GeoSpark是一种用于大规模空间数据处理的集群计算。 GeoSpark通过一组out-of-the-box空间弹性分布式数据集( SRDDs ) 扩展 Apache Spark，它可以跨机器高效地加载。处理、分析、展示大规模空间数据。

准备工作

  1. Windows 和 spark
  2. IDEA
  3. GeoSpark支持Java、Scala两种,本次开发语言选择Java。

GeoSpark

参考https://github.com/jiayuasu/GeoSparkTemplateProject,下载项目到本地。

GeoSpark-Viz Java项目构建

  1. cd ./geospark-viz/java
  2. mvn clean install

由于项目中的数据生成图片不太满意，将map.shp数据解析成polygon.csv,修改下java代码

  1. ConfFile= new FileInputStream(resourcePath+"babylon.polygon2.properties");



通过buildChoroplethMap统计面内得点数生成分级统计图，修改buildScatterPlot和

buildHeatMap输入数据为点数据生成散点图和热力图。





完整代码：

  1. package example;
  3. import com.vividsolutions.jts.geom.Envelope;
  4. import com.vividsolutions.jts.geom.Polygon;
  5. import org.apache.log4j.Level;
  6. import org.apache.log4j.Logger;
  7. import org.apache.spark.SparkConf;
  8. import org.apache.spark.api.java.JavaPairRDD;
  9. import org.apache.spark.api.java.JavaSparkContext;
  10. import org.apache.spark.serializer.KryoSerializer;
  11. import org.apache.spark.storage.StorageLevel;
  12. import org.datasyslab.geospark.enums.FileDataSplitter;
  13. import org.datasyslab.geospark.enums.GridType;
  14. import org.datasyslab.geospark.enums.IndexType;
  15. import org.datasyslab.geospark.formatMapper.EarthdataHDFPointMapper;
  16. import org.datasyslab.geospark.spatialOperator.JoinQuery;
  17. import org.datasyslab.geospark.spatialRDD.PointRDD;
  18. import org.datasyslab.geospark.spatialRDD.PolygonRDD;
  19. import org.datasyslab.geospark.spatialRDD.RectangleRDD;
  20. import org.datasyslab.geosparkviz.core.ImageGenerator;
  21. import org.datasyslab.geosparkviz.core.ImageStitcher;
  22. import org.datasyslab.geosparkviz.core.RasterOverlayOperator;
  23. import org.datasyslab.geosparkviz.core.Serde.GeoSparkVizKryoRegistrator;
  24. import org.datasyslab.geosparkviz.extension.visualizationEffect.ChoroplethMap;
  25. import org.datasyslab.geosparkviz.extension.visualizationEffect.HeatMap;
  26. import org.datasyslab.geosparkviz.extension.visualizationEffect.ScatterPlot;
  27. import org.datasyslab.geosparkviz.utils.ColorizeOption;
  28. import org.datasyslab.geosparkviz.utils.ImageType;
  30. import java.awt.*;
  31. import java.io.FileInputStream;
  32. import java.io.IOException;
  33. import java.util.Properties;
  35. // TODO: Auto-generated Javadoc
  37. /**
  38.  * The Class Example.
  39.  */
  40. public class Example2019 {
  42. 	/** The spark context. */
  43. 	static JavaSparkContext sparkContext;
  45.     /** The prop. */
  46.     static Properties prop;
  48.     /** The Point input location. */
  49.     static String PointInputLocation;
  51.     /** The Point offset. */
  52.     static Integer PointOffset;
  54.     /** The Point splitter. */
  55.     static FileDataSplitter PointSplitter;
  57.     /** The Point num partitions. */
  58.     static Integer PointNumPartitions;
  60.     /** The Rectangle input location. */
  61.     static String RectangleInputLocation;
  63.     /** The Rectangle offset. */
  64.     static Integer RectangleOffset;
  66.     /** The Rectangle splitter. */
  67.     static FileDataSplitter RectangleSplitter;
  69.     /** The Rectangle num partitions. */
  70.     static Integer RectangleNumPartitions;
  72.     /** The Polygon input location. */
  73.     static String PolygonInputLocation;
  75.     /** The Polygon offset. */
  76.     static Integer PolygonOffset;
  78.     /** The Polygon splitter. */
  79.     static FileDataSplitter PolygonSplitter;
  81.     /** The Polygon num partitions. */
  82.     static Integer PolygonNumPartitions;
