给定一个整数数组。在其中找到一个峰值元素。如果一个数组元素不小于它的邻居,那么它就是一个峰值。对于角元素,我们只需要考虑一个邻居。
例子:
Input: array[]= {5, 10, 20, 15}
Output: 20
The element 20 has neighbours 10 and 15,
both of them are less than 20.
Input: array[] = {10, 20, 15, 2, 23, 90, 67}
Output: 20 or 90
The element 20 has neighbours 10 and 15,
both of them are less than 20, similarly 90 has neighbours 23 and 67.
以下角落案例可以更好地了解问题。
- 如果输入数组按严格递增顺序排序,则最后一个元素始终是峰值元素。例如,50 是 {10, 20, 30, 40, 50} 中的峰元素。
- 如果输入数组按严格降序排序,则第一个元素始终是峰值元素。 100 是 {100, 80, 60, 50, 20} 中的峰值元素。
- 如果输入数组的所有元素都相同,则每个元素都是峰值元素。
从上面的例子可以清楚地看出,输入数组中总是有一个peak元素。
朴素的方法:可以遍历数组并返回其邻居小于该元素的元素。
算法:
- 如果在数组中,第一个元素大于第二个或最后一个元素大于倒数第二个,则打印相应的元素并终止程序。
- else 从第二个索引到倒数第二个索引遍历数组
- 如果对于元素array[i] ,它大于它的两个邻居,即array[i] > array[i-1] 和 array[i] > array[i+1] ,然后打印该元素并终止。
C++
// A C++ program to find a peak element
#include
using namespace std;
// Find the peak element in the array
int findPeak(int arr[], int n)
{
// first or last element is peak element
if (n == 1)
return 0;
if (arr[0] >= arr[1])
return 0;
if (arr[n - 1] >= arr[n - 2])
return n - 1;
// check for every other element
for (int i = 1; i < n - 1; i++) {
// check if the neighbors are smaller
if (arr[i] >= arr[i - 1] && arr[i] >= arr[i + 1])
return i;
}
}
// Driver Code
int main()
{
int arr[] = { 1, 3, 20, 4, 1, 0 };
int n = sizeof(arr) / sizeof(arr[0]);
cout << "Index of a peak point is "
<< findPeak(arr, n);
return 0;
}
// This code is contributed by Arnab Kundu
Java
// A Java program to find a peak element
import java.util.*;
class GFG{
// Find the peak element in the array
static int findPeak(int arr[], int n)
{
// First or last element is peak element
if (n == 1)
return 0;
if (arr[0] >= arr[1])
return 0;
if (arr[n - 1] >= arr[n - 2])
return n - 1;
// Check for every other element
for(int i = 1; i < n - 1; i++)
{
// Check if the neighbors are smaller
if (arr[i] >= arr[i - 1] &&
arr[i] >= arr[i + 1])
return i;
}
return 0;
}
// Driver Code
public static void main(String[] args)
{
int arr[] = { 1, 3, 20, 4, 1, 0 };
int n = arr.length;
System.out.print("Index of a peak point is " +
findPeak(arr, n));
}
}
// This code is contributed by Princi Singh
Python3
# A Python3 program to find a peak element
# Find the peak element in the array
def findPeak(arr, n) :
# first or last element is peak element
if (n == 1) :
return 0
if (arr[0] >= arr[1]) :
return 0
if (arr[n - 1] >= arr[n - 2]) :
return n - 1
# check for every other element
for i in range(1, n - 1) :
# check if the neighbors are smaller
if (arr[i] >= arr[i - 1] and arr[i] >= arr[i + 1]) :
