From 11e1789d83ed099cf247eda872659a22db2b0db8 Mon Sep 17 00:00:00 2001
From: Inga Kirschnick <inga.kirschnick@uni-bielefeld.de>
Date: Mon, 19 Jun 2023 13:41:56 +0200
Subject: [PATCH] visualization testing
---
app/static/js/CorpusAnalysis/CQiClient.js | 328 ++++++++++--------
.../js/CorpusAnalysis/CorpusAnalysisApp.js | 103 ++++--
.../js/ResourceLists/CorpusTextInfoList.js | 34 +-
app/templates/corpora/analysis.html.j2 | 88 +++--
4 files changed, 330 insertions(+), 223 deletions(-)
diff --git a/app/static/js/CorpusAnalysis/CQiClient.js b/app/static/js/CorpusAnalysis/CQiClient.js
index fcc0c87d..92cc6422 100644
--- a/app/static/js/CorpusAnalysis/CQiClient.js
+++ b/app/static/js/CorpusAnalysis/CQiClient.js
@@ -101,164 +101,188 @@ class CQiCorpus {
getCorpusData() {
return new Promise((resolve, reject) => {
const dummyData = {
- "num_tokens": 2000, // number of tokens in the corpus
- "num_unique_words": 500, // number of unique words in the corpus
- "num_unique_lemmas": 200, // number of unique lemmas in the corpus
- "num_sentences": 90, // number of sentences in the corpus
- "average_sentence_length": 11, // average number of tokens per sentence in the corpus
- "num_ent_types": 30, // number of entities in the corpus
- "num_unique_ent_types":10,
- "ent_type_freqs": {
- "str": 10, // number of ent_types with ent_type "str"
- // ...
- },
- "texts": [
- {
- "num_tokens": 11, // number of tokens in the text
- "num_unique_words": 12, // number of unique words in the text
- "word_freqs": { // frequency of unique words in the text (sorted by frequency)
- "str": "int", // number of tokens with word "str"
- // ...
+ "corpus": {
+ "bounds": [1, 689],
+ "counts": {
+ "token": 743,
+ "ent": 321,
+ "s": 234
+ },
+ "freqs": {
+ "word": {
+ "1": 876,
+ "2": 234,
+ "3": 657
},
- "num_unique_lemmas": 15, // number of unique lemmas in the text
- "lemma_freqs": { // frequency of unique lemmas in the text (sorted by frequency)
- "str": "int", // number of tokens with lemma "str"
- // ...
+ "lemma": {
+ "1": 543,
+ "2": 876,
+ "3": 321
},
- "num_sentences": 4, // number of sentences in the text
- "average_sentence_length": 3, // average number of tokens per sentence in the text
- "num_ent_types": 12, // number of ent_types in the text
- "num_unique_ent_types": 28, // number of unique ent_types in the text
- "num_entities_by_id": {
- "1": "int", // number of entities with id 1
- // ...
- },
- "author": "Author Name",
- "title": "Titel",
- "publishing_year": 1950
- },
- {
- "num_tokens": 15, // number of tokens in the text
- "num_unique_words": 4, // number of unique words in the text
- "word_freqs": { // frequency of unique words in the text (sorted by frequency)
- "str": "int", // number of tokens with word "str"
- // ...
- },
- "num_unique_lemmas": 90, // number of unique lemmas in the text
- "lemma_freqs": { // frequency of unique lemmas in the text (sorted by frequency)
- "str": "int", // number of tokens with lemma "str"
- // ...
- },
- "num_sentences": 11, // number of sentences in the text
- "average_sentence_length": 3, // average number of tokens per sentence in the text
- "num_ent_types": 4, // number of ent_types in the text
- "num_unique_ent_types": 300, // number of unique ent_types in the text
- "num_entities_by_id": {
- "1": "int", // number of entities with id 1
- // ...