  84.     /** The Line string input location. */
  85.     static String LineStringInputLocation;
  87.     /** The Line string offset. */
  88.     static Integer LineStringOffset;
  90.     /** The Line string splitter. */
  91.     static FileDataSplitter LineStringSplitter;
  93.     /** The Line string num partitions. */
  94.     static Integer LineStringNumPartitions;
  96.     /** The US main land boundary. */
  97.     static Envelope USMainLandBoundary;
  99.     /** The earthdata input location. */
  100.     static String earthdataInputLocation;
  102.     /** The earthdata num partitions. */
  103.     static Integer earthdataNumPartitions;
  105.     /** The HDF increment. */
  106.     static int HDFIncrement = 5;
  108.     /** The HDF offset. */
  109.     static int HDFOffset = 2;
  111.     /** The HDF root group name. */
  112.     static String HDFRootGroupName = "MOD_Swath_LST";
  114.     /** The HDF data variable name. */
  115.     static String HDFDataVariableName = "LST";
  117.     /** The HDF data variable list. */
  118.     static String[] HDFDataVariableList = {"LST","QC","Error_LST","Emis_31","Emis_32"};
  120.     /** The HD fswitch XY. */
  121.     static boolean HDFswitchXY = true;
  123.     /** The url prefix. */
  124.     static String urlPrefix = "";
  126. 	/**
  127. 	 * Builds the scatter plot.
  128. 	 *
  129. 	 * @param outputPath the output path
  130. 	 * @return true, if successful
  131. 	 */
  132. 	public static boolean buildScatterPlot(String outputPath)
  133. 	{
  134. 		try{
  135. 			PointRDD spatialRDD = new PointRDD(sparkContext, PointInputLocation, PointOffset, PointSplitter, false, PointNumPartitions, StorageLevel.MEMORY_ONLY());
  136. 			//PolygonRDD spatialRDD = new PolygonRDD(sparkContext, PolygonInputLocation, PolygonSplitter, false, PolygonNumPartitions, StorageLevel.MEMORY_ONLY());
  137. 			ScatterPlot visualizationOperator = new ScatterPlot(1000,600,USMainLandBoundary,false);
  138. 			visualizationOperator.CustomizeColor(255, 255, 255, 255, Color.GREEN, true);
  139. 			visualizationOperator.Visualize(sparkContext, spatialRDD);
  140. 			ImageGenerator imageGenerator = new  ImageGenerator();
  141. 			imageGenerator.SaveRasterImageAsLocalFile(visualizationOperator.rasterImage, outputPath, ImageType.PNG);
  143. //			visualizationOperator = new ScatterPlot(1000,600,USMainLandBoundary,false,-1,-1,false,true);
  144. //			visualizationOperator.CustomizeColor(255, 255, 255, 255, Color.GREEN, true);
  145. //			visualizationOperator.Visualize(sparkContext, spatialRDD);
  146. //			imageGenerator = new ImageGenerator();
  147. //			imageGenerator.SaveVectorImageAsLocalFile(visualizationOperator.vectorImage, outputPath,ImageType.SVG);
  148. //
  149. //			visualizationOperator = new ScatterPlot(1000,600,USMainLandBoundary,false,-1,-1,true,true);
  150. //			visualizationOperator.CustomizeColor(255, 255, 255, 255, Color.GREEN, true);
  151. //			visualizationOperator.Visualize(sparkContext, spatialRDD);
  152. //			imageGenerator = new ImageGenerator();
  153. //			imageGenerator.SaveVectorImageAsLocalFile(visualizationOperator.distributedVectorImage, outputPath+"-distributed",ImageType.SVG);
  154. //
  155. 		}
  156. 		catch(Exception e)
  157. 		{
  158. 			e.printStackTrace();
  159. 			return false;
  160. 		}
  161. 		return true;
  163. 	}
  165. 	/**
  166. 	 * Builds the heat map.
  167. 	 *
  168. 	 * @param outputPath the output path
  169. 	 * @return true, if successful
  170. 	 */
  171. 	public static boolean buildHeatMap(String outputPath)
  172. 	{
  173. 		try{
