元素明智地结合numpy数组列表

Question

I am trying to do some linear combination of numpy arrays.

I have three lists of numpy arrays:

a = [np.random.normal(0,1, [1,2]), np.random.normal(0,1, [3,4]), np.random.normal(0,1, [10,11])] b = [np.random.normal(0,1, [1,2]), np.random.normal(0,1, [3,4]), np.random.normal(0,1, [10,11])] c = [np.random.normal(0,1, [1,2]), np.random.normal(0,1, [3,4]), np.random.normal(0,1, [10,11])]

I want to element-wise combine each element in each array in list a and b based on corresponding element's value of c , to get a new list d : say d_i = a_i * c_i + (1-c_i) *b_i (linear combination).

What I thought was to pick each element in each array in a and find corresponding elements in b and c and then combine. However, I found this is troublesome, inefficient and a bit stupid. Could anyone suggest a better way?

Answer 1

Well assuming all of your lists are the same length then I don't think that there is going to be anything much more efficient than

d = [a[i] * c[i] + (1-c[i]) * b[i] for i in range(len(a))]

Now if all you need to do is operate upon the list d one time then maybe you could speed things up with a generator comprehension?

d = (a[i] * c[i] + (1-c[i]) * b[i] for i in range(len(a)))

But at the end of the day there is no way to create a linear combination of elements in less than linear time.