OPENAI 01が生成したQ&Aを発見
OPENAI01が回答した公開質問を発見
Fair Jewelry Distribution Fix
"from typing import List def fair_jewelry_distribution(v: List[int]) -> str: n = len(v) idx = sorted(range(n), key=lambda i: -v[i]) best_asn = None best_diff = None for init in 'ABC': asn = [''] * n b_sum = c_sum = b_cnt = c_cnt = 0 i = idx[0] asn[i] = init if init == 'B': b_sum += v[i] b_cnt += 1 elif init == 'C': c_sum += v[i] c_cnt += 1 for i in idx[1:]: if b_sum < c_sum: asn[i] = 'B' b_sum += v[i] b_cnt += 1 else: asn[i] = 'C' c_sum += v[i] c_cnt += 1 imp = True while imp: imp = False best_local_diff = abs(b_sum - c_sum) best_move = None for i in range(n): cur_owner = asn[i] if cur_owner == 'B': if c_cnt >= 1: new_diff = abs((b_sum - v[i]) - (c_sum + v[i])) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'C') new_diff = abs((b_sum - v[i]) - c_sum) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') elif cur_owner == 'C': if b_cnt >= 1: new_diff = abs((b_sum + v[i]) - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') else: # cur_owner == 'A' new_diff = abs((b_sum + v[i]) - c_sum) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum + v[i])) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'C') for i in range(n): for j in range(n): if asn[i] != asn[j]: o_i, o_j = asn[i], asn[j] b_sum_new = b_sum c_sum_new = c_sum b_cnt_new = b_cnt c_cnt_new = c_cnt if o_i == 'B': b_sum_new -= v[i] b_cnt_new -= 1 elif o_i == 'C': c_sum_new -= v[i] c_cnt_new -= 1 if o_j == 'B': b_sum_new -= v[j] b_cnt_new -= 1 elif o_j == 'C': c_sum_new -= v[j] c_cnt_new -= 1 if o_j == 'B': b_sum_new += v[i] b_cnt_new += 1 elif o_j == 'C': c_sum_new += v[i] c_cnt_new += 1 if o_i == 'B': b_sum_new += v[j] b_cnt_new += 1 elif o_i == 'C': c_sum_new += v[j] c_cnt_new += 1 if b_cnt_new > 0 and c_cnt_new > 0: new_diff = abs(b_sum_new - c_sum_new) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('swap', i, j) if best_move: if best_move[0] == 'move': _, i, new_owner = best_move old_owner = asn[i] if old_owner == 'B': b_sum -= v[i] b_cnt -= 1 elif old_owner == 'C': c_sum -= v[i] c_cnt -= 1 if new_owner == 'B': b_sum += v[i] b_cnt += 1 elif new_owner == 'C': c_sum += v[i] c_cnt += 1 asn[i] = new_owner imp = True elif best_move[0] == 'swap': _, i, j = best_move o_i, o_j = asn[i], asn[j] asn[i], asn[j] = o_j, o_i if o_i == 'B': b_sum -= v[i] b_cnt -= 1 elif o_i == 'C': c_sum -= v[i] c_cnt -= 1 if o_j == 'B': b_sum -= v[j] b_cnt -= 1 elif o_j == 'C': c_sum -= v[j] c_cnt -= 1 if o_j == 'B': b_sum += v[i] b_cnt += 1 elif o_j == 'C': c_sum += v[i] c_cnt += 1 if o_i == 'B': b_sum += v[j] b_cnt += 1 elif o_i == 'C': c_sum += v[j] c_cnt += 1 imp = True if b_cnt == 0 or c_cnt == 0: for i in range(n): if asn[i] == 'A': if b_cnt == 0: asn[i] = 'B' b_sum += v[i] b_cnt += 1 break elif c_cnt == 0: asn[i] = 'C' c_sum += v[i] c_cnt += 1 break diff = abs(b_sum - c_sum) if best_diff is None or diff < best_diff: best_diff = diff best_asn = asn.copy() return ''.join(best_asn)" TL;DR Select from a list of positive integers two non-empty disjoint subsets that minimize the difference between their sums. Problem Statement Alice has a collection of n valuable jewelry items, each with a specific value. She wants to divide some of these items between her two children, Bob and Carol, such that both receive at least one item. Alice’s goal is to ensure fairness in the distribution by minimizing the difference in the total value of the items given to Bob and Carol. Your task is to help Alice determine a way to distribute the jewelry between Bob and Carol that minimizes the difference in their respective total values. Input A list of n positive integers values, where values[i] represents the value of the i-th jewelry item. Constraints 2 <= n < 500 1 <= values[i] < 2^32 Output A string of n characters output, where output[i] has to be one of the following: A — the i-th item is kept by Alice. B — the i-th item is given to Bob. C — the i-th item is given to Carol. Example Input [39, 44, 9, 57] Output BCBA Explanation One way to distribute the items: Bob gets items with values 39 and 9, for a total of 48. Carol gets the item with a value of 44, for a total of 44. The difference between their total values is ∣48 − 44∣ = 4, which is minimized. The item with value 57 is not distributed in this case. In addition, CBCA, ABBC, and ACCB are all considered correct. I get the error message "Difference too large.: 2552253 should equal 0." [3312443431, 1620086332, 3082128354, 2633632741, 2178198869, 1237839727, 4249808474, 3532791149, 1303708026, 2523730641, 37 79202129, 2351949559, 2047245187, 4119249656, 782379584, 600679180, 428691842, 3929207130, 2757546813, 4040425163, This is a test case with the format expected-diff should equal output-diff. Do you know the cause? The above problem is the problem that has been solved so far, and the code above it is the problem. Also, if you find the cause, I would appreciate it if you could fix it. Please try to keep the solution as unchanged as possible.
