Assign values to array efficiently

Question

How I can do for do this code efficiently?

import numpy as np

array = np.zeros((10000,10000)) 
lower = 5000  
higher = 10000 
for x in range(lower, higher): 
    for y in range(lower, higher):
        array[x][y] = 1     
print(array)

I think must be a efficient way to do this with a numpy library (without loops).

Answer 1

Try this :

array[lower:higher, lower:higher] = 1
# OR
array[lower:higher, lower:higher].fill(1) # Faster

As you're dwelling with huge array, the second process will be faster to the first one. Here is sample time check-up with low-scale data :

>>> from timeit import timeit as t
>>> t("""import numpy as np; a=np.zeros((100,100)); a[50:100,50:100].fill(1)""")
3.619488961998286
>>> t("""import numpy as np; a=np.zeros((100,100)); a[50:100,50:100] = 1""")
3.688145470998279