Question

我的用于计算欧式距离的代码。首先，我读取了一个文件，其中有一系列系统发育距离度量，并根据这些度量来计算欧几里德距离。我的问题是此刻将文件保存到输出中。我构造for循环的方式使我可以堆叠数据，但是，我希望将数据堆叠。请在下面查看我的输出和所需输出的详细信息。

# -*- coding: utf-8 -*-
import os
import sys
import pandas as pd
import numpy as np
from scipy.spatial.distance import squareform, pdist
import scipy
pd.options.mode.chained_assignment = None  # default='warn'
from itertools import combinations
from collections import Counter
import pickle
f = open(sys.argv[1], 'r')
w = open(sys.argv[2], 'w')

freader=pd.read_csv(f,sep='\t')
vector2=['kU.','kUn.','kL.']#,'kLn.','Sim.','Trip.','RF.','KC.','KCw.']                                                                 
vector1=['kU','kUn','kL']#,'kLn','Sim','Trip','RF','KC','KCw']


comb1=sum([map(list, combinations(vector1, i)) for i in range(len(vector1) + 1)], [])

for i in comb1:
    if i!=[]:
        new_f1 = freader[i]
        j = [word.replace(word, word + '.') for word in i]
        new_f2 = freader[j]
        ary = scipy.spatial.distance.cdist(new_f1, new_f2)
        v=np.diag(ary)
        v = v.tolist()
        distances=''.join(i)
        euclidean='\n'.join(map(str,v))
        w.write(distances + '\n' + euclidean + '\n')
        #print w

f.close()

给我堆积的输出文件，例如：

kU
0.1196105158
0.2359754815
kUn
0.5221363287
0.0006352575
kL
0.0986327691
0.2722213035
kUkUn
0.5356612934
0.2359763366
kUkL
0.1550325728
0.3602622183
kUnkL
0.5313706511
0.2722220447
kUkUnkL
0.5446663606
0.3602627784

但是我想要这个未堆叠的输出文件：

kU              kUn             kL              kUkUn           kUkL            kUnkL           kUkUnkL
0.1196105158    0.5221363287    0.0986327691    0.5356612934    0.1550325728    0.5313706511    0.5446663606
0.2359754815    0.0006352575    0.2722213035    0.2359763366    0.3602622183    0.2722220447    0.3602627784

Answer 1

您可以重塑基础数组

pd.DataFrame(df.values.reshape(len(df)//3, 3)).set_index(0).T

    kU              kUn             kL              kUkUn           kUkL            kUnkL   kUkUnkL
1   0.1196105158    0.5221363287    0.0986327691    0.5356612934    0.1550325728    0.5313706511    0.5446663606
2   0.2359754815    0.0006352575    0.2722213035    0.2359763366    0.3602622183    0.2722220447    0.3602627784

如何从堆叠中取出我的数据

1 个答案: