Skip to main content

Aquatic Biogeochemical Interpolation Library

Project description

Abil.py · GitHub license Build Status dev

Overview

Abil.py provides functions to interpolate distributions of biogeochemical observations using Machine Learning algorithms in Python. The library is optimized to interpolate many predictions in parallel and is thus particularly suited for distribution models of species, genes and transcripts. The library relies on scikit-learn.

Installation

Prerequisites

Ensure you have the following installed on your system:

Install via pip

Run the following command to install the package directly from GitHub:

pip install abil

Install via cloning (for development)

If you want to modify the package, clone the repository and install it in editable mode:

git clone https://github.com/nanophyto/Abil.git
cd Abil
pip install -e .

Documentation

See the documentation for instructions on how to setup and run the models.

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

abil-25.3.19.tar.gz (163.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

abil-25.3.19-py3-none-any.whl (37.1 kB view details)

Uploaded Python 3

File details

Details for the file abil-25.3.19.tar.gz.

File metadata

  • Download URL: abil-25.3.19.tar.gz
  • Upload date:
  • Size: 163.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for abil-25.3.19.tar.gz
Algorithm Hash digest
SHA256 2c6120f3ccb3c7ee7c0da3a8c4af80795d8dc93c4525d30471a69926804e0faa
MD5 9990a85afa9e9e67026900e518c54c6d
BLAKE2b-256 1cfadd8948229685c6bedab6e254a922251575a1a79594b546b740f0ed4e9104

See more details on using hashes here.

File details

Details for the file abil-25.3.19-py3-none-any.whl.

File metadata

  • Download URL: abil-25.3.19-py3-none-any.whl
  • Upload date:
  • Size: 37.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for abil-25.3.19-py3-none-any.whl
Algorithm Hash digest
SHA256 c6fec947e00280c5a60093f4e5e71fe5e2c4075157abce24dc18c4339a995a46
MD5 48c557cc95edc74d5aa7b977b4e7c907
BLAKE2b-256 9fca4bc0c0dd718c00d68d7606ed367ffad8ba891f2f482958176b31038c0ca6

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