python - 绘制由散点数据决定颜色的Shapefile

Question

我的问题

用 shapefile 绘制热图

1.简介

• 一堆shapefile代表行政边界
• 一个 pandas.Dataframe 包含一些具有(经度，纬度，值)的点

代码在这里:

 map = Basemap(llcrnrlon=xc1,llcrnrlat=yc1,urcrnrlon=xc2,urcrnrlat=yc2)
 ##Assuming "shape.shp" is my shapefile
 map.readshapefile('./shape','shape',zorder =1,)
 patches=[]
 cs=plt.cm.Greens(np.arange(18)/18.)
 for info, shape in zip(map.shape_info, map.shape):
     x,y=zip(*shape)
     patches.append( Polygon(np.array(shape), True) )  # facecolor= '#6582B3'
 ax.add_collection(PatchCollection(patches, facecolor= cs,edgecolor='none',     
                   linewidths=1.5, zorder=2))

 ## scatter the point, assuming "pt" is the Dataframe
 pt_lat = pt.lat.as_matrix()
 pt_lon   = power.lon.as_matrix()
 plt.scatter(pt_lon,pt_lat,marker='o',s=50,lw= 0,zorder = 3, alpha = 0.75)

图片在这里:

http://i11.tietuku.com/9785abb6097b7c0e.png

2。我的目标

在上图中，每个shapefile的颜色都是基于预定义的colormap。

• Plotting Each area (In my case, 18 shapefile) with the color corresponding to the sum of pt.values within.
• In other words, the inner point data decide the shapefile's color

添加--2015-01-11

感谢@MaxNoe 的回答。

学习了你的代码，但还是有问题。
这是我的代码和图片:

 fig = plt.figure(figsize =(8,6))
 ax = plt.subplot()
 map = Basemap(llcrnrlon=xc1,llcrnrlat=yc1,urcrnrlon=xc2,urcrnrlat=yc2) 
 map.readshapefile('./shape','shape')

 patches=[]
 for info, shape in zip(map.shape_info, map.shape):
     x,y=zip(*shape)
 patches.append(Polygon(np.array(shape), True) )

 xx = pt.lon.iloc[:].as_matrix()
 yy = pt.lat.iloc[:].as_matrix()
 value = pt.value.iloc[:].as_matrix()

 sh = (len(xx),2)
 position = np.zeros(len(xx)*2).reshape(*sh)
 for i in range(0,len(xx),1):
     position[i] = np.array([xx[i],yy[i]])

 poly_values = []
 for patch in patches:
     mask = np.array([patch.contains_point(xy) for xy in position])
     poly_values.append(value[mask].sum())

 coll = PatchCollection(patches, cmap = 'Greens')
 coll.set_array(np.array(poly_values))
 ax.add_collection(coll)
 plt.colorbar(coll,label = "polygon")

 point_plot = plt.scatter(xx,yy,marker='o',s=80,lw= 0,zorder = 3, c = "r",alpha = 0.75)

 ax.set_frame_on(False)
 divider = make_axes_locatable(ax)
 cax = divider.append_axes("right", size="4%", pad=0.1)
 cbar = plt.colorbar(coll,label = "polygon",cax= cax)

http://i4.tietuku.com/9a7b0cbc16f2e0b0.png

• It seems like the color for polygon[i] isn't according to the poly_value[i]
• I think the problem is coll.set_array doesn't work.
• Otherwise, I have checked each polygon and the scatter point value within, the poly_value[i] and the actual condition is not match(bigger than reality). I think the I may use value.mask wrong.

Answer 1

• 您可以使用 Polygon.contains_point 检查点是否在其中。

• 我使用此函数创建一个 bool 掩码来寻址该多边形内的点，并使用 .sum() 获取此多边形的值。

• 然后我使用 PatchCollection.set_array 设置值。

这是代码(没有 basemap ，因为我没有形状文件):

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
from matplotlib.collections import PatchCollection

# some random numbers for demonstration
data = np.random.normal(0, 1, (100, 2))
value = np.random.normal(0, 1, 100)

polygons = [
    Polygon([(0, 0), (0, 3), (-3, 3), (-3, 0)], closed=True),
    Polygon([(0, 0), (0, -3), (-3, -3), (-3, 0)], closed=True),
    Polygon([(0, 0), (0, 3), (3, 3), (3, 0)], closed=True),
    Polygon([(0, 0), (0, -3), (3, -3), (3, 0)], closed=True),
]


poly_values = []
for poly in polygons:
    mask = np.array([poly.contains_point(xy) for xy in data])
    poly_values.append(value[mask].sum())


coll = PatchCollection(polygons, cmap='magma')
coll.set_array(np.array(poly_values))

fig, ax = plt.subplots()
ax.add_collection(coll)
points = ax.scatter(data[:, 0], data[:, 1], c=value, cmap='viridis', linewidth=0)
fig.colorbar(coll, label='polygons')
fig.colorbar(points, label='points')
plt.show()

结果: