public Image getImageWordmap(Dictionary <string, int> wordCount, int width, int height)
{
//List to show wordmap
List <string> wordslist = new List <string>();
List <int> frequencylist = new List <int>();
var items = from pair in wordCount
orderby pair.Value descending
select pair;
//add sports words and frequency to the list
foreach (var kvp in items)
{
wordslist.Add(kvp.Key);
frequencylist.Add(kvp.Value);
}
//create word cloud generation
var wc = new WordCloudGen(width, height);
// display wordmap image of sports news
Image wordmap = wc.Draw(wordslist, frequencylist);
return(wordmap);
}
public static void GenerateWordCloud(List <KeyValuePair <string, int> > sortedList)
{
/* creating a WordCloud image */
List <string> words = new List <string>();
List <int> freq = new List <int>();
// seperating the keyvalue pairs into the correct format of two lists
foreach (KeyValuePair <string, int> e in sortedList)
{
words.Add(e.Key);
}
foreach (KeyValuePair <string, int> f in sortedList)
{
freq.Add(f.Value);
}
// 500, 500 refers to the image quality, true gives size based on freq, null gives words random colors, -1, 1 are step sizes
var wc = new WordCloudGen(500, 500, true, null, -1, 1);
// save image to solution's image folder
wc.Draw(words, freq).Save(@"c:\users\nickt\source\repos\testai\testai\Images\wordcloud.bmp");
Console.WriteLine("picture saved as wordcloud.bmp");
foreach (KeyValuePair <string, int> test in sortedList)
{
Console.WriteLine(test);
}
}
public void CommentInfoCommand(MessageInfo message, string[] args)
{
if (args.Length != 4 && args.Length != 5)
{
_service.SendToGroup(message.GroupNumber, "使用方法: !直播 评论 <Vtuber名字> <序号> [复读排序]");
return;
}
var vtuber = Config.DefaultConfig.GetVtuber(args[2]);
if (vtuber == null)
{
_service.SendToGroup(message.GroupNumber, "数据库中不存在" + args[2]);
return;
}
var history = _liveCollection.FindAsync(doc => doc.Channel == vtuber.YoutubeChannelId).GetAwaiter().GetResult().ToList();
if (!history.Any())
{
_service.SendToGroup(message.GroupNumber, "未找到任何记录，请等待下次直播，机器人将自动记录");
return;
}
_service.SendToGroup(message.GroupNumber, "正在查询..");
var info = history[int.Parse(args[3]) - 1];
var comments = _chatCollection.FindAsync(doc => doc.VideoId == info.VideoId).GetAwaiter().GetResult().ToList();
var dic = new Dictionary <string, int>();
foreach (var comment in comments)
{
if (!dic.ContainsKey(comment.DisplayMessage))
{
dic.Add(comment.DisplayMessage, 0);
}
dic[comment.DisplayMessage]++;
}
var msg = string.Empty;
if (args.Length == 5 && args.Last() == "复读")
{
var dicDesc = dic.OrderByDescending(v => v.Value).ToDictionary(key => key.Key, value => value.Value);
var wordCloud = new WordCloud.WordCloud(1920, 1080);
var image = wordCloud.Draw(dicDesc.Keys.Take(30).ToList(), dicDesc.Values.Take(30).ToList());
_service.SendImageToGroup(message.GroupNumber, image);
return;
}
var count = comments.Where(v => v.TextMessageDetails?.HasValues ?? false).Count(v =>
v.TextMessageDetails["messageText"].ToObject <string>().ChineseRatio() > 80 &&
v.DisplayMessage.Length >= 2 && v.DisplayMessage.ToCharArray()
.All(c => !c.IsHinaganaOrKatakana() && c.IsSimplifiedChinese()));
msg = $"关于 {vtuber.OriginalName} 直播的评论分析:" +
$"\r\n标题: {info.Title}" +
$"\r\n评论总数: {comments.Count}" +
$"\r\n平均每分钟评论数: {(comments.Count / (info.EndTime - info.BeginTime).TotalMinutes):F}" +
$"\r\n最多复读的词: {dic.First(v => v.Value == dic.Max(d => d.Value)).Key} (复读 {dic.Max(v => v.Value)} 次)" +
$"\r\n疑似大陆天狗评论数: {count} (估算)";
_service.SendToGroup(message.GroupNumber, msg);
}
private async void Button1_Click(object sender, EventArgs e)
{
if (textBox1.Text == "")
{
return;
}
_query = textBox1.Text;
var result = "";
var client = new HttpClient();
var uri = Host + "cx=" + Cx + "&key=" + Key + "&num=" + Num + "&start=" + Start + "&q=" + System.Net.WebUtility.UrlEncode(_query);
var response = await client.GetAsync(uri);
var contentString = await response.Content.ReadAsStringAsync();
dynamic parsedJson = JsonConvert.DeserializeObject(contentString);
var items = parsedJson?.items;
for (var i = Start; i < Num; i++)
{
result += items?[i].snippet.ToString();
}
var extractor = new TfidfExtractor();
var pairs = extractor.ExtractTagsWithWeight(result, 30);
var words = new List <string>();
var freqs = new List <int>();
foreach (var pair in pairs)
{
if (pair.Word.Equals("..."))