Jewelry Distribution Correction
"from typing import List def fair_jewelry_distribution(v: List[int]) -> str: n = len(v) idx = sorted(range(n), key=lambda i: -v[i]) best_asn = None best_diff = None for init in 'ABC': asn = [''] * n b_sum = c_sum = b_cnt = c_cnt = 0 i = idx[0] asn[i] = init if init == 'B': b_sum += v[i] b_cnt += 1 elif init == 'C': c_sum += v[i] c_cnt += 1 for i in idx[1:]: if b_sum < c_sum: asn[i] = 'B' b_sum += v[i] b_cnt += 1 else: asn[i] = 'C' c_sum += v[i] c_cnt += 1 imp = True while imp: imp = False best_local_diff = abs(b_sum - c_sum) best_move = None for i in range(n): cur_owner = asn[i] if cur_owner == 'B': if c_cnt >= 1: new_diff = abs((b_sum - v[i]) - (c_sum + v[i])) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'C') new_diff = abs((b_sum - v[i]) - c_sum) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') elif cur_owner == 'C': if b_cnt >= 1: new_diff = abs((b_sum + v[i]) - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') else: # cur_owner == 'A' new_diff = abs((b_sum + v[i]) - c_sum) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum + v[i])) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'C') for i in range(n): for j in range(n): if asn[i] != asn[j]: o_i, o_j = asn[i], asn[j] b_sum_new = b_sum c_sum_new = c_sum b_cnt_new = b_cnt c_cnt_new = c_cnt if o_i == 'B': b_sum_new -= v[i] b_cnt_new -= 1 elif o_i == 'C': c_sum_new -= v[i] c_cnt_new -= 1 if o_j == 'B': b_sum_new -= v[j] b_cnt_new -= 1 elif o_j == 'C': c_sum_new -= v[j] c_cnt_new -= 1 if o_j == 'B': b_sum_new += v[i] b_cnt_new += 1 elif o_j == 'C': c_sum_new += v[i] c_cnt_new += 1 if o_i == 'B': b_sum_new += v[j] b_cnt_new += 1 elif o_i == 'C': c_sum_new += v[j] c_cnt_new += 1 if b_cnt_new > 0 and c_cnt_new > 0: new_diff = abs(b_sum_new - c_sum_new) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('swap', i, j) if best_move: if best_move[0] == 'move': _, i, new_owner = best_move old_owner = asn[i] if old_owner == 'B': b_sum -= v[i] b_cnt -= 1 elif old_owner == 'C': c_sum -= v[i] c_cnt -= 1 if new_owner == 'B': b_sum += v[i] b_cnt += 1 elif new_owner == 'C': c_sum += v[i] c_cnt += 1 asn[i] = new_owner imp = True elif best_move[0] == 'swap': _, i, j = best_move o_i, o_j = asn[i], asn[j] asn[i], asn[j] = o_j, o_i if o_i == 'B': b_sum -= v[i] b_cnt -= 1 elif o_i == 'C': c_sum -= v[i] c_cnt -= 1 if o_j == 'B': b_sum -= v[j] b_cnt -= 1 elif o_j == 'C': c_sum -= v[j] c_cnt -= 1 if o_j == 'B': b_sum += v[i] b_cnt += 1 elif o_j == 'C': c_sum += v[i] c_cnt += 1 if o_i == 'B': b_sum += v[j] b_cnt += 1 elif o_i == 'C': c_sum += v[j] c_cnt += 1 imp = True if b_cnt == 0 or c_cnt == 0: for i in range(n): if asn[i] == 'A': if b_cnt == 0: asn[i] = 'B' b_sum += v[i] b_cnt += 1 break elif c_cnt == 0: asn[i] = 'C' c_sum += v[i] c_cnt += 1 break diff = abs(b_sum - c_sum) if best_diff is None or diff < best_diff: best_diff = diff best_asn = asn.copy() return ''.join(best_asn)" TL;DR Select from a list of positive integers two non-empty disjoint subsets that minimize the difference between their sums. Problem Statement Alice has a collection of n valuable jewelry items, each with a specific value. She wants to divide some of these items between her two children, Bob and Carol, such that both receive at least one item. Alice’s goal is to ensure fairness in the distribution by minimizing the difference in the total value of the items given to Bob and Carol. Your task is to help Alice determine a way to distribute the jewelry between Bob and Carol that minimizes the difference in their respective total values. Input A list of n positive integers values, where values[i] represents the value of the i-th jewelry item. Constraints 2 <= n < 500 1 <= values[i] < 2^32 Output A string of n characters output, where output[i] has to be one of the following: A — the i-th item is kept by Alice. B — the i-th item is given to Bob. C — the i-th item is given to Carol. Example Input [39, 44, 9, 57] Output BCBA Explanation One way to distribute the items: Bob gets items with values 39 and 9, for a total of 48. Carol gets the item with a value of 44, for a total of 44. The difference between their total values is ∣48 − 44∣ = 4, which is minimized. The item with value 57 is not distributed in this case. In addition, CBCA, ABBC, and ACCB are all considered correct. I get an error message saying "Difference too large.: 2552253 should equal 0." It's in the form of "expected-diff should equal output-diff." Do you know the cause? The problem above is the problem I've solved so far, and the code above that is the problem. Also, if you find the cause, I'd be happy if you could fix it. I'd like you to keep the solution as unchanged as possible.
