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Merge branch 'visualizations-update' of gitlab.ub.uni-bielefeld.de:sfb1288inf/nopaque into visualizations-update

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This commit is contained in:
Inga Kirschnick 2023-06-19 13:42:05 +02:00
commit 11b697145b
3 changed files with 212 additions and 5 deletions
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193
app/corpora/cqi_over_socketio/cqi_corpora_corpus.py
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@ -1,6 +1,8 @@
from collections import Counter
from flask import session
import cqi
import math
import random
from app import db, socketio
from app.decorators import socketio_login_required
from app.models import Corpus
@ -38,10 +40,191 @@ def cqi_corpora_corpus_query(cqi_client: cqi.CQiClient, corpus_name: str, subcor
@cqi_over_socketio
def cqi_corpora_corpus_update_db(cqi_client: cqi.CQiClient, corpus_name: str):
corpus = Corpus.query.get(session['d']['corpus_id'])
corpus.num_tokens = cqi_client.corpora.get(corpus_name).attrs['size']
cqi_corpus = cqi_client.corpora.get(corpus_name)
corpus.num_tokens = cqi_corpus.size
db.session.commit()
@socketio.on('cqi.corpora.corpus.get_visualization_data', namespace=ns)
@socketio_login_required
@cqi_over_socketio
def cqi_corpora_corpus_get_visualization_data(cqi_client: cqi.CQiClient, corpus_name: str):
corpus = cqi_client.corpora.get(corpus_name)
# s_attrs = [x for x in corpus.structural_attributes.list() if not x.has_values]
# p_attrs = corpus.positional_attributes.list()
# payload = {
# 's_attrs': {},
# 'p_attrs': {},
# 'values': {
# 's_attrs': {},
# 'p_attrs': {}
# }
# }
# for s_attr in s_attrs:
# s_attr_lbound, s_attr_rbound = s_attr.cpos_by_id(text_id)
# s_attr_cpos_range = range(s_attr_lbound, s_attr_rbound + 1)
# payload['text']['lexicon'][text_id] = {
# 's_attrs': [s_attr_lbound, s_attr_rbound],
# 'counts': {
# 'token': s_attr_rbound - s_attr_lbound + 1
# },
# 'freqs': {
# p_attr.name: dict(Counter(p_attr.ids_by_cpos(list(s_attr_cpos_range))))
# for p_attr in p_attrs
# }
# }
# for p_attr in p_attrs:
# payload['p_attrs'] = dict(
# )
# payload['values']['p_attrs'] = dict(
# zip(
# range(0, p_attr.lexicon_size),
# p_attr.values_by_ids(list(range(0, p_attr.lexicon_size)))
# )
# )
text = corpus.structural_attributes.get('text')
text_value_names = []
text_values = []
for text_sub_attr in corpus.structural_attributes.list(filters={'part_of': text}):
text_value_names.append(text_sub_attr.name[(len(text.name) + 1):])
text_values.append(text_sub_attr.values_by_ids(list(range(0, text.size))))
s = corpus.structural_attributes.get('s')
ent = corpus.structural_attributes.get('ent')
ent_value_names = []
ent_values = []
for ent_sub_attr in corpus.structural_attributes.list(filters={'part_of': ent}):
ent_value_names.append(ent_sub_attr.name[(len(ent.name) + 1):])
ent_values.append(ent_sub_attr.values_by_ids(list(range(0, ent.size))))
word = corpus.positional_attributes.get('word')
lemma = corpus.positional_attributes.get('lemma')
pos = corpus.positional_attributes.get('pos')
simple_pos = corpus.positional_attributes.get('simple_pos')
payload = {}
payload['corpus'] = {'lexicon': {}, 'values': []}
payload['corpus']['lexicon'][0] = {
'bounds': [0, corpus.size - 1],
'counts': {
'text': text.size,
's': s.size,
'ent': ent.size,
'token': corpus.size
},
'freqs': {
'word': dict(
zip(
range(0, word.lexicon_size),
word.freqs_by_ids(list(range(0, word.lexicon_size)))
)
),
'lemma': dict(
zip(
range(0, lemma.lexicon_size),
lemma.freqs_by_ids(list(range(0, lemma.lexicon_size)))
)
),
'pos': dict(
zip(
range(0, pos.lexicon_size),
pos.freqs_by_ids(list(range(0, pos.lexicon_size)))
)
),
'simple_pos': dict(
zip(
range(0, simple_pos.lexicon_size),
simple_pos.freqs_by_ids(list(range(0, simple_pos.lexicon_size)))
)
)
}
}
payload['text'] = {'lexicon': {}, 'values': None}
for text_id in range(0, text.size):
text_lbound, text_rbound = text.cpos_by_id(text_id)
text_cpos_range = range(text_lbound, text_rbound + 1)
text_s_ids = s.ids_by_cpos(list(text_cpos_range))
text_ent_ids = ent.ids_by_cpos(list(text_cpos_range))
payload['text']['lexicon'][text_id] = {
'bounds': [text_lbound, text_rbound],
'counts': {
's': len([x for x in text_s_ids if x != -1]),
'ent': len([x for x in text_ent_ids if x != -1]),
'token': text_rbound - text_lbound + 1
},
'freqs': {
'word': dict(
Counter(word.ids_by_cpos(list(text_cpos_range)))
),
'lemma': dict(
Counter(lemma.ids_by_cpos(list(text_cpos_range)))
),
'pos': dict(
Counter(pos.ids_by_cpos(list(text_cpos_range)))
),
'simple_pos': dict(
Counter(simple_pos.ids_by_cpos(list(text_cpos_range)))
)
}
}
payload['text']['values'] = text_value_names
payload['s'] = {'lexicon': {}, 'values': None}
for s_id in range(0, s.size):
payload['s']['lexicon'][s_id] = {
# 'bounds': s.cpos_by_id(s_id)
}
payload['s']['values'] = [
sub_attr.name[(len(s.name) + 1):]
for sub_attr in corpus.structural_attributes.list(filters={'part_of': s})
]
payload['ent'] = {'lexicon': {}, 'values': None}
for ent_id in range(0, ent.size):
payload['ent']['lexicon'][ent_id] = {
# 'bounds': ent.cpos_by_id(ent_id)
}
payload['ent']['values'] = ent_value_names
payload['lookups'] = {
'corpus': {},
'text': {
text_id: {
text_value_name: text_values[text_value_name_idx][text_id_idx]
for text_value_name_idx, text_value_name in enumerate(text_value_names)
} for text_id_idx, text_id in enumerate(range(0, text.size))
},
's': {},
'ent': {
ent_id: {
ent_value_name: ent_values[ent_value_name_idx][ent_id_idx]
for ent_value_name_idx, ent_value_name in enumerate(ent_value_names)
} for ent_id_idx, ent_id in enumerate(range(0, ent.size))
},
'word': dict(
zip(
range(0, word.lexicon_size),
word.values_by_ids(list(range(0, word.lexicon_size)))
)
),
'lemma': dict(
zip(
range(0, lemma.lexicon_size),
lemma.values_by_ids(list(range(0, lemma.lexicon_size)))
)
),
'pos': dict(
zip(
range(0, pos.lexicon_size),
pos.values_by_ids(list(range(0, pos.lexicon_size)))
)
),
'simple_pos': dict(
zip(
range(0, simple_pos.lexicon_size),
simple_pos.values_by_ids(list(range(0, simple_pos.lexicon_size)))
)
)
}
# print(payload)
return {'code': 200, 'msg': 'OK', 'payload': payload}
@socketio.on('cqi.corpora.corpus.paginate', namespace=ns)
@socketio_login_required
@cqi_over_socketio
@ -52,13 +235,13 @@ def cqi_corpora_corpus_paginate(cqi_client: cqi.CQiClient, corpus_name: str, pag
per_page < 1
or page < 1
or (
cqi_corpus.attrs['size'] > 0
and page > math.ceil(cqi_corpus.attrs['size'] / per_page)
cqi_corpus.size > 0
and page > math.ceil(cqi_corpus.size / per_page)
)
):
return {'code': 416, 'msg': 'Range Not Satisfiable'}
first_cpos = (page - 1) * per_page
last_cpos = min(cqi_corpus.attrs['size'], first_cpos + per_page)
last_cpos = min(cqi_corpus.size, first_cpos + per_page)
cpos_list = [*range(first_cpos, last_cpos)]
lookups = lookups_by_cpos(cqi_corpus, cpos_list)
payload = {}
@ -67,7 +250,7 @@ def cqi_corpora_corpus_paginate(cqi_client: cqi.CQiClient, corpus_name: str, pag
# the lookups for the items
payload['lookups'] = lookups
# the total number of items matching the query
payload['total'] = cqi_corpus.attrs['size']
payload['total'] = cqi_corpus.size
# the number of items to be displayed on a page.
payload['per_page'] = per_page
# The total number of pages