- },
- "author": "Author Name",
- "title": "Titel 1",
- "publishing_year": 1962
+ "pos": {
+ "1": 456,
+ "2": 789,
+ "3": 234
+ },
+ "simple_pos": {
+ "1": 987,
+ "2": 876,
+ "3": 543
+ },
+ "ent": {
+ "1": 654,
+ "2": 321,
+ "3": 987
+ }
+ }
+ },
+ "text": {
+ "1": {
+ "bounds": [0, 435],
+ "counts": {
+ "token": 345,
+ "ent_type": 123,
+ "s": 89
+ },
+ "freqs": {
+ "word": {
+ "1": 25,
+ "2": 90,
+ "3": 200
+ },
+ "lemma": {
+ "1": 654,
+ "2": 321,
+ "3": 987
+ },
+ "pos": {
+ "1": 543,
+ "2": 876,
+ "3": 234
+ },
+ "simple_pos": {
+ "1": 987,
+ "2": 654,
+ "3": 321
+ },
+ "ent_type": {
+ "1": 234,
+ "2": 789,
+ "3": 543
+ }
+ },
+ "values": {
+ "author": 1,
+ "publishing_year":1950,
+ "title": 1
+ }
},
- {
- "num_tokens": 11, // number of tokens in the text
- "num_unique_words": 12, // number of unique words in the text
- "word_freqs": { // frequency of unique words in the text (sorted by frequency)
- "str": "int", // number of tokens with word "str"
- // ...
- },
- "num_unique_lemmas": 64, // number of unique lemmas in the text
- "lemma_freqs": { // frequency of unique lemmas in the text (sorted by frequency)
- "str": "int", // number of tokens with lemma "str"
- // ...
- },
- "num_sentences": 52, // number of sentences in the text
- "average_sentence_length": 3, // average number of tokens per sentence in the text
- "num_ent_types": 45, // number of ent_types in the text
- "num_unique_ent_types": 68, // number of unique ent_types in the text
- "num_entities_by_id": {
- "1": "int", // number of entities with id 1
- // ...
- },
- "author": "Author Name",
- "title": "Titel 2",
- "publishing_year": 1850
+ "2": {
+ "bounds": [435, 689],
+ "counts": {
+ "token": 389,
+ "ent_type": 198,
+ "s": 145
+ },
+ "freqs": {
+ "word": {
+ "1": 60,
+ "2": 70,
+ "3": 100
+ },
+ "lemma": {
+ "1": 654,
+ "2": 321,
+ "3": 987
+ },
+ "pos": {
+ "1": 543,
+ "2": 876,
+ "3": 234
+ },
+ "simple_pos": {
+ "1": 987,
+ "2": 654,
+ "3": 321
+ },
+ "ent_type": {
+ "1": 234,
+ "2": 789,
+ "3": 543
+ }
+ },
+ "values": {
+ "author": 2,
+ "publishing_year":1951,
+ "title": 2
+ }
+ }
+ },
+ "s": {
+ "1": {
+ "bounds": [345, 678]
+ }
+ },
+ "ent": {
+ "1": {
+ "bounds": [567, 890],
+ "values": {
+ "type": 789
+ }
+ }
+ },
+ "token": {
+ "310": {
+ "values": {
+ "word": 1,
+ "lemma": 2,
+ "pos": 1,
+ "simple_pos": 1
+ }
+ }
+ },
+ "value_lookups": {
+ "text": {
+ "author": {
+ "1": "John Doe",
+ "2": "Jane Smith"
+ },
+ "title": {
+ "1": "Test Title 1",
+ "2": "Test Title 2"
+ }
},
- {
- "num_tokens": 56, // number of tokens in the text
- "num_unique_words": 13, // number of unique words in the text
- "word_freqs": { // frequency of unique words in the text (sorted by frequency)
- "str": "int", // number of tokens with word "str"
- // ...
- },
- "num_unique_lemmas": 43, // number of unique lemmas in the text
- "lemma_freqs": { // frequency of unique lemmas in the text (sorted by frequency)
- "str": "int", // number of tokens with lemma "str"
- // ...
- },
- "num_sentences": 45, // number of sentences in the text
- "average_sentence_length": 56, // average number of tokens per sentence in the text
- "num_ent_types": 8792, // number of ent_types in the text
- "num_unique_ent_types": 56758, // number of unique ent_types in the text
- "num_entities_by_id": {
- "1": "int", // number of entities with id 1
- // ...
- },
- "author": "Author Name",
- "title": "Titel 3",
- "publishing_year": 1504
+ "ent": {
+ "type": {
+ "1": "Person",
+ "2": "Organization"
+ }
},
- {
- "num_tokens": 54345, // number of tokens in the text
- "num_unique_words": 561, // number of unique words in the text
- "word_freqs": { // frequency of unique words in the text (sorted by frequency)
- "str": "int", // number of tokens with word "str"
- // ...
- },
- "num_unique_lemmas": 546, // number of unique lemmas in the text
- "lemma_freqs": { // frequency of unique lemmas in the text (sorted by frequency)
- "str": "int", // number of tokens with lemma "str"
- // ...