return i
# Driver code.
arr = [ 1, 3, 20, 4, 1, 0 ]
n = len(arr)
print("Index of a peak point is", findPeak(arr, n))
# This code is contributed by divyeshrabadiya07
C#
// A C# program to find a peak element
using System;
public class GFG{
// Find the peak element in the array
static int findPeak(int []arr, int n)
{
// First or last element is peak element
if (n == 1)
return 0;
if (arr[0] >= arr[1])
return 0;
if (arr[n - 1] >= arr[n - 2])
return n - 1;
// Check for every other element
for(int i = 1; i < n - 1; i++)
{
// Check if the neighbors are smaller
if (arr[i] >= arr[i - 1] &&
arr[i] >= arr[i + 1])
return i;
}
return 0;
}
// Driver Code
public static void Main(String[] args)
{
int []arr = { 1, 3, 20, 4, 1, 0 };
int n = arr.Length;
Console.Write("Index of a peak point is " +
findPeak(arr, n));
}
}
// This code is contributed by 29AjayKumar
Javascript
C++
// A C++ program to find a peak element
// using divide and conquer
#include
using namespace std;
// A binary search based function
// that returns index of a peak element
int findPeakUtil(int arr[], int low,
int high, int n)
{
// Find index of middle element
// (low + high)/2
int mid = low + (high - low) / 2;
// Compare middle element with its
// neighbours (if neighbours exist)
if ((mid == 0 || arr[mid - 1] <= arr[mid]) &&
(mid == n - 1 || arr[mid + 1] <= arr[mid]))
return mid;
// If middle element is not peak and its
// left neighbour is greater than it,
// then left half must have a peak element
else if (mid > 0 && arr[mid - 1] > arr[mid])
return findPeakUtil(arr, low, (mid - 1), n);
// If middle element is not peak and its
// right neighbour is greater than it,
// then right half must have a peak element
else
return findPeakUtil(
arr, (mid + 1), high, n);
}
// A wrapper over recursive function findPeakUtil()
int findPeak(int arr[], int n)
{
return findPeakUtil(arr, 0, n - 1, n);
}
// Driver Code
int main()
{
int arr[] = { 1, 3, 20, 4, 1, 0 };
int n = sizeof(arr) / sizeof(arr[0]);
cout << "Index of a peak point is "
<< findPeak(arr, n);
return 0;
}
// This code is contributed by rathbhupendra
C
// C program to find a peak
// element using divide and conquer
#include
// A binary search based function that
// returns index of a peak element
int findPeakUtil(
int arr[], int low, int high, int n)
{
// Find index of middle element
// (low + high)/2
int mid = low + (high - low) / 2;
// Compare middle element with
// its neighbours (if neighbours exist)
if ((mid == 0 || arr[mid - 1] <= arr[mid]) && (mid == n - 1 || arr[mid + 1] <= arr[mid]))
return mid;
// If middle element is not peak and
// its left neighbour is greater
// than it, then left half must have a peak element
else if (mid > 0 && arr[mid - 1] > arr[mid])
return findPeakUtil(arr, low, (mid - 1), n);
// If middle element is not peak and
// its right neighbour is greater
// than it, then right half must have a peak element
else
return findPeakUtil(arr, (mid + 1), high, n);
}
// A wrapper over recursive function findPeakUtil()
int findPeak(int arr[], int n)
{
return findPeakUtil(arr, 0, n - 1, n);
}
/* Driver program to check above functions */
int main()
{
int arr[] = { 1, 3, 20, 4, 1, 0 };
int n = sizeof(arr) / sizeof(arr[0]);
printf(
"Index of a peak point is %d", findPeak(arr, n));
return 0;
}
Java
// A Java program to find a peak
// element using divide and conquer
import java.util.*;
import java.lang.*;
import java.io.*;
class PeakElement {
// A binary search based function
// that returns index of a peak element
static int findPeakUtil(
int arr[], int low, int high, int n)
{
// Find index of middle element
// (low + high)/2
int mid = low + (high - low) / 2;
// Compare middle element with its
// neighbours (if neighbours exist)
