vector<int> solve(vector<int>& nums, int k) {
vector<int>ans;
if(k>nums.size())return ans;
deque<int>dq;
for(int i = 0; i < k; i++)
{
while(!dq.empty() && nums[dq.back()]<=nums[i])
{
dq.pop_back();
}
dq.push_back(i);
}
ans.push_back(nums[dq.front()]);
for(int i = k; i < nums.size(); i++)
{
if(!dq.empty() && dq.front()<=i-k)dq.pop_front();
while(!dq.empty() && nums[dq.back()]<=nums[i])
{
dq.pop_back();
}
dq.push_back(i);
ans.push_back(nums[dq.front()]);
}
return ans;
}
# Python program to find the maximum for
# each and every contiguous subarray of
# size k
from collections import deque
# A Deque (Double ended queue) based
# method for printing maximum element
# of all subarrays of size k
def printMax(arr, n, k):
""" Create a Double Ended Queue, Qi that
will store indexes of array elements.
The queue will store indexes of useful
elements in every window and it will
maintain decreasing order of values from
front to rear in Qi, i.e., arr[Qi.front[]]
to arr[Qi.rear()] are sorted in decreasing
order"""
Qi = deque()
# Process first k (or first window)
# elements of array
for i in range(k):
# For every element, the previous
# smaller elements are useless
# so remove them from Qi
while Qi and arr[i] >= arr[Qi[-1]] :
Qi.pop()
# Add new element at rear of queue
Qi.append(i);
# Process rest of the elements, i.e.
# from arr[k] to arr[n-1]
for i in range(k, n):
# The element at the front of the
# queue is the largest element of
# previous window, so print it
print(str(arr[Qi[0]]) + " ", end = "")
# Remove the elements which are
# out of this window
while Qi and Qi[0] <= i-k:
# remove from front of deque
Qi.popleft()
# Remove all elements smaller than
# the currently being added element
# (Remove useless elements)
while Qi and arr[i] >= arr[Qi[-1]] :
Qi.pop()
# Add current element at the rear of Qi
Qi.append(i)
# Print the maximum element of last window
print(str(arr[Qi[0]]))
# Driver code
if __name__=="__main__":
arr = [12, 1, 78, 90, 57, 89, 56]
k = 3
printMax(arr, len(arr), k)
# This code is contributed by Shiv Shankar