Fair Jewelry Distribution Fix
"from typing import List def fair_jewelry_distribution(v: List[int]) -> str: n = len(v) idx = sorted(range(n), key=lambda i: -v[i]) best_asn = None best_diff = None for init in 'ABC': asn = [''] * n b_sum = c_sum = b_cnt = c_cnt = 0 i = idx[0] asn[i] = init if init == 'B': b_sum += v[i] b_cnt += 1 elif init == 'C': c_sum += v[i] c_cnt += 1 for i in idx[1:]: if b_sum < c_sum: asn[i] = 'B' b_sum += v[i] b_cnt += 1 else: asn[i] = 'C' c_sum += v[i] c_cnt += 1 imp = True while imp: imp = False best_local_diff = abs(b_sum - c_sum) best_move = None for i in range(n): cur_owner = asn[i] if cur_owner == 'B': if c_cnt >= 1: new_diff = abs((b_sum - v[i]) - (c_sum + v[i])) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'C') new_diff = abs((b_sum - v[i]) - c_sum) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') elif cur_owner == 'C': if b_cnt >= 1: new_diff = abs((b_sum + v[i]) - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') else: # cur_owner == 'A' new_diff = abs((b_sum + v[i]) - c_sum) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum + v[i])) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'C') for i in range(n): for j in range(n): if asn[i] != asn[j]: o_i, o_j = asn[i], asn[j] b_sum_new = b_sum c_sum_new = c_sum b_cnt_new = b_cnt c_cnt_new = c_cnt if o_i == 'B': b_sum_new -= v[i] b_cnt_new -= 1 elif o_i == 'C': c_sum_new -= v[i] c_cnt_new -= 1 if o_j == 'B': b_sum_new -= v[j] b_cnt_new -= 1 elif o_j == 'C': c_sum_new -= v[j] c_cnt_new -= 1 if o_j == 'B': b_sum_new += v[i] b_cnt_new += 1 elif o_j == 'C': c_sum_new += v[i] c_cnt_new += 1 if o_i == 'B': b_sum_new += v[j] b_cnt_new += 1 elif o_i == 'C': c_sum_new += v[j] c_cnt_new += 1 if b_cnt_new > 0 and c_cnt_new > 0: new_diff = abs(b_sum_new - c_sum_new) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('swap', i, j) if best_move: if best_move[0] == 'move': _, i, new_owner = best_move old_owner = asn[i] if old_owner == 'B': b_sum -= v[i] b_cnt -= 1 elif old_owner == 'C': c_sum -= v[i] c_cnt -= 1 if new_owner == 'B': b_sum += v[i] b_cnt += 1 elif new_owner == 'C': c_sum += v[i] c_cnt += 1 asn[i] = new_owner imp = True elif best_move[0] == 'swap': _, i, j = best_move o_i, o_j = asn[i], asn[j] asn[i], asn[j] = o_j, o_i if o_i == 'B': b_sum -= v[i] b_cnt -= 1 elif o_i == 'C': c_sum -= v[i] c_cnt -= 1 if o_j == 'B': b_sum -= v[j] b_cnt -= 1 elif o_j == 'C': c_sum -= v[j] c_cnt -= 1 if o_j == 'B': b_sum += v[i] b_cnt += 1 elif o_j == 'C': c_sum += v[i] c_cnt += 1 if o_i == 'B': b_sum += v[j] b_cnt += 1 elif o_i == 'C': c_sum += v[j] c_cnt += 1 imp = True if b_cnt == 0 or c_cnt == 0: for i in range(n): if asn[i] == 'A': if b_cnt == 0: asn[i] = 'B' b_sum += v[i] b_cnt += 1 break elif c_cnt == 0: asn[i] = 'C' c_sum += v[i] c_cnt += 1 break diff = abs(b_sum - c_sum) if best_diff is None or diff < best_diff: best_diff = diff best_asn = asn.copy() return ''.join(best_asn)" TL;DR Select from a list of positive integers two non-empty disjoint subsets that minimize the difference between their sums. Problem Statement Alice has a collection of n valuable jewelry items, each with a specific value. She wants to divide some of these items between her two children, Bob and Carol, such that both receive at least one item. Alice’s goal is to ensure fairness in the distribution by minimizing the difference in the total value of the items given to Bob and Carol. Your task is to help Alice determine a way to distribute the jewelry between Bob and Carol that minimizes the difference in their respective total values. Input A list of n positive integers values, where values[i] represents the value of the i-th jewelry item. Constraints 2 <= n < 500 1 <= values[i] < 2^32 Output A string of n characters output, where output[i] has to be one of the following: A — the i-th item is kept by Alice. B — the i-th item is given to Bob. C — the i-th item is given to Carol. Example Input [39, 44, 9, 57] Output BCBA Explanation One way to distribute the items: Bob gets items with values 39 and 9, for a total of 48. Carol gets the item with a value of 44, for a total of 44. The difference between their total values is ∣48 − 44∣ = 4, which is minimized. The item with value 57 is not distributed in this case. In addition, CBCA, ABBC, and ACCB are all considered correct. I get an error message saying "Difference too large.: 2552253 should equal 0." It's in the form of "expected-diff should equal output-diff." Do you know the cause? The problem above is the problem I've solved so far, and the code above that is the problem. Also, if you find the cause, I'd be happy if you could fix it. I'd like you to keep the solution as unchanged as possible.
