With
input = [0,0,5,9,0,4,10,3,0]
as list I need an output, which is going to be two highest values in input while setting other list elements to zero.
output = [0,0,0,9,0,0,10,0,0]
The closest I got:
from itertools import compress
import numpy as np
import operator
input= [0,0,5,9,0,4,10,3,0]
top_2_idx = np.argsort(test)[-2:]
test[top_2_idx[0]]
test[top_2_idx[1]]
Can you please help?
You can sort, find the two largest values, and then use a list comprehension:
input = [0,0,5,9,0,4,10,3,0]
*_, c1, c2 = sorted(input)
result = [0 if i not in {c1, c2} else i for i in input]
Output:
[0, 0, 0, 9, 0, 0, 10, 0, 0]
heapq.nlargest rather than sorted.Not as pretty as Ajax's solution but a O(n) solution and a little more dynamic:
from collections import deque
def zero_non_max(lst, keep_top_n):
"""
Returns a list with all numbers zeroed out
except the keep_top_n.
>>> zero_non_max([0, 0, 5, 9, 0, 4, 10, 3, 0], 3)
>>> [0, 0, 5, 9, 0, 0, 10, 0, 0]
"""
lst = lst.copy()
top_n = deque(maxlen=keep_top_n)
for index, x in enumerate(lst):
if len(top_n) < top_n.maxlen or x > top_n[-1][0]:
top_n.append((x, index))
lst[index] = 0
for val, index in top_n:
lst[index] = val
return lst
lst = [0, 0, 5, 9, 0, 4, 10, 3, 0]
print(zero_non_max(lst, 2))
Output:
[0, 0, 0, 9, 0, 0, 10, 0, 0]
Pure numpy approach:
import numpy as np
arr = np.array([0, 0, 5, 9, 0, 4, 10, 3, 0])
top_2_idx = np.argsort(arr)[-2:]
np.put(arr, np.argwhere(~np.isin(arr, arr[top_2_idx])), 0)
print(arr)
The output:
[ 0 0 0 9 0 0 10 0 0]
It's possible to achieve this with a single list traversal, making the algorithm O(n):
First find the two highest values with a single traversal;
Then create a list of zeros and add in the found maxima.
def two_max(lst):
# Find two highest values in a single traversal
max_i, max_j = 0, 1
for i in range(len(lst)):
_, max_i, max_j = sorted((max_i, max_j, i), key=lst.__getitem__)
# Make a new list with zeros and replace both maxima
new_lst = [0] * len(lst)
new_lst[max_i], new_lst[max_j] = lst[max_i], lst[max_j]
return new_lst
lst = [0, 0, 5, 9, 0, 4, 10, 3, 0]
print(two_max(lst)) # [0, 0, 0, 9, 0, 0, 10, 0, 0]
Note that if the maximum value in the list appears more than twice, only the two left-most values will appear.
As a sidenote, do not use names such as input in your code as this overshadows the built-in function of the same name.
Here is another numpy-based solution that avoids sorting the entire array, which takes O(nlogn) time.
import numpy as np
arr = np.array([0,0,5,9,0,4,10,3,0])
arr[np.argpartition(arr,-2)[:-2]] = 0
If you want to create a new array as output:
result = np.zeros_like(arr)
idx = np.argpartition(arr,-2)[-2:]
result[idx] = arr[idx]
A corresponding Python-native solution is to use heap.nlargest, which also avoids sorting the entire array.
import heapq
arr = [0,0,5,9,0,4,10,3,0]
l = len(arr)
idx1, idx2 = heapq.nlargest(2, range(l), key=arr.__getitem__)
result = [0] * l
result[idx1] = arr[idx1]
result[idx2] = arr[idx2]
