使用scipy/numpy在python中合并数据 [英] binning data in python with scipy/numpy

问题描述

有没有更有效的方法来对预先指定的bin中的数组取平均值?例如，我有一个数字数组以及一个与该数组中bin起始和结束位置相对应的数组，我只想取这些bin中的均值?我下面有执行此操作的代码，但我想知道如何减少和改进它.谢谢.

is there a more efficient way to take an average of an array in prespecified bins? for example, i have an array of numbers and an array corresponding to bin start and end positions in that array, and I want to just take the mean in those bins? I have code that does it below but i am wondering how it can be cut down and improved. thanks.

from scipy import *
from numpy import *

def get_bin_mean(a, b_start, b_end):
    ind_upper = nonzero(a >= b_start)[0]
    a_upper = a[ind_upper]
    a_range = a_upper[nonzero(a_upper < b_end)[0]]
    mean_val = mean(a_range)
    return mean_val


data = rand(100)
bins = linspace(0, 1, 10)
binned_data = []

n = 0
for n in range(0, len(bins)-1):
    b_start = bins[n]
    b_end = bins[n+1]
    binned_data.append(get_bin_mean(data, b_start, b_end))

print binned_data

推荐答案

使用一种替代方法是使用 numpy.histogram() :

An alternative to this is to use numpy.histogram():

bin_means = (numpy.histogram(data, bins, weights=data)[0] /
             numpy.histogram(data, bins)[0])

亲自尝试哪一个更快...:)

Try for yourself which one is faster... :)

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