Jewelry Distribution Algorithm Issue
"from typing import List def fair_jewelry_distribution(v: List[int]) -> str: n = len(v) idx = sorted(range(n), key=lambda i: -v[i]) best_asn = None best_diff = None for init in 'ABC': asn = [''] * n b_sum = c_sum = b_cnt = c_cnt = 0 i = idx[0] asn[i] = init if init == 'B': b_sum += v[i] b_cnt += 1 elif init == 'C': c_sum += v[i] c_cnt += 1 for i in idx[1:]: if b_sum < c_sum: asn[i] = 'B' b_sum += v[i] b_cnt += 1 else: asn[i] = 'C' c_sum += v[i] c_cnt += 1 imp = True while imp: imp = False best_local_diff = abs(b_sum - c_sum) best_move = None for i in range(n): cur_owner = asn[i] if cur_owner == 'B': if c_cnt >= 1: new_diff = abs((b_sum - v[i]) - (c_sum + v[i])) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'C') new_diff = abs((b_sum - v[i]) - c_sum) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') elif cur_owner == 'C': if b_cnt >= 1: new_diff = abs((b_sum + v[i]) - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') else: # cur_owner == 'A' new_diff = abs((b_sum + v[i]) - c_sum) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum + v[i])) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'C') for i in range(n): for j in range(n): if asn[i] != asn[j]: o_i, o_j = asn[i], asn[j] b_sum_new = b_sum c_sum_new = c_sum b_cnt_new = b_cnt c_cnt_new = c_cnt if o_i == 'B': b_sum_new -= v[i] b_cnt_new -= 1 elif o_i == 'C': c_sum_new -= v[i] c_cnt_new -= 1 if o_j == 'B': b_sum_new -= v[j] b_cnt_new -= 1 elif o_j == 'C': c_sum_new -= v[j] c_cnt_new -= 1 if o_j == 'B': b_sum_new += v[i] b_cnt_new += 1 elif o_j == 'C': c_sum_new += v[i] c_cnt_new += 1 if o_i == 'B': b_sum_new += v[j] b_cnt_new += 1 elif o_i == 'C': c_sum_new += v[j] c_cnt_new += 1 if b_cnt_new > 0 and c_cnt_new > 0: new_diff = abs(b_sum_new - c_sum_new) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('swap', i, j) if best_move: if best_move[0] == 'move': _, i, new_owner = best_move old_owner = asn[i] if old_owner == 'B': b_sum -= v[i] b_cnt -= 1 elif old_owner == 'C': c_sum -= v[i] c_cnt -= 1 if new_owner == 'B': b_sum += v[i] b_cnt += 1 elif new_owner == 'C': c_sum += v[i] c_cnt += 1 asn[i] = new_owner imp = True elif best_move[0] == 'swap': _, i, j = best_move o_i, o_j = asn[i], asn[j] asn[i], asn[j] = o_j, o_i if o_i == 'B': b_sum -= v[i] b_cnt -= 1 elif o_i == 'C': c_sum -= v[i] c_cnt -= 1 if o_j == 'B': b_sum -= v[j] b_cnt -= 1 elif o_j == 'C': c_sum -= v[j] c_cnt -= 1 if o_j == 'B': b_sum += v[i] b_cnt += 1 elif o_j == 'C': c_sum += v[i] c_cnt += 1 if o_i == 'B': b_sum += v[j] b_cnt += 1 elif o_i == 'C': c_sum += v[j] c_cnt += 1 imp = True if b_cnt == 0 or c_cnt == 0: for i in range(n): if asn[i] == 'A': if b_cnt == 0: asn[i] = 'B' b_sum += v[i] b_cnt += 1 break elif c_cnt == 0: asn[i] = 'C' c_sum += v[i] c_cnt += 1 break diff = abs(b_sum - c_sum) if best_diff is None or diff < best_diff: best_diff = diff best_asn = asn.copy() return ''.join(best_asn)" TL;DR Select from a list of positive integers two non-empty disjoint subsets that minimize the difference between their sums. Problem Statement Alice has a collection of n valuable jewelry items, each with a specific value. She wants to divide some of these items between her two children, Bob and Carol, such that both receive at least one item. Alice’s goal is to ensure fairness in the distribution by minimizing the difference in the total value of the items given to Bob and Carol. Your task is to help Alice determine a way to distribute the jewelry between Bob and Carol that minimizes the difference in their respective total values. Input A list of n positive integers values, where values[i] represents the value of the i-th jewelry item. Constraints 2 <= n < 500 1 <= values[i] < 2^32 Output A string of n characters output, where output[i] has to be one of the following: A — the i-th item is kept by Alice. B — the i-th item is given to Bob. C — the i-th item is given to Carol. Example Input [39, 44, 9, 57] Output BCBA Explanation One way to distribute the items: Bob gets items with values 39 and 9, for a total of 48. Carol gets the item with a value of 44, for a total of 44. The difference between their total values is ∣48 − 44∣ = 4, which is minimized. The item with value 57 is not distributed in this case. In addition, CBCA, ABBC, and ACCB are all considered correct. I get an error message saying "Difference too large.: 2552253 should equal 0." It's in the form of "expected-diff should equal output-diff." Do you know the cause? The problem above is the problem I've solved so far, and the code above that is the problem. Also, if you find the cause, I'd be grateful if you could fix it.
貪欲法の最適化問題
"#こんな難しい問題初めてなんだが・・・ #貪欲法（だと思う）をすればいい。最初ちょっと混乱してしまった #↓ #どうやらWrong Answerらしい。 #ちょっと考え直してみた #とにかく難しい貪欲法.こんなムズイの？やばいな #意味が分からん from typing import List def fair_jewelry_distribution(v: List[int]) -> str: n = len(v) idx = sorted(range(n), key=lambda i: -v[i]) best_asn = None best_diff = None for init in 'ABC': asn = [''] * n b_sum = c_sum = b_cnt = c_cnt = 0 i = idx[0] asn[i] = init if init == 'B': b_sum += v[i] b_cnt += 1 elif init == 'C': c_sum += v[i] c_cnt += 1 for i in idx[1:]: if b_sum < c_sum: asn[i] = 'B' b_sum += v[i] b_cnt += 1 else: asn[i] = 'C' c_sum += v[i] c_cnt += 1 imp = True while imp: imp = False best_local_diff = abs(b_sum - c_sum) best_move = None for i in range(n): cur_owner = asn[i] if cur_owner == 'B': if c_cnt >= 1: new_diff = abs((b_sum - v[i]) - (c_sum + v[i])) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'C') new_diff = abs((b_sum - v[i]) - c_sum) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') elif cur_owner == 'C': if b_cnt >= 1: new_diff = abs((b_sum + v[i]) - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') else: # cur_owner == 'A' new_diff = abs((b_sum + v[i]) - c_sum) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum + v[i])) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'C') for i in range(n): for j in range(n): if asn[i] != asn[j]: o_i, o_j = asn[i], asn[j] b_sum_new = b_sum c_sum_new = c_sum b_cnt_new = b_cnt c_cnt_new = c_cnt if o_i == 'B': b_sum_new -= v[i] b_cnt_new -= 1 elif o_i == 'C': c_sum_new -= v[i] c_cnt_new -= 1 if o_j == 'B': b_sum_new -= v[j] b_cnt_new -= 1 elif o_j == 'C': c_sum_new -= v[j] c_cnt_new -= 1 if o_j == 'B': b_sum_new += v[i] b_cnt_new += 1 elif o_j == 'C': c_sum_new += v[i] c_cnt_new += 1 if o_i == 'B': b_sum_new += v[j] b_cnt_new += 1 elif o_i == 'C': c_sum_new += v[j] c_cnt_new += 1 if b_cnt_new > 0 and c_cnt_new > 0: new_diff = abs(b_sum_new - c_sum_new) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('swap', i, j) if best_move: if best_move[0] == 'move': _, i, new_owner = best_move old_owner = asn[i] if old_owner == 'B': b_sum -= v[i] b_cnt -= 1 elif old_owner == 'C': c_sum -= v[i] c_cnt -= 1 if new_owner == 'B': b_sum += v[i] b_cnt += 1 elif new_owner == 'C': c_sum += v[i] c_cnt += 1 asn[i] = new_owner imp = True elif best_move[0] == 'swap': _, i, j = best_move o_i, o_j = asn[i], asn[j] asn[i], asn[j] = o_j, o_i if o_i == 'B': b_sum -= v[i] b_cnt -= 1 elif o_i == 'C': c_sum -= v[i] c_cnt -= 1 if o_j == 'B': b_sum -= v[j] b_cnt -= 1 elif o_j == 'C': c_sum -= v[j] c_cnt -= 1 if o_j == 'B': b_sum += v[i] b_cnt += 1 elif o_j == 'C': c_sum += v[i] c_cnt += 1 if o_i == 'B': b_sum += v[j] b_cnt += 1 elif o_i == 'C': c_sum += v[j] c_cnt += 1 imp = True if b_cnt == 0 or c_cnt == 0: for i in range(n): if asn[i] == 'A': if b_cnt == 0: asn[i] = 'B' b_sum += v[i] b_cnt += 1 break elif c_cnt == 0: asn[i] = 'C' c_sum += v[i] c_cnt += 1 break diff = abs(b_sum - c_sum) if best_diff is None or diff < best_diff: best_diff = diff best_asn = asn.copy() return ''.join(best_asn)" TL;DR Select from a list of positive integers two non-empty disjoint subsets that minimize the difference between their sums. Problem Statement Alice has a collection of n valuable jewelry items, each with a specific value. She wants to divide some of these items between her two children, Bob and Carol, such that both receive at least one item. Alice’s goal is to ensure fairness in the distribution by minimizing the difference in the total value of the items given to Bob and Carol. Your task is to help Alice determine a way to distribute the jewelry between Bob and Carol that minimizes the difference in their respective total values. Input A list of n positive integers values, where values[i] represents the value of the i-th jewelry item. Constraints 2 <= n < 500 1 <= values[i] < 2^32 Output A string of n characters output, where output[i] has to be one of the following: A — the i-th item is kept by Alice. B — the i-th item is given to Bob. C — the i-th item is given to Carol. Example Input [39, 44, 9, 57] Output BCBA Explanation One way to distribute the items: Bob gets items with values 39 and 9, for a total of 48. Carol gets the item with a value of 44, for a total of 44. The difference between their total values is ∣48 − 44∣ = 4, which is minimized. The item with value 57 is not distributed in this case. In addition, CBCA, ABBC, and ACCB are all considered correct. I get an error message saying "Difference too large.: 2552253 should equal 0." It's in the form of "expected-diff should equal output-diff." Do you know the cause? The problem above is the problem I've solved so far, and the code above that is the problem. Also, if you find the cause, I'd be grateful if you could fix it.
