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基于随机定位的地图信息获取方式

基于随机定位的地图信息获取方式

基本定义

场景

一个应用要用到地图,地图拖动时,要填补新的版图上的地理信息

目的

快速获取屏幕内需要的地图信息,不获取多余无用的地图信息

功能要点

1.确定地图范围,获取的信息不超出显示屏过多

(比如屏幕地图查询100平方米的信息,服务返回的信息不能超过130平米的地图信息)

2.动态快速获取信息,通过定位快速获取周围地理信息,第一时间从缓存获取或者数据库获取,且不要有复杂查询和大量查询。

绝对定位:坐标,传人任何一个点,都能通过角色定位知道这个点在哪,以及其他延伸计算

通过地图的中心定位,优先快速确定要获取那些位置的地理信息,快速获取对应的图块。

3.根据维度调整信息获取范围和格式

粒度:通过两个点确定查询信息的范围,同时确定粒度(地图缩放级别)

(4).原先有的信息短时间不重复获取

(拖动地图导致50%地图位置换了,还有50%地图不变,不用再次请求)

确定地图范围

通过两个点,或者中心定位+范围,要快速得出在范围内地图信息

地图切割

分块

将地图切割均等大小

块级别

地图显示可以是世界地图,也可以是城镇地图,缩放差距很大,地图块也要级别表示具体缩放场景

坐标

一个绝对坐标,作为参考

每一个切割的分块地图都有一个坐标,坐标唯一

确定分块坐标唯一依据:分块级别,经纬度,

分块地图表示方法

获取范围内的分块地图

矩形对角线两个点,可以确定范围

入参:坐标1,坐标2,粒度(地图缩放级别)

返回:分块地图坐标

将问题细分化,可以分解为,先求所有图块的x坐标,再求y坐标,然后数组相乘,或多所有图块的二维坐标(x,y)

输入:点A,点B,地图扩展系数

返回:两个点覆盖的范围

Fun(coordinate c1,coordinate c2,granularity g) return Array(Map-Coordinate)

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	public static DecimalFormat df = new DecimalFormat("#0.0000");
	/**
	 * -求两个点包含图块坐标范围
	 * @param x1 点A
	 * @param x2 点B
	 * @param granularity 地图扩展系数
	 * @return A,B两点包含的图块的一维坐标
	 */
	public static double[] range_position(double x1,double x2,double granularity) {
		
		double minX = Math.min(x1, x2);
		double maxX = Math.max(x1, x2);
		
		//左边界
		double left = Math.floor(minX/granularity) * granularity;
		//右边界
		double right = Math.ceil(maxX/granularity) * granularity;
		//相差
		double difference = right - left;
		
		double d_pointNumber = difference/granularity;
		
		//一维坐标数
		int pointNumber = (int) (int)Math.ceil(Double.valueOf(df.format(d_pointNumber)));
		
		double[] points = new double[pointNumber];
		points[0] = Double.valueOf(df.format(left + granularity/2));
		for(int i = 1; i<pointNumber; i++) {
			points[i] = Double.valueOf(df.format(points[i-1] + granularity));
		}
		return points;
	}

调用上面方法两次,分别传入 x坐标 和 y坐标,求出(x,y) 集合,得到所有图块二维坐标。

快速获取图块信息

地图信息要快速获取,上面返回坐标,通过坐标扩展级别能确定唯一性,因此可以通过唯一key对应一个图块

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//图块唯一key
//参数 x y 坐标 扩展系数  图块边长
public static String getMpk(double x,double y, int gly,double mapLength) {
		return MapBlock.head + gly + "-"+ df.format(mapLength) + "(" +x + ","+ y + ")";
	}

首先应该是初始化的时候,将地图分块信息读取,放入缓存,或者数据库

如果传入两个点,就能获得对应的图块唯一key,直接从缓存获取或者数据库查询

code-动态获取屏幕内地图

传入矩形对角线两个坐标,返回矩形内所有图块

实现类:

MapRangePosition

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package net.narule.algorithm.map;

import java.text.DecimalFormat;
import java.util.ArrayList;
import java.util.List;

