Problem p02774 (python)

Fixed submission:
import numpy as np
# from numba import njit

atcoder={
    'name': 'numba_modules',
    'file': 'numba_modules.cpython-34m.so',
    'func': ['solve1', 'solve2'],
    'gz': 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

Buggy submission (verdict: Runtime Error):
import numpy as np
# from numba import njit

# @njit('(i8,i8[:],i8[:])')
def solve1(m, minus, plus):
    minus = np.sort(minus)
    plus = np.sort(plus)[::-1]
    # ２分探索
    lo = minus[0] * plus[0]
    hi = minus[-1] * plus[-1]
    while hi - lo > 1:
        mid = (lo + hi) // 2
        num = 0
        j = plus.shape[0] - 1
        for i in range(plus.shape[0]):
            while j >= 0 and minus[j] * plus[i] > mid:
                j -= 1
            if j > -1:
                num += j + 1
            else:
                break
        if num > m:
            hi = mid
        elif num < m:
            lo = mid
        else:
            hi = mid
            break

    j = minus.shape[0] - 1
    res = minus[0] * plus[0]
    for i in range(plus.shape[0]):
        while j >= 0 and minus[j] * plus[i] > hi:
            j -= 1
        if j > -1:
            res = max(res, minus[j] * plus[i])
        else:
            break
    return res

# @njit('(i8,i8[:],i8[:])')
def solve2(m, minus, plus):
    minus = np.sort(minus)[::-1]
    plus = np.sort(plus)
    # ２分探索
    lo = 0
    hi = plus[-1] * plus[-2] if len(plus) > 1 else 0
    hi += minus[-1] * minus[-2] if len(minus) > 1 else 0
    while hi - lo > 1:
        mid = (lo + hi) // 2
        num = 0

        j1 = plus.shape[0] - 1
        if j1 > 0:
            for i in range(plus.shape[0]):
                s = mid // plus[i]
                while j1 >= 0 and plus[j1] > s:
                    j1 -= 1
                if j1 > i:
                    num += j1 - i

        j2 = minus.shape[0] - 1
        if j2 > 0:
            for i in range(minus.shape[0]):
                s = mid // -minus[i]
                while j2 >= 0 and minus[j2] < -s:
                    j2 -= 1
                if j2 > i:
                    num += j2 - i

        if num > m:
            hi = mid
        elif num < m:
            lo = mid
        else:
            hi = mid
            break

    j1 = plus.shape[0] - 1
    j2 = minus.shape[0] - 1
    res = 0
    if j1 > 0:
        for i in range(plus.shape[0]):
            while j1 >= 0 and plus[j1] * plus[i] > hi:
                j1 -= 1
            if j1 > i:
                res = max(res, plus[j1] * plus[i])
            else:
                break
    if j2 > 0:
        for i in range(minus.shape[0]):
            while j2 >= 0 and minus[j2] * minus[i] > hi:
                j2 -= 1
            if j2 > i:
                res = max(res, minus[j2] * minus[i])
            else:
                break
    return res


def main():
    N, K = [int(x) for x in input().split()]
    A = np.fromstring(input(), np.int64, sep=' ')
    minus = A[A < 0]
    zero = A[A == 0]
    plus = A[A > 0]

    n_zero = len(zero)
    p_minus = len(minus) * len(plus)
    p_zero = n_zero * (len(minus) + len(plus)) + n_zero * (n_zero - 1) // 2

    if K <= p_minus:
        ans = solve1(K, minus, plus)
        print(ans)
    elif K <= p_minus + p_zero:
        print(0)
    else:
        ans = solve2(K - p_minus - p_zero, minus, plus)
        print(ans)

if __name__ == '__main__':
    main()

Buggy submission (verdict: Runtime Error):
import numpy as np

def solve1(m, minus, plus):
    minus = np.sort(minus)
    plus = np.sort(plus)[::-1]
    # ２分探索
    lo = minus[0] * plus[0]
    hi = minus[-1] * plus[-1]
    while hi - lo > 1:
        mid = (lo + hi) // 2
        num = 0
        j = minus.shape[0] - 1
        for i in range(plus.shape[0]):
            while j >= 0 and minus[j] * plus[i] > mid:
                j -= 1
            if j > -1:
                num += j + 1
            else:
                break
        if num > m:
            hi = mid
        elif num < m:
            lo = mid
        else:
            hi = mid
            break