Fair Jewelry Distribution Code
"rom typing import List def fair_jewelry_distribution(v: List[int]) -> str: n = len(v) idx = sorted(range(n), key=lambda i: -v[i]) best_asn = None best_diff = None for init in 'ABC': asn = [''] * n b_sum = c_sum = b_cnt = c_cnt = 0 i = idx[0] asn[i] = init if init == 'B': b_sum += v[i] b_cnt += 1 elif init == 'C': c_sum += v[i] c_cnt += 1 for i in idx[1:]: if b_sum < c_sum: asn[i] = 'B' b_sum += v[i] b_cnt += 1 else: asn[i] = 'C' c_sum += v[i] c_cnt += 1 imp = True while imp: imp = False best_local_diff = abs(b_sum - c_sum) best_move = None for i in range(n): cur_owner = asn[i] if cur_owner == 'B': if c_cnt >= 1: new_diff = abs((b_sum - v[i]) - (c_sum + v[i])) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'C') new_diff = abs((b_sum - v[i]) - c_sum) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') elif cur_owner == 'C': if b_cnt >= 1: new_diff = abs((b_sum + v[i]) - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') else: # cur_owner == 'A' new_diff = abs((b_sum + v[i]) - c_sum) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum + v[i])) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'C') for i in range(n): for j in range(n): if asn[i] != asn[j]: o_i, o_j = asn[i], asn[j] b_sum_new = b_sum c_sum_new = c_sum b_cnt_new = b_cnt c_cnt_new = c_cnt if o_i == 'B': b_sum_new -= v[i] b_cnt_new -= 1 elif o_i == 'C': c_sum_new -= v[i] c_cnt_new -= 1 if o_j == 'B': b_sum_new -= v[j] b_cnt_new -= 1 elif o_j == 'C': c_sum_new -= v[j] c_cnt_new -= 1 if o_j == 'B': b_sum_new += v[i] b_cnt_new += 1 elif o_j == 'C': c_sum_new += v[i] c_cnt_new += 1 if o_i == 'B': b_sum_new += v[j] b_cnt_new += 1 elif o_i == 'C': c_sum_new += v[j] c_cnt_new += 1 if ((b_cnt_new > 0 or ('B' not in [o_i, o_j])) and (c_cnt_new > 0 or ('C' not in [o_i, o_j]))): new_diff = abs(b_sum_new - c_sum_new) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('swap', i, j) if best_move: if best_move[0] == 'move': _, i, new_owner = best_move old_owner = asn[i] if old_owner == 'B': b_sum -= v[i] b_cnt -= 1 elif old_owner == 'C': c_sum -= v[i] c_cnt -= 1 if new_owner == 'B': b_sum += v[i] b_cnt += 1 elif new_owner == 'C': c_sum += v[i] c_cnt += 1 asn[i] = new_owner imp = True elif best_move[0] == 'swap': _, i, j = best_move o_i, o_j = asn[i], asn[j] asn[i], asn[j] = o_j, o_i if o_i == 'B': b_sum -= v[i] b_cnt -= 1 elif o_i == 'C': c_sum -= v[i] c_cnt -= 1 if o_j == 'B': b_sum -= v[j] b_cnt -= 1 elif o_j == 'C': c_sum -= v[j] c_cnt -= 1 if o_j == 'B': b_sum += v[i] b_cnt += 1 elif o_j == 'C': c_sum += v[i] c_cnt += 1 if o_i == 'B': b_sum += v[j] b_cnt += 1 elif o_i == 'C': c_sum += v[j] c_cnt += 1 imp = True if b_cnt == 0 or c_cnt == 0: for i in range(n): if asn[i] == 'A': if b_cnt == 0: asn[i] = 'B' b_sum += v[i] b_cnt += 1 break elif c_cnt == 0: asn[i] = 'C' c_sum += v[i] c_cnt += 1 break diff = abs(b_sum - c_sum) if best_diff is None or diff < best_diff: best_diff = diff best_asn = asn.copy() return ''.join(best_asn)" TL;DR Select from a list of positive integers two non-empty disjoint subsets that minimize the difference between their sums. Problem Statement Alice has a collection of n valuable jewelry items, each with a specific value. She wants to divide some of these items between her two children, Bob and Carol, such that both receive at least one item. Alice’s goal is to ensure fairness in the distribution by minimizing the difference in the total value of the items given to Bob and Carol. Your task is to help Alice determine a way to distribute the jewelry between Bob and Carol that minimizes the difference in their respective total values. Input A list of n positive integers values, where values[i] represents the value of the i-th jewelry item. Constraints 2 <= n < 500 1 <= values[i] < 2^32 Output A string of n characters output, where output[i] has to be one of the following: A — the i-th item is kept by Alice. B — the i-th item is given to Bob. C — the i-th item is given to Carol. Example Input [39, 44, 9, 57] Output BCBA Explanation One way to distribute the items: Bob gets items with values 39 and 9, for a total of 48. Carol gets the item with a value of 44, for a total of 44. The difference between their total values is ∣48 − 44∣ = 4, which is minimized. The item with value 57 is not distributed in this case. In addition, CBCA, ABBC, and ACCB are all considered correct. Wrong Answer (Difference too large.: 57523 should equal 0.The test case is equal to the answer, so it cannot be seen, but there are cases where the difference can be narrowed further. Correction)
