Linux Mint安装matplotlib basemap
测试环境：
（1）Ubuntu18.04
（2）Python3.6
（3）basemap-1.2.0.rel
下载basemap
下载地址：
https://github.com/matplotlib/basemap/releases/
下载完成后解压，控制台进入到解压后 目录
安装依赖库
直接使用python setup.py install 安装会提示缺少geos库,为了方便把相关库都安装上.以下命令在终端都是以超级用户运行
sudo apt-get install libgeos*
最好把gdal库也安装上
sudo apt-get install libgdal*
安装python依赖库
sudo apt-get install python-dev
sudo apt-get install python3-dev
checkinstall安装basemap
首先安装checkinstall
sudo apt-get install checkinstall
然后进入到解压后的目录
sudo checkinstall python setup.py install
或者
sudo checkinstall python3 setup.py installl
使用checkinstall安装的时候会有一些提示,直接enter跳过即可,最后生成的.deb包,生成后自动安装.
如果不出意外的话便可成功安装了,如果还出现其他错误就根据错误贴到网上自己查找一下.
参考链接:https://answers.launchpad.net/ubuntu/+source/matplotlib/+question/55943
最后分享一段代码,用来生成过去一个月强度大于4.5的地震发生地点.
# -----------------------------------------------------------------------------
# Copyright (c) 2014, Nicolas P. Rougier. All Rights Reserved.
# Distributed under the (new) BSD License.
# -----------------------------------------------------------------------------
# Based on : https://peak5390.wordpress.com
# -> 2012/12/08/matplotlib-basemap-tutorial-plotting-global-earthquake-activity/
# -----------------------------------------------------------------------------
import urllib
import numpy as np
import matplotlib
matplotlib.rcParams['toolbar'] = 'None'
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from matplotlib.animation import FuncAnimation
# Open the earthquake data
# -------------------------
# -> 网址是：http://earthquake.usgs.gov/earthquakes/feed/v1.0/csv.php
feed = "http://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/"
# Significant earthquakes in the past 30 days 过去30天发生的强大地震
# url = urllib.urlopen(feed + "significant_month.csv")
# Earthquakes of magnitude > 4.5 in the past 30 days 过去30天发生的强度大于4.5的地震
url = urllib.request.urlopen(feed + "4.5_month.csv") #Python3.5使用这个
# url = urllib.urlopen(feed + "4.5_month.csv") #Python2.7使用这个
# Earthquakes of magnitude > 2.5 in the past 30 days 过去30天发生的强度大于2.5的地震
# url = urllib.urlopen(feed + "2.5_month.csv")
# Earthquakes of magnitude > 1.0 in the past 30 days 过去30天发生的强度大于1的地震
# url = urllib.request.urlopen(feed + "1.0_month.csv")
# Earthquakes of all magnitude in the past 30 days 过去30天发生的全部地震
# url = urllib.request.urlopen(feed + "all_month.csv")
# Set earthquake data 设置地震数据
data = url.read()
data = data.split(b'\n')[+1:-1]
E = np.zeros(len(data), dtype=[('position', float, 2),
('magnitude', float, 1)])
for i in range(len(data)):
row = data[i].split(b',')
E['position'][i] = np.float(row[2]),np.float(row[1])
E['magnitude'][i] = np.float(row[4])
fig = plt.figure(figsize=(14,10))
ax = plt.subplot(1,1,1)
P = np.zeros(50, dtype=[('position', float, 2),
('size', float, 1),
('growth', float, 1),
('color', float, 4)])
# Basemap projection
width = 28000000; lon_0 = -105; lat_0 = 40
map = Basemap(projection='moll',lon_0=0,resolution='c') #设置地图样式
map.drawcoastlines(color='0.50', linewidth=0.25)
map.fillcontinents(color='0.95')
scat = ax.scatter(P['position'][:,0], P['position'][:,1], P['size'], lw=0.5,
edgecolors = P['color'], facecolors='None', zorder=10)
def update(frame):
current = frame % len(E)
i = frame % len(P)
P['color'][:,3] = np.maximum(0, P['color'][:,3] - 1.0/len(P))
P['size'] += P['growth']
magnitude = E['magnitude'][current]
P['position'][i] = map(*E['position'][current])
P['size'][i] = 5
P['growth'][i]= np.exp(magnitude) * 0.1
if magnitude < 6:
P['color'][i] = 0,0,1,1
else:
P['color'][i] = 1,0,0,1
scat.set_edgecolors(P['color'])
scat.set_facecolors(P['color']*(1,1,1,0.25))
scat.set_sizes(P['size'])
scat.set_offsets(P['position'])
plt.title("Earthquakes > 4.5 in the last 30 days")
animation = FuncAnimation(fig, update, interval=10)
plt.show()
