将一维数组重塑为接近正方形的二维数组

import numpy as np
from math import isqrt

def np_squarishrt(n):
    """
    Finds two factors of n, p and q, such that p * q == n and p is as close as possible to sqrt(n).
    """
    a = np.arange(1, isqrt(n) + 1, dtype=int) # Changed to include isqrt(n) itself
    b = n // a
    i = np.where(a * b == n)[0][-1]
    return a[i], b[i]

a = np.arange(500)
b = a.reshape(np_squarishrt(len(a)))
print(b.shape)  # 输出 (20, 25)

from itertools import chain, combinations
from math import isqrt
import numpy as np

def factors(n):
    """
    Generates the prime factors of n using the Sieve of Eratosthenes.
    """
    while n > 1:
        for i in range(2, int(n + 1)): # Changed n to int(n + 1) to avoid float errors
            if n % i == 0:
                n //= i
                yield i
                break


def uniq_powerset(iterable):
    """
    Generates the unique combinations of elements from an iterable.
    """
    s = list(iterable)
    return chain.from_iterable(set(combinations(s, r)) for r in range(len(s)+1))


def squarishrt(n):
    """
    Finds two factors of n, p and q, such that p * q == n and p is as close as possible to sqrt(n).
    """
    p = isqrt(n)
    if p**2 == n:
        return p, p
    bestp = 1
    f = list(factors(n))
    for t in uniq_powerset(f):
        if 2 * len(t) > len(f):
            break
        p = np.prod(t) if t else 1
        q = n // p
        if p > q:
            p, q = q, p
        if p > bestp:
            bestp = p
    return bestp, n // bestp

a = np.arange(500)
b = a.reshape(squarishrt(len(a)))
print(b.shape)  # 输出 (20, 25)