Question

通过阅读Python文档和stackoverflow我无法弄清楚的东西。可能我在想错误的方向..

假设我有一个预定义的2D Numpy数组，如下所示：

a = np.zeros(shape=(3,2)) 
print a
array([[ 0.,  0.],
       [ 0.,  0.],
       [ 0.,  0.]])

现在我想用一维数据阵列（逐个）填充这个2D数组的每一列，如：

b = np.array([1,2,3])

# Some code, that I just can't figure out. I've studied insert, column_stack, 
# h_stack, append. Nothing seems to do what I need

print a
array([[ 1.,  0.],
       [ 2.,  0.],
       [ 3.,  0.]])

c = np.array([4,5,6])

# Some code, that I just can't figure out. I've studied insert, column_stack, 
# h_stack, append. Nothing seems to do what I need

print a
array([[ 1.,  4.],
       [ 2.,  5.],
       [ 3.,  6.]])

任何建议都将不胜感激！

Answer 1

您可以使用切片分配给列：

>>> a[:,0] = b
>>> a
array([[ 1.,  0.],
       [ 2.,  0.],
       [ 3.,  0.]])

要一次性分配所有内容而不是一次分配一次，请使用np.column_stack：

>>> np.column_stack((b, c))
array([[1, 4],
       [2, 5],
       [3, 6]])

如果你需要它在同一个数组中，而不是只有相同的名称，你可以指定一个包含整个矩阵的切片（如列表中常见的那样）：

>>> a[:] = np.column_stack((b, c))
>>> a
array([[ 1.,  4.],
       [ 2.,  5.],
       [ 3.,  6.]])

使用数组作为列填充预定义的numpy数组

1 个答案: