117 lines
3.9 KiB
Python
117 lines
3.9 KiB
Python
#!/usr/bin/env python3
|
|
# -*- encoding: utf-8 -*-
|
|
|
|
# Copyright (c) 2017 Adler Neves <adlerosn@gmail.com>
|
|
#
|
|
# MIT License
|
|
#
|
|
# Permission is hereby granted, free of charge, to any person obtaining
|
|
# a copy of this software and associated documentation files (the
|
|
# "Software"), to deal in the Software without restriction, including
|
|
# without limitation the rights to use, copy, modify, merge, publish,
|
|
# distribute, sublicense, and/or sell copies of the Software, and to
|
|
# permit persons to whom the Software is furnished to do so, subject to
|
|
# the following conditions:
|
|
#
|
|
# The above copyright notice and this permission notice shall be
|
|
# included in all copies or substantial portions of the Software.
|
|
#
|
|
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
|
|
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
|
|
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
|
|
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
|
|
# LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
|
|
# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
|
|
# WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
|
|
|
|
flatten = lambda lst: [item for sublist in lst for item in sublist]
|
|
|
|
with open('unitexable_test/corpus.answers_final.txt') as f:
|
|
answers = [[word.split('/') for word in sentence.splitlines()] for sentence in f.read().strip().split('\n\n')]
|
|
|
|
with open('unitexable_test/corpus.guesses_final.txt') as f:
|
|
guesses = [[word.split('/') for word in sentence.splitlines()] for sentence in f.read().strip().split('\n\n')]
|
|
|
|
assert len(answers) == len(guesses)
|
|
|
|
tags = list()
|
|
|
|
for i in range(len(answers)):
|
|
assert len(answers[i]) == len(answers[i])
|
|
for j in range(len(answers[i])):
|
|
assert len(answers[i][j]) == len(answers[i][j])
|
|
tags += list(zip(
|
|
[k[1] for k in answers[i]],
|
|
[k[1] for k in guesses[i]]
|
|
))
|
|
|
|
convertAns = [
|
|
]
|
|
|
|
convertGss = [
|
|
|
|
]
|
|
|
|
for i, tag in enumerate(tags):
|
|
tag = list(tag)
|
|
for subst in convertAns:
|
|
if tag[0] == subst[0]:
|
|
tag[0] = subst[1]
|
|
for subst in convertGss:
|
|
if tag[1] == subst[0]:
|
|
tag[1] = subst[1]
|
|
tags[i] = tag
|
|
|
|
allTags = sorted(list(set(flatten(tags))))
|
|
|
|
confusionMatrix = dict()
|
|
|
|
equality = {True:0, False:0}
|
|
|
|
from statisticsMetrics import getConfusionMatrixEmptyData
|
|
|
|
for tag in allTags:
|
|
confusionMatrix[tag] = getConfusionMatrixEmptyData()
|
|
|
|
for ans, gss in tags:
|
|
if ans not in confusionMatrix:
|
|
confusionMatrix[ans] = getConfusionMatrixEmptyData()
|
|
if gss not in confusionMatrix:
|
|
confusionMatrix[gss] = getConfusionMatrixEmptyData()
|
|
# if gss == '???':
|
|
# continue
|
|
equality[gss==ans]+=1
|
|
for clazz in allTags:
|
|
# if clazz == '???':
|
|
# continue
|
|
confusionMatrix[clazz][clazz==ans][clazz==gss]+=1
|
|
# "Preposition" in "True" "Positive" increments
|
|
|
|
#if '???' in confusionMatrix:
|
|
# del confusionMatrix['???']
|
|
|
|
import json
|
|
|
|
with open('unitexable_test/confusion_matrix.json','w') as f:
|
|
f.write(json.dumps(confusionMatrix,indent=4,sort_keys=True))
|
|
|
|
sumConfusionMatrix = getConfusionMatrixEmptyData()
|
|
for cm in confusionMatrix.values():
|
|
for x in [True, False]:
|
|
for y in [True, False]:
|
|
sumConfusionMatrix[x][y] += cm[x][y]
|
|
|
|
with open('unitexable_test/confusion_matrix_sum.json','w') as f:
|
|
f.write(json.dumps(sumConfusionMatrix,indent=4,sort_keys=True))
|
|
|
|
with open('unitexable_test/equality.json','w') as f:
|
|
f.write(json.dumps(equality,indent=4,sort_keys=True))
|
|
|
|
from statisticsMetrics import getStatistics as statistics
|
|
|
|
with open('unitexable_test/confusion_matrix.stats.json','w') as f:
|
|
f.write(json.dumps({clazz:statistics(cm) for clazz, cm in confusionMatrix.items()},indent=4,sort_keys=True))
|
|
|
|
with open('unitexable_test/confusion_matrix_sum.stats.json','w') as f:
|
|
f.write(json.dumps(statistics(sumConfusionMatrix),indent=4,sort_keys=True))
|