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@ -0,0 +1,10 @@
FROM python:3.8.16-bullseye
ADD . /app
RUN pip install flask flask-compress jieba numpy progressbar2 nltk langdetect
WORKDIR /app
RUN mkdir data
ENTRYPOINT [ "/usr/local/bin/python", "app.py" ]

@ -1 +1,3 @@
# ptt-sententree
## Reference
https://github.com/twitter/SentenTree

@ -6,8 +6,8 @@ from pprint import pprint
import threading
import random
import string
import dataHandlerPTT as ptt
import dataHandlerPTTPush as pttPush
# import dataHandlerPTT as ptt
# import dataHandlerPTTPush as pttPush
import generalText as gen
import json
@ -33,9 +33,9 @@ def eventStream(eventQueue):
yield "event:{event}\n{data}\n\n".format(event=eventNode['event'], data=data)
@app.route('/data/<path:path>')
@app.route('/img/<path:path>')
def send_data(path):
return send_from_directory('data', path)
return send_from_directory('resource/img', path)
@app.route('/generalTxt')
@ -57,7 +57,7 @@ def generalText_addText():
@app.route('/')
def index():
return redirect('/ptt')
return redirect('/generalTxt')
@app.route('/ptt_push')
@ -151,10 +151,13 @@ def send_resource(path):
return send_from_directory('resource', path)
@app.route("/dcard_dev")
def dcard_dev():
return render_template('dcard.html', title='DCard Sentntree 測試版')
@app.route('/generaltxt/help')
def generaltxt_help():
return render_template('generaltxt_help.html', title="使用說明")
@app.route('/data/<path:path>')
def get_data(path):
return send_from_directory('data', path)
if __name__ == "__main__":
app.run(debug=True, port=4998, host='0.0.0.0', threaded=True)
app.run(debug=True, port=4980, host='0.0.0.0', threaded=False)

@ -15,7 +15,7 @@ from numpy import prod
from jieba import posseg
from progressbar import ProgressBar
from datetime import datetime
from PTTData import PTTData
#from PTTData import PTTData
defaultDate = {
@ -29,7 +29,7 @@ with open('/home/vis/pttDatabase/PTTData/Gossiping/content/content.pck', 'rb') a
f.close()
defaultStopWords = []
data = PTTData('Gossiping', '/home/vis/pttDatabase/PTTData')
#data = PTTData('Gossiping', '/home/vis/pttDatabase/PTTData')
sentence_length = 100
use_push_count = False

@ -2,6 +2,7 @@ import jieba
import csv
import nltk
import re
import json
from jieba import posseg
from nltk import tokenize
from langdetect import detect
@ -31,38 +32,37 @@ def processText(randId, text, stopwords):
return ''
lang = detect(text)
sentenses = []
sentenses_raw = []
print(lang)
if (lang == 'zh-cn' or lang == 'zh-tw' or lang == 'ko'):
splitted = re.split('。|[\n]+', text)
print(splitted)
cutted = []
for i in splitted:
cutted.append(filterPOS(i))
for spl in splitted:
cutted.append(filterPOS(spl))
print(cutted)
for i in cutted:
result = []
for j in i:
if (j in stopwords):
continue
result.append(j)
if (len(result) >= 20):
sentenses.append(' '.join(result.copy()))
result = []
if (result != []):
sentenses.append(' '.join(result))
for spl, raw in zip(cutted, splitted):
sentenses.append(' '.join(spl))
sentenses_raw.append(raw)
else:
sentenses = []
for sentence in tokenize.sent_tokenize(text):
words = sentence.lower().split(' ')
sentenses_raw = []
for sentence_raw in tokenize.sent_tokenize(text):
words = sentence_raw.lower().split(' ')
print([''.join([a for a in w1 if a.isalpha()]) for w1 in words])
sentence = ' '.join([w for w in [''.join([a for a in w1 if a.isalpha()]) for w1 in words] if w not in [sw.lower() for sw in stopwords]])
sentenses.append(sentence)
sentenses_raw.append(sentence_raw)
result = []
result.append(['id', 'text', 'count'])
for index, sentence in enumerate(sentenses):
result.append([index, sentence, 1000])
with open('data/' + randId + '.tsv', 'w', newline='', encoding="utf-8") as f:
writer = csv.writer(f, delimiter='\t')
writer.writerows(result)
f.close()
return ('data/' + randId + '.tsv')
for index, raw_pair in enumerate(zip(sentenses, sentenses_raw)):
sentence, sentence_raw = raw_pair
result.append({
'id': index,
'text': sentence,
'count': 10,
'rawtxt': sentence_raw,
})
with open('data/' + randId + '.json', 'w', newline='', encoding="utf-8") as fp:
json.dump(result, fp, ensure_ascii=False, indent=4)
return ('data/' + randId + '.json')

