如何使用Python创建非ascii树形图?

时间:2011-02-23 08:24:07

标签: python r numpy rpy2 dendrogram

尝试使用此找到的代码块创建树形图,并在调用之前一直工作:

r('mt_dist <- dist(t(mt))')

然后喷出错误:

  

RPy_RException:dist(t(mt))中的错误:( list)对象无法强制输入'double'

直到那时它看起来很好......我可能错过了一些非常简单的东西

任何帮助?

#importing modules
from numpy import array
from random import normalvariate,shuffle
from rpy import r

# creating a random matrix
# creating it with different 'samples' in different columns
mt = []
for l in range(20): #20 lines
    line = []
    means = range(1,9)
    for c in range(8): # 8 columns
        #Colum 1: mean 1; Column 2: mean 2.... values normally distributed s.d. = 0.5       
        line.append(normalvariate(means.pop(), 0.5))

    mt.append(line)

# once we have a matrix, transform it in an array
mt_array = array(mt)

# The R work
# Pass the array to 'mt' variable in R
r.assign("mt", mt_array)

# manipulate R via r('command')
r('print(mt)') #print the matrix 'mt' to check values

#The clustering process
#Calculating distances with 'dist'
#'dist' calculates distance among lines, so I am transposing (with t()) in order to have my columns clustered
## I guess 'dist' uses euclidian distance as default

r('mt_dist <- dist(t(mt))')
# hclust does the clustering with upgma as default

r('result = hclust(mt_dist)')

# directs the output to a determinde file
r('png("output_file.png")')

# plot the result
labels = ["sample A", "sample B","sample C", "sample D","sample E", "sample F", "sample G", "sample H"]
r.assign("labels", labels)
r('plot(result, labels=labels, main="My title")')

# 'close' you output
r('dev.off()')

1 个答案:

答案 0 :(得分:1)

这不是您的RPy _...异常问题的答案。而是为你的标题How do I create a non-ascii dendrogram with Python?提供答案。您可以尝试使用此dendrogram