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)

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