/**
 * -地图范围定位
 * @author Narule
 *
 */
public class MapRangePosition {

	/**
	 * -给定一个矩形,返回矩形接触的区域
	 * @param c1
	 * @param c2
	 * @return
	 */
	public static List<MapBlock> getRangeMapBlock(Coordinate c1,Coordinate c2){
		//扩展系数
		int calculateGly = Granularity.calculateGly(c1, c2);
		//图块边长
		double mapSideLength = calculateGly * Granularity.unit_length;
		
		double z = c1.getZ();
		double[] range_position_x = range_position(c1.getX(),c2.getX(), mapSideLength);
		double[] range_position_y = range_position(c1.getY(),c2.getY(), mapSideLength);
		ArrayList<MapBlock> list = new ArrayList<>();
		for (double x : range_position_x) {
			for (double y : range_position_y) {
				Coordinate coordinate = new Coordinate(x,y,z);
				MapBlock mapBlock = new MapBlock(coordinate,getMpk(x, y, calculateGly, mapSideLength),calculateGly);
				list.add(mapBlock);
			}
		}
		return list;
	}
	
	public static String getMpk(Coordinate c,int gly,double mapLength) {
		return MapBlock.head + gly + "_"+ mapLength + "(" +c.getX() + ","+ c.getY() + ")";
	}
	
	public static String getMpk(double x,double y, int gly,double mapLength) {
		return MapBlock.head + gly + "-"+ df.format(mapLength) + "(" +x + ","+ y + ")";
	}
	
	public static DecimalFormat df = new DecimalFormat("#0.0000");
	
	/**
	 * -求两个点包含图块坐标范围
	 * @param x1 点A
	 * @param x2 点B
	 * @param granularity 地图扩展系数
	 * @return A,B两点包含的图块的一维坐标
	 */
	public static double[] range_position(double x1,double x2,double granularity) {
		
		double minX = Math.min(x1, x2);
		double maxX = Math.max(x1, x2);
		
		//左边界
		double left = Math.floor(minX/granularity) * granularity;
		//右边界
		double right = Math.ceil(maxX/granularity) * granularity;
		//相差
		double difference = right - left;
		
		double d_pointNumber = difference/granularity;
		
		//一维坐标数
		int pointNumber = (int) (int)Math.ceil(Double.valueOf(df.format(d_pointNumber)));
		
		double[] points = new double[pointNumber];
		points[0] = Double.valueOf(df.format(left + granularity/2));
		for(int i = 1; i<pointNumber; i++) {
			points[i] = Double.valueOf(df.format(points[i-1] + granularity));
		}
		return points;
	}
	
	
	public static void main(String[] args) {
		Coordinate A = new Coordinate(118.21,29.11,5);
		Coordinate B = new Coordinate(120.30,30.33,5);
        
		List<MapBlock> rangeMapBlock = getRangeMapBlock(A, B);
		System.out.println("坐标测试 A:" + A + " B:" + B);
		System.out.println("包含图块:");
		for (MapBlock mapBlock : rangeMapBlock) {
			System.out.println(mapBlock);
		}
		System.out.println("size" + rangeMapBlock.size());
		
        Coordinate CNA = new Coordinate(73.33,3.51,5);
		Coordinate CNB = new Coordinate(135.05,53.33,5);
        
		System.out.println("-----------------");
		System.out.println("-----------------");
		System.out.println("-----------------");
		List<MapBlock> chineseMapBlock = getRangeMapBlock(CNA,CNB);
		System.out.println("中国坐标 A:" + CNA + " B:" + CNB);
		System.out.println("包含图块:");
		for (MapBlock mapBlock : chineseMapBlock) {
			System.out.println(mapBlock);
		}
		System.out.println("size" + chineseMapBlock.size());
	}
}

测试结果

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坐标测试 A:(x,y,z):[118.21, 29.11, 5.0] B:(x,y,z):[120.3, 30.33, 5.0]
包含图块:
MapBlock [position=(x,y,z):[118.0, 29.2, 5.0], key=mpk-8000-0.8000(118.0,29.2), level=8000]
MapBlock [position=(x,y,z):[118.0, 30.0, 5.0], key=mpk-8000-0.8000(118.0,30.0), level=8000]
MapBlock [position=(x,y,z):[118.8, 29.2, 5.0], key=mpk-8000-0.8000(118.8,29.2), level=8000]
MapBlock [position=(x,y,z):[118.8, 30.0, 5.0], key=mpk-8000-0.8000(118.8,30.0), level=8000]
MapBlock [position=(x,y,z):[119.6, 29.2, 5.0], key=mpk-8000-0.8000(119.6,29.2), level=8000]
MapBlock [position=(x,y,z):[119.6, 30.0, 5.0], key=mpk-8000-0.8000(119.6,30.0), level=8000]
MapBlock [position=(x,y,z):[120.4, 29.2, 5.0], key=mpk-8000-0.8000(120.4,29.2), level=8000]
MapBlock [position=(x,y,z):[120.4, 30.0, 5.0], key=mpk-8000-0.8000(120.4,30.0), level=8000]
size8
-----------------
-----------------
-----------------
中国坐标 A:(x,y,z):[73.33, 3.51, 5.0] B:(x,y,z):[135.05, 53.33, 5.0]
包含图块:
MapBlock [position=(x,y,z):[88.0, 17.6, 5.0], key=mpk-352000-35.2000(88.0,17.6), level=352000]
MapBlock [position=(x,y,z):[88.0, 52.8, 5.0], key=mpk-352000-35.2000(88.0,52.8), level=352000]
MapBlock [position=(x,y,z):[123.2, 17.6, 5.0], key=mpk-352000-35.2000(123.2,17.6), level=352000]
MapBlock [position=(x,y,z):[123.2, 52.8, 5.0], key=mpk-352000-35.2000(123.2,52.8), level=352000]
size4