if ((mid == 0 || arr[mid - 1] <= arr[mid])
&& (mid == n - 1 || arr[mid + 1] <= arr[mid]))
return mid;
// If middle element is not peak
// and its left neighbor is
// greater than it, then left half
// must have a peak element
else if (mid > 0 && arr[mid - 1] > arr[mid])
return findPeakUtil(arr, low, (mid - 1), n);
// If middle element is not peak
// and its right neighbor
// is greater than it, then right
// half must have a peak
// element
else
return findPeakUtil(
arr, (mid + 1), high, n);
}
// A wrapper over recursive function
// findPeakUtil()
static int findPeak(int arr[], int n)
{
return findPeakUtil(arr, 0, n - 1, n);
}
// Driver method
public static void main(String[] args)
{
int arr[] = { 1, 3, 20, 4, 1, 0 };
int n = arr.length;
System.out.println(
"Index of a peak point is " + findPeak(arr, n));
}
}
Python3
# A python3 program to find a peak
# element element using divide and conquer
# A binary search based function
# that returns index of a peak element
def findPeakUtil(arr, low, high, n):
# Find index of middle element
# (low + high)/2
mid = low + (high - low)/2
mid = int(mid)
# Compare middle element with its
# neighbours (if neighbours exist)
if ((mid == 0 or arr[mid - 1] <= arr[mid]) and
(mid == n - 1 or arr[mid + 1] <= arr[mid])):
return mid
# If middle element is not peak and
# its left neighbour is greater
# than it, then left half must
# have a peak element
elif (mid > 0 and arr[mid - 1] > arr[mid]):
return findPeakUtil(arr, low, (mid - 1), n)
# If middle element is not peak and
# its right neighbour is greater
# than it, then right half must
# have a peak element
else:
return findPeakUtil(arr, (mid + 1), high, n)
# A wrapper over recursive
# function findPeakUtil()
def findPeak(arr, n):
return findPeakUtil(arr, 0, n - 1, n)
# Driver code
arr = [1, 3, 20, 4, 1, 0]
n = len(arr)
print("Index of a peak point is", findPeak(arr, n))
# This code is contributed by
# Smitha Dinesh Semwal
C#
// A C# program to find
// a peak element element
// using divide and conquer
using System;
class GFG {
// A binary search based
// function that returns
// index of a peak element
static int findPeakUtil(int[] arr, int low,
int high, int n)
{
// Find index of
// middle element
int mid = low + (high - low) / 2;
// Compare middle element with
// its neighbours (if neighbours
// exist)
if ((mid == 0 || arr[mid - 1] <= arr[mid]) && (mid == n - 1 || arr[mid + 1] <= arr[mid]))
return mid;
// If middle element is not
// peak and its left neighbor
// is greater than it, then
// left half must have a
// peak element
else if (mid > 0 && arr[mid - 1] > arr[mid])
return findPeakUtil(arr, low,
(mid - 1), n);
// If middle element is not
// peak and its right neighbor
// is greater than it, then
// right half must have a peak
// element
else
return findPeakUtil(arr, (mid + 1),
high, n);
}
// A wrapper over recursive
// function findPeakUtil()
static int findPeak(int[] arr,
int n)
{
return findPeakUtil(arr, 0,
n - 1, n);
}
// Driver Code
static public void Main()
{
int[] arr = { 1, 3, 20,
4, 1, 0 };
int n = arr.Length;
Console.WriteLine("Index of a peak "
+ "point is " + findPeak(arr, n));
}
}
// This code is contributed by ajit
PHP
0 &&
$arr[$mid - 1] > $arr[$mid])
return findPeakUtil($arr, $low,
($mid - 1), $n);
// If middle element is not peak
// and its right neighbour is
// greater than it, then right
// half must have a peak element
else return(findPeakUtil($arr, ($mid + 1),
$high, $n));
}
// A wrapper over recursive
// function findPeakUtil()
function findPeak($arr, $n)
{
return floor(findPeakUtil($arr, 0,
$n - 1, $n));
}
// Driver Code
$arr = array(1, 3, 20, 4, 1, 0);
$n = sizeof($arr);
echo "Index of a peak point is ",
findPeak($arr, $n);
// This code is contributed by ajit
?>
