项目中包含浮点运算，大概每秒 20 - 100 万左右. 其计算结果每秒只包含1000个左右。 因此大量运算是重复性的。程序运行时，cpu 在 3% - 10% 浮动。打算将结果缓存。根据键值索值。
目前考虑数据类型有: SortedList , SortedDictionary , Dictionary , List 。测试结果如下:
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" alt="" />
代码:
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text; namespace ConsoleApplication1
{
class Program
{
static System.Random random = new Random();
static void Main(string[] args)
{
System.Threading.Thread.Sleep(1000); System.Drawing.PointF[] p = new System.Drawing.PointF[1024];
for (int i = 0; i < 1024; i++)
{
p[i] = new System.Drawing.PointF((float)random.NextDouble(), (float)random.NextDouble());
} double[] find = new double[10];
find[0] = p[10].X;
find[1] = p[800].X;
find[2] = p[200].X;
find[3] = p[199].X;
find[4] = p[485].X;
find[5] = p[874].X;
find[6] = p[912].X;
find[7] = p[110].X;
find[8] = p[12].X;
find[9] = p[600].X; testSortList(p, find);
Console.WriteLine();
testSortedDictionary(p, find);
Console.WriteLine();
testDictionary(p, find);
Console.WriteLine();
testList(p, find); Console.Read(); } static void testSortList(System.Drawing.PointF [] p , double [] find) {
SortedList<double, double> s = new SortedList<double, double>(1024); System.Diagnostics.Stopwatch stopWatch = new System.Diagnostics.Stopwatch();
stopWatch.Start();
foreach (System.Drawing.PointF sp in p)
{
s.Add(sp.X, sp.Y);
}
stopWatch.Stop();
Console.WriteLine("SortedList add:" + stopWatch.ElapsedTicks); stopWatch.Reset();
stopWatch.Start();
foreach (double d in find)
{
Console.WriteLine(s.ContainsKey(d));
}
stopWatch.Stop(); Console.WriteLine("SortedList find:" + stopWatch.ElapsedTicks);
} static void testSortedDictionary(System.Drawing.PointF[] p, double[] find)
{
SortedDictionary<double, double> s = new SortedDictionary<double, double>(); System.Diagnostics.Stopwatch stopWatch = new System.Diagnostics.Stopwatch();
stopWatch.Start();
foreach (System.Drawing.PointF sp in p)
{
s.Add(sp.X, sp.Y);
}
stopWatch.Stop();
Console.WriteLine("SortedDictionary add:" + stopWatch.ElapsedTicks); stopWatch.Reset();
stopWatch.Start();
foreach (double d in find)
{
Console.WriteLine(s.ContainsKey(d));
}
stopWatch.Stop(); Console.WriteLine("SortedDictionary find:" + stopWatch.ElapsedTicks);
} static void testDictionary(System.Drawing.PointF[] p, double[] find)
{
Dictionary<double, double> s = new Dictionary<double, double>(1024); System.Diagnostics.Stopwatch stopWatch = new System.Diagnostics.Stopwatch();
stopWatch.Start();
foreach (System.Drawing.PointF sp in p)
{
s.Add(sp.X, sp.Y);
}
stopWatch.Stop();
Console.WriteLine("Dictionary add:" + stopWatch.ElapsedTicks); stopWatch.Reset();
stopWatch.Start();
foreach (double d in find)
{
Console.WriteLine(s.ContainsKey(d));
}
stopWatch.Stop(); Console.WriteLine("Dictionary find:" + stopWatch.ElapsedTicks);
} static void testList(System.Drawing.PointF[] p, double[] find)
{ List<System.Drawing.PointF> lst = new List<System.Drawing.PointF>(); System.Diagnostics.Stopwatch stopWatch = new System.Diagnostics.Stopwatch();
stopWatch.Start();
foreach (System.Drawing.PointF sp in p)
{
lst.Add(sp);
}
stopWatch.Stop();
Console.WriteLine("List add:" + stopWatch.ElapsedTicks); stopWatch.Reset();
stopWatch.Start();
System.Drawing.PointF p2;
bool bln = false ;
foreach (double d in find)
{
p2 = lst.Find(new Predicate<System.Drawing.PointF>((p1) =>
{
return p1.X == d;
})); //foreach (System.Drawing.PointF p1 in lst)
//{
// if (p1.X == d)
// {
// bln = true;
// break;
// }
//} //for (int i = 0; i < lst.Count; i++ )
//{
// if (lst[i].X == d)
// {
// bln = true;
// break;
// }
//} if (bln)
{
Console.WriteLine("True");
bln = false;
}
else {
Console.WriteLine("False");
}
}
stopWatch.Stop(); Console.WriteLine("List find:" + stopWatch.ElapsedTicks);
} }
}