14
app/static/js/CorpusAnalysis/CQiClient.js
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@ -98,6 +98,20 @@ class CQiCorpus {
this.subcorpora = new CQiSubcorpusCollection(this.socket, this);
}
getVisualizationData() {
return new Promise((resolve, reject) => {
const args = {corpus_name: this.name};
this.socket.emit('cqi.corpora.corpus.get_visualization_data', args, response => {
if (response.code === 200) {
resolve(response.payload);
} else {
reject(response);
}
});
});
}
getCorpusData() {
return new Promise((resolve, reject) => {
const dummyData = {

10
app/static/js/CorpusAnalysis/CorpusAnalysisApp.js
View File

@ -34,6 +34,16 @@ class CorpusAnalysisApp {
.then(
cQiCorpus => {
this.data.corpus = {o: cQiCorpus};
this.data.corpus.o.getVisualizationData().then(data => console.log(data));
// this.data.corpus.o.getVisualizationData()
// .then(
// (visualizationData) => {
// console.log(visualizationData);
// this.renderGeneralCorpusInfo(visualizationData);
// this.renderTextInfoList(visualizationData);
// this.renderTextProportionsGraphic(visualizationData);
// }
// );
this.data.corpus.o.getCorpusData()
.then(corpusData => {
this.renderGeneralCorpusInfo(corpusData);