  174. 			PointRDD spatialRDD = new PointRDD(sparkContext, PointInputLocation, PointOffset, PointSplitter, false, PointNumPartitions, StorageLevel.MEMORY_ONLY());
  175. 			HeatMap visualizationOperator = new HeatMap(1000,600,USMainLandBoundary,false,5);
  176. 			visualizationOperator.Visualize(sparkContext, spatialRDD);
  177. 			ImageGenerator imageGenerator = new  ImageGenerator();
  178. 			imageGenerator.SaveRasterImageAsLocalFile(visualizationOperator.rasterImage, outputPath,ImageType.PNG);
  179. 		}
  180. 		catch(Exception e)
  181. 		{
  182. 			e.printStackTrace();
  183. 			return false;
  184. 		}
  185. 		return true;
  186. 	}
  188. 	/**
  189. 	 * Builds the choropleth map.
  190. 	 *
  191. 	 * @param outputPath the output path
  192. 	 * @return true, if successful
  193. 	 */
  194. 	public static boolean buildChoroplethMap(String outputPath)
  195. 	{
  196. 		try{
  198. 			PointRDD spatialRDD = new PointRDD(sparkContext, PointInputLocation, PointOffset, PointSplitter, false, PointNumPartitions, StorageLevel.MEMORY_ONLY());
  199. 			PolygonRDD queryRDD = new PolygonRDD(sparkContext, PolygonInputLocation,  PolygonSplitter, false, PolygonNumPartitions, StorageLevel.MEMORY_ONLY());
  200. 			spatialRDD.spatialPartitioning(GridType.RTREE);
  201. 			queryRDD.spatialPartitioning(spatialRDD.grids);
  202. 			spatialRDD.buildIndex(IndexType.RTREE,true);
  203. 			JavaPairRDD<Polygon,Long> joinResult = JoinQuery.SpatialJoinQueryCountByKey(spatialRDD,queryRDD,true,false);
  205. 			long start = System.currentTimeMillis();
  206. 			ChoroplethMap visualizationOperator = new ChoroplethMap(1000,600,USMainLandBoundary,false);
  207. 			visualizationOperator.CustomizeColor(255, 255, 255, 255, Color.RED, true);
  208. 			visualizationOperator.Visualize(sparkContext, joinResult);
  210. 			ScatterPlot frontImage = new ScatterPlot(1000,600,USMainLandBoundary,false);
  211. 			frontImage.CustomizeColor(0, 0, 0, 255, Color.GREEN, true);
  212. 			frontImage.Visualize(sparkContext, queryRDD);
  214. 			RasterOverlayOperator overlayOperator = new RasterOverlayOperator(visualizationOperator.rasterImage);
  215. 			overlayOperator.JoinImage(frontImage.rasterImage);
  217. 			ImageGenerator imageGenerator = new ImageGenerator();
  218. 			//imageGenerator.SaveRasterImageAsLocalFile(frontImage.rasterImage, outputPath,ImageType.PNG);
  219. 			imageGenerator.SaveRasterImageAsLocalFile(overlayOperator.backRasterImage, outputPath,ImageType.PNG);
  220. 			//imageGenerator.SaveRasterImageAsLocalFile(visualizationOperator.distributedRasterImage, outputPath,ImageType.PNG);
  221. 			//ImageStitcher.stitchImagePartitionsFromLocalFile(outputPath, 1000,600,0,4, 4);
  223. 			System.out.println("散点图生成完成，共耗时" + (System.currentTimeMillis() - start) + "ms");
  224. 		}
  225. 		catch(Exception e)
  226. 		{
  227. 			e.printStackTrace();
  228. 			return false;
  229. 		}
  230. 		return true;
  231. 	}
  233. 	/**
  234. 	 * Parallel filter render no stitch.
  235. 	 *
  236. 	 * @param outputPath the output path
  237. 	 * @return true, if successful
  238. 	 */
  239. 	public static boolean parallelFilterRenderNoStitch(String outputPath)
  240. 	{
  241. 		try{
  242. 			PointRDD spatialRDD = new PointRDD(sparkContext, PointInputLocation, PointOffset, PointSplitter, false, PointNumPartitions, StorageLevel.MEMORY_ONLY());
  243. 			HeatMap visualizationOperator = new HeatMap(1000,600,USMainLandBoundary,false,2,4,4,true,true);
  244. 			visualizationOperator.Visualize(sparkContext, spatialRDD);
  245. 			ImageGenerator imageGenerator = new ImageGenerator();
