Yutao Zhou's repositories
laspec
A toolkit for LAMOST spectra.
GALAH_DR3
Repository accompanying GALAH DR3
BasicATLAS
Python wrapper for running basic ATLAS-9/SYNTHE stellar models quickly and easily
kalepy
Kernel Density Estimation and (re)sampling
BASTA
BASTA: The BAyesian STellar Algorithm
PyAstronomy
A collection of astronomy-related routines in Python
Chem-I-Calc
Chemical information calculator for resolved stellar spectroscopy
pytorch-handbook
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
Cycle_SN
Generative and Interpretable Deep Learning for Stellar Spectra
astroslam
Stellar LAbel Machine (SLAM).
isochrones
Pythonic stellar model grid access; easy MCMC fitting of stellar properties
astroNN
Deep Learning for Astronomers with Tensorflow
synple
An Easy-to-Use Wrapper for the Spectral Synthesis Code Synspec
GridCal
GridCal, a cross-platform power systems solver written in Python with user interface and embedded python console
smt
Surrogate Modeling Toolbox
Machine-Learning-with-Python
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
lhsmdu
This is an implementation of Deutsch and Deutsch, "Latin hypercube sampling with multidimensional uniformity", Journal of Statistical Planning and Inference 142 (2012) , 763-772
SME
Spectroscopy Made Easy
doepy
Design of Experiment Generator. Read the docs at: https://doepy.readthedocs.io/en/latest/
cnn-explainer
Learning Convolutional Neural Networks with Interactive Visualization. https://poloclub.github.io/cnn-explainer/
pyDOE
Design of experiments for Python
TheCannon.jl
Implementation of The Cannon (Ness+ '15), a data-driven model of stellar spectra
StePar
StePar is an automatic code used to infer stellar atmospheric parameters using the EW method.
lightkurve
A friendly package for Kepler & TESS time series analysis in Python.
apogee
Tools for dealing with APOGEE data
base
Bayesian Analysis for Stellar Evolution
Design-of-experiment-Python
Design-of-experiment (DOE) generator for science, engineering, and statistics