如何在Python中将bin系列浮点值转换为直方图？

Question

我在float中设置了值(总是小于0).我希望将其分为直方图,即e.直方图中的每个条形包含值范围[0,0.150)

我的数据看起来像这样:

0.000
0.005
0.124
0.000
0.004
0.000
0.111
0.112

我的代码如下,我希望得到的结果看起来像

[0, 0.005) 5
[0.005, 0.011) 0
...etc.. 

我尝试用我的这个代码做这样的binning.但它似乎没有用.什么是正确的方法呢？

#! /usr/bin/env python


import fileinput, math

log2 = math.log(2)

def getBin(x):
    return int(math.log(x+1)/log2)

diffCounts = [0] * 5

for line in fileinput.input():
    words = line.split()
    diff = float(words[0]) * 1000;

    diffCounts[ str(getBin(diff)) ] += 1

maxdiff = [i for i, c in enumerate(diffCounts) if c > 0][-1]
print maxdiff
maxBin = max(maxdiff)


for i in range(maxBin+1):
     lo = 2**i - 1
     hi = 2**(i+1) - 1
     binStr = '[' + str(lo) + ',' + str(hi) + ')'
     print binStr + '\t' + '\t'.join(map(str, (diffCounts[i])))

〜

Answer 1

如果可能,不要重新发明轮子.NumPy拥有您需要的一切:

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

a = np.fromfile(open('file', 'r'), sep='\n')
# [ 0.     0.005  0.124  0.     0.004  0.     0.111  0.112]

# You can set arbitrary bin edges:
bins = [0, 0.150]
hist, bin_edges = np.histogram(a, bins=bins)
# hist: [8]
# bin_edges: [ 0.    0.15]

# Or, if bin is an integer, you can set the number of bins:
bins = 4
hist, bin_edges = np.histogram(a, bins=bins)
# hist: [5 0 0 3]
# bin_edges: [ 0.     0.031  0.062  0.093  0.124]