  246. 			imageGenerator.SaveRasterImageAsLocalFile(visualizationOperator.distributedRasterImage, outputPath,ImageType.PNG);
  247. 		}
  248. 		catch(Exception e)
  249. 		{
  250. 			e.printStackTrace();
  251. 			return false;
  252. 		}
  253. 		return true;
  254. 	}
  256. 	/**
  257. 	 * Parallel filter render stitch.
  258. 	 *
  259. 	 * @param outputPath the output path
  260. 	 * @return true, if successful
  261. 	 */
  262. 	public static boolean parallelFilterRenderStitch(String outputPath)
  263. 	{
  264. 		try{
  265. 			PointRDD spatialRDD = new PointRDD(sparkContext, PointInputLocation, PointOffset, PointSplitter, false, PointNumPartitions, StorageLevel.MEMORY_ONLY());
  266. 			HeatMap visualizationOperator = new HeatMap(1000,600,USMainLandBoundary,false,2,4,4,true,true);
  267. 			visualizationOperator.Visualize(sparkContext, spatialRDD);
  268. 			ImageGenerator imageGenerator = new ImageGenerator();
  269. 			imageGenerator.SaveRasterImageAsLocalFile(visualizationOperator.distributedRasterImage, outputPath,ImageType.PNG);
  270. 	        ImageStitcher.stitchImagePartitionsFromLocalFile(outputPath, 1000,600,0,4, 4);
  272. 		}
  273. 		catch(Exception e)
  274. 		{
  275. 			e.printStackTrace();
  276. 			return false;
  277. 		}
  278. 		return true;
  279. 	}
  281. 	/**
  282. 	 * Earthdata visualization.
  283. 	 *
  284. 	 * @param outputPath the output path
  285. 	 * @return true, if successful
  286. 	 */
  287. 	public static boolean earthdataVisualization(String outputPath)
  288. 	{
  290. 		try {
  291. 			EarthdataHDFPointMapper earthdataHDFPoint = new EarthdataHDFPointMapper(HDFIncrement,HDFOffset,HDFRootGroupName,
  292. 					HDFDataVariableList,HDFDataVariableName,HDFswitchXY,urlPrefix);
  293. 	    	PointRDD spatialRDD = new PointRDD(sparkContext, earthdataInputLocation, earthdataNumPartitions, earthdataHDFPoint,StorageLevel.MEMORY_ONLY());
  294. 			ScatterPlot visualizationOperator = new ScatterPlot(1000,600,spatialRDD.boundaryEnvelope,ColorizeOption.EARTHOBSERVATION,false,false);
  295. 			visualizationOperator.CustomizeColor(255, 255, 255, 255, Color.BLUE, true);
  296. 			visualizationOperator.Visualize(sparkContext, spatialRDD);
  297. 			ImageGenerator imageGenerator = new  ImageGenerator();
  298. 			imageGenerator.SaveRasterImageAsLocalFile(visualizationOperator.rasterImage, outputPath, ImageType.PNG);
  299. 		} catch (Exception e) {
  300. 			e.printStackTrace();
  301. 			return false;
  302. 		}
  303. 		return true;
  304. 	}
  306. 	/**
  307. 	 * The main method.
  308. 	 *
  309. 	 * @param args the arguments
  310. 	 * @throws IOException Signals that an I/O exception has occurred.
  311. 	 */
  312. 	public static void main(String[] args) throws IOException {
  313. 		long start = System.currentTimeMillis();
  314. 		Logger.getLogger("org").setLevel(Level.WARN);
  315. 		Logger.getLogger("akka").setLevel(Level.WARN);
  317. 		SparkConf sparkConf = new SparkConf().setAppName("GeoSparkVizDemo").setMaster("local[*]").set("spark.serializer", KryoSerializer.class.getName())
  318. 		.set("spark.kryo.registrator", GeoSparkVizKryoRegistrator.class.getName());
  319. 		sparkContext = new JavaSparkContext(sparkConf);
  321.         prop = new Properties();
  323.         String resourcePath = "src/test/resources/";
  324.         String demoOutputPath = "target/demo";
  325. 		FileInputStream ConfFile= new FileInputStream(resourcePath+"babylon.point.properties");
  326. 		prop.load(ConfFile);
  328.         String scatterPlotOutputPath = System.getProperty("user.dir")+"/"+demoOutputPath + "/scatterplot";
