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?
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]
deque窗口的一个轻微修改版本，使其成为一个真正的滚动窗口。因此，它开始只填充一个元素，然后增长到它的最大窗口大小，然后缩小，因为它的左边缘接近结束:
from collections import deque
def window(seq, n=2):
it = iter(seq)
win = deque((next(it, None) for _ in xrange(1)), maxlen=n)
yield win
append = win.append
for e in it:
append(e)
yield win
for _ in xrange(len(win)-1):
win.popleft()
yield win
for wnd in window(range(5), n=3):
print(list(wnd))
这给了
[0]
[0, 1]
[0, 1, 2]
[1, 2, 3]
[2, 3, 4]
[3, 4]
[4]
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]
在旧版本的Python文档中有一个itertools示例:
from itertools import islice
def window(seq, n=2):
"Returns a sliding window (of width n) over data from the iterable"
" s -> (s0,s1,...s[n-1]), (s1,s2,...,sn), ... "
it = iter(seq)
result = tuple(islice(it, n))
if len(result) == n:
yield result
for elem in it:
result = result[1:] + (elem,)
yield result
文档中的那个更简洁一点，我想它使用了itertools来达到更好的效果。
如果你的迭代器是一个简单的列表/元组，用指定的窗口大小滑动它的简单方法是:
seq = [0, 1, 2, 3, 4, 5]
window_size = 3
for i in range(len(seq) - window_size + 1):
print(seq[i: i + window_size])
输出:
[0, 1, 2]
[1, 2, 3]
[2, 3, 4]
[3, 4, 5]
这里是一个泛化，增加了对step, fillvalue参数的支持:
from collections import deque
from itertools import islice
def sliding_window(iterable, size=2, step=1, fillvalue=None):
if size < 0 or step < 1:
raise ValueError
it = iter(iterable)
q = deque(islice(it, size), maxlen=size)
if not q:
return # empty iterable or size == 0
q.extend(fillvalue for _ in range(size - len(q))) # pad to size
while True:
yield iter(q) # iter() to avoid accidental outside modifications
try:
q.append(next(it))
except StopIteration: # Python 3.5 pep 479 support
return
q.extend(next(it, fillvalue) for _ in range(step - 1))
它每次产生块大小的项目，每次迭代滚动步骤位置，在必要时用fillvalue填充每个块。示例:size=4, step=3, fillvalue='*':
[a b c d]e f g h i j k l m n o p q r s t u v w x y z
a b c[d e f g]h i j k l m n o p q r s t u v w x y z
a b c d e f[g h i j]k l m n o p q r s t u v w x y z
a b c d e f g h i[j k l m]n o p q r s t u v w x y z
a b c d e f g h i j k l[m n o p]q r s t u v w x y z
a b c d e f g h i j k l m n o[p q r s]t u v w x y z
a b c d e f g h i j k l m n o p q r[s t u v]w x y z
a b c d e f g h i j k l m n o p q r s t u[v w x y]z
a b c d e f g h i j k l m n o p q r s t u v w x[y z * *]
有关step参数的用例示例，请参见用python有效地处理大型.txt文件。