- },
- "num_sentences": 5427, // number of sentences in the text
- "average_sentence_length": 657, // average number of tokens per sentence in the text
- "num_ent_types": 3465, // number of ent_types in the text
- "num_unique_ent_types": 45, // number of unique ent_types in the text
- "num_entities_by_id": {
- "1": "int", // number of entities with id 1
- // ...
- },
- "author": "Author Name",
- "title": "Titel 4",
- "publishing_year": 1712
- },
- {
- "num_tokens": 4354, // number of tokens in the text
- "num_unique_words": 45234, // number of unique words in the text
- "word_freqs": { // frequency of unique words in the text (sorted by frequency)
- "testwort": 50, // number of tokens with word "str"
- "testwort2": 1
- },
- "num_unique_lemmas": 15, // number of unique lemmas in the text
- "lemma_freqs": { // frequency of unique lemmas in the text (sorted by frequency)
- "testlemma": 11, // number of tokens with lemma "str"
- "testlemma2": 1
- },
- "num_sentences": 90, // number of sentences in the text
- "average_sentence_length": 7, // average number of tokens per sentence in the text
- "num_ent_types": 19,
- "num_unique_ent_types": 5, // number of unique ent_types in the text
- "num_entities_by_id": {
- "1": "int", // number of entities with id 1
- // ...
- },
- "author": "Author Name 2",
- "title": "Titel 5",
- "publishing_year": 1951
+ "token": {
+ "word": {
+ "1": "apple",
+ "2": "banana",
+ "3": "orange"
+ },
+ "lemma": {
+ "1": "run",
+ "2": "walk",
+ "3": "jump"
+ },
+ "pos": {
+ "1": "noun",
+ "2": "verb",
+ "3": "adjective"
+ },
+ "simple_pos": {
+ "1": "subject",
+ "2": "object",
+ "3": "predicate"
+ }
}
- ]
- };
+ }
+ }
+
resolve(dummyData);
/*
diff --git a/app/static/js/CorpusAnalysis/CorpusAnalysisApp.js b/app/static/js/CorpusAnalysis/CorpusAnalysisApp.js
index cb012730..fbb91b4c 100644
--- a/app/static/js/CorpusAnalysis/CorpusAnalysisApp.js
+++ b/app/static/js/CorpusAnalysis/CorpusAnalysisApp.js
@@ -39,6 +39,8 @@ class CorpusAnalysisApp {
this.renderGeneralCorpusInfo(corpusData);
this.renderTextInfoList(corpusData);
this.renderTextProportionsGraphic(corpusData);
+ this.renderWordFrequenciesGraphic(corpusData);
+ this.renderWordDistributionsGraphic(corpusData);
});
// TODO: Don't do this hgere
cQiCorpus.updateDb();
@@ -103,38 +105,85 @@ class CorpusAnalysisApp {
}
renderGeneralCorpusInfo(corpusData) {
- let corpusGeneralInfoListElement = document.querySelector('.corpus-general-info-list');
- corpusGeneralInfoListElement.querySelector('.corpus-num-tokens').innerHTML = `<b>Number of tokens:</b> ${this.data.corpus.o.size}`;
- corpusGeneralInfoListElement.querySelector('.corpus-text-count').innerHTML = `<b>Corpus text count:</b> ${corpusData.texts.length}`;
- corpusGeneralInfoListElement.querySelector('.corpus-num-unique-words').innerHTML = `<b>Corpus unique word count:</b> ${corpusData.num_unique_words}`;
- corpusGeneralInfoListElement.querySelector('.corpus-num-unique-lemmas').innerHTML = `<b>Corpus unique lemma count:</b> ${corpusData.num_unique_lemmas}`;
- // corpusGeneralInfoListElement.querySelector('.corpus-most-frequent-words').innerHTML = `<b>Corpus most frequent words:</b> ${corpusData.most_frequent_words.join(', ');
- corpusGeneralInfoListElement.querySelector('.corpus-num-sentences').innerHTML = `<b>Corpus sentence count:</b> ${corpusData.num_sentences}`;
- corpusGeneralInfoListElement.querySelector('.corpus-average-sentence-length').innerHTML = `<b>Corpus average sentence length:</b> ${corpusData.average_sentence_length}`;
- corpusGeneralInfoListElement.querySelector('.corpus-num-ent-types').innerHTML = `<b>Corpus entity count:</b> ${corpusData.num_ent_types}`;
- corpusGeneralInfoListElement.querySelector('.corpus-num-unique-ent-types').innerHTML = `<b>Corpus unique entity count:</b> ${corpusData.num_unique_ent_types}`;
