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Datasets:
es833
/
ThousandWorlds

Tasks:
Tabular Regression
Other
Size:
1K<n<10K
Tags:
benchmark
datasets
physical-sciences
scientific-machine-learning
exoplanets
climate
DOI:
Libraries:
Datasets
License:
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  1. README.md +4 -3
README.md CHANGED
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  viewer: false
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  ---
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- # ThousandWorlds
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-
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  <img src="MASCOT.png" align="right" width="220" alt="ThousandWorlds mascot">
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  ThousandWorlds is a benchmark for emulating exoplanet climates: **1760 GCM
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  simulations** across **5 GCMs**, **8 planet parameters**, and atmospheric
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  variables on a 32 x 64 x 10 latitude-longitude-pressure grid. It includes three
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  ## Quickstart
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- The easiest way to use the benchmark is through the Python package:
 
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  ```bash
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  git clone https://github.com/edstevenson/ThousandWorlds.git
 
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  viewer: false
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  ---
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  <img src="MASCOT.png" align="right" width="220" alt="ThousandWorlds mascot">
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+ # ThousandWorlds
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+
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  ThousandWorlds is a benchmark for emulating exoplanet climates: **1760 GCM
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  simulations** across **5 GCMs**, **8 planet parameters**, and atmospheric
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  variables on a 32 x 64 x 10 latitude-longitude-pressure grid. It includes three
 
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  ## Quickstart
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+ The easiest way to use the benchmark is through the
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+ [Python code](https://github.com/edstevenson/ThousandWorlds):
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  ```bash
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  git clone https://github.com/edstevenson/ThousandWorlds.git