Metadata-Version: 2.4
Name: scalemap
Version: 0.1.1
Summary: A modification of umap that incorporates local scale into the embedding.
Author: Rajas Poorna
License-Expression: BSD-3-Clause
Keywords: dimension reduction,umap,manifold learning,embedding
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: NOTICE.md
Requires-Dist: numpy>=1.23
Requires-Dist: scipy>=1.3.1
Requires-Dist: scikit-learn>=1.6
Requires-Dist: numba>=0.51.2
Requires-Dist: pynndescent>=0.5
Requires-Dist: tqdm
Provides-Extra: plot
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Provides-Extra: parametric-umap
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Provides-Extra: tbb
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Provides-Extra: test
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Dynamic: license-file

# ScaleMAP

ScaleMAP is a modification of UMAP that incorporates local scale into the embedding.

This package is currently a quick release. It is derived from `umap-learn` and keeps the same scikit-learn-style estimator interface.

## Installation

```bash
pip install scalemap
```

## Usage

```python
import scaleMAP

mapper = scaleMAP.UMAP(scalemap=True, scale_lambda=1.0)
embedding = mapper.fit_transform(data)
```

The distribution name on PyPI is `scalemap`; the import package is `scaleMAP`.
If you don't set scalemap=True, it will behave just like UMAP. 
scale_lambda=1.0 sets the scaleMAP behavior to be fully on. You can interpolate between fully on and fully off by setting values between 0.0 and 1.0.

## Attribution

ScaleMAP is derived from `umap-learn` by Leland McInnes and contributors. The upstream project is available at:

https://github.com/lmcinnes/umap

The upstream UMAP package is BSD 3-Clause licensed. ScaleMAP is distributed under the same license. See `LICENSE` and `NOTICE.md`.

If you use this package in scientific work, cite the original UMAP work as appropriate:

```bibtex
@article{mcinnes2018umap-software,
  title={UMAP: Uniform Manifold Approximation and Projection},
  author={McInnes, Leland and Healy, John and Saul, Nathaniel and Grossberger, Lukas},
  journal={The Journal of Open Source Software},
  volume={3},
  number={29},
  pages={861},
  year={2018}
}
```
