https://github.com/rubisco-sfa/mlecohydrology
https://github.com/rubisco-sfa/mlecohydrology
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/rubisco-sfa/mlecohydrology
- Owner: rubisco-sfa
- Created: 2023-02-03T16:25:56.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-03-01T15:40:15.000Z (over 1 year ago)
- Last Synced: 2025-02-02T07:28:52.798Z (4 months ago)
- Language: Python
- Size: 66.4 KB
- Stars: 1
- Watchers: 2
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
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README
# MLEcohydrology
This repository contains code/data for work on a machine learning model of Ecohydrology.
## Dependencies
Creating a `conda` environment with all the packages we use requires a lot of time to solve. This can be avoided by simply installing the packages one at a time, using `pip` when `conda` is taking a long time needlessly.
```
conda create --name ml
conda activate ml
conda install pandas
conda install intake-parquet
conda install matplotlib seaborn
conda install scikit-learn
pip install tensorflow
pip install aiohttp
```
## Intake Catalog
As we find new sources of leaf-level fluxes, we are adding them to the
[intake](https://github.com/intake/intake) catalog which you may
access in your own python scripts by the following code snippet.
```python
import intake
cat = intake.open_catalog("https://raw.githubusercontent.com/rubisco-sfa/MLEcohydrology/main/leaf-level.yaml")
```