使用递归的生成器对象

Generator object using recursion

Python2.7

给定列表 alleles 和数组长度 numb_alleles,例如:

alleles = [11, 12, 13, 14, 15, 16]
numb_alleles = 8

我一直在尝试遍历每个笛卡尔积和 select 符合以下 select离子标准的与我的研究相关的等位基因:

  1. 笛卡尔积中的每个第二个值必须大于它之前的值。例如,给定上述条件,笛卡尔积[13, 15, 11, 12, 14, 15, 16, 16]将满足select离子标准,而 [13, 15, 16, 12, 14, 15, 16, 16] 不会因为索引 2 和 3。
  2. alleles 中的每个值都必须存在于笛卡尔积中。 例如,[13, 15, 11, 12, 14, 15, 16, 16] 将满足 selection 标准,而 [13, 15, 11, 12, 14, 15, 11, 13] 则不会,因为 16 不在产品中。

我一直在使用 itertools.product(alleles, repeat = numb_alleles) 遍历每个可能的笛卡尔积以进一步分析。然而,随着 numb_alleles 增加到 10 或 12,整体计算量显着增加。

我试图通过使用下面的递归函数 select 相关的笛卡尔积来解决这个问题。

def check_allele(allele_combination, alleles):
    """Check if all the alleles are present in allele_combination"""
    for allele in alleles:
        if allele not in allele_combination:
            return False
    return True

def recursive_product(alleles, numb_alleles, result):
    current_len = len(result[0])
    new_result = []
    final_result = []

    for comb in result:
        for allele in alleles:
            if current_len % 2 == 0:
                new_result.append(comb + [allele])
            elif current_len % 2 == 1:
                if comb[-1] <= allele:
                    new_result.append(comb + [allele])
                    if (check_allele(comb + [allele], alleles)):
                        final_result.append(comb + [allele])

    if current_len + 1 < numb_alleles:
        return recursive_product(alleles, numb_alleles, new_result)
    else:
        return final_result

a = (recursive_product(alleles, numb_alleles, [[]]))

但是,使用这种方法我仍然无法处理数组 numb_alleles = 12 或当 alleles 的长度增加时,因为我使用的是 return 而不是 [=25] =].因此,它会导致内存不足错误。

我想知道我是否可以将这个函数变成一个生成器,或者是否有人可以建议不同的方法,以便我可以进一步计算 numb_alleles = 12 和更长 [=12] 的输出=]数组。

非常感谢!

你说:"Every second value in the Cartesian product must be larger than the value before it." 但在你的例子中 [13, 15, 11, 12, 14, 15, 16, 16] 槽位 7 (16) 中的项目等于前一个槽位中的项目,所以我假设你的意思是奇数项索引必须 >= 到前一个偶数索引处的项目。

下面的生成器比您当前的方法更有效,并且它避免了在 RAM 中保存大量临时列表。核心思想是使用 itertools.product 为偶数槽生成组合,然后再次使用 product 来填充满足选择标准#1 的奇数槽。我们使用集合操作来确保最终组合包含 alleles.

中的每个项目
from itertools import product

def combine_alleles(alleles, numb_alleles):
    ''' Make combinations that conform to the selection criteria. First create
        the items for the even slots, then create items for the odd slots such
        that each odd slot item >= the corresponding even slot item. Then test
        that the whole combination contains each item in alleles.
    '''
    # If the number of unique items in the even slots is < min_len, then it's
    # impossible to make a full combination containing all of the alleles.
    min_len = len(alleles) - numb_alleles // 2

    # Create a function to test if a given combination
    # contains all of the alleles.
    alleles_set = set(alleles)
    complete = alleles_set.issubset

    # Make lists of alleles that are >= the current allele number
    higher = {k: [u for u in alleles if u >= k] for k in alleles}

    # Make combinations for the even slots
    for evens in product(alleles, repeat=numb_alleles // 2):
        if len(set(evens)) < min_len:
            continue
        # Make combinations for the odd slots that go with this
        # combination of evens.
        a = [higher[u] for u in evens]
        for odds in product(*a):
            if complete(evens + odds):
                yield [u for pair in zip(evens, odds) for u in pair]

# test

alleles = [11, 12, 13, 14, 15, 16]
numb_alleles = 8

for i, t in enumerate(combine_alleles(alleles, numb_alleles), 1):
    print(i, t)

此代码找到 16020 个组合,因此输出太大,无法包含在此处。


这是一个更接近您的版本的替代生成器,但在我的测试中它比我的第一个版本慢一点。

def combine_alleles(alleles, numb_alleles):
    total_len = len(alleles)

    # Make lists of alleles that are >= the current allele number
    higher = {k: [u for u in alleles if u >= k] for k in alleles}

    def combos(i, base):
        remaining = numb_alleles - i
        if len(set(base)) + remaining < total_len:
            return

        if remaining == 0:
            yield base
            return

        ii = i + 1
        for u in higher[base[-1]] if i % 2 else alleles:
           yield from combos(ii, base + [u])

    yield from combos(0, [])

此版本适用于 Python 3。Python 2 没有 yield from,但这很容易修复:

yield from some_iterable

等同于

for t in some_iterable:
    yield t