巧用滑动窗口算法，轻松获取最大值！

2023-09-07 17:57:14

滑动窗口算法的基本原理

滑动窗口算法的基本原理是，它将一个大小为k的窗口从数组的最左侧移动到数组的最右侧，并记录窗口中元素的最大值。当窗口移动到一个新的位置时，算法会从窗口中移除最左侧的元素，并添加一个最右侧的元素。通过这种方式，算法可以跟踪窗口中的最大值，而无需遍历整个数组。

滑动窗口算法的实现

滑动窗口算法可以使用各种编程语言来实现。以下是一个使用Python实现的滑动窗口算法的示例：

def max_sliding_window(nums, k):
  """
  Finds the maximum value in a sliding window of size k.

  Args:
    nums: The array to search.
    k: The size of the sliding window.

  Returns:
    A list of the maximum values in each sliding window.
  """

  # Initialize the output array.
  max_values = []

  # Create a deque to store the indices of the elements in the sliding window.
  window = deque()

  # Iterate over the array.
  for i, num in enumerate(nums):
    # Remove any elements from the deque that are no longer in the sliding window.
    while window and window[0] <= i - k:
      window.popleft()

    # Add the current element to the deque.
    while window and nums[window[-1]] < num:
      window.pop()
    window.append(i)

    # If the sliding window is full, add the maximum value to the output array.
    if len(window) == k:
      max_values.append(nums[window[0]])

  # Return the output array.
  return max_values