根据二进制阵列计算间隔的总和



我有两个矩阵:

  1. 二进制A = [[1,0,1,0],[0,0,1,0]];
  2. 值的矩阵b = [[100,200,300,400],[400,300,100,200]];

我想计算由矩阵A的行形成的间隔的总和。结果将如下:r = [[[300,0,700,0],[0,0,300,0]](通常,不必设置零[[300,700],[300]] - 这也是正确的解决方案(

我已经编写了代码,但是非常可怕(尽管工作正常(

def find_halfsum(row1, row2):
    i = 0
    result = []
    count = 0
    for j in range(len(row1)):
        if row1[j] == 1 and count == 0:
            i = j
            count += 1
        elif row1[j] == 1:
            count += 1
        if count == 2:
            if j == i + 1:
                result.append(row2[i])
            else:
                result.append(sum(row2[i:j]))
            i = j
            count = 1
        if j == len(row1) - 1:
            result.append(sum(row2[i:j + 1]))
    return result

有人知道美丽的解决方案(最好更快((最好借助numpy(?

谢谢

不熟悉python,但我认为您不需要那么多行

define halfSum(matrixA, matrixB):
    sum = 0;
    for i in range(len(matrixA)):
        if matrixA[i] == 1:
           sum += matrixB[i]
        return sum;

您可以使用numpy.add.reduceat

>>> A = np.array([[1, 0, 1, 0], [0, 0, 1, 0]])
>>> B = np.array([[100, 200, 300, 400], [400, 300, 100, 200]])
>>> 
>>> [np.add.reduceat(b, np.flatnonzero(a)) for a, b in zip(A, B)]
[array([300, 700]), array([300])]

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