Javascript
输出:
Index of a peak point is 2
复杂度分析:
- 时间复杂度: O(n)。
需要一次遍历,所以时间复杂度为 O(n) - 空间复杂度: O(1)。
不需要额外的空间,所以空间复杂度是恒定的
有效的方法:分而治之,可用于在 O(Logn) 时间内找到峰值。这个想法是基于二分搜索技术来检查中间元素是否是峰值元素。如果中间元素不是峰值元素,则检查右侧元素是否大于中间元素,则右侧始终存在峰值元素。如果左侧的元素大于中间的元素,则左侧总是有一个峰值元素。形成递归,可以在 log n 时间内找到峰值元素。
算法:
- 创建两个变量l和r ,初始化l = 0和r = n-1
- 迭代下面的步骤直到l <= r ,下限小于上限
- 检查中间值或索引mid = (l+r)/2是否是峰值元素,如果是,则打印元素并终止。
- 否则,如果中间元素左侧的元素更大,则检查左侧的峰值元素,即更新r = mid – 1
- 否则,如果中间元素右侧的元素更大,则检查右侧的峰值元素,即更新l = mid + 1
C++
// A C++ program to find a peak element
// using divide and conquer
#include
using namespace std;
// A binary search based function
// that returns index of a peak element
int findPeakUtil(int arr[], int low,
int high, int n)
{
// Find index of middle element
// (low + high)/2
int mid = low + (high - low) / 2;
// Compare middle element with its
// neighbours (if neighbours exist)
if ((mid == 0 || arr[mid - 1] <= arr[mid]) &&
(mid == n - 1 || arr[mid + 1] <= arr[mid]))
return mid;
// If middle element is not peak and its
// left neighbour is greater than it,
// then left half must have a peak element
else if (mid > 0 && arr[mid - 1] > arr[mid])
return findPeakUtil(arr, low, (mid - 1), n);
// If middle element is not peak and its
// right neighbour is greater than it,
// then right half must have a peak element
else
return findPeakUtil(
arr, (mid + 1), high, n);
}
// A wrapper over recursive function findPeakUtil()
int findPeak(int arr[], int n)
{
return findPeakUtil(arr, 0, n - 1, n);
}
// Driver Code
int main()
{
int arr[] = { 1, 3, 20, 4, 1, 0 };
int n = sizeof(arr) / sizeof(arr[0]);
cout << "Index of a peak point is "
<< findPeak(arr, n);
return 0;
}
// This code is contributed by rathbhupendra
C
// C program to find a peak
// element using divide and conquer
#include
// A binary search based function that
// returns index of a peak element
int findPeakUtil(
int arr[], int low, int high, int n)
{
// Find index of middle element
// (low + high)/2
int mid = low + (high - low) / 2;
// Compare middle element with
// its neighbours (if neighbours exist)
if ((mid == 0 || arr[mid - 1] <= arr[mid]) && (mid == n - 1 || arr[mid + 1] <= arr[mid]))
return mid;
// If middle element is not peak and
// its left neighbour is greater
// than it, then left half must have a peak element
else if (mid > 0 && arr[mid - 1] > arr[mid])
return findPeakUtil(arr, low, (mid - 1), n);
// If middle element is not peak and
// its right neighbour is greater
// than it, then right half must have a peak element
else
return findPeakUtil(arr, (mid + 1), high, n);
}
// A wrapper over recursive function findPeakUtil()
int findPeak(int arr[], int n)
{
return findPeakUtil(arr, 0, n - 1, n);
}
/* Driver program to check above functions */
int main()
{
int arr[] = { 1, 3, 20, 4, 1, 0 };
int n = sizeof(arr) / sizeof(arr[0]);
printf(
"Index of a peak point is %d", findPeak(arr, n));
return 0;
}
Java
// A Java program to find a peak
// element using divide and conquer
import java.util.*;
import java.lang.*;
import java.io.*;
class PeakElement {
// A binary search based function
// that returns index of a peak element
static int findPeakUtil(
int arr[], int low, int high, int n)
{
// Find index of middle element
// (low + high)/2
int mid = low + (high - low) / 2;
// Compare middle element with its
// neighbours (if neighbours exist)
if ((mid == 0 || arr[mid - 1] <= arr[mid])
&& (mid == n - 1 || arr[mid + 1] <= arr[mid]))
return mid;
// If middle element is not peak
// and its left neighbor is
// greater than it, then left half
// must have a peak element
else if (mid > 0 && arr[mid - 1] > arr[mid])
return findPeakUtil(arr, low, (mid - 1), n);
// If middle element is not peak
// and its right neighbor
// is greater than it, then right
