engage.py

import os
import sys
path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../..'))
if not path in sys.path:
    sys.path.insert(1, path)
del path

import knn
from knn.nearest_neighbor1 import NearestNeighbor

print 'Current path', os.getcwd()

ROW_PATH = 'make_it_so/1100_tweets.txt'
INT_INDICES = [0, 1, 3, 4, 5, 6, 7, 8, 10, 12, 13, 15, 16]
FLOAT_INDICES = [2]
BOOL_INDICES = [9]
STRING_INDICES = [11, 14]

TOS_CAST = ['GineokwKoenig',
            'RealNichelle',
            'TheRealNimoy',
            'WilliamShatner',
            'GeorgeTakei']
TNG_CAST = ['levarburton',
            'jonathansfrakes',
            'BrentSpiner',
            'SirPatStew',
            'wilw']

def get_all_rows():
    row_file = open(ROW_PATH)
    try:
        all_rows = row_file.readlines()
        for i in range(len(all_rows)):
            row = all_rows[i]
            row = row.split()
            for index in range(len(row)):
                value = row[index]
                if index in INT_INDICES:
                    value = int(value)
                elif index in FLOAT_INDICES:
                    value = float(value)
                elif index in BOOL_INDICES:
                    value = bool(value)
                elif index in STRING_INDICES:
                    pass
                else:
                    raise Exception(
                        'Unexpected object type for {}'.format(value))
                    
                row[index] = value
            all_rows[i] = row
        return all_rows
    except:
        raise
    finally:
        row_file.close()

def main():
    model = NearestNeighbor()
    all_rows = get_all_rows()
    
    for i in range(1000):
        model.learn_from_row(all_rows[i])
    
    mistakes = 0
    for i in range(1001, 1100):
        actual_value = all_rows[i][14]
        
        predicted_vaule = model.predict_missing_column(all_rows[i], 14)
        print actual_value, predicted_vaule
        if actual_value in  TOS_CAST:
            actual_cast = 'TOS'
        elif actual_value in TNG_CAST:
            actual_cast = 'TNG'
        if predicted_vaule in TOS_CAST:
            predicted_cast = 'TOS'
        elif predicted_vaule in TNG_CAST:
            predicted_cast = 'TNG'
        print actual_cast, predicted_cast
        if actual_cast != predicted_cast:
            print '\twrong'
            mistakes +=1
        print ''
            
    print 'Total mistakes', mistakes
        
if __name__ == '__main__':
    main()