https://github.com/charlesll/modelisationgeochimie
Matériel pour cours de modélisation en Géochimie
Science Score: 13.0%
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○CITATION.cff file
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○Scientific vocabulary similarity
Low similarity (9.8%) to scientific vocabulary
Repository
Matériel pour cours de modélisation en Géochimie
Basic Info
- Host: GitHub
- Owner: charlesll
- License: gpl-3.0
- Language: Jupyter Notebook
- Default Branch: master
- Size: 16.4 MB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 4
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
ModelisationGeochimie
Material for the course Modélisation en Géochimie
November 2024 > !!! Course is ongoing, not all the material is online at the moment !!!
Dependencies
You will need a working installation of Python, please see that with Google. I recommend Anaconda Python, that will provide a fully-featured Python distro with Jupyter Notebooks.
In term of libraries, we will need: - matplotlib - scipy - numpy - pandas - emcee - pymc - corner - uncertainties
Install that on your computer with this command in the terminal (Linux/MacOS, search Google for Windows as I don't know this OS):
'pip install -r requirements.txt'
Running on Binder
Alternatively, the notebooks can be run without installing anything on your computer on the website MyBinder at this address:
https://mybinder.org/v2/gh/charlesll/ModelisationGeochimie/master
Running on Google Colab
You can download the zip of the repository and run it on Google Colab.
You either start a Google Colab notebook and upload your data, or host a copy of the folder on Google Drive and access it via Colab. I recommend doing the latter. In any case, there is a good documentation from google to import data on Colab here: https://colab.research.google.com/notebooks/io.ipynb
Please remember that each time you will start again your Colab Notebook, you will need to install the necessary libraries by typing
'!pip install -r requirements.txt'
in the first cell.
Ressources
https://github.com/valentineap/ComputationalGeoscienceCourse
https://scipy-lectures.org/intro/
https://github.com/jrjohansson/scientific-python-lectures
https://towardsdatascience.com/from-scratch-bayesian-inference-markov-chain-monte-carlo-and-metropolis-hastings-in-python-ef21a29e25a
Contributors
Charles Le Losq, Institut de physique du globe de Paris
Owner
- Name: Charles Le Losq
- Login: charlesll
- Kind: user
- Location: France
- Company: Institut de physique du globe de Paris
- Website: https://charlesll.github.io/
- Twitter: Charles_LeLosq
- Repositories: 49
- Profile: https://github.com/charlesll
Geoscientist, Assistant Professor, willing to improve data reduction protocols through programming and data science
GitHub Events
Total
- Push event: 5
- Fork event: 1
Last Year
- Push event: 5
- Fork event: 1
Issues and Pull Requests
Last synced: about 1 year ago
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- Total pull requests: 0
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- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
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- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0