这个问题不能很好地定义 矩阵 ：“值矩阵”，“数据矩阵”。我认为您的意思是 距离矩阵 。换句话说，对称非负N×N 距离矩阵
D中的元素D_ij表示两个特征向量x_i和x_j之间的距离。那是对的吗？

如果是这样，请尝试以下操作（2010年6月13日编辑，以反映两个不同的树状图）：

import scipy
import pylab
import scipy.cluster.hierarchy as sch
from scipy.spatial.distance import squareform


# Generate random features and distance matrix.
x = scipy.rand(40)
D = scipy.zeros([40,40])
for i in range(40):
    for j in range(40):
        D[i,j] = abs(x[i] - x[j])

condensedD = squareform(D)

# Compute and plot first dendrogram.
fig = pylab.figure(figsize=(8,8))
ax1 = fig.add_axes([0.09,0.1,0.2,0.6])
Y = sch.linkage(condensedD, method='centroid')
Z1 = sch.dendrogram(Y, orientation='left')
ax1.set_xticks([])
ax1.set_yticks([])

# Compute and plot second dendrogram.
ax2 = fig.add_axes([0.3,0.71,0.6,0.2])
Y = sch.linkage(condensedD, method='single')
Z2 = sch.dendrogram(Y)
ax2.set_xticks([])
ax2.set_yticks([])

# Plot distance matrix.
axmatrix = fig.add_axes([0.3,0.1,0.6,0.6])
idx1 = Z1['leaves']
idx2 = Z2['leaves']
D = D[idx1,:]
D = D[:,idx2]
im = axmatrix.matshow(D, aspect='auto', origin='lower', cmap=pylab.cm.YlGnBu)
axmatrix.set_xticks([])
axmatrix.set_yticks([])

# Plot colorbar.
axcolor = fig.add_axes([0.91,0.1,0.02,0.6])
pylab.colorbar(im, cax=axcolor)
fig.show()
fig.savefig('dendrogram.png')

祝好运！让我知道您是否需要更多帮助。

编辑：对于不同的颜色，请调整中的cmap属性imshow。有关示例，请参见scipy /
matplotlib文档。该页面还描述了如何创建自己的颜色图。为了方便起见，我建议使用预先存在的颜色图。在我的示例中，我使用YlGnBu。

Edit: add_axes (see documentation
here)
accepts a list or tuple: (left, bottom, width, height). For example,
(0.5,0,0.5,1) adds an Axes on the right half of the figure.
(0,0.5,1,0.5) adds an Axes on the top half of the figure.

Most people probably use add_subplot for its convenience. I like add_axes
for its control.

To remove the border, use add_axes([left,bottom,width,height], frame_on=False). See example
here.