如何 Select Voronoi 多边形 PatchCollection 的颜色并为其创建离散颜色条？

Question

我正在尝试根据邻居的数量为 Voronoi 对象着色。我根据这个数字创建了一个颜色列表，范围从 4 到 7。然后我将 PatchCollection 的数组设置为相邻数字的集合。这在技术上是可行的，但是，它选择了一些非常难看的颜色，并且侧面的颜色条是连续的，而它应该是离散的。我更愿意这样做，以便 <= 4 个邻居是蓝色的，5 个邻居是绿色的，6 个邻居是灰色的，> = 7 个邻居是红色的。关于如何解决这些问题的任何想法？代码：

    import numpy as np
    import matplotlib.pyplot as plt
    from matplotlib.collections import LineCollection 
    from scipy.spatial import Voronoi
    import curved_analysis as ca
    from matplotlib import patches 
    from matplotlib.collections import PatchCollection

    def vor_plot(particles):
        vor = Voronoi(particles[0,:,:2])

        trial_ridges = vor.ridge_vertices

        line_info = []
        for first, last in trial_ridges:
            if -1 not in (first, last):
                line_info.append([vor.vertices[first], vor.vertices[last]])



        vor_poly = Voronoi(particles[0,:,:2])
        regions = vor_poly.regions

        real_regions = []
        for inner_list in regions:
            if -1 not in inner_list:
                real_regions.append(inner_list)
        real_regions.remove([])
    
        fig, ax = plt.subplots()

        vor_poly = []
        colors = []
        for gon in real_regions:
            xy = vor.vertices[gon]
            vor_poly.append(patches.Polygon(xy))
            colors.append(xy.shape[0])




        lc = LineCollection(line_info, color='k', lw=0.5)

        ax.add_collection(lc)
        ax.scatter(vor.points[:,0], vor.points[:,1], s = 3)
        ax.set_xlim([vor.points[:,0].min()-5, vor.points[:,0].max()+5])
        ax.set_ylim([vor.points[:,1].min()-5, vor.points[:,1].max()+5])

        colors = np.array(colors)
        p = PatchCollection(vor_poly, alpha=0.3)
        p.set_array(colors)
        fig.colorbar(p, ax=ax)
        ax.add_collection(p)
        plt.show()

    if __name__ == "__main__":
        particles = ca.read_xyz("flat.xyz")
        vor_plot(particles)

Answer 1

你可以创建一个可以使用的ListedColormap listing the desired colors. To decide which number maps to which color, a norm，第一种颜色固定为4，最后一种颜色固定为7。颜色图和范数都需要分配给 PatchCollection。要定位刻度标签，可以将 4 个彩色单元格的范围划分为 9 个等距位置，并取奇数索引处的位置。

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection, PatchCollection
from scipy.spatial import Voronoi
from matplotlib import patches
from matplotlib.colors import ListedColormap

particles = np.random.rand(1, 20, 2) * 100

vor = Voronoi(particles[0, :, :2])

trial_ridges = vor.ridge_vertices

line_info = []
for first, last in trial_ridges:
    if -1 not in (first, last):
        line_info.append([vor.vertices[first], vor.vertices[last]])

vor_poly = Voronoi(particles[0, :, :2])
regions = vor_poly.regions

real_regions = []
for inner_list in regions:
    if -1 not in inner_list:
        real_regions.append(inner_list)
real_regions.remove([])

fig, ax = plt.subplots()

vor_poly = []
colors = []
for gon in real_regions:
    xy = vor.vertices[gon]
    vor_poly.append(patches.Polygon(xy))
    colors.append(xy.shape[0])

lc = LineCollection(line_info, color='k', lw=0.5)

ax.add_collection(lc)
ax.scatter(vor.points[:, 0], vor.points[:, 1], s=3)
ax.set_xlim([vor.points[:, 0].min() - 5, vor.points[:, 0].max() + 5])
ax.set_ylim([vor.points[:, 1].min() - 5, vor.points[:, 1].max() + 5])

cmap = ListedColormap(['dodgerblue', 'limegreen', 'grey', 'crimson'])
colors = np.array(colors)
p = PatchCollection(vor_poly, alpha=0.3, cmap=cmap, norm=plt.Normalize(4, 7))
p.set_array(colors)
ax.add_collection(p)
cbar = fig.colorbar(p, ticks=np.linspace(4, 7, 9)[1::2], ax=ax)
cbar.ax.set_yticklabels(['≤ 4', '5', '6', '≥ 7'])
plt.show()

如何 Select Voronoi 多边形 PatchCollection 的颜色并为其创建离散颜色条？

How to Select Colors for a PatchCollection of Voronoi Polygons and Create a Discrete Colorbar for it?

python

matplotlib

polygon

voronoi

graph-coloring