我有一个数组,其中必须将前两个最小值相加,因此结果必须与下一个最小值相加,依此类推,直到到达数组的末尾以给出最终的总数。
但是,如何动态修改方法/函数,因此,如果值发生变化并且我在数组中有6个vehicles
和6个specs
值,则方法/函数合计的返回不会仅限4个索引。
数组值未排序,因此要添加第一个最小值,必须对其进行排序。一旦完成,它将添加新数组的值。
这是我尝试过的:
public static int vehicles = 4;
public static int[] specs = new int[] { 40, 8, 16, 6 };
public static int time(int vehicles, int[] specs)
{
int newValue = 0;
for (int i = 1; i < vehicles; i++)
{
newValue = specs[i];
int j = i;
while (j > 0 && specs[j - 1] > newValue)
{
specs[j] = specs[j - 1];
j--;
}
specs[j] = newValue;
}
// How can I dynamically change this below:
int result1 = specs[0] + specs[1];
int result2 = result1 + specs[2];
int result3 = result2 + specs[3];
int total = result1 + result2 + result3;
return total; // Returns 114
}
这是它的工作原理:
4, [40, 8, 16, 6] = 14 --> [40, 14, 16] = 30 --> [40, 30] = 70 ==>> 14 + 30 + 70 = 114
6, [62, 14, 2, 6, 28, 41 ] = 8 --> [62, 14, 8, 28, 41 ] --> 22 [62, 22, 28, 41 ] --> 50
[62, 50, 41 ] --> 91 [62, 91 ] --> 153 ==> 8 + 22 + 50 + 91 + 153 = 324
答案 0 :(得分:1)
首先,如果由于某些奇怪的原因而不受限于使用数组,请使用List<int>
,这样会使您的生活更轻松。
List<int> integers = { 14, 6, 12, 8 };
integers.Sort();
integers.Reverse();
while( integers.Count > 1 )
{
int i = integers[integers.Count - 1];
int j = integers[integers.Count - 2];
integers[integers.Count - 2] = i + j;
integers.RemoveAt(integers.Count - 1);
}
var result = integers[0];
P.S .:可以很容易地对其进行修改以在阵列版本上运行,您不能RemoveAt()
从阵列上使用,但是可以单独维护lastValidIndex。
答案 1 :(得分:1)
我会使用Linq。
Enumerable.Range(2, specs.Length - 1)
.Select(i => specs
.Take(i)
.Sum())
.Sum();
说明:
specs.Length
结尾。i
的前specs
个值相加,其中i
是该范围内的当前值。要了解有关linq的更多信息,请启动here。
仅当值已经排序时,此代码才有效。
如果要使用linq对值进行排序,则应使用以下代码:
IEnumerable<int> sorted = specs.OrderBy(x => x);
Enumerable.Range(2, sorted.Count() - 1)
.Select(i => sorted
.Take(i)
.Sum())
.Sum();
OrderBy
函数需要知道如何获取用于比较数组值的值。由于数组值是,我们要比较的值只需要使用x => x
进行选择即可。这个lamba取值并再次返回。
答案 2 :(得分:1)
请参阅代码中的注释以获取解释。
using System;
using System.Linq;
class Program
{
static void Main()
{
//var inputs = new [] { 40, 8, 16, 6 }; // total = 114
var inputs = new[] { 62, 14, 2, 6, 28, 41 }; // total = 324
var total = 0;
var query = inputs.AsEnumerable();
while (query.Count() > 1)
{
// sort the numbers
var sorted = query.OrderBy(x => x).ToList();
// get sum of the first two smallest numbers
var sumTwoSmallest = sorted.Take(2).Sum();
// count total
total += sumTwoSmallest;
// remove the first two smallest numbers
query = sorted.Skip(2);
// add the sum of the two smallest numbers into the numbers
query = query.Append(sumTwoSmallest);
}
Console.WriteLine($"Total = {total}");
Console.WriteLine("Press any key...");
Console.ReadKey(true);
}
}
我对我的代码进行了基准测试,在处理大型数据集时结果很糟糕。我怀疑是因为循环中的排序。需要排序是因为我需要在每次迭代中找到2个最小的数字。所以我认为我需要一种更好的方法来解决这个问题。我使用PriorityQueue(来自visualstudiomagazine.com),因为元素是根据优先级出队的,在这种情况下,数字越小优先级越高。
long total = 0;
while (pq.Count() > 0)
{
// get two smallest numbers when the priority queue is not empty
int sum = (pq.Count() > 0 ? pq.Dequeue() : 0) + (pq.Count() > 0 ? pq.Dequeue() : 0);
total += sum;
// put the sum of two smallest numbers in the priority queue if the queue is not empty
if (pq.Count() > 0) pq.Enqueue(sum);
}
以下是发行版本中新(优先级队列)代码和旧代码的一些基准测试结果。结果以毫秒为单位。我没有用旧代码测试100万个数据,因为它太慢了。
+---------+----------+-------------+
| Data | New | Old |
+---------+----------+-------------+
| 10000 | 3.9158 | 5125.9231 |
| 50000 | 16.8375 | 147219.4267 |
| 1000000 | 406.8693 | |
+---------+----------+-------------+
完整代码:
using System;
using System.Diagnostics;
using System.IO;
using System.Linq;
class Program
{
static void Main()
{
const string fileName = @"numbers.txt";
using (var writer = new StreamWriter(fileName))
{
var random = new Random();
for (var i = 0; i < 10000; i++)
writer.WriteLine(random.Next(100));
writer.Close();
}
var sw = new Stopwatch();
var pq = new PriorityQueue<int>();
var numbers = File.ReadAllLines(fileName);
foreach (var number in numbers)
pq.Enqueue(Convert.ToInt32(number));
long total = 0;
sw.Start();
while (pq.Count() > 0)
{
// get two smallest numbers when the priority queue is not empty
int sum = (pq.Count() > 0 ? pq.Dequeue() : 0) + (pq.Count() > 0 ? pq.Dequeue() : 0);
total += sum;
// put the sum of two smallest numbers in the priority queue if the queue is not empty
if (pq.Count() > 0) pq.Enqueue(sum);
}
sw.Stop();
Console.WriteLine($"Total = {total}");
Console.WriteLine($"Time = {sw.Elapsed.TotalMilliseconds}");
total = 0;
var query = File.ReadAllLines(fileName).Select(x => Convert.ToInt32(x));
sw.Restart();
while (query.Count() > 0)
{
// sort the numbers
var sorted = query.OrderBy(x => x).ToList();
// get sum of the first two smallest numbers
var sumTwoSmallest = sorted.Take(2).Sum();
// count total
total += sumTwoSmallest;
// remove the first two smallest numbers
query = sorted.Skip(2);
// add the sum of the two smallest numbers into the numbers
if (query.Count() > 0)
query = query.Append(sumTwoSmallest);
}
sw.Stop();
Console.WriteLine($"Total = {total}");
Console.WriteLine($"Time = {sw.Elapsed.TotalMilliseconds}");
Console.WriteLine("Press any key...");
Console.ReadKey(true);
}
}
PriorityQueue代码:
using System;
using System.Collections.Generic;
// From http://visualstudiomagazine.com/articles/2012/11/01/priority-queues-with-c.aspx
public class PriorityQueue<T> where T : IComparable<T>
{
private List<T> data;
public PriorityQueue()
{
this.data = new List<T>();
}
public void Enqueue(T item)
{
data.Add(item);
int ci = data.Count - 1; // child index; start at end
while (ci > 0)
{
int pi = (ci - 1) / 2; // parent index
if (data[ci].CompareTo(data[pi]) >= 0)
break; // child item is larger than (or equal) parent so we're done
T tmp = data[ci];
data[ci] = data[pi];
data[pi] = tmp;
ci = pi;
}
}
public T Dequeue()
{
// assumes pq is not empty; up to calling code
int li = data.Count - 1; // last index (before removal)
T frontItem = data[0]; // fetch the front
data[0] = data[li];
data.RemoveAt(li);
--li; // last index (after removal)
int pi = 0; // parent index. start at front of pq
while (true)
{
int ci = pi * 2 + 1; // left child index of parent
if (ci > li)
break; // no children so done
int rc = ci + 1; // right child
if (rc <= li && data[rc].CompareTo(data[ci]) < 0) // if there is a rc (ci + 1), and it is smaller than left child, use the rc instead
ci = rc;
if (data[pi].CompareTo(data[ci]) <= 0)
break; // parent is smaller than (or equal to) smallest child so done
T tmp = data[pi];
data[pi] = data[ci];
data[ci] = tmp; // swap parent and child
pi = ci;
}
return frontItem;
}
public T Peek()
{
T frontItem = data[0];
return frontItem;
}
public int Count()
{
return data.Count;
}
public override string ToString()
{
string s = "";
for (int i = 0; i < data.Count; ++i)
s += data[i].ToString() + " ";
s += "count = " + data.Count;
return s;
}
public bool IsConsistent()
{
// is the heap property true for all data?
if (data.Count == 0)
return true;
int li = data.Count - 1; // last index
for (int pi = 0; pi < data.Count; ++pi)
{ // each parent index
int lci = 2 * pi + 1; // left child index
int rci = 2 * pi + 2; // right child index
if (lci <= li && data[pi].CompareTo(data[lci]) > 0)
return false; // if lc exists and it's greater than parent then bad.
if (rci <= li && data[pi].CompareTo(data[rci]) > 0)
return false; // check the right child too.
}
return true; // passed all checks
}
// IsConsistent
}
// PriorityQueue
参考:
答案 3 :(得分:1)
我将使用使用LINQ的最简单的单行解决方案版本:
Array.Sort(specs);
int total = specs.Select((n, i) => specs.Take(i + 1).Sum()).Sum() - (specs.Length > 1 ? specs[0] : 0);
答案 4 :(得分:0)
您可以简单地使用Array.Sort()
对它进行排序,然后将其总和存入一个以最小值开头的新数组中,并将每个下一个值加到最近的总和中,总和就是最后一个总和的值
public static int time(int vehicles, int[] specs)
{
int i, total;
int[] sums = new int[vehicles];
Array.Sort(spec);
sums[0] = specs[0];
for (i = 1; i < vehicles; i++)
sums[i] = sums[i - 1] + spec[i];
total = sums[spec - 1];
}