Metadata-Version: 1.1
Name: labMTsimple
Version: 0.3.1
Summary: Basic usage script for LabMT1.0 dataset
Home-page: https://github.com/andyreagan/labMT-simple
Author: Andy Reagan
Author-email: andy@andyreagan.com
License: UNKNOWN
Download-URL: https://github.com/andyreagan/labMT-simple/tarball/0.3
Description: labMT-simple
        ============
        
        TL;DR a simple labMT usage script
        
        a python module for using the labMT1.0 dataset
        
        no dependencies, unless using the plot function (then we use matplotlib)
        
        Usage
        -----
        
        The Python script test.py uses this module to test a subsample of
        Twitter data:
        
        .. code:: python
        
            ## set up
            from storyLab import *
            labMT,labMTvector,labMTwordList = emotionFileReader(returnVector=True)
        
            ## take a look at these guys
            print labMT['laughter']
            print labMTvector[0:5]
            print labMTwordList[0:5]
        
            ## test shift a subsample of two twitter days
            import codecs ## handle utf8
            f = codecs.open("test/01.02.14.txt","r","utf8")
            saturday = f.read()
            f.close()
            f = codecs.open("test/04.02.14.txt","r","utf8")
            tuesday = f.read()
            f.close()
        
            ## compute valence score
            saturdayValence = emotion(saturday,labMT)
            tuesdayValence = emotion(tuesday,labMT)
            print 'the valence of {0} is {1}'.format('saturday',saturdayValence)
            print 'the valence of {0} is {1}'.format('tuesday',tuesdayValence)
        
            ## compute valence score and return frequency vector for generating wordshift
            saturdayValence,saturdayFvec = emotion(saturday,labMT,shift=True,happsList=labMTvector)
            tuesdayValence,tuesdayFvec = emotion(tuesday,labMT,shift=True,happsList=labMTvector)
        
            ## make a shift: shift(values,ref,comp)
            shiftMag,shiftType = shift(labMTvector,saturdayFvec,tuesdayFvec)
            ## take the absolute value of the shift magnitude
            shiftMagAbs = map(abs,shiftMag)
        
            ## sort them both
            indices = sorted(range(len(shiftMag)), key=shiftMagAbs.__getitem__, reverse=True)
            sortedMag = [shiftMag[i] for i in indices]
            sortedType = [shiftType[i] for i in indices]
            sortedWords = [labMTwordList[i] for i in indices]
        
            ## take a peek at the top words  
            print indices[0:10]
            print sortedMag[0:20]
            print sortedType[0:20]
            print sortedWords[0:20]
        
            ## print each of these to a file
            f = open("test/sampleSortedMag.csv","w")
            for val in sortedMag:
              f.write(str(val))
              f.write("\n")
            f.close()
        
            f = open("test/sampleSortedType.csv","w")
            for val in sortedType:
              f.write(str(val))
              f.write("\n")
            f.close()
        
            f = open("test/sampleSortedWords.csv","w")
            for val in sortedWords:
              f.write(val)
              f.write("\n")
            f.close()
        
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
