插图聚类式热图(带有树状图)/Python [英] Plotly clustered heatmap (with dendrogram)/Python

问题描述

我正在尝试使用Ploly在Python语言中创建一个集群热图(使用树状图)。他们在网站上做的这个没有很好的伸缩性，我已经找到了各种解决方案，但大多数都是用R或JavaScript编写的。我正在尝试创建一个热图，只从热图的左侧创建一个树状图，显示y轴上的集群(从层次集群)。一个非常好看的例子是这个：https://chart-studio.plotly.com/~jackp/6748。我的目的是创建这样的东西，但只使用左侧的树状图。如果有人能用Python语言实现这样的东西，我将非常感激！

让数据X = np.random.randint(0, 10, size=(120, 10))

推荐答案

以下建议使用Dendrograms in Python和chart-studio.plotly.com/~jackp中的元素。此特定绘图使用您的数据X = np.random.randint(0, 10, size=(120, 10))。在我看来，这些相互关联的方法有一个共同点，那就是数据集和数据处理程序有点杂乱无章。因此，我决定用df = pd.DataFrame(X)在 pandas 数据框上构建下面的图，希望能让一切变得更清楚

绘图

完整代码

import plotly.graph_objects as go
import plotly.figure_factory as ff

import numpy as np
import pandas as pd
from scipy.spatial.distance import pdist, squareform
import random
import string

X = np.random.randint(0, 10, size=(120, 10))
df = pd.DataFrame(X)

# Initialize figure by creating upper dendrogram
fig = ff.create_dendrogram(df.values, orientation='bottom')
fig.for_each_trace(lambda trace: trace.update(visible=False))

for i in range(len(fig['data'])):
    fig['data'][i]['yaxis'] = 'y2'

# Create Side Dendrogram
# dendro_side = ff.create_dendrogram(X, orientation='right', labels = labels)
dendro_side = ff.create_dendrogram(X, orientation='right')
for i in range(len(dendro_side['data'])):
    dendro_side['data'][i]['xaxis'] = 'x2'

# Add Side Dendrogram Data to Figure
for data in dendro_side['data']:
    fig.add_trace(data)

# Create Heatmap
dendro_leaves = dendro_side['layout']['yaxis']['ticktext']
dendro_leaves = list(map(int, dendro_leaves))
data_dist = pdist(df.values)
heat_data = squareform(data_dist)
heat_data = heat_data[dendro_leaves,:]
heat_data = heat_data[:,dendro_leaves]

heatmap = [
    go.Heatmap(
        x = dendro_leaves,
        y = dendro_leaves,
        z = heat_data,
        colorscale = 'Blues'
    )
]

heatmap[0]['x'] = fig['layout']['xaxis']['tickvals']
heatmap[0]['y'] = dendro_side['layout']['yaxis']['tickvals']

# Add Heatmap Data to Figure
for data in heatmap:
    fig.add_trace(data)

# Edit Layout
fig.update_layout({'width':800, 'height':800,
                         'showlegend':False, 'hovermode': 'closest',
                         })
# Edit xaxis
fig.update_layout(xaxis={'domain': [.15, 1],
                                  'mirror': False,
                                  'showgrid': False,
                                  'showline': False,
                                  'zeroline': False,
                                  'ticks':""})
# Edit xaxis2
fig.update_layout(xaxis2={'domain': [0, .15],
                                   'mirror': False,
                                   'showgrid': False,
                                   'showline': False,
                                   'zeroline': False,
                                   'showticklabels': False,
                                   'ticks':""})

# Edit yaxis
fig.update_layout(yaxis={'domain': [0, 1],
                                  'mirror': False,
                                  'showgrid': False,
                                  'showline': False,
                                  'zeroline': False,
                                  'showticklabels': False,
                                  'ticks': ""
                        })
# # Edit yaxis2
fig.update_layout(yaxis2={'domain':[.825, .975],
                                   'mirror': False,
                                   'showgrid': False,
                                   'showline': False,
                                   'zeroline': False,
                                   'showticklabels': False,
                                   'ticks':""})

fig.update_layout(paper_bgcolor="rgba(0,0,0,0)",
                  plot_bgcolor="rgba(0,0,0,0)",
                  xaxis_tickfont = dict(color = 'rgba(0,0,0,0)'))

fig.show()

这篇关于插图聚类式热图(带有树状图)/Python的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！