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@ -186,6 +186,7 @@ li a {
from {
opacity: 0;
}
to {
opacity: 1;
}
@ -202,6 +203,7 @@ li a {
from {
opacity: 1;
}
to {
opacity: 0;
}
@ -260,7 +262,7 @@ li a {
#vis {
display: inline-block;
background-color: aliceblue;
background-color: transparent;
position: relative;
border-radius: 30px;
resize: both;

@ -1,6 +1,33 @@
var tsvPath
var stopwords = []
const init = () => {
$(window).on('mousemove', (e) => {
$('#nodeTitle').css({
left: e.pageX,
top: e.pageY
})
})
$('#minRatioLabel').on('mouseenter', () => {
$('#nodeTitle').removeClass('hidden')
$('#nodeTitleContent').html('兩個相鄰單詞之間出現頻率比值的最小值,小於該值不會被演算法選擇')
}).on('mouseleave', () => {
$('#nodeTitle').toggleClass('hidden')
})
$('#maxRatioLabel').on('mouseenter', () => {
$('#nodeTitle').removeClass('hidden')
$('#nodeTitleContent').html('兩個相鄰單詞之間出現頻率比值的最大值,大於該值不會被演算法選擇')
}).on('mouseleave', () => {
$('#nodeTitle').toggleClass('hidden')
})
$('#wordcount').on('mouseenter', () => {
$('#nodeTitle').removeClass('hidden')
$('#nodeTitleContent').html('僅計算中文字的字數')
}).on('mouseleave', () => {
$('#nodeTitle').toggleClass('hidden')
})
}
function clearStopWord() {
stopwords = []
$('#sweContainer').html('')
@ -86,22 +113,41 @@ function submit() {
function buildSentetree() {
console.log("Build.")
var model;
var tree;
var data;
const graph = d3.tsv(tsvPath, buildTree);
let model;
let tree;
let data;
const graph = d3.json(tsvPath, buildTree);
function buildTree(error, rawdata) {
console.log(rawdata)
const data = rawdata.map(d => Object.assign({}, d, { count: +d.count }));
console.log({ data })
let minRatio = $('#minRatio').val()
let maxRatio = $('#maxRatio').val()
console.log({ minRatio, maxRatio })
model = new SentenTree.SentenTreeBuilder()
.tokenize(SentenTree.tokenizer.tokenizeBySpace)
.transformToken(token => (/score(d|s)?/.test(token) ? 'score' : token))
.buildModel(data, { maxSupportRatio: 1 });
.buildModel(data, { maxSupportRatio: maxRatio, minSupportRatio: minRatio });
tree = new SentenTree.SentenTreeVis('#vis', {
fontSize: [15, 40],
gapBetweenGraph: 10
});
tree.data(model.getRenderedGraphs(2))
.on('nodeMouseenter', (node) => {
console.log(node)
$('#nodeTitle').removeClass('hidden')
$('#nodeTitleContent').html('<ul>' + node.data.topEntries.map((n) => "<li>" + data[n.id].rawtxt + "</li>").join('') + "</ul>")
})
.on('nodeMouseleave', () => {
$('#nodeTitle').addClass('hidden')
})
.on('linkMouseenter', (node) => {
$('#nodeTitle').removeClass('hidden')
$('#nodeTitleContent').html('出現次數:' + (node.freq / 10))
}).on('linkMouseleave', () => {
$('#nodeTitle').addClass('hidden')
})
new ResizeSensor(jQuery('#d3kitRoot'), function () {
var scale, origin;
scale = Math.min(2, ($('#graph').outerWidth()) / ($('#d3kitRoot').outerWidth() + 60))
@ -126,3 +172,12 @@ function switchMessageBox() {
$('#toggleTextBox').html('隱藏文字輸入區')
}
}
function countWords() {
text = $("#rawTextBox").val()
let wordCount = text.split(new RegExp("[\u4e00-\u9fa5]")).length - 1
console.log(wordCount)
$("#wordcount").html('字數:' + wordCount)
}
init()

