中国地图填色问题Python API（动态）

2024-07-16 08:37| 来源: 网络整理| 查看: 265

基于中国地图的填色问题动态API

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这几天课设需要使用到中国地图来做填色问题，在上了学校的人工智能原理和算法与数据结构两门课后有感而发，于是用里面的一些知识做了这么一个动态版的中国地图API。

主要思路：

使用一个邻接表实现的无向图数据结构作为中国地图，然后使用一个平行的数组来表示结点的颜色。

代码： #Elwin import time import matplotlib.pyplot as plt import numpy as np import cv2 class ChinaMap(): """China map dynamic visualization class""" def __init__(self): print('[INFO] Try to get China map data...') _start = time.time() _file = requests.get("https://s3.ax1x.com/2020/12/30/rqxLR0.jpg") _img = cv2.imdecode(np.frombuffer(_file.content, np.uint8), 1) self.img = cv2.cvtColor(_img,cv2.COLOR_BGR2GRAY) print('[INFO] OK! Time: %.3f s' % (time.time() - _start)) del _start,_img self.nameList = np.array(["北京市","天津市","上海市","重庆市","河北省","山西省","辽宁省","吉林省","黑龙江省", "江苏省","浙江省","安徽省","福建省","江西省","山东省","河南省","湖北省","湖南省", "广东省","海南省","四川省","贵州省","云南省","陕西省","甘肃省","青海省","台湾省", "内蒙古自治区","广西壮族自治区","西藏自治区","宁夏回族自治区","新疆维吾尔自治区", "香港特别行政区","澳门特别行政区"]) self.locList = np.array([[3277,1373],[3340,1444],[3732,2164],[2547,2378],[3155,1560],[3011,1586], [3748,1146],[3845,929],[3909,746],[3519,2105],[3637,2264],[3401,2135], [3506,2622],[3312,2443],[3338,1684],[3100,1881],[3170,2277],[3073,2504], [3115,2977],[2862,3273],[2356,2257],[2557,2658],[2210,2783],[2741,1930], [2367,1750],[2212,1680],[3808,2747],[2937,1300],[2686,3100],[1308,2229], [2558,1529],[1325,855],[3198,3060],[3136,3062]]) self.adjList = [[1,4], [0,4,14], [9,10], [20,23,16,17,21], [0,1,27,5,15,14,6], [4,27,23,15], [7,27,4], [8,27,6], [27,7], [14,11,10,2], [2,9,11,13,12,26], [9,14,15,16,13,10], [10,13,18,26], [10,11,16,17,18,12], [4,15,11,9,1], [14,4,5,23,16,11], [15,23,3,17,13,11], [16,3,21,28,18,13], [12,13,17,28,19,32,33], [18,28,33], [24,25,29,22,21,3,23], [3,20,22,28,17], [29,20,21,28], [27,30,24,20,3,16,15,5], [27,31,25,20,23,30], [24,31,29,20], [12,10], [31,24,30,23,5,4,6,7,8], [17,21,22,18,19], [31,25,20,22], [27,24,23], [24,25,29,27], [18,33], [18,32,19]] self.colorList = np.array([0 for index in range(len(self.nameList))]) self.color = ["dimgrey","red","orange","#32CD32","#1E90FF"] def showMap(self): """Show China map separately""" plt.axis(False) plt.imshow(self.img,cmap='gray') plt.show() def _getLocation(self,provinceIndex): """Get the location information of the province""" x,y = self.locList[provinceIndex] return x,y def changeColor(self,provinceIndex,color): self.colorList[provinceIndex] = color def getColor(self,provinceIndex): return self.colorList[provinceIndex] def getProvinceName(self,index): return self.nameList[index] def draw(self,time=10,showEdge = True,savePath = None): """Draw the next frame""" plt.cla() plt.ion() self._imshow(showEdge,savePath) plt.plot() plt.pause(time) plt.ioff() def _imshow(self,showEdge = True,savePath = None): """Display the map of China and its graphic model""" plt.axis(False) fig = plt.imshow(self.img,cmap='gray') fig.axes.get_xaxis().set_visible(False) fig.axes.get_yaxis().set_visible(False) _colorList = [self.color[i] for i in self.colorList] for provinceIndex in range(len(self.locList)): x,y = self._getLocation(provinceIndex) plt.scatter(x,y,c = _colorList[provinceIndex],s = 100) if showEdge: for nebProvince in self.adjList[provinceIndex]: nebX,nebY = self._getLocation(nebProvince) plt.plot((x,nebX),(y,nebY),c = _colorList[nebProvince]) if savePath: plt.savefig(savePath, bbox_inches='tight', pad_inches = 0) def reload(self): self.colorList = np.array([0 for index in range(len(self.nameList))]) plt.figure(figsize=(6,6)) print('[INFO] Successfully reload the Map!') def __len__(self): return len(self.nameList) def adjacency(self,provinceIndex): return self.adjList[provinceIndex] def stop(self): """Stop painting""" plt.show() 使用方式： cnMap = ChinaMap() #Initialization print(cnMap.getProvinceName(0)) for i in range(1,20,3): cnMap.changeColor(i,1) cnMap.draw() cnMap.stop() [INFO] Try to get China map data... [INFO] OK! Time: 0.177 s 北京市

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最后放一个使用该API做的一个简单算法可视化~ 这个可视化用的是一种变相的启发式搜索算法来实现的，能够适应在任意形状的无向图填色问题之中。在这里插入图片描述

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