公正な宝石配分
"#こんな難しい問題初めてなんだが・・・ #貪欲法（だと思う）をすればいい。最初ちょっと混乱してしまった from typing import List def fair_jewelry_distribution(v: List[int]) -> str: n = len(v) idx = sorted(range(n), key=lambda i: -v[i]) best_asn = None best_diff = None for init in 'ABC': asn = [''] * n b_sum = c_sum = b_cnt = c_cnt = 0 i = idx[0] asn[i] = init if init == 'B': b_sum += v[i] b_cnt += 1 elif init == 'C': c_sum += v[i] c_cnt += 1 for i in idx[1:]: if b_sum < c_sum: asn[i] = 'B' b_sum += v[i] b_cnt += 1 else: asn[i] = 'C' c_sum += v[i] c_cnt += 1 imp = True while imp: imp = False best_local_diff = abs(b_sum - c_sum) best_move = None for i in range(n): cur_owner = asn[i] if cur_owner == 'B': if c_cnt >= 1: new_diff = abs((b_sum - v[i]) - (c_sum + v[i])) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'C') new_diff = abs((b_sum - v[i]) - c_sum) if new_diff < best_local_diff and b_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') elif cur_owner == 'C': if b_cnt >= 1: new_diff = abs((b_sum + v[i]) - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum - v[i])) if new_diff < best_local_diff and c_cnt > 1: best_local_diff = new_diff best_move = ('move', i, 'A') else: # cur_owner == 'A' new_diff = abs((b_sum + v[i]) - c_sum) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'B') new_diff = abs(b_sum - (c_sum + v[i])) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('move', i, 'C') for i in range(n): for j in range(n): if asn[i] == 'B' and asn[j] == 'C': new_diff = abs((b_sum - v[i] + v[j]) - (c_sum - v[j] + v[i])) if new_diff < best_local_diff: best_local_diff = new_diff best_move = ('swap', i, j) if best_move: if best_move[0] == 'move': _, i, new_owner = best_move if asn[i] == 'B': b_sum -= v[i] b_cnt -= 1 elif asn[i] == 'C': c_sum -= v[i] c_cnt -= 1 if new_owner == 'B': b_sum += v[i] b_cnt += 1 elif new_owner == 'C': c_sum += v[i] c_cnt += 1 asn[i] = new_owner imp = True elif best_move[0] == 'swap': _, i, j = best_move asn[i], asn[j] = 'C', 'B' b_sum = b_sum - v[i] + v[j] c_sum = c_sum - v[j] + v[i] imp = True if b_cnt == 0 or c_cnt == 0: for i in range(n): if asn[i] == 'A': if b_cnt == 0: asn[i] = 'B' b_sum += v[i] b_cnt += 1 break elif c_cnt == 0: asn[i] = 'C' c_sum += v[i] c_cnt += 1 break diff = abs(b_sum - c_sum) if best_diff is None or diff < best_diff: best_diff = diff best_asn = asn.copy() return ''.join(best_asn) " TL;DR Select from a list of positive integers two non-empty disjoint subsets that minimize the difference between their sums. Problem Statement Alice has a collection of n valuable jewelry items, each with a specific value. She wants to divide some of these items between her two children, Bob and Carol, such that both receive at least one item. Alice’s goal is to ensure fairness in the distribution by minimizing the difference in the total value of the items given to Bob and Carol. Your task is to help Alice determine a way to distribute the jewelry between Bob and Carol that minimizes the difference in their respective total values. Input A list of n positive integers values, where values[i] represents the value of the i-th jewelry item. Constraints 2 <= n < 500 1 <= values[i] < 2^32 Output A string of n characters output, where output[i] has to be one of the following: A — the i-th item is kept by Alice. B — the i-th item is given to Bob. C — the i-th item is given to Carol. Example Input [39, 44, 9, 57] Output BCBA Explanation One way to distribute the items: Bob gets items with values 39 and 9, for a total of 48. Carol gets the item with a value of 44, for a total of 44. The difference between their total values is ∣48 − 44∣ = 4, which is minimized. The item with value 57 is not distributed in this case. In addition, CBCA, ABBC, and ACCB are all considered correct. Wrong Answer (The test case is equal to the answer, so it cannot be seen, but there are cases where the difference can be narrowed further. Correction)
Jewelry Distribution Algorithm Improvement