+ document.querySelector('.corpus-num-tokens').innerHTML = corpusData.corpus.counts.token;
+ document.querySelector('.corpus-num-s').innerHTML = corpusData.corpus.counts.s;
+ // corpusGeneralInfoListElement.querySelector('.corpus-text-count').innerHTML = <b>Corpus text count:</b> ${Object.entries(corpusData.text).length;
+ document.querySelector('.corpus-num-unique-words').innerHTML = Object.entries(corpusData.corpus.freqs.word).length;
+ document.querySelector('.corpus-num-unique-lemmas').innerHTML = Object.entries(corpusData.corpus.freqs.lemma).length;
+ document.querySelector('.corpus-num-unique-pos').innerHTML = Object.entries(corpusData.corpus.freqs.pos).length;
+ document.querySelector('.corpus-num-unique-simple-pos').innerHTML = Object.entries(corpusData.corpus.freqs.simple_pos).length;
}
renderTextInfoList(corpusData) {
- let corpusTextInfoListElement = document.querySelector('.corpus-text-info-list');
- let corpusTextInfoList = new CorpusTextInfoList(corpusTextInfoListElement);
- corpusTextInfoList.add(corpusData.texts);
-
+ // let corpusTextInfoListElement = document.querySelector('.corpus-text-info-list');
+ // let corpusTextInfoList = new CorpusTextInfoList(corpusTextInfoListElement);
+ // for (let text of Object.values(corpusData.text)) {
+ // text.values.title = corpusData.value_lookups.text.title[text.values.title];
+ // }
+ // corpusTextInfoList.add(Object.values(corpusData.text));
+
+ // let textCountChipElement = document.querySelector('.text-count-chip');
+ // textCountChipElement.innerHTML = `Text count: ${Object.values(corpusData.text).length}`;
}
renderTextProportionsGraphic(corpusData) {
- let textProportionsGraphicElement = document.querySelector('#text-proportions-graphic');
- let graphData = [
- {
- values: corpusData.texts.map(text => text.num_tokens),
- labels: corpusData.texts.map(text => `${text.title} (${text.publishing_year})`),
- type: 'pie'
- }
- ];
- let graphLayout = {
- height: 400,
- width: 500
- };
- Plotly.newPlot(textProportionsGraphicElement, graphData, graphLayout);
+ // let textProportionsGraphicElement = document.querySelector('#text-proportions-graphic');
+ // let texts = Object.values(corpusData.text);
+ // let graphData = [
+ // {
+ // values: texts.map(text => text.counts.token),
+ // labels: texts.map(text => `${text.values.title} (${text.values.publishing_year})`),
+ // type: 'pie'
+ // }
+ // ];
+ // let graphLayout = {
+ // height: 400,
+ // width: 500
+ // };
+ // Plotly.newPlot(textProportionsGraphicElement, graphData, graphLayout);
+ }
+
+ renderWordFrequenciesGraphic(corpusData) {
+ // let wordFrequenciesGraphicElement = document.querySelector('#word-frequencies-graphic');
+ // let words = Object.entries(corpusData.value_lookups.token.word);
+ // let texts = Object.values(corpusData.text);
+ // let graphData = [];
+ // for (let word of words) {
+ // let data = {
+ // x: texts.map(text => `${text.values.title} (${text.values.publishing_year})`),
+ // y: texts.map(text => text.freqs.word[word[0]]),
+ // name: word[1],
+ // type: 'bar'
+ // };
+ // graphData.push(data);
+ // }
+
+ // let graphLayout = {
+ // height: 400,
+ // width: 500,
+ // barmode: 'stack',
+ // type: 'bar'
+ // };
+ // Plotly.newPlot(wordFrequenciesGraphicElement, graphData, graphLayout);
+ }
+
+ renderWordDistributionsGraphic(corpusData) {
+ // let wordDistributionGraphicElement = document.querySelector('#word-distributions-graphic');
+ // var trace1 = {
+ // x: [1, 2, 3, 4],
+ // y: [10, 11, 12, 13],
+ // mode: 'markers',
+ // marker: {
+ // size: [40, 60, 80, 100]
+ // }
+ // };
+ // var data = [trace1];
+ // var layout = {
+ // title: 'Marker Size',
+ // showlegend: false,
+ // height: 600,
+ // width: 600
+ // };
+ // Plotly.newPlot(wordDistributionGraphicElement, data, layout);
}
}
diff --git a/app/static/js/ResourceLists/CorpusTextInfoList.js b/app/static/js/ResourceLists/CorpusTextInfoList.js
