1import cartopy.crs as ccrs 2import matplotlib.pyplot as plt 3from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER 4import matplotlib.ticker as mticker 5import numpy as np 6import pandas as pd 7import requests 8from bs4 import BeautifulSoup 9 10def get_catalog(): 11 url = 'http://news.ceic.ac.cn/index.html' 12 web_data = requests.get(url) 13 web_data.encoding = web_data.apparent_encoding 14 web_data = web_data.text 15 f = open('earthquake.csv', 'w') 16 Date = [] 17 Latitude = [] 18 Longitude = [] 19 Magnitude = [] 20 soup = BeautifulSoup(web_data, 'lxml') 21 22 rows = soup.find_all('tr') 23 for i in rows: 24 cols = i.find_all('td') 25 if len(cols) != 0: 26 Magnitude.append(cols[0].text) 27 Date.append(cols[1].text.split()[0]) 28 Latitude.append(cols[2].text) 29 Longitude.append(cols[3].text) 30 f.write('Date,Latitude,Longitude,Magnitude\n') 31 for i in range(len(Date)): 32 line = Date[i] + ',' + Latitude[i] + ',' + Longitude[i] + ',' + Magnitude[i] 33 print(Date[i] + ',' + Latitude[i] + ',' + Longitude[i] + ',' + Magnitude[i]) 34 f.write(line + '\n') 35 f.close() 36 37def plot_map(): 38 plt.figure(figsize=(12, 8)) 39 plt.rcParams['font.sans-serif'] = 'FangSong' # 设置中文字体为仿宋 40 plt.rcParams['axes.unicode_minus'] = False # 正常显示坐标轴上的铀号 41 ax = plt.axes(projection=ccrs.PlateCarree()) 42 ax.coastlines() 43 ax.stock_img() # 将参考底图图像添加到地图,如果没有这条命令，底图是没有背景色的 44 # 画经纬度网格 45 gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, linewidth=1.2, color='k', alpha=0.3, linestyle='--') 46 gl.xlabels_top = False # 关闭顶端的经纬度标签 47 gl.ylabels_right = False # 关闭右侧的经纬度标签 48 gl.xformatter = LONGITUDE_FORMATTER # x轴设为经度的格式 49 gl.yformatter = LATITUDE_FORMATTER # y轴设为纬度的格式 50 51 #设置经纬度网格的间隔 52 gl.xlocator = mticker.FixedLocator(np.arange(-180, 180, 30)) 53 gl.ylocator = mticker.FixedLocator(np.arange(-90, 90, 30)) 54 # 设置显示范围 55 ax.set_extent([-180, 180, -90, 90],crs=ccrs.PlateCarree()) 56 #设置坐标标签 57 ax.set_xticks(list(range(-180,180,60)), crs=ccrs.PlateCarree()) 58 ax.set_yticks(list(range(-90,90,30)), crs=ccrs.PlateCarree()) 59 plt.xticks(fontsize = 20) 60 plt.yticks(fontsize = 20) 61 62 # 填加大地测量座标系下的线条 63 # ny_lon, ny_lat = -75, 43 64 # delhi_lon, delhi_lat = 77.23, 28.61 65 # plt.plot([ny_lon, delhi_lon], [ny_lat, delhi_lat], 66 # color='blue', linewidth=2, marker='o', 67 # transform=ccrs.Geodetic(), 68 # ) 69 # 填加直角座标系下的线条 70 # plt.plot([ny_lon, delhi_lon], [ny_lat, delhi_lat], 71 # color='red', linestyle='--', 72 # transform=ccrs.PlateCarree(), 73 # ) 74 # 填加文字 75 # plt.text(ny_lon - 3, ny_lat - 12, '纽约', 76 # horizontalalignment='right', color = 'red', 77 # transform=ccrs.Geodetic()) 78 # plt.text(delhi_lon + 3, delhi_lat - 12, 'Delhi', 79 # horizontalalignment='left', color = 'red', 80 # transform=ccrs.Geodetic()) 81 82 # 画震中分布 83 data = pd.read_csv('earthquake.csv') 84 scatter = ax.scatter(data.Longitude, data.Latitude, 85 s= (0.2* 2 ** data.Magnitude)**2, 86 c='red', alpha=0.8, 87 # c=data.depth / data.depth.max(), alpha=0.8, 88 transform=ccrs.PlateCarree()) 89 # 填加图例 90 kw = dict(prop="sizes", num=5, color='red', fmt="M {x:.1f}", 91 func=lambda s: np.log2(np.sqrt(s)/0.2)) 92 legend2 = ax.legend(*scatter.legend_elements(**kw), 93 loc="lower left", title="Mag") 94 ax.add_artist(legend2) 95 96 plt.tight_layout() 97 plt.savefig('world.png',dpi = 600) 98 # plt.show() 99 100#################主程序################### 101get_catalog() 102plot_map()
