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https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nopaque.git
synced 2024-11-15 01:05:42 +00:00
Add get_sentences to wrapper
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@ -5,7 +5,7 @@ from app import logger # only works if imported into opaque web app
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class CQiWrapper(CQiClient):
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"""
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'''
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CQIiWrapper object
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High level wrapper that groups and renames some functions of CQiClient
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@ -16,7 +16,7 @@ class CQiWrapper(CQiClient):
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port -- port of the cqp server
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username -- username used to connect to the cqp server
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password -- password of the user to connect to the cqp server
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"""
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'''
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SUBCORPUS_NAMES = []
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@ -27,20 +27,21 @@ class CQiWrapper(CQiClient):
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self.password = password
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def connect(self):
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"""
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'''
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Connect with CQP server
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Connects via socket to the CQP server using the given username and
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password from class initiation.
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"""
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'''
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self.ctrl_connect(self.username, self.password)
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def __create_attribute_strings(self):
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"""
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'''
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Creates all needed attribute strings to query for word, lemma etc. in
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the given corpus.
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For example: CORPUS_NAME.word to query words
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"""
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Automaticalle creates strings for all pre defined tags.
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'''
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p_attrs = self.corpus_positional_attributes(self.corpus_name)
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struct_attrs = self.corpus_structural_attributes(self.corpus_name)
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self.attr_strings = {}
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@ -54,40 +55,45 @@ class CQiWrapper(CQiClient):
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self.attr_strings['struct_attrs'][struct_attr] = (self.corpus_name
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+ '.'
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+ struct_attr)
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# logger.warning(('All positional and '
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# 'structural attributes: {}').format(self.attr_strings))
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logger.warning(('All positional and '
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'structural attributes: {}').format(self.attr_strings))
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def select_corpus(self, corpus_name):
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'''
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Checks if given copus name exists. If it exists set it as the main
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corpus name used to create the needed query attribute strings like
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CORPUS_NAME.word.
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'''
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if corpus_name in self.corpus_list_coprora():
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self.corpus_name = corpus_name
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self.__create_attribute_strings()
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# logger.warning('{} does exist.'.format(corpus_name))
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logger.warning('{} does exist.'.format(corpus_name))
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else:
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# logger.warning('{} does not exist.'.format(corpus_name))
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pass
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logger.warning('{} does not exist.'.format(corpus_name))
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raise Exception('Given Corpus Name is not in corpora list.')
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def disconnect(self):
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"""
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'''
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Disconnect from CQP server
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Disconnects from the CQP server. Closes used socket after disconnect.
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"""
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'''
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self.ctrl_bye()
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self.connection.close()
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# logger.warning('Disconnected from cqp server.')
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logger.warning('Disconnected from cqp server.')
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def query_subcorpus(self, query, result_subcorpus_name='Query-results'):
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"""
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'''
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Create subcorpus
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Input query will be used to create a subcorpus holding all cpos match
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positions for that query.
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Keyword arguments:
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result_subcorpus_name -- user set name of the subcorpus which holds all
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result_subcorpus_name -- set name of the subcorpus which holds all
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cpos match positions, produced by the query
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query -- query written in cqp query language
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"""
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'''
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self.cqp_query(self.corpus_name, result_subcorpus_name, query)
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self.result_subcorpus = (self.corpus_name
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+ ':'
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@ -95,19 +101,19 @@ class CQiWrapper(CQiClient):
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self.SUBCORPUS_NAMES.append(self.result_subcorpus)
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self.nr_matches = self.cqp_subcorpus_size(self.result_subcorpus)
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print('Nr of all matches is:', self.nr_matches)
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# logger.warning('Nr of all matches is: {}'.format(self.nr_matches))
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logger.warning('Nr of all matches is: {}'.format(self.nr_matches))
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def show_subcorpora(self):
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"""
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'''
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Show all subcorpora currently saved by the cqp server.
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"""
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'''
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return self.cqp_list_subcorpora(self.corpus_name)
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def show_query_results(self,
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context_len=10,
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result_len=1000,
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result_offset=0):
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"""
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'''
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Show query results
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Shows the actual matched strings produce by the query. Uses the cpos
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@ -118,15 +124,20 @@ class CQiWrapper(CQiClient):
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Keyword arguments:
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context_len -- defines how many words before and after a match will be
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shown (default 10)
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result_len -- defines how many results are actually grabbed
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"""
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result_len -- defines for how many matches all informations like lemma
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and POS are being grabbed
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result_offset -- defines the offset of the matches being requested. If
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the offset is 100 informations for matches 100 to result_len are being
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grabbed
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'''
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t0 = time.time()
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self.context_len = context_len
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self.corpus_max_len = self.cl_attribute_size(
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self.attr_strings['positional_attrs']['word']
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)
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self.nr_matches = min(result_len, self.nr_matches)
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if self.nr_matches == 0:
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# logger.warning('Query resulted in 0 matches.')
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logger.warning('Query resulted in 0 matches.')