index 3e697d2d..6e8e8310 100644
--- a/app/static/js/ResourceLists/CorpusTextInfoList.js
+++ b/app/static/js/ResourceLists/CorpusTextInfoList.js
@@ -29,11 +29,11 @@ class CorpusTextInfoList extends ResourceList {
<tr class="list-item clickable hoverable">
<td><span class="title"></span> (<span class="publishing_year"></span>)</td>
<td><span class="num_tokens"></span></td>
+ <td><span class="num_sentences"></span></td>
<td><span class="num_unique_words"></span></td>
<td><span class="num_unique_lemmas"></span></td>
- <td><span class="num_sentences"></span></td>
- <td><span class="average_sentence_length"></span></td>
- <td><span class="num_unique_ent_types"></span></td>
+ <td><span class="num_unique_pos"></span></td>
+ <td><span class="num_unique_simple_pos"></span></td>
</tr>
`.trim();
}
@@ -44,11 +44,11 @@ class CorpusTextInfoList extends ResourceList {
'title',
'publishing_year',
'num_tokens',
+ 'num_sentences',
'num_unique_words',
'num_unique_lemmas',
- 'num_sentences',
- 'average_sentence_length',
- 'num_unique_ent_types'
+ 'num_unique_pos',
+ 'num_unique_simple_pos'
];
}
@@ -68,11 +68,11 @@ class CorpusTextInfoList extends ResourceList {
<tr>
<th>Text<span class="sort right material-icons" data-sort="title" style="cursor:pointer; color:#aa9cc9">arrow_drop_down</span></th>
<th>Number of tokens<span class="sort right material-icons" data-sort="num_tokens" style="cursor:pointer">arrow_drop_down</span></th>
+ <th>Number of sentences<span class="sort right material-icons" data-sort="num_sentences" style="cursor:pointer">arrow_drop_down</span></th>
<th>Number of unique words<span class="sort right material-icons" data-sort="num_unique_words" style="cursor:pointer">arrow_drop_down</span></th>
<th>Number of unique lemmas<span class="sort right material-icons" data-sort="num_unique_lemmas" style="cursor:pointer">arrow_drop_down</span></th>
- <th>Number of sentences<span class="sort right material-icons" data-sort="num_sentences" style="cursor:pointer">arrow_drop_down</span></th>
- <th>Average sentence length<span class="sort right material-icons" data-sort="average_sentence_length" style="cursor:pointer">arrow_drop_down</span></th>
- <th>Number of unique entity types<span class="sort right material-icons" data-sort="num_unique_ent_types" style="cursor:pointer">arrow_drop_down</span></th>
+ <th>Number of unique pos<span class="sort right material-icons" data-sort="num_unique_pos" style="cursor:pointer">arrow_drop_down</span></th>
+ <th>Number of unique simple pos<span class="sort right material-icons" data-sort="num_unique_simple_pos" style="cursor:pointer">arrow_drop_down</span></th>
</tr>
</thead>
<tbody class="list"></tbody>
@@ -83,14 +83,14 @@ class CorpusTextInfoList extends ResourceList {
mapResourceToValue(corpusTextData) {
return {
- title: corpusTextData.title,
- publishing_year: corpusTextData.publishing_year,
- num_tokens: corpusTextData.num_tokens,
- num_unique_words: corpusTextData.num_unique_words,
- num_unique_lemmas: corpusTextData.num_unique_lemmas,
- num_sentences: corpusTextData.num_sentences,
- average_sentence_length: corpusTextData.average_sentence_length,
- num_unique_ent_types: corpusTextData.num_unique_ent_types
+ title: corpusTextData.values.title,
+ publishing_year: corpusTextData.values.publishing_year,
+ num_tokens: corpusTextData.counts.token,
+ num_sentences: corpusTextData.counts.s,
+ num_unique_words: Object.entries(corpusTextData.freqs.word).length,
+ num_unique_lemmas: Object.entries(corpusTextData.freqs.lemma).length,
+ num_unique_pos: Object.entries(corpusTextData.freqs.pos).length,
+ num_unique_simple_pos: Object.entries(corpusTextData.freqs.simple_pos).length
};
}
diff --git a/app/templates/corpora/analysis.html.j2 b/app/templates/corpora/analysis.html.j2
index d10126cd..1452d2d0 100644
