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Commit dbd580b3 authored by Stephan Porada's avatar Stephan Porada :speech_balloon:
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Get results with wrapper 3.0

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app/corpora/CQiWrapper/CQiWrapper.py
+ 67
− 57
View file @ dbd580b3
from .CQiClient import CQiClient
from .CQi import CONST_FIELD_MATCH, CONST_FIELD_MATCHEND
import re
import time
from app import logger # only works if imported into opaque web app
......@@ -94,6 +94,7 @@ class CQiWrapper(CQiClient):
+ result_subcorpus_name)
self.SUBCORPUS_NAMES.append(self.result_subcorpus)
self.nr_matches = self.cqp_subcorpus_size(self.result_subcorpus)
print('Nr of all matches is:', self.nr_matches)
# logger.warning('Nr of all matches is: {}'.format(self.nr_matches))
def show_subcorpora(self):
......@@ -104,7 +105,8 @@ class CQiWrapper(CQiClient):
def show_query_results(self,
context_len=10,
result_len=1000):
result_len=1000,
result_offset=0):
"""
Show query results
......@@ -131,14 +133,16 @@ class CQiWrapper(CQiClient):
# match_boundries shows the start and end cpos of one match as a
# pair of cpositions
# [(1355, 1357), (1477, 1479)] Example for two boundry pairs
offset_start = 0 + (result_offset + 1) if result_offset != 0 else result_offset
offset_end = self.nr_matches + result_offset
match_boundaries = zip(self.cqp_dump_subcorpus(self.result_subcorpus,
CONST_FIELD_MATCH,
0,
self.nr_matches - 1),
offset_start,
offset_end),
self.cqp_dump_subcorpus(self.result_subcorpus,
CONST_FIELD_MATCHEND,
0,
self.nr_matches - 1))
offset_start,
offset_end))
# Generate all cpos between match boundries including start and end boundries.
# Also generate cpos for left and right context.
......@@ -152,7 +156,7 @@ class CQiWrapper(CQiClient):
lc = {'lc': lc_cpos}
match_cpos = list(range(start, end + 1))
match = {'hit': match_cpos}
rc_cpos = list(range(end + 1, min([self.corpus_max_len, end + self.context_len + 1])))
rc_cpos = list(range(end, min([self.corpus_max_len, end + self.context_len])))
rc = {'rc': rc_cpos}
lc.update(match)
lc.update(rc)
......@@ -161,81 +165,87 @@ class CQiWrapper(CQiClient):
# print(all_matches)
# print(all_cpos)
# Get all sentences IDs for all above collected cpos in all_cpos
s_ids = self.cl_cpos2struc('CORPUS.s', all_cpos) # CHANGE to CORPUS.s will always be like this in nopaque
# Get all cpos for all sneteces boundries
s_lookup = {}
for s_id in set(s_ids):
s_start, s_end = self.cl_struc2cpos('CORPUS.s', s_id) # CHANGE to CORPUS.s will always be like this in nopaque
# print(s_start, s_end)
s_cpos = range(s_start, s_end)
s_lookup.update({s_id: list(s_cpos)})
# print(list(s_cpos))
all_cpos.extend(s_cpos)
# s_lookup = {}
# for s_id in set(s_ids):
# s_start, s_end = self.cl_struc2cpos('UTOPIEN.s', s_id)
# # CHANGE to UTOPIEN.s will always be like this in nopaque
# s_cpos = range(s_start, s_end)
# s_lookup.update({s_id: list(s_cpos)})
# # print(list(s_cpos))
# all_cpos.extend(s_cpos)
t0 = time.time()
all_cpos = list(set(all_cpos)) # get rid of cpos duplicates
t1 = time.time()
t_total = t1 - t0
print('TIME FOR ALL CPOS:', t_total)
print('CPOS SUM:', len(all_cpos))
# Get cpos informations like CORPUS_NAME.word or CORPUS_NAME.lemma for
# all cpos entries in all_cpos_list
# Also saves these informations into self.results dict
t6 = time.time()
all_cpos_infos, text_lookup = self.get_cpos_infos(all_cpos)
t7 = time.time()
t_final = t7 - t6
print('GOT ALL RESULTS IN:', t_final)
self.results = {'matches': all_matches, 'cpos_lookup': all_cpos_infos,
's_lookup': s_lookup, 'text_lookup': text_lookup}
'text_lookup': text_lookup}
return self.results
# print(self.results)
def get_cpos_infos(self, all_cpos):
'''
Get cpos informations like CORPUS_NAME.word or CORPUS_NAME.lemma for
all cpos entries specified in the parameter all_cpos.
