将清单大致等份的最佳方法是什么?例如,如果列表有7个元素,并将其分为2部分,我们希望其中一部分有3个元素,而另一部分应该有4个元素。

我正在寻找类似even_split(L, n)的东西,它将L分解为n部分。

def chunks(L, n):
    """ Yield successive n-sized chunks from L.
    """
    for i in range(0, len(L), n):
        yield L[i:i+n]

上面的代码给出了3个块,而不是3个块。我可以简单地转置(遍历这个,取每列的第一个元素,称之为第一部分,然后取第二个元素,把它放在第二部分,等等),但这破坏了项目的顺序。


当前回答

在这种情况下,我自己编写了代码:

def chunk_ports(port_start, port_end, portions):
    if port_end < port_start:
        return None

    total = port_end - port_start + 1

    fractions = int(math.floor(float(total) / portions))

    results = []

    # No enough to chuck.
    if fractions < 1:
        return None

    # Reverse, so any additional items would be in the first range.
    _e = port_end
    for i in range(portions, 0, -1):
        print "i", i

        if i == 1:
            _s = port_start
        else:
            _s = _e - fractions + 1

        results.append((_s, _e))

        _e = _s - 1

    results.reverse()

    return results

Divide_ports(1,10,9)将返回

[(1, 2), (3, 3), (4, 4), (5, 5), (6, 6), (7, 7), (8, 8), (9, 9), (10, 10)]

其他回答

看看numpy.split:

>>> a = numpy.array([1,2,3,4])
>>> numpy.split(a, 2)
[array([1, 2]), array([3, 4])]

舍入linspace并将其用作索引是一种比amit12690建议的更简单的解决方案。

function chunks=chunkit(array,num)

index = round(linspace(0,size(array,2),num+1));

chunks = cell(1,num);

for x = 1:num
chunks{x} = array(:,index(x)+1:index(x+1));
end
end

1>

import numpy as np

data # your array

total_length = len(data)
separate = 10
sub_array_size = total_length // separate
safe_separate = sub_array_size * separate

splited_lists = np.split(np.array(data[:safe_separate]), separate)
splited_lists[separate - 1] = np.concatenate(splited_lists[separate - 1], 
np.array(data[safe_separate:total_length]))

splited_lists # your output

2>

splited_lists = np.array_split(np.array(data), separate)

这是另一种变体,它将“剩余”元素均匀地分布在所有块中,一次一个,直到一个都不剩。在这个实现中,较大的块出现在流程的开头。

def chunks(l, k):
  """ Yield k successive chunks from l."""
  if k < 1:
    yield []
    raise StopIteration
  n = len(l)
  avg = n/k
  remainders = n % k
  start, end = 0, avg
  while start < n:
    if remainders > 0:
      end = end + 1
      remainders = remainders - 1
    yield l[start:end]
    start, end = end, end+avg

例如,从14个元素的列表中生成4个块:

>>> list(chunks(range(14), 4))
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10], [11, 12, 13]]
>>> map(len, list(chunks(range(14), 4)))
[4, 4, 3, 3]

这就是numpy.array_split*使用d'être的原因:

>>> import numpy as np
>>> print(*np.array_split(range(10), 3))
[0 1 2 3] [4 5 6] [7 8 9]
>>> print(*np.array_split(range(10), 4))
[0 1 2] [3 4 5] [6 7] [8 9]
>>> print(*np.array_split(range(10), 5))
[0 1] [2 3] [4 5] [6 7] [8 9]

*贷方是6号房间的零比雷埃夫斯