文件tx中带Numpy的加权平均数

Question

早上好， 我将这个txt文件空间分隔开：

drive-------------------------------------------------------------------------k='6'   seq nelsa s length: 4044778
# 51 1
# 64 1
# 65 1
# 67 2
# 70 1
# 72 1
# 73 1
# 77 1
# 79 1
# 86 1
# 88 2
# 89 1
# 92 1
# 94 1
# 95 1
# 96 2
# 100 1
# 103 1
# 105 1
# 108 1
# 112 1
# 119 1
# 123 1
# 126 1
# 127 1
# 129 1
# 130 1
# 133 3
# 134 1
# 135 1
# 138 2
# 139 1
# 140 1
# 141 1
# 142 1
# 143 1
# 144 2
# 145 1
# 148 2
# 150 3
# 151 1
# 152 1
# 153 1
# 154 1
# 155 1
# 156 1
# 157 1
# 159 3
# 160 1
# 161 1
# 162 1
# 163 1
# 164 1
# 165 2
# 167 2
# 168 1
# 169 1
# 170 1
# 172 2
# 173 1
# 174 1
# 175 1

-------------------------------------------------------------------------k='7'   seq nelsa s length: 4044778
# 4 1
# 5 1
# 8 1
# 9 1
# 10 3
# 11 3
# 12 4
# 13 7
# 14 6
# 15 5
# 16 11
# 17 7
# 18 14
# 19 8
# 20 15
# 21 13
# 22 10
# 23 6
# 24 22
# 25 14
# 26 19
# 27 17
# 28 20
# 29 25
# 30 15
# 31 22
# 32 18
# 33 23
# 34 30
# 35 24
# 36 35
# 37 39
# 38 27
# 39 33
# 40 36
# 41 34
# 42 40
# 43 43
# 44 44
# 45 44
# 46 43
# 47 50
# 48 51
# 49 54
# 50 55
# 51 44
# 52 49
# 53 56
# 54 35
# 55 52
# 56 47
# 57 48
# 58 65
# 59 56
# 60 53
# 61 54
# 62 66
# 63 47
# 64 61
# 65 50
# 66 46
# 67 69
# 68 65
# 69 66
# 70 59
# 71 59
# 72 55
# 73 73
# 74 91
# 75 73
# 76 56
# 77 66
# 78 63
# 79 67
# 80 78
# 81 51
# 82 69
# 83 60
# 84 64
# 85 73
# 86 58
# 87 60
# 88 64
# 89 73
# 90 63
# 91 65
# 92 59
# 93 69
# 94 67
# 95 73
# 96 50
# 97 53
# 98 68
# 99 65
# 100 63
# 101 55
# 102 73
# 103 76
# 104 66
# 105 70
# 106 75
# 107 66
# 108 56
# 109 49
# 110 68
# 111 52
# 112 66
# 113 67
# 114 66
# 115 52
# 116 61
# 117 59
# 118 65
# 119 67
# 120 56
# 121 60
# 122 64
# 123 53
# 124 59
# 125 66
# 126 58
# 127 77
# 128 51
# 129 67
# 130 53
# 131 56
# 132 62
# 133 64
# 134 56
# 135 42
# 136 71
# 137 57
# 138 53
# 139 52
# 140 65
# 141 59
# 142 61
# 143 60
# 144 64

我必须使用python max weightedţu mean和min来计算从第一个ţ到最后一个ţ的距离，然后用---k=''分隔符来表示每个k。 我怎么能对python说，对每个K进行从#到#的微积分呢？你知道吗

这是我到目前为止写的代码：

#! /usr/bin/python

import numpy
import csv

file = open('Acetobacterium_woodii_DSM_1030.mdistr', 'rb')
data = csv.reader(file, delimiter=' ')
table = [row for row in data]
a = table[10]
print a[2]  

这只是一个例子。 先谢谢你。你知道吗

Answer 1

我相信有一个更优雅的答案，但这是可行的：

#parse data
with open('data.txt') as f:
    lines = f.readlines()
    alldata = []
    kdata = []
    for i,line in enumerate(lines):
        if len(line) > 1:
            if line[0] =='#':
                x = int(line.split(' ')[1])
                y = int(line.split(' ')[2][:-1])
                kdata.append([x,y])
            else:
                if i !=0:
                    alldata.append([kval,kdata])
                ptr = line.find('k=')+3
                kval = int(line[ptr:ptr+1])
                kdata=[]
    alldata.append([kval,kdata])

#analyse data
for kblock in alldata:
    kval = kblock[0]
    sumx = sum([x for z in kblock[1:] for (x,y) in z])
    sumy = sum([y for z in kblock[1:] for (x,y) in z])
    sumxy = sum([x*y for z in kblock[1:] for (x,y) in z])
    mean = sumxy/sumy
    print('The mean of k-{0} is :{1}'.format(kval,mean))

numpy本应是我的首选，但如果您的数据大小可变，则这将变得更加困难。希望这有帮助。你知道吗

Answer 2

简单的解决方案如下：

#! /usr/bin/python
import numpy as np

with open('Acetobacterium_woodii_DSM_1030.mdistr', 'r') as f:
    # read file
    lines = f.read().splitlines()

values = []
weights = []

for line in lines:
    if line.startswith("-"):
        # print statistics and reset variables
        print ("Min: %d, Max: %d, Avg: %d" %(min(values),max(values),
                                             np.average(values, 
                                                        weights=weights)))
        values = []
        weights = []
    elif line.startswith("#"):
        row = line.split()
        values.append(int(row[1]))
        weights.append(int(row[2]))

# print statistics before quitting
print ("Min: %d, Max: %d, Avg: %d" %(min(values),max(values),
                                     np.average(values,
                                                weights=weights)))