'''
# Get all positional attribute informations
cpos_infos = {}
for p_attr_key in self.attr_strings['positional_attrs'].keys():
match_strs = self.cl_cpos2str(self.attr_strings['positional_attrs'][p_attr_key], all_cpos)
cpos_infos[p_attr_key] = match_strs
tmp_s_info = []
tmp_text_info = []
text_lookup = {}
tmp_dict = {}
# Get all strucutural attribute informations
tmp_info = {}
structs_to_check = []
for struct_attr_key in self.attr_strings['struct_attrs'].keys():
check = self.attr_strings['struct_attrs'][struct_attr_key]
if check == 'CORPUS.s':
struct_ids = self.cl_cpos2struc(check, all_cpos)
for id in struct_ids:
tmp_s_info.append({struct_attr_key: id})
elif check == 'CORPUS.text':
struct_ids = self.cl_cpos2struc(check, all_cpos)
key = self.attr_strings['struct_attrs'][struct_attr_key]
has_value = self.corpus_structural_attribute_has_values(key)
struct_ids = self.cl_cpos2struc(key, all_cpos)
if has_value is False: # Get IDs of strucutural elements without values (this means get IDs of XML tags. Struct elements only have values if they are XML attributes)
tmp_info[struct_attr_key] = []
for id in struct_ids:
tmp_text_info.append({struct_attr_key: id})
tmp_info[struct_attr_key].append(id)
else:
struct_ids = struct_ids = self.cl_cpos2struc(check, all_cpos)
struct_values = self.cl_struc2str(self.attr_strings['struct_attrs'][struct_attr_key], struct_ids)
for value in struct_values:
for id in struct_ids:
tmp_dict.update({id: {struct_attr_key: value}})
print(tmp_dict)
print(text_lookup)
# struct_entry = self.cl_cpos2struc(self.attr_strings['struct_attrs'][struct_attr_key], all_cpos)
# has_value = self.corpus_structural_attribute_has_values(self.attr_strings['struct_attrs'][struct_attr_key])
# if has_value:
# match_strs = self.cl_struc2str(self.attr_strings['struct_attrs'][struct_attr_key], struct_entry)
# elif self.attr_strings['struct_attrs'][struct_attr_key] == 'CORPUS.s':
# pass
# else:
# match_strs = [None for i in struct_entry]
# cpos_infos[struct_attr_key] = zip(struct_entry, match_strs)
tmp_list = []
attr_key_list = []
structs_to_check.append({key: struct_attr_key})
struct_attr_values = list(tmp_info.values())
struct_attr_keys = list(tmp_info.keys())
# Build textlookup dictionary
text_lookup_ids = list(set(struct_attr_values[0])) # First is always one text
text_lookup = {}
for d in structs_to_check:
s_key, s_value = zip(*d.items())
s_value = s_value[0].split('_')[1]
struct_values = self.cl_struc2str(s_key[0], text_lookup_ids)
zipped = dict(zip(text_lookup_ids, struct_values))
for zip_key, zip_value in zipped.items():
check = text_lookup.get(zip_key)
if check is None:
text_lookup[zip_key] = {s_value: zip_value}
else:
text_lookup[zip_key].update({s_value: zip_value})
# zip keys and values together
attr_values_list = []
attr_keys_list = []
for key in cpos_infos.keys():
tmp_list.append(cpos_infos[key])
attr_key_list.append(key)
joined_cpos_infos = zip(all_cpos, *tmp_list)
attr_values_list.append(cpos_infos[key])
attr_keys_list.append(key)
attr_keys_list.extend(struct_attr_keys)
attr_values_list.extend(struct_attr_values)
joined_cpos_infos = zip(all_cpos, *attr_values_list)
dict_cpos_infos = {}
for info in joined_cpos_infos:
dict_cpos_infos[info[0]] = dict(zip(attr_key_list, info[1:]))
for key, s_id, text_id in zip(dict_cpos_infos.keys(), tmp_s_info, tmp_text_info):
dict_cpos_infos[key].update(s_id)
dict_cpos_infos[key].update(text_id)
dict_cpos_infos[info[0]] = dict(zip(attr_keys_list, info[1:]))
return dict_cpos_infos, text_lookup
app/corpora/events.py
+ 5
− 42
View file @ dbd580b3
......@@ -4,10 +4,6 @@ from app.models import Corpus
from flask import current_app, request
from flask_login import current_user, login_required
from .CQiWrapper.CQiWrapper import CQiWrapper
import sys
import gzip
import zlib
import json
'''
' A dictionary containing lists of, with corpus ids associated, Socket.IO
......@@ -47,46 +43,13 @@ def corpus_analysis(message):
