如何在 Python 中将一系列浮点值合并到直方图中

Howto bin series of float values into histogram in Python?(如何在 Python 中将一系列浮点值合并到直方图中?)

问题描述

我有一组浮点值(总是小于 0).我想将其放入直方图中，IE.直方图中的每个条形都包含值范围 [0,0.150)

I have set of value in float (always less than 0). Which I want to bin into histogram, i,e. each bar in histogram contain range of value [0,0.150)

我拥有的数据如下所示:

The data I have looks like this:

0.000
0.005
0.124
0.000
0.004
0.000
0.111
0.112

在我下面的代码中，我希望得到看起来像这样的结果

Whith my code below I expect to get result that looks like

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

我试图用我的这段代码做这样的分箱.但它似乎不起作用.正确的做法是什么?

I tried to do do such binning with this code of mine. But it doesn't seem to work. What's the right way to do it?

#! /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 + '	' + '	'.join(map(str, (diffCounts[i])))

~

推荐答案

如果可能，不要重新发明轮子.NumPy 拥有您需要的一切:

When possible, don't reinvent the wheel. NumPy has everything you need:

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

a = np.fromfile(open('file', 'r'), sep='
')
# [ 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]

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