Brute Force || Palindrome Computation
Intuition\n Describe your first thoughts on how to solve this problem. \nThe task here is to minimize the cost of transforming an array into a palindrome. The c
# Intuition\n<!-- Describe your first thoughts on how to solve this problem. -->\nThe task here is to minimize the cost of transforming an array into a palindrome. The cost is computed as the sum of absolute differences between each array element and a suggested median value.\n# Approach\n<!-- Describe your approach to solving the problem. -->\nIn our first pass, we find the median of the array. If this median is already a palindrome, we\'re done, and the cost is computed using this median. Otherwise, we explore potential palindromes by considering numbers with the same prefix and their mirrored counterparts.\n# Complexity\n- Time complexity: `O(n * m)`, where `n` is the number of elements in the array and `m` is the length of the median.\n- Space complexity: `O(1)`, as the space used is constant.\n# Code\n```\nimport numpy as np\n\ndef calculate_cost(nums, median):\n    total_cost = 0\n    for num in nums:\n        total_cost += abs(num - median)\n    return total_cost\n\ndef explore_potential_palindromes(x):\n    x_str = str(x)\n    n = len(x_str)\n    m = (n + 1) // 2\n\n    prefix = int(x_str[:m])\n\n    possible_palindromes = [10**n - 1, 10**(n - 1) - 1]\n    other_possible = [prefix, prefix - 1, prefix + 1]\n\n    for some in other_possible:\n        some_str = str(some)\n        if n % 2 != 0:\n            some_str = some_str[:-1]\n        mirrored_part = some_str[::-1]\n        palindrome_candidate = str(some) + mirrored_part\n        possible_palindromes.append(int(palindrome_candidate))\n\n    return possible_palindromes\n\nclass Solution:\n    def minimumCost(self, nums: List[int]) -> int:\n        suggested_median = int(np.median(nums))\n        median_str = str(suggested_median)\n\n        if median_str == median_str[::-1]:\n            return calculate_cost(nums, suggested_median)\n\n        potential_palindromes = explore_potential_palindromes(suggested_median)\n        min_cost = float(\'inf\')\n\n        for candidate in potential_palindromes:\n            min_cost = min(min_cost, calculate_cost(nums, candidate))\n\n        return min_cost\n```\n### \u270D\uFE0F Random Dev Quote\n![](https://quotes-github-readme.vercel.app/api?type=horizontal&theme=gruvbox)\n
['Python3']