python的matplotlib的Basemap案例
作者：互联网
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
# city population in 2017
locations = {"Sydney":5131326,"Melbourne":4850740,
"Brisbane":2408223,"Adelaide":1333927,
"Perth":2043138,"Hobart":226884,
"Darwin":146612,"Canberra":410301}
# Latitude and Longitude in degrees
names = {"Sydney":(-33.86785,151.20732),"Melbourne":(-37.8142,144.96332),
"Brisbane":(-27.46794,153.02809),"Adelaide":(-34.92866,138.59863),
"Perth":(-31.95224,115.8614),"Hobart":(-42.87936,147.32941),
"Darwin":(-12.46113,130.84185),"Canberra":(-35.28346,149.12807)}
# setup mercator map projection
basemap = Basemap(projection="merc",
resolution="h",
area_thresh=0.1,
llcrnrlon=112,llcrnrlat=-45,
urcrnrlon=155,urcrnrlat=-8)
# draw several map elements
basemap.drawcoastlines(linewidth=0.6,linestyle="-",color="#b7cfe9",zorder=3)
basemap.drawrivers(linewidth=0.8,linestyle="-",color="#689CD2",zorder=2)
basemap.fillcontinents(color="#BF9E30",lake_color="#689CD2",zorder=1)
basemap.drawmapboundary(color="gray",fill_color="#689CD2")
basemap.drawmeridians(np.arange(0,360,15),color="#4e8bca",labels=[0,0,0,1],labelstyle="+/-")
basemap.drawparallels(np.arange(-90,90,15),color="#4e8bca",labels=[1,1,0,0],labelstyle="+/-")
# convert lon/lat (in degrees) to x/y map projection coordinates (in meters)
# longitude is transformed into x and latitude is transformed into y
names_values = []
names_keys = list(names.keys())
for i,name in enumerate(names_keys):
names_values.append(names[name])
lat_x,long_y = list(zip(*names_values))
x,y = basemap(long_y,lat_x)
# draw city markers and add text to markers
size_factor = 80.0
offset_factor = 21000
rotation = 30
max_population = max(locations.values())
for city_name,city_x,city_y in zip(names_keys,x,y):
size = (size_factor/max_population)*locations[city_name]
x_offset = offset_factor
y_offset = offset_factor
basemap.scatter(city_x,
city_y,
s=size,
facecolor="w",
edgecolors="r",
linewidths=2.0,
zorder=10)
plt.text(city_x+x_offset,city_y+y_offset,city_name)
# setup map title
font = dict(family="serif",fontsize=15,weight="bold")
plt.title("Australian Population of Capital City",**font)
plt.show()
import datetime
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap
# setup miller projection
basemap = Basemap(projection="mill",
resolution="h",
area_thresh=0.1,
llcrnrlon=-180,
llcrnrlat=-90,
urcrnrlon=180,
urcrnrlat=90)
# draw coastlines
basemap.drawcoastlines(linewidth=0.6,zorder=2)
# draw mapboundary
basemap.drawmapboundary(fill_color="aqua")
# fill continents with color "coral", and lake "aqua"
basemap.fillcontinents(color="coral",lake_color="aqua",zorder=1)
# draw meridians and parallels
basemap.drawmeridians(np.arange(-120,150,60),linewidth=0.6,labels=[0,0,0,1])
basemap.drawparallels(np.arange(-60,80,30),linewidth=0.6,labels=[1,0,0,0])
# shade the night areas, and use current time in UTC
date = datetime.datetime.utcnow()
basemap.nightshade(date)
# format title with date and time
content = "Shade dark regions of the map %s (UTC)"
dtFormat = "%d %b %Y %H:%M:%S"
stringTime = date.strftime(dtFormat)
plt.title(content % stringTime,fontsize=15)
plt.show()
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap
class MapDisVisualization(Basemap):
# get city names
def getCityNames(self,names):
namesKeys = list(names.keys())
return namesKeys
# define distance between cityA and cityB
def citiesDistance(self,x,y):
d = np.power(np.power(x[0]-y[0],2)+np.power(x[1]-y[1],2),0.5)
distance = round(d,4)
return distance
# compute distance between target city and every other city
def centerCityDistance(self,city,names):
distanceDict = {}
namesKeys = self.getCityNames(names)
for i,name in enumerate(namesKeys):
if name != city:
distanceDict[name] = self.citiesDistance(names[city],names[name])
return distanceDict
# compute line width and line color
def setcolorandwidth(self,city,names):
size_factor = 2.0
namesKeys = self.getCityNames(names)
distanceDict = self.centerCityDistance(city,names)
distanceList = list(distanceDict.values())
maxDistance = max(distanceList)
for i,name in enumerate(namesKeys):
if name != city:
self.drawgreatcircle(names[city][1],names[city][0],
names[name][1],names[name][0],
linewidth=size_factor,
color=mpl.cm.Blues(distanceDict[name]/float(maxDistance)))
# visualize city distance on the map
def showmap(self,city,names):
self.setcolorandwidth(city,names)
namesKeys = self.getCityNames(names)
number = len(namesKeys)
titleContent = "a map of visualizing distance between %s and every other city (%d cities)"
font = dict(family="serif",fontsize=15,weight="black")
plt.title(titleContent % (city,(number-1)),fontdict=font)
plt.show()
def main(projection,city):
# get a Basemap instance
m = MapDisVisualization(projection=projection,
resolution="h",
area_thresh=0.1,
llcrnrlon=112,llcrnrlat=-50,
urcrnrlon=180,urcrnrlat=-8)
# draw several elements on the map
m.drawcoastlines(linewidth=0.6,linestyle="-",zorder=2)
m.fillcontinents(alpha=0.5,zorder=1)
m.drawmapboundary(color="gray")
m.drawmeridians(np.arange(100,180,15),linewidth=0.4,labels=[0,0,0,1])
m.drawparallels(np.arange(-90,0,15),linewidth=0.4,labels=[1,0,0,0])
# Latitude and Longitude in degrees
names = {"Sydney":(-33.86785,151.20732),"Wellington":(-41.28664,174.77557),
"Brisbane":(-27.46794,153.02809),"Adelaide":(-34.92866,138.59863),
"Perth":(-31.95224,115.8614),"Auckland":(-36.86667,174.76667),
"Darwin":(-12.46113,130.84185),"Canberra":(-35.28346,149.12807)}
#show the distance between Sydney and every other city
m.showmap(city,names)
if __name__ == "__main__":
# use projection mercator and choose Sydney
main("merc","Sydney")
标签：city,name,python,Basemap,self,matplotlib,color,names,basemap 来源： https://blog.csdn.net/weixin_43118073/article/details/113447031