14.5. Computing the Voronoi diagram of a set of points
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.spatial import Voronoi, voronoi_plot_2d
def normalizer(dataArray):
if dataArray.max() - dataArray.min() == 0:
return dataArray
return (dataArray-dataArray.min())/(dataArray.max() - dataArray.min())
def comparisionPlot(columnName0, columnName1, hueColumn, dataDf):
# add 4 distant dummy points to help coloring the edge
# dataPoints = np.append((dataDfNormalized)[['P-MEAN', 'RANK']], [[2,2], [-2,2], [2,-2], [-2,-2]], axis = 0)
# normal version
dataPoints = dataDf[[columnName0, columnName1]]
# plot Voronoi diagrame
vor = Voronoi(dataPoints)
voronoi_plot_2d(vor, show_vertices = True, point_size = 2)
# color list
colorList = []
for regionIndex in range(len(vor.regions)):
if not -1 in vor.regions[regionIndex]:
polygon = [vor.vertices[i] for i in vor.regions[regionIndex]]
if len(polygon) == 0:
colorList += colorList[-1:]
continue
colorList += [np.array(polygon).transpose().min()]
colorList += colorList[-1:]
colorList = normalizer(np.array(colorList))
# colorize
for regionIndex in range(len(vor.regions)):
if not -1 in vor.regions[regionIndex]:
polygon = [vor.vertices[i] for i in vor.regions[regionIndex]]
plt.fill(*zip(*polygon),color=np.repeat(colorList[regionIndex],3))
# fix the range of axes
plt.xlim([-0.2,1.2]), plt.ylim([-0.2,1.2])
plt.show()
What is the *zip
in line 38
*zip()
函数是 zip()
函数的逆过程,将 zip
对象变成原先组合前的数据。
zip(*iterables)
*zip(*iterables)
What is the *polygon
in line 38
Change polygon from interator to iterable.