我需要一个滚动窗口(又名滑动窗口)可迭代的序列/迭代器/生成器。(默认的Python迭代可以被认为是一种特殊情况，其中窗口长度为1。)我目前正在使用以下代码。我怎样才能做得更优雅和/或更有效?
def rolling_window(seq, window_size):
it = iter(seq)
win = [it.next() for cnt in xrange(window_size)] # First window
yield win
for e in it: # Subsequent windows
win[:-1] = win[1:]
win[-1] = e
yield win
if __name__=="__main__":
for w in rolling_window(xrange(6), 3):
print w
"""Example output:
[0, 1, 2]
[1, 2, 3]
[2, 3, 4]
[3, 4, 5]
"""
对于window_size == 2的特定情况(即，在序列中迭代相邻的重叠对)，请参见如何从列表中迭代重叠(当前，下一个)值对?
尝试我的部分，简单，一行，使用islice的python方式。但是，可能不是最佳效率。
from itertools import islice
array = range(0, 10)
window_size = 4
map(lambda i: list(islice(array, i, i + window_size)), range(0, len(array) - window_size + 1))
# output = [[0, 1, 2, 3], [1, 2, 3, 4], [2, 3, 4, 5], [3, 4, 5, 6], [4, 5, 6, 7], [5, 6, 7, 8], [6, 7, 8, 9]]
解释:
通过使用window_size的islice创建窗口，并在所有数组上使用map迭代此操作。
我喜欢t ():
from itertools import tee, izip
def window(iterable, size):
iters = tee(iterable, size)
for i in xrange(1, size):
for each in iters[i:]:
next(each, None)
return izip(*iters)
for each in window(xrange(6), 3):
print list(each)
给:
[0, 1, 2]
[1, 2, 3]
[2, 3, 4]
[3, 4, 5]
我使用下面的代码作为一个简单的滑动窗口，它使用生成器来大幅提高可读性。根据我的经验，到目前为止，它的速度足以用于生物信息学序列分析。
我把它包括在这里是因为我还没有看到这种方法被使用过。同样，我对它的比较性能没有任何评价。
def slidingWindow(sequence,winSize,step=1):
"""Returns a generator that will iterate through
the defined chunks of input sequence. Input sequence
must be sliceable."""
# Verify the inputs
if not ((type(winSize) == type(0)) and (type(step) == type(0))):
raise Exception("**ERROR** type(winSize) and type(step) must be int.")
if step > winSize:
raise Exception("**ERROR** step must not be larger than winSize.")
if winSize > len(sequence):
raise Exception("**ERROR** winSize must not be larger than sequence length.")
# Pre-compute number of chunks to emit
numOfChunks = ((len(sequence)-winSize)/step)+1
# Do the work
for i in range(0,numOfChunks*step,step):
yield sequence[i:i+winSize]
#Importing the numpy library
import numpy as np
arr = np.arange(6) #Sequence
window_size = 3
np.lib.stride_tricks.as_strided(arr, shape= (len(arr) - window_size +1, window_size),
strides = arr.strides*2)
"""Example output:
[0, 1, 2]
[1, 2, 3]
[2, 3, 4]
[3, 4, 5]
"""
