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73 lines
3.0 KiB
Python
73 lines
3.0 KiB
Python
#!/usr/bin/env python3
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# -*- encoding: utf-8 -*-
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# Copyright (c) 2017 Adler Neves <adlerosn@gmail.com>
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#
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# MIT License
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#
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# Permission is hereby granted, free of charge, to any person obtaining
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# a copy of this software and associated documentation files (the
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# "Software"), to deal in the Software without restriction, including
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# without limitation the rights to use, copy, modify, merge, publish,
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# distribute, sublicense, and/or sell copies of the Software, and to
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# permit persons to whom the Software is furnished to do so, subject to
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# the following conditions:
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#
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# The above copyright notice and this permission notice shall be
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# included in all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
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# LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
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# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
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# WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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import os
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encodings_to_try = ['utf-8','iso-8859-1','cp1252','ascii']
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dir_to_look_corpora = 'downloaded'
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allInOne = []
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def decode_try_multiple(stringbytes, encodings = ['utf-8','ascii']):
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lastException = UnicodeDecodeError('empty',b'',0,1,'No encodings provided')
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for encoding in encodings:
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try: return stringbytes.decode(encoding)
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except UnicodeDecodeError as exc: lastException = exc
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raise lastException
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for corpus_fn in sorted(list(filter(lambda a: a!='readme.md', os.listdir(dir_to_look_corpora)))):
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corpus_path = os.path.join(dir_to_look_corpora, corpus_fn)
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with open(corpus_path, 'rb') as f:
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fileBytes = f.read()
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fileString = decode_try_multiple(fileBytes, encodings_to_try)
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allInOne.append(fileString.strip())
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allInOne = '\n'.join(allInOne).strip()
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allInOne = [[word.split('_',1) for word in sentence.split(' ') if len(word)>0] for sentence in allInOne.splitlines()]
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x = [[word[0] for word in sentence] for sentence in allInOne]
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y = [[word[1] for word in sentence] for sentence in allInOne]
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from sklearn.model_selection import train_test_split
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train, test = train_test_split(allInOne, test_size=0.6, random_state=96)
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tr_s = '\n\n'.join(['\n'.join(['/'.join(wrd) for wrd in snt]) for snt in train])
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te_s = '\n\n'.join(['\n'.join(['/'.join(wrd) for wrd in snt]) for snt in test])
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te_u = '\n'.join([' '.join([wrd[0] for wrd in snt]) for snt in test])
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with open('unitexable_train/corpus.txt.answersheet.txt','w') as f:
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f.write(tr_s)
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with open('unitexable_train/corpus.txt','w') as f:
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f.write(tr_s)
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with open('unitexable_test/corpus.txt','w') as f:
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f.write(te_s)
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with open('unitexable_test/corpus.answersheet.txt','w') as f:
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f.write(te_s)
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with open('unitexable_test/corpus.answers_final.txt','w') as f:
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f.write(te_s)
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with open('unitexable_test/corpus.txt.untagged.txt','w') as f:
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f.write(te_u)
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