@ -9,44 +9,58 @@
</head>
<body>
<div id="nodeTitle" class="nodeTitle hidden">
<div id="nodeTitleContent">test</div>
</div>
<div id="stopWordEditorLayer" class="info hidden">
<div id="stopWordEditor">
<h4 id="sweTitle" style="margin:10px; display: inline;">編輯停用詞</h4>
<ul id="sweContainer" class="w3-ul w3-hoverable" style="margin-bottom: 10px;"></ul>
<div>
<input class="w3-input w3-border" style="width: 85%; display: inline;" type="text" id="newStopWord" placeholder="新增停用詞(以空白隔開)">
<button class="general-button w3-right" type="button" id="confirm" style="background-color: #379; margin-left: 8px;" onclick="addStopWord()">新增</button>
<input class="w3-input w3-border" style="width: 85%; display: inline;" type="text" id="newStopWord"
placeholder="新增停用詞(以空白隔開)">
<button class="general-button w3-right" type="button" id="confirm"
style="background-color: #379; margin-left: 8px;" onclick="addStopWord()">新增</button>
</div>
<div id="sweButtons" style="margin: 20px 0px;">
<button class="general-button" type="button" id="confirm" style="background-color: #379; margin: 0px 10px" onclick="hideStopWordEditor(); submit()">確認</button>
<button class="general-button" type="button" id="confirm" style="background-color: #379; margin: 0px 10px" onclick="downloadStopWord()">匯出停用詞</button>
<button class="general-button" type="button" id="confirm" style="background-color: #379; margin: 0px 10px" onclick="clearStopWord()">全部清除</button>
<button class="general-button w3-right" type="button" id="confirm" style="background-color: #379; margin: 0px 20px" onclick="hideStopWordEditor()">返回</button>
<button class="general-button" type="button" id="confirm"
style="background-color: #379; margin: 0px 10px"
onclick="hideStopWordEditor(); submit()">確認</button>
<button class="general-button" type="button" id="confirm"
style="background-color: #379; margin: 0px 10px" onclick="downloadStopWord()">匯出停用詞</button>
<button class="general-button" type="button" id="confirm"
style="background-color: #379; margin: 0px 10px" onclick="clearStopWord()">全部清除</button>
<button class="general-button w3-right" type="button" id="confirm"
style="background-color: #379; margin: 0px 20px" onclick="hideStopWordEditor()">返回</button>
</div>
</div>
</div>
<div class='w3-bar w3-teal'>
<button class="w3-button w3-teal" type="button" onclick="location.href='/ptt'">PTT Sententree</button>
<button class="w3-button" type="button" onclick="location.href='/ptt_push'">推文Sententree</button>
<button class="w3-button w3-teal" type="button" onclick="location.href='/generalTxt'" style="color: darkseagreen;">泛用文字視覺化工具</button>
<button class="w3-button w3-teal" type="button" onclick="location.href='/generalTxt'"
style="color: darkseagreen;">泛用文字視覺化工具</button>
</div>
<div id='heading'>
<h2>泛用文字視覺化工具</h2>
<p>SentenTree <a href="https://github.com/twitter/SentenTree">https://github.com/twitter/SentenTree</a></p>
<p id='comment'>這是泛用.txt檔視覺化工具能夠簡單處理文字檔的視覺化。</p>
<p id='comment'>支援的語言:繁體中文、英文以及所有使用空格分詞的語言。</p>
<p id='comment'>使用繁體中文Jieba斷詞器不保證簡體中文能夠正常使用。</p>
<p id="comment">點此查看<a href="/generaltxt/help">使用說明</a></p>
</div>
<div style="margin:10px;">
<button class="general-button" type="button" id="editSWButton" style="margin:10px 0px;" onclick="showStopwordEditor()">編輯停用詞</button>
<button class="general-button" type="button" id="editSWButton" style="margin:10px 0px;"
onclick="showStopwordEditor()">編輯停用詞</button>
<label id="minRatioLabel">Min Ratio</label>
<input type="number" step="0.0001" id="minRatio" value="0.001" min="0.0001" max="1">
<label id="maxRatioLabel">Max Ratio</label>
<input type="number" step="0.0001" id="maxRatio" value="1" min="0.0001" max="1">
</div>
<div id='rawText' class=''>
<div id="wordcount">字數0</div>
<textarea id='rawTextBox' rows=25 placeholder="輸入要視覺化的文字
換行為斷句"></textarea>
換行為斷句" onchange="countWords()"></textarea>
<button class='general-button' style='margin: 10px 0px' onclick="submit()">提交</button>
</div>
<div>
<button id='toggleTextBox' class='general-button' style='margin: 0px 10px' onclick="switchMessageBox()">隱藏文字視窗</button>
<button id='toggleTextBox' class='general-button' style='margin: 0px 10px'
onclick="switchMessageBox()">隱藏文字視窗</button>
<div id='graph' class='hidden'>
<div id='vis'></div>
</div>

