Metadata-Version: 2.1
Name: multimatch
Version: 0.1.0
Summary: Multidimensional scanpath comparison
Home-page: https://github.com/adswa/multimatch
Author: Adina Wagner
Author-email: adina.wagner@t-online.de
License: UNKNOWN
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        # multimatch
        ## Reimplementation of MultiMatch toolbox (Dewhurst et al., 2012) in Python.
        
        The **MultiMatch** method proposed by Jarodzka, Holmqvist and Nyström (2010),
        implemented in Matlab as the MultiMatch toolbox and validated by Dewhurst
        and colleagues (2012) is a vector-based, multi-dimensional approach to
        compute scanpath similarity.
        
        For a complete overview of this software, please take a look at the
        [Documentation](https://multimatch.readthedocs.io/en/latest)
        
        The method represents scanpaths as geometrical vectors in a two-dimensional
        space: Any scanpath is build up of a vector sequence in which the vectors
        represent saccades, and the start and end position of saccade vectors represent
        fixations. Two such sequences (which can differ in length) are compared on the
        five dimensions **'vector shape'**, **'vector length'** (saccadic amplitude),
        **'vector position'**, **'vector direction'** and **'fixation duration'** for a
        multidimensional similarity evaluation (all in range [0, 1] with 0 denoting
        maximal dissimilarity and 1 denoting identical scanpaths on the given measure).
        The original Matlab toolbox was kindly
        provided via email by Dr. Richard Dewhurst and the method was ported into Python
        with the intent of providing an open source alternative to the matlab toolbox.
        
        ### Installation instructions
        
        It is recommended to use a dedicated virtualenv:
        
            # create and enter a new virtual environment (optional)
            virtualenv --python=python3 ~/env/multimatch
            . ~/env/multimatch/bin/activate
        
        multimatch can be installed via pip. To automatically install multimatch with all
        dependencies, use:
        
            # install from pyPi
            pip install multimatch
        
        
        ### Support/Contributing
        
        Bug reports, feedback, or any other contribution are always appreciated. To
        report a bug, request a feature, or ask a question, please open an
        [issue](https://github.com/adswa/multimatch/issues/new).
        [Pull requests](https://help.github.com/en/articles/creating-a-pull-request-from-a-fork)
        are always welcome.
        
        
        ### Examplary usage of multimatch in a terminal
        
        **required inputs:**
        - two tab-separated files with nx3 fixation vectors (x coordinate in px, y coordinate in px, duration)
        
        `` multimatch data/fixvectors/segment_10_sub-19.tsv data/fixvectors/segment_10_sub-01.tsv ``
        
        
        
        **optional inputs:**
        - --screensize: in pixel, supply first x and then y dimension. The default size is 1280 x 720px
        
        `` multimatch data/fixvectors/segment_10_sub-19.tsv data/fixvectors/segment_10_sub-01.tsv --screensize 1280 720 ``
        
        if scanpath simplification should be performed, please specify in addition
        - --amplitude-threshold (-am) in px
        - --direction-threshold (-di) in degree
        - --duration-threshold (-du) in seconds
        
        Example usage with grouping:
        
        `` multimatch data/fixvectors/segment_10_sub-19.tsv
        data/fixvectors/segment_10_sub-01.tsv --direction-threshold 45.0
        --duration-threshold 0.3 --amplitude-threshold 147.0 ``
        
        
        ### References:
        
        Dewhurst, R., Nyström, M., Jarodzka, H., Foulsham, T., Johansson, R. &
        Holmqvist, K. (2012). It depends on how you look at it: scanpath comparison in
        multiple dimensions with MultiMatch, a vector-based approach. Behaviour Research
        Methods, 44(4), 1079-1100. [doi: 10.3758/s13428-012-0212-2.](https://doi.org/10.3758/s13428-012-0212-2)
        
        Dijkstra, E. W. (1959). A note on two problems in connexion withgraphs.
        Numerische Mathematik, 1, 269–271. [https://doi.org/10.1007/BF01386390](https://doi.org/10.1007/BF01386390)
        
        Jarodzka, H., Holmqvist, K., & Nyström, M. (eds.) (2010). A vector-based,
        multidimensional scanpath similarity measure. In Proceedings of the 2010
        symposium on eye-tracking research & applications (pp. 211-218). ACM.
        [doi: 10.1145/1743666.1743718](https://doi.org/10.1145/1743666.1743718)
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Provides-Extra: devel-docs
