如何找到所有点的2D numpy数组中的点大于参考数组中的对应点的百分比？

Question

Python newbie here. Given a list ( mylist ) of 2D numpy arrays, and a reference 2D numpy array ( refarr ), I'm looking for a way to create an array ( percentage_array ) in which each point (i,j) is the percentage of corresponding (i,j) points in the mylist arrays that are greater than [i,j] in refarr . I could do this by looping through all the points in the array and though the list, eg:

percentage_array = numpy.empty(arr.shape)
for i in range(arr.shape[0]):
    for j in range(arr.shape[1]):
        t = 0 
        f = 0
        for arr in mylist:
            if arr[i,j] > refarr[i,j]:
                t += 1 # counting the number of arrays for which [i,j] is true
            elif arr[i,j] <= refarr[i,j]:
                f += 1 # counting the number of arrays for which [i,j] is false
        percentage_array[i,j] = t/(t+f) # fraction of arrays which have 
                                        # arr[i,j] > refarr[i,j]

...but this is neither quick nor elegant (I'm dealing with large amounts of data). Are there better ways to do this?

Answer 1

You can create a 3d array with

a = np.array(myList)

Then you can compare this array to your original one using broadcasting:

a < refarr # gives a 3D array of booleans because refarr is broadcasted to a 3D array

and to count the percentage of values where the condition is met, you average on the first axis:

(a < refarr[None, :, :]).mean(axis = 0)

The main drawback of this approach is that you have to create an array a which may be big. Otherwise I'd consider treating arrays one by one.