{
continue;
}
words.Add(pair.Word);
freqs.Add(Convert.ToInt32(pair.Weight * Math.Pow(10, 6)));
}
var wc = new WordCloud.WordCloud(1920, 1080);
var image = wc.Draw(words, freqs);
pictureBox1.Image = image;
button2.Enabled = true;
button2.Visible = true;
}
private void button1_Click(object sender, EventArgs e)
{
var s = new Stopwatch();
s.Start();
var wc = new WordCloudGen(1000, 600);
if (resultPictureBox.Image != null)
{
resultPictureBox.Image.Dispose();
}
Image i = wc.Draw(Words, Frequencies);
s.Stop();
elapsedLabel.Text = s.Elapsed.TotalMilliseconds.ToString();
resultPictureBox.Image = i;
}
public void createWordCloud()
{
List <string> listTagName = new List <string>();
List <int> listFreqs = new List <int>();
List <Tuple <TAG, int> > listNumNotePerTag = new List <Tuple <TAG, int> >();
listNumNotePerTag = xlTag.statisticNumberNotePerTag();
int maxCount = listNumNotePerTag.Max(t => t.Item2);
maxCount++;
listNumNotePerTag.Sort(delegate(Tuple <TAG, int> tuple1, Tuple <TAG, int> tuple2)
{
return(tuple2.Item2.CompareTo(tuple1.Item2));
});
foreach (var entry in listNumNotePerTag)
{
listTagName.Add(entry.Item1.mContent);
listFreqs.Add(maxCount - entry.Item2);
}
var wc = new WordCloudGen(400, 400);
System.Drawing.Image wordCloudImage = wc.Draw(listTagName, listFreqs);
// Đổi từ kiểu dữ liệu Drawing.Image sang ImageSource ==> bi
BitmapImage bi = new BitmapImage();
bi.BeginInit();
System.IO.MemoryStream ms = new System.IO.MemoryStream();
wordCloudImage.Save(ms, System.Drawing.Imaging.ImageFormat.Png);
ms.Seek(0, System.IO.SeekOrigin.Begin);
bi.StreamSource = ms;
bi.EndInit();
// Đặt hình mới được tạo vào (Đây là hình Word Cloud)
wordCloud.Source = bi;
}
private void button3_Click(object sender, EventArgs e)
{
Cursor.Current = Cursors.WaitCursor;
string filePath = Path.Combine(Directory.GetCurrentDirectory(), "sportsNews.txt");
string sportsText = File.ReadAllText(filePath);
wordmap wm = new wordmap();
List <string> prepVerbList = wm.GetprepVerbList();
label2.Text = "loading preposition and verb files ...";
sportsText = wm.normalize(sportsText);
label2.Text = "normalizing text ...";
string[] words = wm.tokenize(sportsText);
label2.Text = "tokenizing text ...";
Dictionary <string, int> SportswordCount = wm.CalcWordCount(words);
label2.Text = "lemmatizing and counting words frequencies ...";
SportswordCount = wm.deletePrepVerb(prepVerbList, SportswordCount);
label2.Text = "deleting preposition and verb from words ...";
filePath = Path.Combine(Directory.GetCurrentDirectory(), "politicsNews .txt");
string politicsText = File.ReadAllText(filePath);
politicsText = wm.normalize(politicsText);
label2.Text = "normalizing text ...";
words = wm.tokenize(politicsText);
label2.Text = "tokenizing text ...";
Dictionary <string, int> PoliticswordCount = wm.CalcWordCount(words);
label2.Text = "lemmatizing and counting words frequencies ...";
PoliticswordCount = wm.deletePrepVerb(prepVerbList, PoliticswordCount);
label2.Text = "deleting preposition and verb from words ...";
