def read_data(): N, B = map(int, input().split()) Xs = [] Ys = [] Ps = [] for i in range(N): x, y, p = map(int, input().split()) Xs.append(x) Ys.append(y) Ps.append(p) return N, B, Xs, Ys, Ps def solve(N, B, Xs, Ys, Ps): if len(Xs) == 0: return 0 Xs = compress(Xs) Ys = compress(Ys) if max(Xs) > max(Ys): Xs, Ys = Ys, Xs cum, cumP = preprocess(Xs, Ys, Ps) return find_max(cum, cumP, B) def compress(As): Avals = list(set(As)) Avals.sort() val2idx = {a:i for i, a in enumerate(Avals)} return [val2idx[a] for a in As] def preprocess(Xs, Ys, Ps): max_x = max(Xs) max_y = max(Ys) mat = [[0] * (max_y + 2) for _ in range(max_x + 2)] for x, y, p in zip(Xs, Ys, Ps): mat[x + 1][y + 1] = p cum = [[0] * (max_y + 2) for _ in range(max_x + 2)] cumP = [[0] * (max_y + 2) for _ in range(max_x + 2)] for x in range(1, max_x + 2): cumx = cum[x] cumx_prev = cum[x - 1] cumPx = cumP[x] cumPx_prev = cumP[x - 1] matx = mat[x] tmp = 0 tmpP = 0 for y in range(1, max_y + 2): if matx[y]: tmp += 1 tmpP += matx[y] cumx[y] = cumx_prev[y] + tmp cumPx[y] = cumPx_prev[y] + tmpP return cum, cumP def find_max(cum, cumP, B): nrow = len(cum) ncol = len(cum[0]) max_n = 0 for t in range(nrow - 1): cum_t = cum[t] cumP_t = cumP[t] for b in range(t + 1, nrow): n = find_max_n(cum_t, cumP_t, cum[b], cumP[b], B, ncol) if n > max_n: max_n = n return max_n def find_max_n(t, Pt, b, Pb, B, ncol): max_n = 0 left = 0 for right in range(1, ncol): p = Pb[right] - Pt[right] while p - Pb[left] + Pt[left] > B: left += 1 n = b[right] - t[right] - b[left] + t[left] if n > max_n: max_n = n return max_n if __name__ == '__main__': N, B, Xs, Ys, Ps = read_data() print(solve(N, B, Xs, Ys, Ps))