如何覆蓋matplotlib中的shapefile

Question

在matplotlib中如何覆蓋圖中外部右上角位置所示的shapefile（文件夾中可用）。

Answer 1

通過banderkat引用的代碼：

import matplotlib.pyplot as plt 
import Image 
import numpy as np 

im = Image.open('Jbc4j.jpg') 
width = im.size[0] 
height = im.size[1] 

# We need a float array between 0-1, rather than 
# a uint8 array between 0-255 
im = np.array(im).astype(np.float)/255 

a = np.random.randint(0,100,100) 
b = range(100) 
fig = plt.figure(1,figsize=(5, 7), dpi=80, facecolor='w') 
ax = fig.add_subplot(111) 
ax.scatter(a,b) 
fig.canvas.draw() 

# With newer (1.0) versions of matplotlib, you can 
# use the "zorder" kwarg to make the image overlay 
# the plot, rather than hide behind it... (e.g. zorder=10) 
fig.figimage(im, fig.bbox.xmax - width, fig.bbox.ymax - height, zorder=0) 

# (Saving with the same dpi as the screen default to 
# avoid displacing the logo image) 
fig.savefig('temp.png', dpi=80) 

plt.show() 

產生以下結果（成像裁剪以節省空間）。

改變zorder=1將放置在上面的圖像。

其他有用的參考資料：

• How to change background color for scatter plot in matplotlib
• How do you change the size of figures drawn with matplotlib?
• Python/Matplotlib - Change the relative size of a subplot
• In Matplotlib, what does the argument mean in fig.add_subplot(111)?
• Customizing Location of Subplot Using GridSpec

Answer 2

您可以使用底圖工具包加載和繪製shapefile。在這裏，我將ShapeFile繪製在單獨的座標軸中，並使用'subplot2grid'將其對齊到其他座標軸的右上角。

import numpy as np 
import matplotlib.pyplot as plt 
from mpl_toolkits.basemap import Basemap 
import matplotlib.gridspec as gridspec 


def plotShapeFile(): 
    # Lambert Conformal Conic map. 
    m = Basemap(llcrnrlon=-100.,llcrnrlat=0.,urcrnrlon=-20.,urcrnrlat=57., 
       projection='lcc',lat_1=20.,lat_2=40.,lon_0=-60., 
       resolution ='l',area_thresh=1000.) 
    # read shapefile. 
    shp_info = m.readshapefile('C:/basemap-1.0.6/basemap-1.0.6/examples/huralll020','hurrtracks',drawbounds=False) 
    # find names of storms that reached Cat 4. 
    names = [] 
    for shapedict in m.hurrtracks_info: 
     cat = shapedict['CATEGORY'] 
     name = shapedict['NAME'] 
     if cat in ['H4','H5'] and name not in names: 
      # only use named storms. 
      if name != 'NOT NAMED': names.append(name) 

    # plot tracks of those storms. 
    for shapedict,shape in zip(m.hurrtracks_info,m.hurrtracks): 
     name = shapedict['NAME'] 
     cat = shapedict['CATEGORY'] 
     if name in names: 
      xx,yy = zip(*shape) 
      # show part of track where storm > Cat 4 as thick red. 
      if cat in ['H4','H5']: 
       m.plot(xx,yy,linewidth=1.5,color='r') 
      elif cat in ['H1','H2','H3']: 
       m.plot(xx,yy,color='k') 

    # draw coastlines, meridians and parallels. 
    m.drawcoastlines() 
    m.drawcountries() 
    m.drawmapboundary(fill_color='#99ffff') 
    m.fillcontinents(color='#cc9966',lake_color='#99ffff') 
    m.drawparallels(np.arange(10,70,20),labels=[1,1,0,0]) 
    m.drawmeridians(np.arange(-100,0,20),labels=[0,0,0,1]) 




if __name__ == '__main__': 
    fig=plt.figure() 
    plt.subplots_adjust(wspace=0.001, hspace=0.001) 

    ax1=plt.subplot2grid((5,5), (0,0), colspan=4, rowspan=4) 
    labels = 'Frogs', 'Hogs', 'Dogs', 'Logs' 
    fracs = [15,30,45, 10] 
    explode=(0, 0.05, 0, 0) 
    p1,t1,at1 = plt.pie(fracs, explode=explode, labels=labels, autopct='%1.1f%%', shadow=True) 
    plt.title('Raining Hogs and Dogs', bbox={'facecolor':'0.8', 'pad':5}) 

    ax2=plt.subplot2grid((5,5), (0,4), colspan=1, rowspan=1) 
    #draw shapeFile on the current active axes, i.e. ax2 
    plotShapeFile() 

    plt.tight_layout() 
    plt.show() 

下面是鏈接引用我用：

http://sourceforge.net/projects/matplotlib/files/matplotlib-toolkits/basemap-1.0.6/ http://matplotlib.org/basemap/users/examples.html

輸出：