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return None
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else:
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# Get match cpos boundries
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@ -144,7 +155,8 @@ class CQiWrapper(CQiClient):
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offset_start,
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offset_end))
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# Generate all cpos between match boundries including start and end boundries.
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# Generate all cpos between match boundries including start and end
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# boundries.
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# Also generate cpos for left and right context.
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# Save those cpos into dict as lists for the keys 'lc', 'hit' and 'rc'
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# Also collect all cpos together in one list for the final request of
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@ -157,42 +169,34 @@ class CQiWrapper(CQiClient):
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lc = {'lc': lc_cpos}
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match_cpos = list(range(start, end))
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match = {'hit': match_cpos}
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rc_cpos = list(range(end, min([self.corpus_max_len, end + self.context_len])))
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rc_cpos = list(range(end, min([self.corpus_max_len,
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end + self.context_len])))
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rc = {'rc': rc_cpos}
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lc.update(match)
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lc.update(rc)
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all_cpos.extend(lc_cpos + match_cpos + rc_cpos)
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all_matches.append(lc)
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# print(all_matches)
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# print(all_cpos)
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# Get all cpos for all sneteces boundries
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# s_lookup = {}
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# for s_id in set(s_ids):
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# s_start, s_end = self.cl_struc2cpos('UTOPIEN.s', s_id)
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# # CHANGE to UTOPIEN.s will always be like this in nopaque
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# s_cpos = range(s_start, s_end)
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# s_lookup.update({s_id: list(s_cpos)})
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# # print(list(s_cpos))
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# all_cpos.extend(s_cpos)
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t0 = time.time()
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all_cpos = list(set(all_cpos)) # get rid of cpos duplicates
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all_cpos = list(set(all_cpos)) # get rid of cpos duplicates
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len_all_cpos = len(all_cpos)
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t1 = time.time()
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t_total = t1 - t0
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print('TIME FOR ALL CPOS:', t_total)
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print('CPOS SUM:', len(all_cpos))
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logger.warning('Time to create all CPOS for query: {}'.format(t_total))
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print('Requesting {} CPOS with one query.'.format(len_all_cpos))
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# Get cpos informations like CORPUS_NAME.word or CORPUS_NAME.lemma for
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# all cpos entries in all_cpos_list
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# Also saves these informations into self.results dict
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t6 = time.time()
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t2 = time.time()
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all_cpos_infos, text_lookup = self.get_cpos_infos(all_cpos)
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t7 = time.time()
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t_final = t7 - t6
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print('GOT ALL RESULTS IN:', t_final)
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self.results = {'matches': all_matches, 'cpos_lookup': all_cpos_infos,
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'text_lookup': text_lookup}
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t3 = time.time()
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t_final = t3 - t2
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print('Got infos for {} CPOS in {} seconds:'.format(len_all_cpos,
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t_final))
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self.results = {'matches': all_matches,
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'cpos_lookup': all_cpos_infos,
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'text_lookup': text_lookup,
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'nr_matches': self.nr_matches}
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return self.results
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def get_cpos_infos(self, all_cpos):
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@ -250,3 +254,44 @@ class CQiWrapper(CQiClient):
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for info in joined_cpos_infos:
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dict_cpos_infos[info[0]] = dict(zip(attr_keys_list, info[1:]))
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return dict_cpos_infos, text_lookup
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def get_sentences(self,
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match_cpos_list,
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get_surrounding_s=False,
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l_r_s_context_additional_len=1):
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'''
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Get sentence informations for one match also set if and how much left
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right context sentences should be grabbed surrounding the given CPOS.
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'''
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t0 = time.time()
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key = self.corpus_name + '.s'
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first_cpos, last_cpos = match_cpos_list[0], match_cpos_list[-1]
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context_sentences = {}
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s_ids = self.cl_cpos2struc(key, [first_cpos, last_cpos])
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for s_id in s_ids:
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s_start, s_end = self.cl_struc2cpos(key, s_id)
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s_cpos = list(range(s_start, s_end + 1))
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context_sentences[s_id] = s_cpos
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if get_surrounding_s:
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max_s_id = self.cl_attribute_size(key)
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additional_s_ids = []
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additional_s = list(range(max(s_ids[0]
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- l_r_s_context_additional_len,
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0),
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min(s_ids[-1]
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+ l_r_s_context_additional_len,
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max_s_id) + 1))
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additional_s_ids.extend(additional_s)
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for s_id in additional_s_ids:
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s_start, s_end = self.cl_struc2cpos(key, s_id)
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s_cpos = list(range(s_start, s_end + 1))
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context_sentences[s_id] = s_cpos
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all_cpos = []
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for key in context_sentences.keys():
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all_cpos.extend(context_sentences[key])
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all_cpos = list(set(all_cpos))
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all_cpos_infos, text_lookup = self.get_cpos_infos(all_cpos)
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t1 = time.time()
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t_total = t1 - t0
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logger.warning('Got all sentences informations in {} seconds'. format(t_total))
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return context_sentences, all_cpos_infos, text_lookup
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