Charles's repositories

evodcinv

Inversion of dispersion curves using Evolutionary Algorithms

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fast_methods

N-Dimensional Fast Methods: Fast Marching, Fast Sweeping, Group Marching, Fast Iterative, etc.

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Game-of-Life

This is a 100% Java-made recreation of "Conway's Game of Life"

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NoisePy

Gathers all of our ambient noise modules in python

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BayHunter

McMC transdimensional Bayesian inversion of surface wave dispersion and receiver functions

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CC-FJpy

A Python Package for seismic ambient noise cross-correlation and the frequency-Bessel transform method

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COVID-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

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delta

Holds meta data information about the GeoNet sensor network. Issues may be submitted here https://github.com/GeoNet/help

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DisperNet

The Codes and Python Package of DisperNet: An Effective Method of Extracting and Classifying the Dispersion Curves in the Frequency-Bessel Dispersion Spectrum

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DisperPicker

Automatically extracting dispersion curves via deep learning

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DispersionCurves

Forward modeling and inversion of dispersion curves

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easyQuake

Simplified machine-learning driven earthquake detection, location, and analysis.

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Elastic_stresses_py

Simple coseismic stress and displacement calculator (a mini-Coulomb, but in Python)

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EQTransformer

EQTransformer, a python package for earthquake signal detection and phase picking using AI.

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ML-notes

notes about machine learning

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PhaseLink

PhaseLink: A deep learning approach to seismic phase association

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PhaseNet_practical

2020-04-29 ML reading group practical - Using PhaseNet

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PhaseTravelTime

Easy way to calculate P and S seismic travel times based on 1D velocity model

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PickDispersionCurves

A simple python GUI for extracting dispersion curves from dispersion spectrum.

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pykonal

Travel-time calculator based on the fast-marching method solution to the Eikonal equation.

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QuakeMigrate

A Python package for automatic earthquake detection and location using waveform migration and stacking.

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RF_INV

Receiver function inversion by reversible-jump Markov-chain Monte Carlo

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S-SNAP1.1

The program corresponds to the paper named "Tracking Earthquake Sequences in Real Time: Application of Seismicity-Scanning based on Navigated Automatic Phase-Picking (S-SNAP) to the 2019 Ridgecrest, California Sequence" by Tan et al. 2020. Geophysical Journal International.

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source-separation

Code to reproduce "Separation and denoising of seismically-induced signals with dual-path recurrent neural network architecture" paper 2020

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