@ -0,0 +1,46 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<link href="/static/css/w3.css" type="text/css" rel="stylesheet">
<link href="/static/css/main.css" type="text/css" rel="stylesheet">
<title>使用說明</title>
</head>
<body>
<h1>使用說明</h1>
<h2>基本說明</h2>
<p>泛用文字視覺化工具能夠簡單處理文字檔的視覺化。<br>
支援的語言:繁體中文、英文以及所有使用空格分詞的語言。<br>
使用繁體中文Jieba斷詞器不保證簡體中文能夠正常使用。</p>
<h2>參數</h2>
<p>此工具提供 <span style="color: red;">minRatio</span><span style="color: red;">maxRatio</span> 兩個參數的設定<br>
兩個參數代表相鄰兩個單詞(有被連接的單詞)之間的最大或最小比值<br>
例如maxRatio 為 0.8 時,代表兩個相鄰的單詞出現的頻率必須小於 0.8,否則單詞就不會被演算法選中。
</p>
<h2>輸入資料前處理</h2>
<p>本工具會將輸入資料做預先處理。以中文語料為例,處理流程大致如下:</p>
<p>1. 斷句:使用中文的全形句號(。)及換行進行斷句</p>
<p>2. 斷詞並標記詞性:使用 Jieba 將每個句子分別斷詞,並標註其詞性</p>
<p>3. 過濾詞性:將英文及數字過濾,以免產生過多雜訊</p>
<h2>停用詞</h2>
<p>使用者可以編輯停用詞,被設定為停用詞的單詞,將不會被選擇到 sententree 中。</p>
<p>在輸入停用詞時,可以一次輸入多個停用詞,並使用空格(半形)分開。</p>
<h2>Sententree 圖形</h2>
<p>輸入一份文件預設會產生2個 sententree 圖形,圖 1 為一個 sententree 的圖形</p>
<p>每個圖形中間最大的單詞為<span style="color:blue;">根單詞</span></p>
<p>其中第二個圖形中不會包含第一個圖形的根單詞</p>
<p>單詞之間的連線代表兩個單詞有在同一個句子中出現過</p>
<p>灰色連線代表演算法在搜尋時,兩個單詞屬於同一個階層(出現在相同的句子中)</p>
<p>橘色連線代表兩個單詞屬於不同階層</p>
<p>連線的粗細代表兩個單詞同時出現的比例</p>
<p>將滑鼠移到單詞上,能夠看到包含該單詞的完整句子(最多顯示 5 筆),如圖 2</p>
<img style="width: 100%;" src="/img/general_txt_help_g01.png">
<span>圖 1Sententree 圖形</span>
<img style="width: 100%;" src="/img/general_txt_help_g02.png">
<span>圖 2完整句子顯示</span>
</body>
</html>
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