    j = minus.shape[0] - 1
    res = minus[0] * plus[0]
    for i in range(plus.shape[0]):
        while j >= 0 and minus[j] * plus[i] > hi:
            j -= 1
        if j > -1:
            res = max(res, minus[j] * plus[i])
        else:
            break
    return res

def solve2(m, minus, plus):
    minus = np.sort(minus)[::-1]
    plus = np.sort(plus)
    # ２分探索
    lo = 0
    hi = plus[-1] * plus[-2] if len(plus) > 1 else 0
    hi += minus[-1] * minus[-2] if len(minus) > 1 else 0
    while hi - lo > 1:
        mid = (lo + hi) // 2
        num = 0

        j1 = plus.shape[0] - 1
        if j1 > 0:
            for i in range(plus.shape[0]):
                while j1 >= 0 and plus[j1] * plus[i] > mid:
                    j1 -= 1
                if j1 > i:
                    num += j1 - i

        j2 = minus.shape[0] - 1
        if j2 > 0:
            for i in range(minus.shape[0]):
                while minus[j2] * minus[i] > mid:
                    j2 -= 1
                if j2 > i:
                    num += j2 - i

        if num > m:
            hi = mid
        elif num < m:
            lo = mid
        else:
            hi = mid
            break

    j1 = plus.shape[0] - 1
    j2 = minus.shape[0] - 1
    res = 0
    if j1 > 0:
        for i in range(plus.shape[0]):
            while j1 >= 0 and plus[j1] * plus[i] > hi:
                j1 -= 1
            if j1 > i:
                res = max(res, plus[j1] * plus[i])
            else:
                break
    if j2 > 0:
        for i in range(minus.shape[0]):
            while j2 >= 0 and minus[j2] * minus[i] > hi:
                j2 -= 1
            if j2 > i:
                res = max(res, minus[j2] * minus[i])
            else:
                break
    return res


def main():
    N, K = [int(x) for x in input().split()]
    A = np.fromstring(input(), np.int64, sep=' ')
    minus = A[A < 0]
    zero = A[A == 0]
    plus = A[A > 0]

    n_minus = len(minus)
    n_zero = len(zero)
    n_plus = len(plus)

    p_minus = n_minus * n_plus
    p_zero = n_zero * (n_minus + n_plus) + n_zero * (n_zero - 1) // 2

    if K <= p_minus:
        ans = solve1(K, minus, plus)
        print(ans)
    elif K <= p_minus + p_zero:
        print(0)
    else:
        ans = solve2(K - p_minus - p_zero, minus, plus)
        print(ans)

if __name__ == '__main__':
    main()

Buggy submission (verdict: Runtime Error):
import numpy as np

def solve1(m, minus, plus):
    minus = np.sort(minus)
    plus = np.sort(plus)[::-1]
    # ２分探索
    lo = minus[0] * plus[0]
    hi = minus[-1] * plus[-1]
    while hi - lo > 1:
        mid = (lo + hi) // 2
        num = 0
        j = minus.shape[0] - 1
        for i in range(plus.shape[0]):
            while j >= 0 and minus[j] * plus[i] > mid:
                j -= 1
            if j > -1:
                num += j + 1
            else:
                break
        if num > m:
            hi = mid
        elif num < m:
            lo = mid
        else:
            hi = mid
            break

    j = minus.shape[0] - 1
    res = 0
    for i in range(plus.shape[0]):
        while j >= 0 and minus[j] * plus[i] > hi:
            j -= 1
        if j > -1:
            res = min(res, minus[j] * plus[i])
    return res

def solve2(m, minus, plus):
    minus = np.sort(minus)[::-1]
    plus = np.sort(plus)
    # ２分探索
    lo = 0
    hi = plus[-1] * plus[-2] if len(plus) > 1 else 0
    hi += minus[-1] * minus[-2] if len(minus) > 1 else 0
    while hi - lo > 1:
        mid = (lo + hi) // 2
        num = 0

        j1 = plus.shape[0] - 1
        if j1 > 0:
            for i in range(plus.shape[0]):
                while j1 >= 0 and plus[j1] * plus[i] > mid:
                    j1 -= 1
                if j1 > i:
                    num += j1 - i

        j2 = minus.shape[0] - 1
        if j2 > 0:
            for i in range(minus.shape[0]):
                while minus[j2] * minus[i] > mid:
                    j2 -= 1
                if j2 > i:
                    num += j2 - i

        if num > m:
            hi = mid
        elif num < m:
            lo = mid
        else:
            hi = mid
            break

