee

A parallel-tempered version of emcee.

AADG3

asteroFLAG Artificial Dataset Generator v3

barbershop

A Python package that aids the user in making dynamic cuts to data in various parameter spaces, using a simple GUI.

BayesianOptimization

A Python implementation of global optimization with gaussian processes.

bgfits

Code for fitting background of power spectrum of asteroseismic targets (Kuszlewicz et al. in prep.)

Clumpiness

Predict the evolutionary state of a red giant (Hydrogen shell or core Helium burning) using time domain photometry.

course-v3

The 3rd edition of course.fast.ai

echelle

Dynamic echelle diagrams for asteroseismology

forest-confidence-interval

Confidence intervals for scikit-learn forest algorithms

growing_hierarchical_som

Self-Organizing Map [https://en.wikipedia.org/wiki/Self-organizing_map] is a popular method to perform cluster analysis. SOM shows two main limitations: fixed map size constraints how the data is being mapped and hierarchical relationships are not easily recognizable. Thus Growing Hierarchical SOM has been designed to overcome this issues

JazzHands

jsk389.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

keras-tcn

Keras Temporal Convolutional Network.

lightkurve

A beautiful package for Kepler, K2, and TESS flux time series analysis in Python.

LombScargle.jl

Compute Lomb-Scargle periodogram, suitable for unevenly sampled data. It supports multi-threading

minisom

:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps

proximity-xgboost

Compute proximity matrix using xgboost

SALib

Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.

shap

A unified approach to explain the output of any machine learning model.

Speedy

Fast estimation of the background of red giant power spectra.

starclass

Stellar Classification

starwars

Seismology with Adversarial Recurrent Stars

StellarClassification

Stellar Classification in TASOC

upsilon

Automated Classification of Periodic Variable Stars Using Machine Learning

XPlot

A collection of older plotting libraries for F#. Recommended to use Plotly.NET instead https://plotly.net/