  329.         String heatMapOutputPath = System.getProperty("user.dir")+"/"+demoOutputPath+"/heatmap";
  330.         String choroplethMapOutputPath = System.getProperty("user.dir")+"/"+demoOutputPath+"/choroplethmap";
  331.         String parallelFilterRenderStitchOutputPath = System.getProperty("user.dir")+"/"+demoOutputPath+"/parallelfilterrenderstitchheatmap";
  332.         String earthdataScatterPlotOutputPath = System.getProperty("user.dir")+"/"+demoOutputPath+"/earthdatascatterplot";
  334.         PointInputLocation = System.getProperty("user.dir")+"/"+resourcePath+prop.getProperty("inputLocation");
  335.         PointOffset = Integer.parseInt(prop.getProperty("offset"));;
  336.         PointSplitter = FileDataSplitter.getFileDataSplitter(prop.getProperty("splitter"));
  337.         PointNumPartitions = Integer.parseInt(prop.getProperty("numPartitions"));
  339. 		ConfFile= new FileInputStream(resourcePath+"babylon.rectangle.properties");
  340. 		prop.load(ConfFile);
  341.         RectangleInputLocation = System.getProperty("user.dir")+"/"+resourcePath+prop.getProperty("inputLocation");
  342.         RectangleOffset = Integer.parseInt(prop.getProperty("offset"));
  343.         RectangleSplitter = FileDataSplitter.getFileDataSplitter(prop.getProperty("splitter"));
  344.         RectangleNumPartitions = Integer.parseInt(prop.getProperty("numPartitions"));
  346. 		ConfFile= new FileInputStream(resourcePath+"babylon.polygon2.properties");
  347. 		prop.load(ConfFile);
  348. 		PolygonInputLocation = System.getProperty("user.dir")+"/"+resourcePath+prop.getProperty("inputLocation");
  349. 		PolygonOffset = Integer.parseInt(prop.getProperty("offset"));
  350. 		PolygonSplitter = FileDataSplitter.getFileDataSplitter(prop.getProperty("splitter"));
  351. 		PolygonNumPartitions = Integer.parseInt(prop.getProperty("numPartitions"));
  353. 		ConfFile= new FileInputStream(resourcePath+"babylon.linestring.properties");
  354. 		prop.load(ConfFile);
  355.         LineStringInputLocation = System.getProperty("user.dir")+"/"+resourcePath+prop.getProperty("inputLocation");
  356.         LineStringOffset = Integer.parseInt(prop.getProperty("offset"));
  357.         LineStringSplitter = FileDataSplitter.getFileDataSplitter(prop.getProperty("splitter"));
  358.         LineStringNumPartitions = Integer.parseInt(prop.getProperty("numPartitions"));
  360.         USMainLandBoundary = new Envelope(-126.790180,-64.630926,24.863836,50.000);
  362.         earthdataInputLocation = System.getProperty("user.dir")+"/src/test/resources/modis/modis.csv";
  363.         earthdataNumPartitions = 5;
  364.         HDFIncrement=5;
  365.         HDFOffset=2;
  366.         HDFRootGroupName = "MOD_Swath_LST";
  367.         HDFDataVariableName = "LST";
  368.         HDFswitchXY = true;
  369.         urlPrefix = System.getProperty("user.dir")+"/src/test/resources/modis/";
  371.         if(buildScatterPlot(scatterPlotOutputPath)&&buildHeatMap(heatMapOutputPath)
  372.         		&&buildChoroplethMap(choroplethMapOutputPath)&&parallelFilterRenderStitch(parallelFilterRenderStitchOutputPath+"-stitched")
  373.         		&&parallelFilterRenderNoStitch(parallelFilterRenderStitchOutputPath)&&earthdataVisualization(earthdataScatterPlotOutputPath))
  374.         {
  375. 			System.out.println("散点图生成完成，共耗时" + (System.currentTimeMillis() - start) + "ms");
  376.         	System.out.println("All GeoSparkViz Demos have passed.");
  377.         }
  378.         else
  379.         {
  380.         	System.out.println("GeoSparkViz Demos failed.");
  382.         }
  383.         sparkContext.stop();
  384. 	}
  386. }

