SciPy 的树状图 (Python) 在 matplotlib 中更大的调色板

Question

我正在尝试扩展我的 color_palette 在 matplotlib 或 seaborn 中用于 scipy 树状图 所以每个簇的颜色不同。

目前，color_palette 只有几种颜色，因此多个聚类被映射到相同的颜色。我知道有 1600 万种 RGB 颜色，所以...

如何在这种类型的图形中使用来自巨大调色板的更多颜色？

#!/usr/bin/python

from __future__ import print_function
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import colorsys
from scipy.cluster.hierarchy import dendrogram,linkage,fcluster
from scipy.spatial import distance
np.random.seed(0) #43984

#Dims
n,m = 10,1000

#DataFrame: rows = Samples, cols = Attributes
attributes = ["a" + str(j) for j in range(m)]
DF_data = pd.DataFrame(np.random.randn(n, m),#
                columns = attributes)

A_dist = distance.cdist(DF_data.as_matrix().T, DF_data.as_matrix().T)
DF_dist = pd.DataFrame(A_dist, index = attributes, columns = attributes)

#Linkage Matrix
Z = linkage(squareform(DF_dist.as_matrix()),method="average") #metric="euclidead" necessary since the input is a dissimilarity measure? 



#Create dendrogram
D_dendro = dendrogram(
         Z, 
         labels=DF_dist.index,
         no_plot=True,
         color_threshold=3.5,
         count_sort = "ascending",
         #link_color_func=lambda k: colors[k]
         )

#Display dendrogram
def plotTree(D_dendro):
    fig,ax = plt.subplots(figsize=(25, 10))
    icoord = np.array( D_dendro['icoord'] )
    dcoord = np.array( D_dendro['dcoord'] )
    color_list = np.array( D_dendro['color_list'] )
    x_min, x_max = icoord.min(), icoord.max()
    y_min, y_max = dcoord.min(), dcoord.max()

    for xs, ys, color in zip(icoord, dcoord, color_list):
        plt.plot(xs, ys,  color)
    plt.xlim( x_min-10, x_max + 0.1*abs(x_max) )
    plt.ylim( y_min, y_max + 0.1*abs(y_max) )
    plt.title("Dendrogram", fontsize=30)
    plt.xlabel("Clusters", fontsize=25)
    plt.ylabel("Distance", fontsize=25)
    plt.yticks(fontsize = 20)

    plt.show()

    return(fig,ax)
fig,ax = plotTree(D_dendro) #wrapper I made

#Dims
print(
    len(set(D_dendro["color_list"])), "^ # of colors from dendrogram",
    len(D_dendro["ivl"]), "^ # of labels",sep="\n")
# 7
# ^ # of colors from dendrogram
# 1000
# ^ # of labels

Answer 1

大多数 matplotlib 颜色图会给你一个介于 0 和 1 之间的值。例如，

import matplotlib.pyplot as plt
import numpy as np
print [plt.cm.Greens(i) for i in np.linspace(0, 1, 5)]

将打印

[(0.9686274528503418, 0.98823529481887817, 0.96078431606292725, 1.0),
 (0.77922338878407194, 0.91323337695177864, 0.75180316742728737, 1.0),
 (0.45176470875740049, 0.76708959481295413, 0.46120723030146432, 1.0),
 (0.13402538141783546, 0.54232989970375511, 0.26828144368003398, 1.0),
 (0.0, 0.26666668057441711, 0.10588235408067703, 1.0)]

因此您不再需要受限于提供给您的值。只需选择一个颜色图，然后根据某个分数从该颜色图中获取颜色。例如，在您的代码中，您可以考虑

for xs, ys in zip(icoord, dcoord):
    color = plt.cm.Spectral( ys/6.0 )
    plt.plot(xs, ys,  color)

或类似的东西。我不确定您想如何准确地显示颜色，但我相信您可以很容易地修改代码以实现您想要的任何颜色组合...

您可以尝试的另一件事是

N = D_dendro["color_list"]
colorList = [ plt.cm.Spectral( float(i)/(N-1) )  for i in range(N)]

并传递 colorList。

玩一下……

SciPy 的树状图 (Python) 在 matplotlib 中更大的调色板

Bigger color-palette in matplotlib for SciPy's dendrogram (Python)

python

colors

matplotlib

scipy

seaborn