python - 如何使用 Basemap (Python) 绘制美国 50 个州？

Question

我知道强大的包Basemap可用于绘制带有州界的美国 map 。我从 basemap 中改编了这个例子 GitHub用于绘制按各自人口密度着色的 48 个州的存储库:

现在我的问题是:是否有一种简单的方法可以将阿拉斯加和夏威夷添加到这张 map 并将它们放置在自定义位置，例如左下角？像这样:

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap as Basemap
from matplotlib.colors import rgb2hex
from matplotlib.patches import Polygon
# Lambert Conformal map of lower 48 states.
m = Basemap(llcrnrlon=-119,llcrnrlat=22,urcrnrlon=-64,urcrnrlat=49,
        projection='lcc',lat_1=33,lat_2=45,lon_0=-95)
# draw state boundaries.
# data from U.S Census Bureau
# http://www.census.gov/geo/www/cob/st2000.html
shp_info = m.readshapefile('st99_d00','states',drawbounds=True)
# population density by state from
# http://en.wikipedia.org/wiki/List_of_U.S._states_by_population_density
popdensity = {
'New Jersey':  438.00,
'Rhode Island':   387.35,
'Massachusetts':   312.68,
'Connecticut':    271.40,
'Maryland':   209.23,
'New York':    155.18,
'Delaware':    154.87,
'Florida':     114.43,
'Ohio':  107.05,
'Pennsylvania':  105.80,
'Illinois':    86.27,
'California':  83.85,
'Hawaii':  72.83,
'Virginia':    69.03,
'Michigan':    67.55,
'Indiana':    65.46,
'North Carolina':  63.80,
'Georgia':     54.59,
'Tennessee':   53.29,
'New Hampshire':   53.20,
'South Carolina':  51.45,
'Louisiana':   39.61,
'Kentucky':   39.28,
'Wisconsin':  38.13,
'Washington':  34.20,
'Alabama':     33.84,
'Missouri':    31.36,
'Texas':   30.75,
'West Virginia':   29.00,
'Vermont':     25.41,
'Minnesota':  23.86,
'Mississippi':   23.42,
'Iowa':  20.22,
'Arkansas':    19.82,
'Oklahoma':    19.40,
'Arizona':     17.43,
'Colorado':    16.01,
'Maine':  15.95,
'Oregon':  13.76,
'Kansas':  12.69,
'Utah':  10.50,
'Nebraska':    8.60,
'Nevada':  7.03,
'Idaho':   6.04,
'New Mexico':  5.79,
'South Dakota':  3.84,
'North Dakota':  3.59,
'Montana':     2.39,
'Wyoming':      1.96,
'Alaska':     0.42}
# choose a color for each state based on population density.
colors={}
statenames=[]
cmap = plt.cm.hot # use 'hot' colormap
vmin = 0; vmax = 450 # set range.
for shapedict in m.states_info:
    statename = shapedict['NAME']
    # skip DC and Puerto Rico.
    if statename not in ['District of Columbia','Puerto Rico']:
        pop = popdensity[statename]
        # calling colormap with value between 0 and 1 returns
        # rgba value.  Invert color range (hot colors are high
        # population), take sqrt root to spread out colors more.
        colors[statename] = cmap(1.-np.sqrt((pop-vmin)/(vmax-vmin)))[:3]
    statenames.append(statename)
# cycle through state names, color each one.
ax = plt.gca() # get current axes instance
for nshape,seg in enumerate(m.states):
    # skip DC and Puerto Rico.
    if statenames[nshape] not in ['District of Columbia','Puerto Rico']:
        color = rgb2hex(colors[statenames[nshape]]) 
        poly = Polygon(seg,facecolor=color,edgecolor=color)
        ax.add_patch(poly)
plt.title('Filling State Polygons by Population Density')
plt.show()

Answer 1

对于任何感兴趣的人，我能够自己修复它。每个部分(阿拉斯加和夏威夷)的 (x,y) 坐标应该被翻译。在翻译之前，我还将阿拉斯加缩小到 35%。

第二个for循环应该修改如下:

for nshape,seg in enumerate(m.states):
    # skip DC and Puerto Rico.
    if statenames[nshape] not in ['Puerto Rico', 'District of Columbia']:
    # Offset Alaska and Hawaii to the lower-left corner. 
        if statenames[nshape] == 'Alaska':
        # Alaska is too big. Scale it down to 35% first, then transate it. 
            seg = list(map(lambda (x,y): (0.35*x + 1100000, 0.35*y-1300000), seg))
        if statenames[nshape] == 'Hawaii':
            seg = list(map(lambda (x,y): (x + 5100000, y-900000), seg))

        color = rgb2hex(colors[statenames[nshape]]) 
        poly = Polygon(seg,facecolor=color,edgecolor=color)
        ax.add_patch(poly)

这是新的美国 map (使用“Greens”颜色图)。