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evaluation.py
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evaluation.py
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#!/usr/bin/env python
#-*- coding:utf-8 -*-
#---------------------------------------------------------------
# PyNLPl - Test Units for Evaluation
# by Maarten van Gompel, ILK, Universiteit van Tilburg
# http://ilk.uvt.nl/~mvgompel
# proycon AT anaproy DOT nl
#
# Licensed under GPLv3
#
#-------------------------------------------------------------
from __future__ import print_function
from __future__ import unicode_literals
from __future__ import division
from __future__ import absolute_import
from pynlpl.common import u
import sys
import os
import unittest
import random
from pynlpl.evaluation import AbstractExperiment, WPSParamSearch, ExperimentPool, ClassEvaluation
class ParamExperiment(AbstractExperiment):
def defaultparameters(self):
return {'a':1,'b':1,'c':1}
def run(self):
self.result = 0
for line in self.inputdata:
self.result += int(line) * self.parameters['a'] * self.parameters['b'] - self.parameters['c']
def score(self):
return self.result
@staticmethod
def sample(inputdata,n):
n = int(n)
if n > len(inputdata):
return inputdata
else:
return random.sample(inputdata,int(n))
class PoolExperiment(AbstractExperiment):
def start(self):
self.startcommand('sleep',None,None,None,str(self.parameters['duration']))
print("STARTING: sleep " + str(self.parameters['duration']))
class WPSTest(unittest.TestCase):
def test_wps(self):
inputdata = [ 1,2,3,4,5,6 ]
parameterscope = [ ('a',[2,4]), ('b',[2,5,8]), ('c',[3,6,9]) ]
search = WPSParamSearch(ParamExperiment, inputdata, len(inputdata), parameterscope)
solution = search.searchbest()
self.assertEqual(solution, (('a', 4), ('b', 8), ('c', 3)) )
class ExperimentPoolTest(unittest.TestCase):
def test_pool(self):
pool = ExperimentPool(4)
for i in range(0,15):
pool.append( PoolExperiment(None, duration=random.randint(1,6)) )
for experiment in pool.run():
print("DONE: sleep " + str(experiment.parameters['duration']))
self.assertTrue(True) #if we got here, no exceptions were raised and it's okay
class ClassEvaluationTest2(unittest.TestCase):
def setUp(self):
self.goals = ['sun','sun','rain','cloudy','sun','rain']
self.observations = ['cloudy','cloudy','cloudy','rain','sun','sun']
def test001(self):
e = ClassEvaluation(self.goals, self.observations)
print()
print(e)
print(e.confusionmatrix())
class ClassEvaluationTest(unittest.TestCase):
def setUp(self):
self.goals = ['cat','cat','cat','cat','cat','cat','cat','cat', 'dog', 'dog','dog','dog','dog','dog' ,'rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit']
self.observations = ['cat','cat','cat','cat','cat','dog','dog','dog', 'cat','cat','rabbit','dog','dog','dog' ,'rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','rabbit','dog','dog']
def test001(self):
"""Class evaluation test -- (See also http://en.wikipedia.org/wiki/Confusion_matrix , using same data)"""
e = ClassEvaluation(self.goals, self.observations)
print
print(e)
print(e.confusionmatrix())
self.assertEqual(e.tp['cat'], 5)
self.assertEqual(e.fp['cat'], 2)
self.assertEqual(e.tn['cat'], 17)
self.assertEqual(e.fn['cat'], 3)
self.assertEqual(e.tp['rabbit'], 11)
self.assertEqual(e.fp['rabbit'], 1)
self.assertEqual(e.tn['rabbit'], 13)
self.assertEqual(e.fn['rabbit'], 2)
self.assertEqual(e.tp['dog'], 3)
self.assertEqual(e.fp['dog'], 5)
self.assertEqual(e.tn['dog'], 16)
self.assertEqual(e.fn['dog'], 3)
self.assertEqual( round(e.precision('cat'),6), 0.714286)
self.assertEqual( round(e.precision('rabbit'),6), 0.916667)
self.assertEqual( round(e.precision('dog'),6), 0.375000)
self.assertEqual( round(e.recall('cat'),6), 0.625000)
self.assertEqual( round(e.recall('rabbit'),6), 0.846154)
self.assertEqual( round(e.recall('dog'),6),0.500000)
self.assertEqual( round(e.fscore('cat'),6), 0.666667)
self.assertEqual( round(e.fscore('rabbit'),6), 0.880000)
self.assertEqual( round(e.fscore('dog'),6),0.428571)
self.assertEqual( round(e.accuracy(),6), 0.703704)
if __name__ == '__main__':
unittest.main()