Metadata-Version: 2.1
Name: mass_ts
Version: 0.1.2
Summary: MASS (Mueen's Algorithm for Similarity Search)
Home-page: https://github.com/tylerwmarrs/mass_ts
Author: Tyler Marrs
Author-email: tylerwmarrs@gmail.com
License: Apache Software License 2.0
Description: MASS (Mueen's Algorithm for Similarity Search)
        ----------------------------------------------
        
        [<img src="https://img.shields.io/pypi/v/mass_ts.svg">](https://pypi.python.org/pypi/mass_ts)
        [<img src="https://img.shields.io/travis/tylerwmarrs/mass-ts.svg">](https://travis-ci.org/tylerwmarrs/mass-ts)
        [<img src="https://readthedocs.org/projects/mass-ts/badge/?version=latest">](https://mass-ts.readthedocs.io/en/latest/?badge=latest)
        
        MASS is the fundamental algorithm that the matrix profile algorithm is built on top of. It allows you to search a time series for a smaller series. The result is an array of distances. To find the "closest" section of a time series to yours, simply find the minimum distance(s).
        
        mass-ts is a python 2 and 3 compatible library.
        
        * Free software: Apache Software License 2.0
        
        
        Features
        --------
        
        * MASS - the first implementation of MASS
        * MASS2 - the second implementation of MASS that is significantly faster. Typically this is the one you will use.
        * MASS3 - a piecewise version of MASS2 that can be tuned to your hardware. Generally this is used to search very large time series.
        * MASS2_batch - a batch version of MASS2 that reduces overall memory usage, provides parallelization and enables you to find top K number of matches within the time series. The goal of using this implementation is for very large time series similarity search.
        
        Installation
        ------------
        ```
        pip install mass-ts
        ```
        
        Example Usage
        -------------
        A dedicated repository for practical examples can be found at the [mass-ts-examples repository](https://github.com/tylerwmarrs/mass-ts-examples).
        
        ```python
        
        import numpy as np
        import mass_ts as mts
        
        ts = np.loadtxt('ts.txt')
        query = np.loadtxt('query.txt')
        
        # mass
        distances = mts.mass(ts, query)
        
        # mass2
        distances = mts.mass2(ts, query)
        
        # mass3
        distances = mts.mass3(ts, query, 256)
        
        # mass2_batch
        # start a multi-threaded batch job with all cpu cores and give me the top 5 matches.
        # note that batch_size partitions your time series into a subsequence similarity search.
        # even for large time series in single threaded mode, this is much more memory efficient than
        # MASS2 on its own.
        batch_size = 10000
        top_matches = 5
        n_jobs = -1
        indices, distances = mts.mass2_batch(ts, query, batch_size, 
            top_matches=top_matches, n_jobs=n_jobs)
        
        # find minimum distance
        min_idx = np.argmin(distances)
        ```
        
        Citations
        ---------
        Abdullah Mueen, Yan Zhu, Michael Yeh, Kaveh Kamgar, Krishnamurthy Viswanathan, Chetan Kumar Gupta and Eamonn Keogh (2015), The Fastest Similarity Search Algorithm for Time Series Subsequences under Euclidean Distance, URL: http://www.cs.unm.edu/~mueen/FastestSimilaritySearch.html
        
        
        =======
        History
        =======
        
        0.1.0 (2019-05-16)
        ------------------
        
        * First release on PyPI.
        
        
        0.1.1 (2019-05-17)
        ------------------
        
        * Minor precision bug fixes.
        
        
        0.1.2 (2019-05-19)
        ------------------
        
        * mass2_batch release for efficient large time series searching.
Keywords: mass_ts
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
