Metadata-Version: 2.3
Name: diresa
Version: 1.0.8
Summary: Diresa - distance-regularized siamese twin autoencoder
Project-URL: Homepage, https://gitlab.com/etrovub/ai4wcm/public/diresa
Project-URL: Issues, https://gitlab.com/etrovub/ai4wcm/public/diresa/-/issues
Author-email: Geert De Paepe <geert.de.paepe@vub.be>
License-File: LICENSE
Keywords: climate,learning,machine,tensorflow,weather
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.6
Requires-Dist: tensorflow-probability>=0.15
Requires-Dist: tensorflow>=2.7
Description-Content-Type: text/markdown

# *DIRESA*


### Overview

*DIRESA* is a Python package for dimension reduction based on 
[TensorFlow](https://www.tensorflow.org). The distance-regularized 
Siamese twin autoencoder architecture is designed to preserve distance 
(ordering) in latent space while capturing the non-linearities in
the datasets.


### Prerequisites

The *DIRESA* package depends on the [tensorflow](https://www.tensorflow.org) 
and [tensorflow_probability](https://www.tensorflow.org/probability) packages. 
These can be installed with the following commands:

``` bash
  pip install tensorflow
  pip install tensorflow_probability
```

### Install *DIRESA*

Install *DIRESA* with the following command:

``` bash
  pip install diresa
```

### Documentation

The *DIRESA* documentation can be found on [Read the Docs](https://diresa-learn.readthedocs.io)