2009-11-12 55 views
8

我有一组float(总是小于0)的值。我想把它分成直方图, 我,例如。直方图各条包含的值范围[0,0.150)Howto将一系列float值转换为Python中的直方图?

我的数据是这样的:

0.000 
0.005 
0.124 
0.000 
0.004 
0.000 
0.111 
0.112 

蒙山我的代码下面我期望得到的结果,看起来像

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

我试图用我的这个代码做这样的装箱。 但它似乎没有工作。什么是正确的做法?

#! /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]))) 

+0

好了, “你所期望的......”,如果有)定义为0,0.005范围(右开),示例[0.005,0.011) (关闭左侧) 那么输出应该是: [0,0.005)4 [0.005,0.011)1 etc ... – Gacek 2009-11-12 10:56:36

+0

“似乎不工作?”任何具体的投诉?或者你是否期望每个人都必须运行它并尝试猜测你不喜欢输出的内容? – 2009-11-12 10:58:00

+0

为避免重新发明轮子,尤其是在下一步绘制直方图时:应考虑使用处理所有这些的Matplotlib框架。 – RedGlyph 2009-11-12 12:13:23

回答

13

如果可能,请勿重新发明轮子。 NumPy的有你需要的一切:

#!/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] 
+0

如果你想要一个归一化的直方图,你可以添加下面的代码: hist = hist * 1。0/sum(hist) – dval 2015-12-04 22:34:28

+0

如果你希望bin范围内的积分为1,使用['density = True'](http://docs.scipy.org/doc/numpy-1.10.1/reference/生成/ numpy.histogram.html)。 – unutbu 2015-12-05 02:01:00

2

第一个错误是:

Traceback (most recent call last): 
    File "C:\foo\foo.py", line 17, in <module> 
    diffCounts[ str(getBin(diff)) ] += 1 
TypeError: list indices must be integers 

你为什么需要一个STR当一个int转换为海峡?解决这个问题,那么我们得到:

Traceback (most recent call last): 
    File "C:\foo\foo.py", line 17, in <module> 
    diffCounts[ getBin(diff) ] += 1 
IndexError: list index out of range 

,因为你只取得5桶。我不明白你的桶装方案,但让我们把它50桶,看看会发生什么:

6 
Traceback (most recent call last): 
    File "C:\foo\foo.py", line 21, in <module> 
    maxBin = max(maxdiff) 
TypeError: 'int' object is not iterable 

maxdiff是单值超出你的整数列表的,那么什么是max在这里做什么?删除它,现在我们得到:

6 
Traceback (most recent call last): 
    File "C:\foo\foo.py", line 28, in <module> 
    print binStr + '\t' + '\t'.join(map(str, (diffCounts[i]))) 
TypeError: argument 2 to map() must support iteration 

果然,您使用的是单值作为第二个参数map。让我们简化从这个最后两行:

binStr = '[' + str(lo) + ',' + str(hi) + ')' 
print binStr + '\t' + '\t'.join(map(str, (diffCounts[i]))) 

这样:

print "[%f, %f)\t%r" % (lo, hi, diffCounts[i]) 

现在它打印:

6 
[0.000000, 1.000000) 3 
[1.000000, 3.000000) 0 
[3.000000, 7.000000) 2 
[7.000000, 15.000000) 0 
[15.000000, 31.000000) 0 
[31.000000, 63.000000) 0 
[63.000000, 127.000000) 3 

我不知道自己能做什么在这里,因为我真的不明白你希望使用的bucketing。它似乎涉及二进制的权力,但对我来说没有意义...

3
from pylab import * 
data = [] 
inf = open('pulse_data.txt') 
for line in inf: 
    data.append(float(line)) 
inf.close() 
#binning 
B = 50 
minv = min(data) 
maxv = max(data) 
bincounts = [] 
for i in range(B+1): 
    bincounts.append(0) 
for d in data: 
    b = int((d - minv)/(maxv - minv) * B) 
    bincounts[b] += 1 
# plot histogram 

plot(bincounts,'o') 
show()