I have a numpy array:
arr = [0.23, 2.32, 4.04, 5.02, 6.84, 10.12, 10.34, 11.93,12.44]
I want to get the index of the closest integer I enter. For example if I enter 10 then I should get back index 5 (10.12) or if I enter 12 i should get back index 7 (11.93).
If your list isn't sorted, you will need a linear time solution using abs + argmin:
>>> np.abs(np.array(arr) - 12).argmin()
7
However, if your list is sorted (ascending or descending), you can employ binary search for a sub-linear time solution (very fast):
# https://ideone.com/aKEpI2 — improved by @user2357112
def binary_search(arr, val):
# val must be in the closed interval between arr[i-1] and arr[i],
# unless one of i-1 or i is beyond the bounds of the array.
i = np.searchsorted(arr, val)
if i == 0:
# Smaller than the smallest element
return i
elif i == len(arr):
# Bigger than the biggest element
return i - 1
elif val - arr[i - 1] <= arr[i] - val:
# At least as close to arr[i - 1] as arr[i]
return i - 1
# Closer to arr[i] than arr[i - 1]
return i
cases = [10, 12, 100, 10.12] # 5, 7, 8, 5
print(*[binary_search(arr, c) for c in cases], sep=',')
searchsorted soln gives the wrong answer for 10 (4 instead of 5).
searchsorted if you want the nearest element. Particularly, searching for 0 returns -1, searching for 10.12 fails to report the index of 10.12, and searching for a value between two values of the array always picks the index of the left value, even if the right value is closer.