我有2个文件:
问题是:
我正在生成随机密钥[它是混洗字母线a = j,k = u,...],解密文本并将其与语言分析进行比较,这意味着如果文本是1000个字符长,这意味着我必须比较1000 -3 = 997四元语言与语言分析文件,意味着单次尝试中最多997 * 52000 = 51.8mil比较,需要大约20 000个键才能获得原始文本=>高达51.8百万* 20 000比较。目前我在string [] []中有语言分析文件。我需要尽可能快地进行比较。
我的想法:
创建“帮助”数组,其中包含语言分析的第一个字母(后面只有LA),如此A = 0; B = 3564(以B(BAAA)开始的第一个四分位数是3564.在LA中的字符串); ...当我将有四分之一的cyphrated文本,例如BECA我将开始我的FOR循环从3564搜索tetragram BECA。来自LA的字符串而不是0.是否有任何类型的多维数组 - 哈希表,目录,这将为我解决这个问题,并且会足够快吗?
答案 0 :(得分:2)
听起来你指的是类似于Bucket Sort的方法。
因为Tetragram中只有26 ^ 4(456,976)种可能的组合,所以应该可以在单个数组结构中表示整个四元组值的集合。 (你可以让它变得多维,只是为了让生活更轻松)。这应该是超快速查找。
void Main()
{
var buckets = new double[26,26,26,26];
PopulateBucketsFromFile(buckets);
foreach(string tetragram in input)
{
var frequency = buckets[
GetBucketIndex(tetragram, 1),
GetBucketIndex(tetragram, 2),
GetBucketIndex(tetragram, 3),
GetBucketIndex(tetragram, 4)];
}
}
// This reduces repetetive code: if your program still isn't fast
// enough you may try inlining this method (although it's likely
// that the JITter will just do this for you.
int GetBucketIndex(string tetragram, int i)
{
return tetragram[i] - 'A';
}
是否有任何类型的多维数组 - 哈希表,目录,这可以为我解决这个问题并且速度足够快?
“足够快”?没有测试它是不可能的,这对你来说是否足够快。
我的基准测试表明,我可以比较1000个字符串中的所有997四分之一,每秒超过50,000次。这够快吗?
使用词典,我每秒只能做大约8000次。这慢了5倍,但代码更简单。正如你在评论中提到的那样,这仍然比你以前做的要快得多。 “足够快”将取决于您的业务案例。
基准,供参考:
/* This is a benchmarking template I use in LINQPad when I want to do a
* quick performance test. Just give it a couple of actions to test and
* it will give you a pretty good idea of how long they take compared
* to one another. It's not perfect: You can expect a 3% error margin
* under ideal circumstances. But if you're not going to improve
* performance by more than 3%, you probably don't care anyway.*/
void Main()
{
// Enter setup code here
var random = new Random();
var chars = new char[1000];
for (int i = 0; i < chars.Length; i++)
{
chars[i] = (char)random.Next('A', 'Z' + 1);
}
var str = new string(chars);
var probabilities = Enumerable.Range(0, (int)Math.Pow(26, 4)).Select(i => random.NextDouble()).ToList();
var probabArray = new double[26,26,26,26];
for (int i = 0; i < probabilities.Count; i++)
{
int j1 = i % 26,
j2 = i / 26 % 26,
j3 = i / 26 / 26 % 26,
j4 = i / 26 / 26 / 26 % 26;
probabArray[j1, j2, j3, j4] = probabilities[i];
}
var probabDict = probabilities.Select((p, i) => new{
prob = p,
str = new string(new char[]{(char)(i%26 + 'A'), (char)(i / 26 % 26 + 'A'), (char)(i / 26 / 26 % 26 + 'A'), (char)(i / 26 / 26 / 26 % 26 + 'A')})
}).ToDictionary(e => e.str, e => e.prob);
var actions = new[]
{
new TimedAction("first", () =>
{
for(int i = 0; i < str.Length - 3; i++)
{
var prob = probabArray[str[i] - 'A', str[i + 1] - 'A', str[i + 2] - 'A', str[i + 3] - 'A'];
}
}),
new TimedAction("second", () =>
{
for(int i = 0; i < str.Length - 3; i++)
{
var prob = probabDict[str.Substring(i, 4)];
}
}),
// Enter additional tests here
};
const int TimesToRun = 10000; // Tweak this as necessary
TimeActions(TimesToRun, actions);
}
#region timer helper methods
// Define other methods and classes here
public void TimeActions(int iterations, params TimedAction[] actions)
{
Stopwatch s = new Stopwatch();
int length = actions.Length;
var results = new ActionResult[actions.Length];
// Perform the actions in their initial order.
for(int i = 0; i < length; i++)
{
var action = actions[i];
var result = results[i] = new ActionResult{Message = action.Message};
// Do a dry run to get things ramped up/cached
result.DryRun1 = s.Time(action.Action, 10);
result.FullRun1 = s.Time(action.Action, iterations);
}
// Perform the actions in reverse order.
for(int i = length - 1; i >= 0; i--)
{
var action = actions[i];
var result = results[i];
// Do a dry run to get things ramped up/cached
result.DryRun2 = s.Time(action.Action, 10);
result.FullRun2 = s.Time(action.Action, iterations);
}
results.Dump();
}
public class ActionResult
{
public string Message {get;set;}
public double DryRun1 {get;set;}
public double DryRun2 {get;set;}
public double FullRun1 {get;set;}
public double FullRun2 {get;set;}
}
public class TimedAction
{
public TimedAction(string message, Action action)
{
Message = message;
Action = action;
}
public string Message {get;private set;}
public Action Action {get;private set;}
}
public static class StopwatchExtensions
{
public static double Time(this Stopwatch sw, Action action, int iterations)
{
sw.Restart();
for (int i = 0; i < iterations; i++)
{
action();
}
sw.Stop();
return sw.Elapsed.TotalMilliseconds;
}
}
#endregion
结果:
Message DryRun1 DryRun2 FullRun1 FullRun2
first 0.5502 0.3217 221.5343 222.9831
second 2.4481 1.063 1384.6288 1138.6466