mirror of https://github.com/Yomguithereal/fog.git
44 lines
1.1 KiB
Markdown
44 lines
1.1 KiB
Markdown
[![Build Status](https://travis-ci.org/Yomguithereal/fog.svg)](https://travis-ci.org/Yomguithereal/fog)
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# Fog
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A fuzzy matching/clustering library for Python.
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## Installation
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You can install `fog` with pip with the following command:
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```
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pip install fog
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```
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## Usage
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* [Metrics](#metrics)
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- [sparse_cosine_similarity](#sparse_cosine_similarity)
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### Metrics
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#### sparse_cosine_similarity
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Computes the cosine similarity of two sparse weighted sets. Those sets have to be represented as counters.
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```python
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from fog.metrics import sparse_cosine_similarity
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# Basic
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sparse_cosine_similarity({'apple': 34, 'pear': 3}, {'pear': 1, 'orange': 1})
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>>> ~0.062
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# Using custom key
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A = {'apple': {'weight': 34}, 'pear': {'weight': 3}}
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B = {'pear': {'weight': 1}, 'orange': {'weight': 1}}
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sparse_cosine_similarity(A, B, key=lambda x: x['weight'])
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```
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*Arguments*
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* **A** *Counter*: first weighted set. Must be a dictionary mapping keys to weights.
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* **B** *Counter*: second weighted set. Muset be a dictionary mapping keys to weights.
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* **key** *?callable*: Optional function retrieving the weight from values.
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