Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome
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Updated
Nov 26, 2024
Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome
An application based on Python and designed as a solution for geology related daily work.
List of resources for mineral exploration and machine learning, generally with useful code and examples.
The Virtual Planet Simulator
A set of tools for getting the most from your geochemical data.
an open-sourced highly automated machine learning Python framework for data-driven geochemistry discovery
GebPy is a Python-based, open source tool for the generation of geological data of minerals, rocks and complete lithological sequences. The data can be generated randomly or with respect to user-defined constraints, for example a specific element concentration within minerals and rocks or the order of units within a complete lithological profile.
A code for calculating the standard state thermodynamic properties at a given temperature and pressure.
Easily calling PhreeqcRM from Matlab
Python client for the Earthchem REST and OGC APIs
Looking at the problems associated with geoscience datasets for data science
Coupled atmosphere-interior framework to simulate the temporal evolution of rocky planets.
A two-phase (water + gas) reactive transport model, written in Julia, that also simulates geochemical reactions between water-gas-mineral phases via a link with PHREEQC.
Thermodynamic calculations and diagrams for geochemistry
R package to analyze Groundwater, Geothermal water and Gas Geochemistry information
Python library for processing and standardizing carbonate clumped-isotope analyses, from low-level data out of a dual-inlet mass spectrometer to final, “absolute” Δ47, Δ48, and Δ49 values with fully propagated analytical error estimates.
Package for apatite-based thermodynamic models: ApThermo (melt hygrometry) and ApREE (REE partitioning).
Read IRMS (Isotope Ratio Mass Spectrometry) data files into R
Interactive Jupyter notebook exploring the features of GEOROC 2.0. Demonstrates data access via API, data formatting, cleaning, resampling, and visualization for geochemical analysis.
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