"from typing import List def fair_jewelry_distribution(values: List[int]) -> str: n = len(values) indices = list(range(n)) sorted_items = sorted(indices, key=lambda i: -values[i]) assignment = [''] * n bob_sum = 0 carol_sum = 0 bob_count = 0 carol_count = 0 for i in sorted_items: if bob_sum <= carol_sum: assignment[i] = 'B' bob_sum += values[i] bob_count += 1 else: assignment[i] = 'C' carol_sum += values[i] carol_count += 1 improved = True while improved: improved = False best_diff = abs(bob_sum - carol_sum) best_move = None for i in range(n): current_owner = assignment[i] if current_owner == 'B': if carol_count >= 1: new_bob_sum = bob_sum - values[i] new_carol_sum = carol_sum + values[i] new_diff = abs(new_bob_sum - new_carol_sum) if new_diff < best_diff and bob_count > 1: best_diff = new_diff best_move = (i, 'C') new_bob_sum = bob_sum - values[i] new_diff = abs(new_bob_sum - carol_sum) if new_diff < best_diff and bob_count > 1: best_diff = new_diff best_move = (i, 'A') elif current_owner == 'C': if bob_count >= 1: new_carol_sum = carol_sum - values[i] new_bob_sum = bob_sum + values[i] new_diff = abs(new_bob_sum - new_carol_sum) if new_diff < best_diff and carol_count > 1: best_diff = new_diff best_move = (i, 'B') new_carol_sum = carol_sum - values[i] new_diff = abs(bob_sum - new_carol_sum) if new_diff < best_diff and carol_count > 1: best_diff = new_diff best_move = (i, 'A') else: # current_owner == 'A' new_bob_sum = bob_sum + values[i] new_diff = abs(new_bob_sum - carol_sum) if new_diff < best_diff: best_diff = new_diff best_move = (i, 'B') new_carol_sum = carol_sum + values[i] new_diff = abs(bob_sum - new_carol_sum) if new_diff < best_diff: best_diff = new_diff best_move = (i, 'C') if best_move: i, new_owner = best_move old_owner = assignment[i] if old_owner == 'B': bob_sum -= values[i] bob_count -= 1 elif old_owner == 'C': carol_sum -= values[i] carol_count -= 1 if new_owner == 'B': bob_sum += values[i] bob_count += 1 elif new_owner == 'C': carol_sum += values[i] carol_count += 1 assignment[i] = new_owner improved = True if bob_count == 0 or carol_count == 0: for i in range(n): if assignment[i] == 'A': if bob_count == 0: assignment[i] = 'B' bob_sum += values[i] bob_count += 1 break elif carol_count == 0: assignment[i] = 'C' carol_sum += values[i] carol_count += 1 break return ''.join(assignment)" TL;DR Select from a list of positive integers two non-empty disjoint subsets that minimize the difference between their sums. Problem Statement Alice has a collection of n valuable jewelry items, each with a specific value. She wants to divide some of these items between her two children, Bob and Carol, such that both receive at least one item. Alice’s goal is to ensure fairness in the distribution by minimizing the difference in the total value of the items given to Bob and Carol. Your task is to help Alice determine a way to distribute the jewelry between Bob and Carol that minimizes the difference in their respective total values. Input A list of n positive integers values, where values[i] represents the value of the i-th jewelry item. Constraints 2 <= n < 500 1 <= values[i] < 2^32 Output A string of n characters output, where output[i] has to be one of the following: A — the i-th item is kept by Alice. B — the i-th item is given to Bob. C — the i-th item is given to Carol. Input: [39, 44, 9, 57] Expected: BCBA Output: CCBB Fix
Jewelry Distribution Problem Solution
from typing import List def fair_jewelry_distribution(values: List[int]) -> str: return "" TL;DR Select from a list of positive integers two non-empty disjoint subsets that minimize the difference between their sums. Problem Statement Alice has a collection of n valuable jewelry items, each with a specific value. She wants to divide some of these items between her two children, Bob and Carol, such that both receive at least one item. Alice’s goal is to ensure fairness in the distribution by minimizing the difference in the total value of the items given to Bob and Carol. Your task is to help Alice determine a way to distribute the jewelry between Bob and Carol that minimizes the difference in their respective total values. Input A list of n positive integers values, where values[i] represents the value of the i-th jewelry item. Constraints 2 <= n < 500 1 <= values[i] < 2^32 Output A string of n characters output, where output[i] has to be one of the following: A — the i-th item is kept by Alice. B — the i-th item is given to Bob. C — the i-th item is given to Carol. Example Input [39, 44, 9, 57] Output BCBA Explanation One way to distribute the items: Bob gets items with values 39 and 9, for a total of 48. Carol gets the item with a value of 44, for a total of 44. The difference between their total values is ∣48 − 44∣ = 4, which is minimized. The item with value 57 is not distributed in this case. In addition, CBCA, ABBC, and ACCB are all considered correct.