项目可视化一览



参考资料：

https://www.jianshu.com/p/1a531de087df

https://www.helplib.com/GitHub/article_127813

GeoSpark入门-可视化的更多相关文章

  1. （一）Superset 1.3图表篇——Table

    本系列文章基于Superset 1.3.0版本.1.3.0版本目前支持分布,趋势,地理等等类型共59张图表.本次1.3版本的更新图表有了一些新的变化,而之前也一直没有做过非常细致的图表教程. 而且目前 ...

  2. 一起学微软Power BI系列-官方文档-入门指南(4)Power BI的可视化

    在前面的系列文章中,我们介绍了官方有关获取数据,以及建模的原始文档和基本介绍.今天继续给大家介绍官方文档中,有关可视化的内容.实际上获获取数据和建模更注重业务关系的处理,而可视化则关注对数据的解读.这 ...

  3. d3.js:数据可视化利器之快速入门

    hello,data! 在进入d3.js之前,我们先用一个小例子回顾一下将数据可视化的基本流程. 任务 用横向柱状图来直观显示以下数据: var data = [10,15,23,78,57,29,3 ...

  4. Roslyn 入门：使用 Visual Studio 的语法可视化窗格查看和了解代码的语法树

    使用 Visual Studio 提供的 Syntax Visualizer,我们可以实时看到一个代码文件中的语法树.这对我们基于 Roslyn 编写静态分析和修改工具非常有帮助.本文将介绍如何安装它 ...

  5. 数据可视化入门之show me the numbers

           数据的可视化一直是自己瞎玩着学,近来想系统的学数据可视化的东西,于是搜索资料时看到有人推荐<show me the numbers>作为入门. 由于搜不到具体的书籍内容,只能 ...

  6. 数据可视化-svg入门基础（二）

    接上一篇:数据可视化-svg入门基础(一),基础一主要是介绍了svg概念,元素样式设置等. svg是(scalable vector graphic)伸缩矢量图像. 一.目录 (1)图形元素 (2)文 ...

