matplotlib 中用于 SciPy 的树状图（Python）的更大调色板

Question

我正在尝试在matplotlib 或seaborn 中扩展我的color_palette 以用于scipy 的树状图，以便为每个集群着色不同。

目前，color_palette 只有几种颜色，因此多个集群被映射到相同的颜色。我知道RGB 有大约 1600 万种颜色，所以...

我怎样才能在这种类型的图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。我不确定你想如何显示你的颜色，但我相信你可以很容易地修改你的代码来实现你想要的任何颜色组合......

你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。

玩一会儿……