Metadata-Version: 2.1
Name: fuzzycorr
Version: 0.1.0
Summary: A numpy implementation of Robust Rank Correlation Coefficients.
Home-page: https://github.com/mikulatomas/fuzzycorr
Author: Tomáš Mikula
Author-email: mail@tomasmikula.cz
License: MIT license
Keywords: fuzzycorr correlation fuzzy
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: test
License-File: LICENSE
License-File: AUTHORS.md

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# fuzzycorr
A ``numpy`` implementation of Robust Rank Correlation Coefficients (fuzzy correlation) based on paper:

```
Bodenhofer, U., and F. Klawonn. "Robust rank correlation coefficients on the basis of fuzzy."
Mathware & Soft Computing 15.1 (2008): 5-20.
```

This implementation is experimental and need future optimization and testing.

## Installation

This package will be avaliable soon on ``pip``.

## Basic usage

```python
from fuzzycorr import fuzzy_correlation_factory
from fuzzycorr.strict_orderings import lukasiewicz_strict_ordering_factory
from fuzzycorr.t_norms import godel

# create strict fuzzy ordering or supply own one
strict_ordering = lukasiewicz_strict_ordering_factory(r=0.2)

# create fuzzy correlation function with tnorm
fuzzy_corr = fuzzy_correlation_factory(strict_ordering, godel)

# load data
x = np.random.random(10)
y = np.random.random(10)

# calculate fuzzy correlation
fuzzy_corr(x, y)
```

Visit [example Jupiter Notebook](example.ipynb).