  7. Seaborn数据可视化入门

    在本节学习中,我们使用Seaborn作为数据可视化的入门工具 Seaborn的官方网址如下:http://seaborn.pydata.org 一:definition Seaborn is a Py ...

  8. Matplotlib数据可视化（1）：入门介绍

      1 matplot入门指南¶ matplotlib是Python科学计算中使用最多的一个可视化库,功能丰富,提供了非常多的可视化方案,基本能够满足各种场景下的数据可视化需求.但功能丰富从另一方面来 ...

  9. Keras入门（六）模型训练实时可视化

      在北京做某个项目的时候,客户要求能够对数据进行训练.预测,同时能导出模型,还有在页面上显示训练的进度.前面的几个要求都不难实现,但在页面上显示训练进度当时笔者并没有实现.   本文将会分享如何在K ...

随机推荐

  1. 【2018寒假集训 Day2】【动态规划】钱币兑换（exchange）（自己翻译的2333）

    钱币兑换(exchange) 问题描述: Dave偶然获得了未来几天的美元(dollars)与马克(marks)之间的兑换率.例如Dave开始有100marks,请编写个程序帮助Dave找出最好的买卖 ...

  2. 个人收藏--未整理—C# http/https 上传下载文件

    c# HTTP/HTTPS 文件上传. 分类: .net 2015-02-03 08:36 541人阅读 评论(0) 收藏 举报 方法主体 [csharp] view plaincopy public ...

  3. centos 7 MysSQL 5.6.39 源码安装

    MySQL 5.6.39 二进制安装 CentOS 7 将默认数据库MySQL替换成了Mariadb. 这里会从系统的环境准备开始一步一步安装. 环境准备 系统版本 内核版本 IP地址 Centos ...

  4. Windows的定时任务(Schedule Task)设置

    一.设置 1 点击“开始” 2 点击“控制面板” 3 双击“任务计划” 4 双击“添加任务计划” 5 到了“任务计划向导”界面,点击“下一步” 6 点击“浏览”选择需要定时运行的程序(exe文件,ba ...

  5. PTA 1139 1138 1137 1136

    PAT 1139 1138 1137 1136 一个月不写题,有点生疏..脑子跟不上手速,还可以啦,反正今天很开心. PAT 1139 First Contact 18/30 找个时间再修bug 23 ...

  6. 机器学习笔记（六） ---- 支持向量机（SVM）

    支持向量机(SVM)可以说是一个完全由数学理论和公式进行应用的一种机器学习算法,在小批量数据分类上准确度高.性能好,在二分类问题上有广泛的应用. 同样是二分类算法,支持向量机和逻辑回归有很多相似性,都 ...

  7. 深入比特币原理（四）——锁定脚本(locking script)与解锁脚本(unlocking script)

    通常比特币都是以虚拟货币的概念出现在大众眼前,实际上比特币是第一个真正的区块链"平台",利用它去中心化.不可篡改.可追溯等特点不光可以实现多种交易模式(如点对点交易.多重签名交易等 ...

  8. shell 循环读取文件及字符串转为数组

    文件/etc/hdocker_config内容如下: 30.72.63.94 30.72.63.95 30.72.63.96 30.72.63.97 /tmp/lasclocker.tar maste ...

  9. php上传下载文件

    之前做一个上传下载的项目,发现网上的和自己需求不是很一样,翻阅了下书籍和整理了下网上的一些代码.做了一个上传下载的demo,上传通过php本身的uploadfile函数,并返回以时间戳命名的文件名后, ...

  10. luogu P2507 [SCOI2008]配对

    题目描述 你有 n 个整数Ai和n 个整数Bi.你需要把它们配对,即每个Ai恰好对应一个Bp[i].要求所有配对的整数差的绝对值之和尽量小,但不允许两个相同的数配对.例如A={5,6,8},B={5, ...