Metadata-Version: 2.1
Name: stVAE
Version: 0.1b0
Summary: Style transfer variational autoencoder
Home-page: https://github.com/NRshka/stvae/source
Author: ['N. Russkikh', 'A. Makarov', 'D. Antonets', 'D. Shtokalo']
Author-email: makarov.alxr@yandex.ru
License: MIT license
Description: ==================
        Style transfer VAE
        ==================
        
        The official pytorch implementation of "*Style transfer with variational autoencoders is a promising approach to RNA-Seq data harmonization and analysis*".
        The package contains a code for training and testing the model, as well as a code for working with different types of datasets.
        
        **Installation**
        
        To install the latest version from PyPI, use:
        
        >>> pip install stvae
        
        **Benchmarks**
        
        The original code containing code with testing several models can be found here_.
        
        .. _here: https://github.com/NRshka/stvae-source
        
        **Example**
        
        .. code-block:: python
        
           ds = stvae.datasets.MouseDataset()
           cfg = stvae.Config()
           train, test, classif = ds.split(0.15, True, 0.15)
           cfg.count_classes = ds.n_labels
           cfg.count_classes = ds.n_batches
           cfg.input_dim = ds.nb_genes
           model = stvae.stVAE(cfg)
           model.train(train, None)
           d = model.test(test, classif)
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Natural Language :: Russian
Classifier: Programming Language :: Python :: 3.7
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
