Space-time prediction with sparse and irregular space-time multi-timeserie.
Project description
steams
Space-time prediction with sparse and irregular space-time multi-timeseries.
Models presented in this packages are using an adaptive distance attention mechanism. The weight of the attention are based either on the Ordinary Kriging equation system or the Nadaraya-Watson Kernel.
Install from PyPi
pip install steams
install from source
cd /tmp
git clone https://git.nilu.no/aqdl/steams_pkg.git
cd steams_pkg
pip3 install -e .
Package 'steams' has been tested on python 3.8 and 3.9
Running 'steams' with CUDA (v11.3), requires a manual installation of pytorch:
pip3 install torch==1.11.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
steams-0.18.tar.gz
(15.1 kB
view details)
Built Distribution
steams-0.18-py3-none-any.whl
(16.8 kB
view details)
File details
Details for the file steams-0.18.tar.gz
.
File metadata
- Download URL: steams-0.18.tar.gz
- Upload date:
- Size: 15.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | cf32045a1dad3d86abbfa3f923b40e18811824112b9f726577f47afd716c0605 |
|
MD5 | bdb0f8948990f8a784e8c2ab1eafcbd1 |
|
BLAKE2b-256 | 1b11e0f5f87a46b3416be39f7f0543f73d6d68a02afb3ce8ce3142df63ec78de |
File details
Details for the file steams-0.18-py3-none-any.whl
.
File metadata
- Download URL: steams-0.18-py3-none-any.whl
- Upload date:
- Size: 16.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7763699f352274d35acda1ea9985303df7cc1a35e028d38a428e9edbf33cc76c |
|
MD5 | 821ace87057fccc2723d24fc178d082d |
|
BLAKE2b-256 | 6549ea8ff09a6932d43e174b2c5317747295ff2cd904a511572f3348e623b05b |