// half must have a peak
// element
else
return findPeakUtil(
arr, (mid + 1), high, n);
}
// A wrapper over recursive function
// findPeakUtil()
static int findPeak(int arr[], int n)
{
return findPeakUtil(arr, 0, n - 1, n);
}
// Driver method
public static void main(String[] args)
{
int arr[] = { 1, 3, 20, 4, 1, 0 };
int n = arr.length;
System.out.println(
"Index of a peak point is " + findPeak(arr, n));
}
}
蟒蛇3
# A python3 program to find a peak
# element element using divide and conquer
# A binary search based function
# that returns index of a peak element
def findPeakUtil(arr, low, high, n):
# Find index of middle element
# (low + high)/2
mid = low + (high - low)/2
mid = int(mid)
# Compare middle element with its
# neighbours (if neighbours exist)
if ((mid == 0 or arr[mid - 1] <= arr[mid]) and
(mid == n - 1 or arr[mid + 1] <= arr[mid])):
return mid
# If middle element is not peak and
# its left neighbour is greater
# than it, then left half must
# have a peak element
elif (mid > 0 and arr[mid - 1] > arr[mid]):
return findPeakUtil(arr, low, (mid - 1), n)
# If middle element is not peak and
# its right neighbour is greater
# than it, then right half must
# have a peak element
else:
return findPeakUtil(arr, (mid + 1), high, n)
# A wrapper over recursive
# function findPeakUtil()
def findPeak(arr, n):
return findPeakUtil(arr, 0, n - 1, n)
# Driver code
arr = [1, 3, 20, 4, 1, 0]
n = len(arr)
print("Index of a peak point is", findPeak(arr, n))
# This code is contributed by
# Smitha Dinesh Semwal
C#
// A C# program to find
// a peak element element
// using divide and conquer
using System;
class GFG {
// A binary search based
// function that returns
// index of a peak element
static int findPeakUtil(int[] arr, int low,
int high, int n)
{
// Find index of
// middle element
int mid = low + (high - low) / 2;
// Compare middle element with
// its neighbours (if neighbours
// exist)
if ((mid == 0 || arr[mid - 1] <= arr[mid]) && (mid == n - 1 || arr[mid + 1] <= arr[mid]))
return mid;
// If middle element is not
// peak and its left neighbor
// is greater than it, then
// left half must have a
// peak element
else if (mid > 0 && arr[mid - 1] > arr[mid])
return findPeakUtil(arr, low,
(mid - 1), n);
// If middle element is not
// peak and its right neighbor
// is greater than it, then
// right half must have a peak
// element
else
return findPeakUtil(arr, (mid + 1),
high, n);
}
// A wrapper over recursive
// function findPeakUtil()
static int findPeak(int[] arr,
int n)
{
return findPeakUtil(arr, 0,
n - 1, n);
}
// Driver Code
static public void Main()
{
int[] arr = { 1, 3, 20,
4, 1, 0 };
int n = arr.Length;
Console.WriteLine("Index of a peak "
+ "point is " + findPeak(arr, n));
}
}
// This code is contributed by ajit
PHP
0 &&
$arr[$mid - 1] > $arr[$mid])
return findPeakUtil($arr, $low,
($mid - 1), $n);
// If middle element is not peak
// and its right neighbour is
// greater than it, then right
// half must have a peak element
else return(findPeakUtil($arr, ($mid + 1),
$high, $n));
}
// A wrapper over recursive
// function findPeakUtil()
function findPeak($arr, $n)
{
return floor(findPeakUtil($arr, 0,
$n - 1, $n));
}
// Driver Code
$arr = array(1, 3, 20, 4, 1, 0);
$n = sizeof($arr);
echo "Index of a peak point is ",
findPeak($arr, $n);
// This code is contributed by ajit
?>
Javascript
输出:
Index of a peak point is 2
复杂度分析:
- 时间复杂度: O(Logn)。
其中 n 是输入数组中的元素数。在每一步中,我们的搜索都变成了一半。所以可以比作二分查找,所以时间复杂度是O(log n) - 空间复杂度: O(1)。
不需要额外的空间,所以空间复杂度是恒定的。
锻炼:
考虑以下修改后的峰值元素定义。如果数组元素大于其相邻元素,则该数组元素是一个峰值。请注意,数组可能不包含具有此修改定义的峰值元素。
参考:
http://courses.csail.mit.edu/6.006/spring11/lectures/lec02.pdf
http://www.youtube.com/watch?v=HtSuA80QTyo
询问:亚马逊
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