--- a/app/templates/corpora/analysis.html.j2
+++ b/app/templates/corpora/analysis.html.j2
@@ -35,44 +35,70 @@
<div class="col s12">
<h4><i class="material-icons left">query_stats</i>Visualizations</h4>
</div>
- <div class="col s4" >
- <div class="card hoverable">
- <div class="card-content">
- <span class="card-title">General information about the Corpus</span>
- <p></p>
- <br>
- <ul class="corpus-general-info-list">
- <li class="corpus-num-tokens"></li>
- <br>
- <li class="corpus-text-count"></li>
- <br>
- <li class="corpus-num-unique-words"></li>
- <br>
- <li class="corpus-num-unique-lemmas"></li>
- <br>
- <li class="corpus-num-sentences"></li>
- <br>
- <li class="corpus-average-sentence-length"></li>
- <br>
- <li class="corpus-num-ent-types"></li>
- <br>
- <li class="corpus-num-unique-ent-types"></li>
- <br>
- </ul>
+ </div>
+ <div class="row">
+ <div class="col s2">
+ <div class="card hoverable" style="border-radius: 10px !important; background-color:#6b3f89; color:white">
+ <div class="card-content" style="padding:10px !important; text-align:center;">
+ <p>Number of tokens</p>
+ <span class="card-title corpus-num-tokens"></span>
+ </div>
+ </div>
+ </div>
+ <div class="col s2">
+ <div class="card hoverable" style="border-radius: 10px !important; background-color:#6b3f89; color:white">
+ <div class="card-content" style="padding:10px !important; text-align:center">
+ <p>Number of sentences</p>
+ <span class="card-title corpus-num-s"></span>
</div>
</div>
</div>
- <div class="col s8">
+ <div class="col s2">
+ <div class="card hoverable" style="border-radius: 10px !important; background-color:#6b3f89; color:white">
+ <div class="card-content" style="padding:10px !important; text-align:center">
+ <p>Number of unique words</p>
+ <span class="card-title corpus-num-unique-words"></span>
+ </div>
+ </div>
+ </div>
+ <div class="col s2">
+ <div class="card hoverable" style="border-radius: 10px !important; background-color:#6b3f89; color:white">
+ <div class="card-content" style="padding:10px !important; text-align:center">
+ <p>Number of unique lemmas</p>
+ <span class="card-title corpus-num-unique-lemmas"></span>
+ </div>
+ </div>
+ </div>
+ <div class="col s2">
+ <div class="card hoverable" style="border-radius: 10px !important; background-color:#6b3f89; color:white">
+ <div class="card-content" style="padding:10px !important; text-align:center">
+ <p>Number of unique pos</p>
+ <span class="card-title corpus-num-unique-pos"></span>
+ </div>
+ </div>
+ </div>
+ <div class="col s2">
+ <div class="card hoverable" style="border-radius: 10px !important; background-color:#6b3f89; color:white">
+ <div class="card-content" style="padding:10px !important; text-align:center">
+ <p>Number of unique simple_pos</p>
+ <span class="card-title corpus-num-unique-simple-pos"></span>
+ </div>
+ </div>
+ </div>
+ </div>
+ <div class="row">
+ <div class="col s12">
<div class="card hoverable">
<div class="card-content">
<span class="card-title">Text information</span>
+ <div class="chip text-count-chip" style="background-color:#6b3f89; color:white""></div>
<div class="corpus-text-info-list no-autoinit"></div>
</div>
</div>
</div>
</div>
<div class="row">
- <div class="col s6">
+ <div class="col s3">
<div class="card hoverable">
<div class="card-content">
<span class="card-title">Text proportions within the corpus</span>
@@ -80,7 +106,7 @@
</div>
</div>
</div>
- <div class="col s6">
+ <div class="col s3">
<div class="card hoverable">
<div class="card-content">
<span class="card-title">Word frequencies</span>
@@ -88,6 +114,14 @@
</div>
</div>
</div>
+ <div class="col s6">
+ <div class="card hoverable">
+ <div class="card-content">
+ <span class="card-title">Word distributions</span>
+ <div id="word-distributions-graphic"></div>
+ </div>
+ </div>
+ </div>
</div>
</div>
--
GitLab