从 scipy dendrogram 中检索叶子颜色

Question

我无法从scipy dendrogram 字典中获取颜色叶子。如文档和github issue 中所述，树状图字典中的color_list 键指的是链接，而不是叶子。最好有另一个指向叶子的键，有时您需要它来为其他类型的图形着色，例如下面示例中的散点图。

import numpy as np
import matplotlib.pyplot as plt
from scipy.cluster.hierarchy import linkage, dendrogram

# DATA EXAMPLE
x = np.array([[ 5, 3],
              [10,15],
              [15,12],
              [24,10],
              [30,30],
              [85,70],
              [71,80]])

# DENDROGRAM
plt.figure()
plt.subplot(121)
z = linkage(x, 'single')
d = dendrogram(z)

# COLORED PLOT
# This is what I would like to achieve. Colors are assigned manually by looking
# at the dendrogram, because I failed to get it from d['color_list'] (it refers 
# to links, not observations)
plt.subplot(122)
points = d['leaves']
colors = ['r','r','g','g','g','g','g']
for point, color in zip(points, colors):
    plt.plot(x[point, 0], x[point, 1], 'o', color=color)

在此示例中手动颜色分配似乎很容易，但我正在处理庞大的数据集，所以在我们在字典中获得这个新功能（颜色叶子）之前，我试图以某种方式使用包含在字典，但到目前为止我没有想法。谁能帮帮我？

谢谢。

Answer 1

以下方法似乎有效。树状图返回的字典包含带有链接颜色的“color_list”。 'icoord' 和 'dcoord' 分别是 x。 y，绘制这些链接的坐标。当链接从一个点开始时，这些 x 位置是 5, 15, 25, ...。因此，测试这些 x 位置可以将我们从链接带回到对应点。并允许将链接的颜色分配给该点。

import numpy as np
import matplotlib.pyplot as plt
from scipy.cluster.hierarchy import linkage, dendrogram

# DATA EXAMPLE
x = np.random.uniform(0, 10, (20, 2))

# DENDROGRAM
plt.figure()
plt.subplot(121)
z = linkage(x, 'single')
d = dendrogram(z)
plt.yticks([])

# COLORED PLOT
plt.subplot(122)
points = d['leaves']
colors = ['none'] * len(points)
for xs, c in zip(d['icoord'], d['color_list']):
    for xi in xs:
        if xi % 10 == 5:
            colors[(int(xi)-5) // 10] = c
for point, color in zip(points, colors):
    plt.plot(x[point, 0], x[point, 1], 'o', color=color)
    plt.text(x[point, 0], x[point, 1], f' {point}')
plt.show()

PS：This post 关于匹配点与其聚类也可能是相关的。

Answer 2

对于 scipy 1.7.1，新功能已实现，并且树状图函数在输出字典中返回一个条目“leaves_color_list”，可用于轻松执行此任务。

这是 OP 的工作代码（见最后一行“NEW CODE”）

import numpy as np
import matplotlib.pyplot as plt
from scipy.cluster.hierarchy import linkage, dendrogram

# DATA EXAMPLE
x = np.array([[ 5, 3],
              [10,15],
              [15,12],
              [24,10],
              [30,30],
              [85,70],
              [71,80]])

# DENDROGRAM
plt.figure()
plt.subplot(121)
z = linkage(x, 'single')
d = dendrogram(z)

# COLORED PLOT
# This is what I would like to achieve. Colors are assigned manually by looking
# at the dendrogram, because I failed to get it from d['color_list'] (it refers 
# to links, not observations)
plt.subplot(122)

#NEW CODE
plt.scatter(x[d['leaves'],0],x[d['leaves'],1], color=d['leaves_color_list'])