二维数组与一维数组的比较返回二维数组

Question

I am trying to compare a 1D array element-wise to a 2D array, and returns the elements of the 2D array which fulfils the condition in a 2D array form without using a for loop. Preferably using numpy or quicker method.

a = range(1,10)
Tna = np.random.choice(a, size=[250,10,1000], replace=True)
sum_Ta = np.sum(Tna, axis = 1)
percent = np.percentile(sum_Ta, 5, axis =0)

Now I would like to get a 2D array which contains the elements of sum_Ta if the elements are smaller the percent. Such that 250 elements of sum_Ta are comparing with 1 element of percent for 1000 times. Originally I can do, ES = sum_Ta[sum_Ta < percent[:,None]] , but it only gives me a 1D array, not a 2D array.

Answer 1

Assuming you mean that for each row, you want the element of the row to be included if it is less than the percentage associated with its column.

Try the following:

mask = sum_Ta < (percent * np.ones((250,1)))
ES = np.zeros((250, 1000))
ES[mask] = sum_Ta[mask]