    j1 = plus.shape[0] - 1
    j2 = minus.shape[0] - 1
    res = 0
    if j1 > 0:
        for i in range(plus.shape[0]):
            while j1 >= 0 and plus[j1] * plus[i] > hi:
                j1 -= 1
            if j1 > i:
                res = max(res, plus[j1] * plus[i])
            else:
                break
    if j2 > 0:
        for i in range(minus.shape[0]):
            while j2 >= 0 and minus[j2] * minus[i] > hi:
                j2 -= 1
            if j2 > i:
                res = max(res, minus[j2] * minus[i])
            else:
                break
    return res


def main():
    N, K = [int(x) for x in input().split()]
    A = np.fromstring(input(), np.int64, sep=' ')
    minus = A[A < 0]
    zero = A[A == 0]
    plus = A[A > 0]

    n_minus = len(minus)
    n_zero = len(zero)
    n_plus = len(plus)

    p_minus = n_minus * n_plus
    p_zero = n_zero * (n_minus + n_plus) + n_zero * (n_zero - 1) // 2

    if K <= p_minus:
        ans = solve1(K, minus, plus)
        print(ans)
    elif K <= p_minus + p_zero:
        print(0)
    else:
        ans = solve2(K - p_minus - p_zero, minus, plus)
        print(ans)

if __name__ == '__main__':
    main()

Buggy submission (verdict: Runtime Error):
import numpy as np

def solve1(m, minus, plus):
    minus = np.sort(minus)
    plus = np.sort(plus)[::-1]
    # ２分探索
    lo = minus[0] * plus[0]
    hi = minus[-1] * plus[-1]
    while lo < hi:
        mid = (lo + hi) // 2
        num = 0
        j = minus.shape[0] - 1
        for i in range(plus.shape[0]):
            while minus[j] * plus[i] > mid:
                j -= 1
            num += j
        if num > m:
            hi = mid - 1
        elif num < m:
            lo = mid + 1
        else:
            lo = mid
            break

    j = minus.shape[0] - 1
    res = 0
    for i in range(plus.shape[0]):
        while minus[j] * plus[i] > lo:
            j -= 1
        res = min(res, minus[j] * plus[i])
    return res

def solve2(m, minus, plus):
    minus = np.sort(minus)[::-1]
    plus = np.sort(plus)
    # ２分探索
    lo = 0
    hi = plus[-1] * plus[-2] if len(plus) > 1 else 0
    hi += minus[-1] * minus[-2] if len(minus) > 1 else 0
    while hi - lo > 1:
        mid = (lo + hi) // 2
        num = 0

        j1 = plus.shape[0] - 1
        if j1 > 0:
            for i in range(plus.shape[0]):
                while j1 >= 0 and plus[j1] * plus[i] > mid:
                    j1 -= 1
                if j1 > i:
                    num += j1 - i

        j2 = minus.shape[0] - 1
        if j2 > 0:
            for i in range(minus.shape[0]):
                while minus[j2] * minus[i] > mid:
                    j2 -= 1
                if j2 > i:
                    num += j2 - i

        if num > m:
            hi = mid
        elif num < m:
            lo = mid
        else:
            hi = mid
            break

    j1 = plus.shape[0] - 1
    j2 = minus.shape[0] - 1
    res = 0
    if j1 > 0:
        for i in range(plus.shape[0]):
            while j1 >= 0 and plus[j1] * plus[i] > hi:
                j1 -= 1
            if j1 > i:
                res = max(res, plus[j1] * plus[i])
    if j2 > 0:
        for i in range(minus.shape[0]):
            while j2 >= 0 and minus[j2] * minus[i] > hi:
                j2 -= 1
            if j2 > i:
                res = max(res, minus[j2] * minus[i])
    return res


def main():
    N, K = [int(x) for x in input().split()]
    A = np.fromstring(input(), np.int64, sep=' ')
    minus = A[A < 0]
    zero = A[A == 0]
    plus = A[A > 0]

    n_minus = len(minus)
    n_zero = len(zero)
    n_plus = len(plus)

    p_minus = n_minus * n_plus
    p_zero = n_zero * (n_minus + n_plus) + n_zero * (n_zero - 1) // 2

    if K <= p_minus:
        ans = solve1(K, minus, plus)
        print(ans)
    elif K <= p_minus + p_zero:
        print(0)
    else:
        ans = solve2(K - p_minus - p_zero, minus, plus)
        print(ans)

if __name__ == '__main__':
    main()