Metadata-Version: 1.1
Name: varys
Version: 0.5.0
Summary: For parsing and reformatting behavioral event logs.
Home-page: https://github.com/beOn/varys
Author: Ben Acland
Author-email: benacland@gmail.com
License: BSD
Description: contents
        ========
        todo
        
        introduction
        ============
        
        Varys is a python package for anyone who has to work with behavioral data
        logs.
        
        Chances are, you need that data in another format before you can work with it.
        
        Chances are, you have some collection of scripts around somewhere that can
        parse format A, other scripts that write format B, and somewhere in the middle
        you'll sandwich some logic that actually has something to do with your
        experiment.
        
        Our goal is to reduce the load down to this last bit.
        
        Varys breaks its work into three segments: LogParser, EventBuilder, and
        FileWriter. Of these, only EventBuilder needs to be customized per experiment.
        
        LogParser is meant to grow with time to be able to parse an increasingly
        diverse list of input sources. At the moment we support simple TDF and CSV
        formats, as well as the FIDL format used by the eponymous software package
        from Washington University. But we're willing and anxious to work with users
        to expand that list.
        
        EventBuilder takes input from a LogParser, and turns it into a list of
        "event" dictionaries. These can contain arbitrary values, but at a minumum
        must contain "name," "onset" and "duration."
        
        FileWriter takes these ordered dictionaries, and writes files consumable by
        analysis packages. At the time of this writing, we support SPM, FIDL, TDF, and
        python's Pickle, but again we're willing and eagre to expand this list.
        
        We've thrown in some special options for working with neuroimaging data, for
        concatenating runs, and other fun stuff too.
        
        So please, take a look at the examples list, see if any of them sound like
        your situation, and feel free to use them as a starting point for your own
        work.
        
        installation
        ============
        
        pip
        ---
        
        First, install the requirements listed in requirements.txt. You'll need scipy
        to write matlab files, and we use chardet to determine the text encoding of
        log files.
        
        sudo pip install -r requirements.txt
        
        
        
        
Keywords: behavioral
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Science/Research
