Skip to main content

HydroGAP-AI: Hydro-Gap Artificial Intelligence

Project description

HydroGAP-AI

TODO: Write a high level overview of the library

Installation

You can install the library using the following command:

pip install hydrogapai

or directly from this repo using:

pip install git+https://github.com/kperi/HydroGAP-AI.git

Predict gaps in stations

Usage

from hydrogapai.gap_prediction import (
    predict_station_gaps,
)
station_file = "./data/lib/station_11.0_cleaned.csv"
results_folder = './output/test_run'

 
                


reall_combined_dfs, val_full, metrics_gaps, real_predictionst = predict_station_gaps(
    station_file,
    results_folder=results_folder,
    model_type=model_type,
    hyper_opt=False,
)

For a more detailed example of the library including outputs see this notebook

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hydrogapai-0.6.0.tar.gz (17.1 kB view details)

Uploaded Source

File details

Details for the file hydrogapai-0.6.0.tar.gz.

File metadata

  • Download URL: hydrogapai-0.6.0.tar.gz
  • Upload date:
  • Size: 17.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.13

File hashes

Hashes for hydrogapai-0.6.0.tar.gz
Algorithm Hash digest
SHA256 6f3080448cb6d7d5df32212a193e31d5236afaf7727e1b0d9165c0bafbaf6cb0
MD5 11be52c40864f09815998cab9f348dd7
BLAKE2b-256 fa39e3b7393290fb97dd1deacb49c085c504afe7c5e6cf2f1d8f0b2e7e72e216

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page