room=request.sid)
return
""" Prepare and execute a query """
corpus = 'CORPUS'
corpus_name = 'CORPUS'
query = (message['query'])
query_subcorpus = 'Results'
client.cqp_query(corpus, query_subcorpus, query)
client.select_corpus(corpus_name)
client.query_subcorpus(query)
results = client.show_query_results(result_len=int(message['hits_per_page']), context_len=int(message['context']))
data = {'matches': [], 'cpos_lookup': {}, 'text_loopup': {}}
""" Evaluate query results """
match_corpus = '{}:{}'.format(corpus, query_subcorpus)
match_num = min(int(message['hits_per_page']), client.cqp_subcorpus_size(match_corpus))
match_boundaries = zip(client.cqp_dump_subcorpus(match_corpus,
0x10,
0, match_num - 1),
client.cqp_dump_subcorpus(match_corpus,
0x11,
0, match_num - 1))
context = 15
corpus_len = 10000
for match_start, match_end in match_boundaries:
data['matches'].append({'lc': list(range(max(0, match_start - int(message['context'])), match_start)),
'hit': list(range(match_start, match_end + 1)),
'rc': list(range(match_end + 1, min(corpus_len, match_end + 1 + int(message['context']))))})
cpos_list = []
for match in data['matches']:
cpos_list += match['lc'] + match['hit'] + match['rc']
cpos_list = list(set(cpos_list))
lemma_list = client.cl_cpos2str('{}.lemma'.format(corpus), cpos_list)
pos_list = client.cl_cpos2str('{}.pos'.format(corpus), cpos_list)
simple_pos_list = client.cl_cpos2str('{}.simple_pos'.format(corpus), cpos_list)
s_id_list = client.cl_cpos2struc('{}.s'.format(corpus), cpos_list)
text_id_list = client.cl_cpos2struc('{}.text'.format(corpus), cpos_list)
word_list = client.cl_cpos2str('{}.word'.format(corpus), cpos_list)
for cpos, lemma, pos, simple_pos, s_id, text_id, word in zip(cpos_list, lemma_list, pos_list, simple_pos_list, s_id_list, text_id_list, word_list):
data['cpos_lookup'][cpos] = {'lemma': lemma, 'pos': pos, 'simple_pos': simple_pos, 's_id': s_id, 'text_id': text_id, 'word': word}
text_author_list = client.cl_struc2str('{}.text_author'.format(corpus), text_id_list)
text_publishing_year_list = client.cl_struc2str('{}.text_publishing_year'.format(corpus), text_id_list)
text_title_list = client.cl_struc2str('{}.text_title'.format(corpus), text_id_list)
for text_id, text_author, text_publishing_year, text_title in zip(text_id_list, text_author_list, text_publishing_year_list, text_title_list):
data['text_loopup'][text_id] = {'author': text_author, 'publishing_year': text_publishing_year, 'title': text_title}
socketio.emit('corpus_analysis', data, room=request.sid)
socketio.emit('corpus_analysis', results, room=request.sid)
def corpus_analysis_session_handler(app, corpus_id, session_id):
......
app/templates/corpora/analyse_corpus.html.j2
+ 5
− 4
View file @ dbd580b3
......@@ -182,6 +182,7 @@
});
socket.on("corpus_analysis", function(message) {
console.log(message);
var matchElement;
var matchTextTitlesElement;
var matchLeftContextElement;
......@@ -234,7 +235,7 @@
matchHitElement.append(tokenElement);
matchHitElement.append(document.createTextNode(" "));
tokenElements.push(tokenElement);
textTitles.add(result["text_loopup"][token["text_id"]]["title"]);
textTitles.add(result["text_lookup"][token["text"]]["title"]);
}
matchTextTitlesElement.innerText = [...textTitles].join(",");
matchElement.append(matchHitElement);
......@@ -274,9 +275,9 @@
simple_pos: ${token["simple_pos"]}
</td>
<td class="left-align">
Title: ${result["text_loopup"][token["text_id"]]["title"]}<br>
Author: ${result["text_loopup"][token["text_id"]]["title"]}<br>
Publishing year: ${result["text_loopup"][token["text_id"]]["publishing_year"]}
Title: ${result["text_lookup"][token["text"]]["title"]}<br>
Author: ${result["text_lookup"][token["text"]]["title"]}<br>
Publishing year: ${result["text_lookup"][token["text"]]["publishing_year"]}
</td>
</tr>
</table>`,
......
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