中国地图填色问题Python API（动态）
基于中国地图的填色问题动态API
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
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。
