绘制由散点数据决定颜色的Shapefile

Question

我的问题

使用 shapefile 绘制热图

1.intro

一堆shapefile代表行政边界
a 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

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布尔掩码来处理该多边形内的点，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（没有底图，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：

绘制由散点数据决定颜色的Shapefile

Plotting Shapefiles which color decided by the scatter point data within

python

matplotlib

shapefile

matplotlib-basemap

我的问题

1.intro

2。我的目标

添加--2015-01-11