decimal totalsportsWordCount = (decimal)SportswordCount.Sum(x => x.Value);
decimal totalpoliticsWordCount = (decimal)PoliticswordCount.Sum(x => x.Value);
List <string> AllWord = new List <string>();
List <string> sportsWordList = new List <string>();
List <string> politicsWordList = new List <string>();
sportsWordList = SportswordCount.Keys.ToList();
politicsWordList = PoliticswordCount.Keys.ToList();
AllWord = sportsWordList.Union(politicsWordList).ToList();
DataTable Allword = new DataTable();
Allword.Columns.Add("word", typeof(string));
Allword.Columns.Add("SportsCount", typeof(decimal));
Allword.Columns.Add("PoliticsCount", typeof(decimal));
Allword.Columns.Add("Distance", typeof(decimal));
foreach (string word in AllWord)
{
decimal sportValue;
decimal politicsValue;
if (SportswordCount.ContainsKey(word))
{
sportValue = (decimal)SportswordCount[word];
}
else
{
sportValue = 0;
}
if (PoliticswordCount.ContainsKey(word))
{
politicsValue = (decimal)PoliticswordCount[word];
}
else
{
politicsValue = 0;
}
decimal distance = (sportValue / totalsportsWordCount) - (politicsValue / totalpoliticsWordCount);
Allword.Rows.Add(word, sportValue, politicsValue, distance);
}
dataGridView1.Rows.Clear();
dataGridView1.Columns.Clear();
Allword.DefaultView.Sort = "Distance DESC";
Allword = Allword.DefaultView.ToTable();
dataGridView1.DataSource = Allword;
List <string> wordslist = new List <string>();
List <int> frequencylist = new List <int>();
for (int i = 0; i < Allword.Rows.Count; i++)
{
wordslist.Add(Allword.Rows[i]["word"].ToString());
frequencylist.Add((int)(Math.Abs(Convert.ToDecimal(Allword.Rows[i]["Distance"].ToString()) * 10000)));
}
//create word cloud generation
var wc = new WordCloudGen(pictureBox1.Width, pictureBox1.Height);
// display wordmap image of sports news
Image newImage = wc.Draw(wordslist, frequencylist);
pictureBox1.Image = newImage;
label2.Text = "done";
}
public void ChartBlocksTest()
{
var wc = new WordCloud.WordCloud(1920, 1080);
}
private void button1_Click(object sender, EventArgs e)
{
var s = new Stopwatch();
s.Start();
var wc = new WordCloudGen(1000, 600);
if (resultPictureBox.Image != null)
{
resultPictureBox.Image.Dispose();
}
Words.Clear();
Frequencies.Clear();
List <string> AllWords = new List <string>();
List <int> AllFrequencies = new List <int>();
var file_words = File.ReadAllText(@"D:\c#\图云词频计算\words.txt");
var words = file_words.Split('\n');
foreach (var word in words)
{
if (AllWords.Contains(word))
{
//如果已经存在就+1
AllFrequencies[AllWords.IndexOf(word)]++;
}
else
{
bool result = false;
for (int j = 0; j < word.Length; j++)
{
if (Char.IsNumber(word, j))
{
result = true;
}
}
if (!result)
{
//如果不存在 且不为数字就添加
AllWords.Add(word);
AllFrequencies.Add(1);
}
}
}
int index = 0;
foreach (var temp in AllFrequencies)
{
if (temp > 200)
{
Words.Add(AllWords[index]);
Frequencies.Add(temp);
}
index++;
}
Image i = wc.Draw(Words, Frequencies);
s.Stop();
elapsedLabel.Text = s.Elapsed.TotalMilliseconds.ToString();
resultPictureBox.Image = i;
}