描述对象

Coordinate 坐标

表示在地图上的位置

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package net.narule.algorithm.map;

/**
 * -coordinate 定位对象
 * @author Narule
 *
 */
public class Coordinate {
	
	private double x;
	private double y;
	private double z;
	
	
	public Coordinate() {
		super();
	}
	public Coordinate(double x, double y, double z) {
		super();
		this.x = x;
		this.y = y;
		this.z = z;
	}
	public double getX() {
		return x;
	}
	public void setX(double x) {
		this.x = x;
	}
	public double getY() {
		return y;
	}
	public void setY(double y) {
		this.y = y;
	}
	public double getZ() {
		return z;
	}
	public void setZ(double z) {
		this.z = z;
	}
	@Override
	public String toString() {
		return "Coordinate [x=" + x + ", y=" + y + ", z=" + z + "]";
	}
	
}

Granularity 缩放系数

地图缩放大小,标尺

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package net.narule.algorithm.map;

/**
 * -granularity 粒度
 * @author Narule
 *
 */
public class Granularity {

	/**
	 * -缩放级别
	 */
	private static int gly;
	
	/**
	 * -最小单位
	 * 地球赤道40075千米
	 * 经纬度中 0.01有 1.1 千米
	 * 0.001 100m
	 * 0.0001 10m
	 * 10m
	 */
	public static final double unit_length = 0.0001;
	

	public static double unit_granularity = Math.sqrt(Math.pow(unit_length, 2)*2);

	/**
	 * -块图边长
	 */
	private static double mapSideLength;
	
	/**
	 * -计算缩放级别
	 * @param c1
	 * @param c2
	 * @return
	 */
	public static int calculateGly(Coordinate c1,Coordinate c2) {
		double x = Math.abs(c1.getX() - c2.getX());
		double y = Math.abs(c1.getY() - c2.getY());
		double minL = Math.min(x, y);
		
		gly =   (int) Math.ceil(
				minL/unit_granularity
				);
		if(gly <= 10)  gly = 10;
		else if(gly > 10 && gly < 100) gly = gly / 10 * 10;
		else if(gly > 100 && gly < 1000) gly = gly / 100 * 100;
		else if(gly > 1000) gly = gly / 1000 * 1000;
		return gly;
	}


	public static double getGly() {
		return gly;
	}

	public double getMapSideLength() {
		return mapSideLength;
	}
	
	
}

MapBlock 图块

将地图分割成更小的图块,每一块都包含坐标和缩放系数,通过坐标和缩放系数能确定唯一

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package net.narule.algorithm.map;

import java.io.Serializable;

/*
 * -地图块
 */
public class MapBlock implements Serializable{

	/**
	 * 
	 */
	private static final long serialVersionUID = 1L;

	public  static final String head = "mpk-";
	
	private Coordinate position;

	private String key;
	
	private int level;
	
	public MapBlock(Coordinate coordinate){
		this.position = coordinate;
	}
	
	public MapBlock(Coordinate coordinate,String key,int level){
		this.position = coordinate;
		this.key = key;
		this.level = level;
	}
	
	public Coordinate getPosition() {
		return position;
	}

	public void setPosition(Coordinate position) {
		this.position = position;
	}

	public String getKey() {
		return key;
	}

	public void setKey(String key) {
		this.key = key;
	}

	

	@Override
	public String toString() {
		return "MapBlock [position=" + position + ", key=" + key + ", level=" + level + "]";
	}

	public int getLevel() {
		return level;
	}

	public void setLevel(int level) {
		this.level = level;
	}
	
}

This post is licensed under CC BY 4.0 by the author.

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