如何在 Seaborn/Python 中的 clustermap 中将标签添加到侧面颜色条

Question

我已经编写了一个 Python 脚本来绘制 clustermap。

import sys
import importlib
import matplotlib.pyplot as plt

# import PRCC function
import PRCC as prcc
import QSP_analysis as qa

#%%
import numpy as np
from pyDOE2 import lhs
# Reading data
num_samples = 20
num_param = 15
num_readout = 9

header, data = qa.read_csv('3.csv')
param_names = header[1:num_param+1]
read_names = header[num_param+1:]
lhd = data[:,1:num_param+1].astype(float)
readout = data[:,num_param+1:].astype(float)


Rho, Pval, Sig, Pval_correct = prcc.partial_corr(lhd, readout, 1e-14,Type = 'Spearman', MTC='Bonferroni')

sig_txt = np.zeros((num_param, num_readout), dtype='U8')
sig_txt[Pval_correct<5e-2] = '*'
sig_txt[Pval_correct<1e-6] = '**'
sig_txt[Pval_correct<1e-9] = '***'
param_group = ["beige"]*10 + ["khaki"]*(num_param-10)
readout_group = ["#B4B4FF"]*2+ ["mediumslateblue"]*(num_readout-2)
importlib.reload(qa)
cm = qa.cluster_map(np.transpose(Pval), read_names,param_names, 
                  (10,6), cmap="bwr",
                  annot=np.transpose(sig_txt),
                  row_colors = readout_group,
                  col_colors = param_group,
                  col_cluster=False, row_cluster=False,
                  show_dendrogram = [False, False])
cm.savefig('heat.png',format='png', dpi=600,bbox_inches='tight')

代码中的函数如下：

def read_csv(filename, header_line = 1, dtype = str):
    with open(filename) as csvfile:
        reader = csv.reader(csvfile, delimiter=',', quotechar='|')
        # header
        header = ''
        for i in range(header_line):
            header = next(reader)
        # data
        data = np.asarray(list(reader), dtype = dtype)
        return header, data  

def cluster_map(data, row_label, col_label, fig_size, annot = None,
                show_dendrogram = [True, True], **kwarg):
    
    df = pd.DataFrame(data=data, index = row_label, columns = col_label)
    g = sns.clustermap(df, annot = annot, fmt = '',
                       vmin=-1, vmax=1, cbar_kws={"ticks":[-1, -.5,  0, .5,  1]}, **kwarg)
    #row_order = g.dendrogram_row.reordered_ind
    #col_order = g.dendrogram_col.reordered_ind
    g.ax_heatmap.set_yticklabels(g.ax_heatmap.get_yticklabels(), rotation=0)
    g.ax_heatmap.set_xticklabels(g.ax_heatmap.get_xticklabels(), rotation=-55, ha = 'left')
    g.ax_row_dendrogram.set_visible(show_dendrogram[0])
    g.ax_col_dendrogram.set_visible(show_dendrogram[1])
    g.fig.set_size_inches(*fig_size)
    return g

PRCC 函数是调用MATLAB 并计算PRCC 值的脚本。主脚本读取一个包含 20 行 24 列且 headers 不同的 csv 文件。代码的输出是一个基于某些列（垂直：read_names 和 horizontal:param_names）的 clustermap。

我添加了一个颜色条来对水平和垂直轴上的变量进行分类。输出图如下。如何为这些添加标签 color-bar：水平标签（ABM" 和 "QSP"）和垂直标签（"端点" 和 "预处理"）？

Cluster-map from the script

Answer 1

以下示例代码假设您使用 row_cluster=False, col_cluster=False) 调用 sns.clustermap，因此行和列保持其原始顺序（如果重新排序，原始组将分开）。

itertools 中的

groupby 可用于颜色列表。它们的累积和表示颜色之间的边界。平均这些位置适合放置标签。

from matplotlib import pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
from itertools import groupby

def cluster_map(data, row_label, col_label, fig_size, annot=None, row_color_labels=None, col_color_labels=None,
                show_dendrogram=[True, True], **kwarg):
    df = pd.DataFrame(data=data, index=row_label, columns=col_label)
    g = sns.clustermap(df, annot=annot, fmt='',
                       vmin=-1, vmax=1, cbar_kws={"ticks": [-1, -.5, 0, .5, 1]}, **kwarg)
    g.ax_heatmap.set_yticklabels(g.ax_heatmap.get_yticklabels(), va='center')
    if row_color_labels is not None:
        row_colors = kwarg['row_colors']
        borders = np.cumsum([0] + [sum(1 for i in g) for k, g in groupby(row_colors)])
        for b0, b1, label in zip(borders[:-1], borders[1:], row_color_labels):
            g.ax_row_colors.text(-0.06, (b0 + b1) / 2, label, color='black', ha='right', va='center', rotation=90,
                                 transform=g.ax_row_colors.get_yaxis_transform())
    if col_color_labels is not None:
        col_colors = kwarg['col_colors']
        borders = np.cumsum([0] + [sum(1 for i in g) for k, g in groupby(col_colors)])
        for b0, b1, label in zip(borders[:-1], borders[1:], col_color_labels):
            g.ax_col_colors.text((b0 + b1) / 2, 1.06, label, color='black', ha='center', va='bottom',
                                 transform=g.ax_col_colors.get_xaxis_transform())

cluster_map(np.random.uniform(-1, 1, size=(7, 12)),
            fig_size=(12, 12),
            col_label=[*'ABCDEFGHIJKL'],
            row_label=['Alkaid', 'Mizar', 'Alioth', 'Megrez', 'Phecda', 'Merak', 'Dubhe'],
            col_colors=["beige"] * 10 + ["khaki"] * (12 - 10),
            row_colors=["#B4B4FF"] * 2 + ["mediumslateblue"] * (7 - 2),
            col_color_labels=["ABM", "QSP"],
            row_color_labels=["endpoint", "pretreatment"],
            row_cluster=False,
            col_cluster=False)

如何在 Seaborn/Python 中的 clustermap 中将标签添加到侧面颜色条

How to add labels to the side color bar in clustermap in Seaborn/Python

python

seaborn