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I have an array of boolean values and need to randomly select a specific quantity of indices for values which are true.
What is the most efficient way to generate the array of indices?
For instance,
BitArray mask = GenerateSomeMask(length: 100000);
int[] randomIndices = RandomIndicesForTrue(mask, quantity: 10);
In this case the length of randomIndices would be 10.
There's a faster way to do this that requires only a single scan of the list.
Consider picking a line at random from a text file when you don't know how many lines are in the file, and the file is too large to fit in memory. The obvious solution is to read the file once to count the lines, pick a random number in the range of 0 to Count-1, and then read the file again up to the chosen line number. That works, but requires you to read the file twice.
A faster solution is to read the first line and save it as the selected line. You replace the selected line with the next line with probability 1/2. When you read the third line, you replace with probability 1/3, etc. When you've read the entire file, you have selected a line at random, and every line had equal probability of being selected. The code looks something like this:
string selectedLine = null;
int numLines = 0;
Random rnd = new Random();
foreach (var line in File.ReadLines(filename))
{
++numLines;
double prob = 1.0/numLines;
if (rnd.Next() >= prob)
selectedLine = line;
}
Now, what if you want to select 2 lines? You select the first two. Then, as each line is read the probability that it will replace one of the two lines is 2/n, where n is the number of lines already read. If you determine that you need to replace a line, you randomly select the line to be replaced. You can follow that same basic idea to select any number of lines at random. For example:
string[] selectedLines = new int[M];
int numLines = 0;
Random rnd = new Random();
foreach (var line in File.ReadLines(filename))
{
++numLines;
if (numLines <= M)
{
selectedLines[numLines-1] = line;
}
else
{
double prob = (double)M/numLines;
if (rnd.Next() >= prob)
{
int ix = rnd.Next(M);
selectedLines[ix] = line;
}
}
}
You can apply that to your BitArray quite easily:
int[] selected = new int[quantity];
int num = 0; // number of True items seen
Random rnd = new Random();
for (int i = 0; i < items.Length; ++i)
{
if (items[i])
{
++num;
if (num <= quantity)
{
selected[num-1] = i;
}
else
{
double prob = (double)quantity/num;
if (rnd.Next() > prob)
{
int ix = rnd.Next(quantity);
selected[ix] = i;
}
}
}
}
You'll need some special case code at the end to handle the case where there aren't quantity set bits in the array, but you'll need that with any solution.
This makes a single pass over the BitArray, and the only extra memory it uses is for the list of selected indexes. I'd be surprised if it wasn't significantly faster than the LINQ version.
Note that I used the probability calculation to illustrate the math. You can change the inner loop code in the first example to:
if (rnd.Next(numLines+1) == numLines)
{
selectedLine = line;
}
++numLines;
You can make a similar change to the other examples. That does the same thing as the probability calculation, and should execute a little faster because it eliminates a floating point divide for each item.
There are two families of approaches you can use: deterministic and non-deterministic. The first one involves finding all the eligible elements in the collection and then picking N at random; the second involves randomly reaching into the collection until you have found N eligible items.
Since the size of your collection is not negligible at 100K and you only want to pick a few out of those, at first sight non-deterministic sounds like it should be considered because it can give very good results in practice. However, since there is no guarantee that N true values even exist in the collection, going non-deterministic could put your program into an infinite loop (less catastrophically, it could just take a very long time to produce results).
Therefore I am going to suggest going for a deterministic approach, even though you are going to pay for the guarantees you need through the nose with resource usage. In particular, the operation will involve in-place sorting of an auxiliary collection; this will practically undo the nice space savings you got by using BitArray.
Theory aside, let's get to work. The standard way to handle this is:
Filter all eligible indices into an auxiliary collection.
Randomly shuffle the collection with Fisher-Yates (there's a convenient implementation on StackOverflow).
Pick the N first items of the shuffled collection. If there are less than N then your input cannot satisfy your requirements.
Translated into LINQ:
var results = mask
.Select((i, f) => Tuple.Create) // project into index/bool pairs
.Where(t => t.Item2) // keep only those where bool == true
.Select(t => t.Item1) // extract indices
.ToList() // prerequisite for next step
.Shuffle() // Fisher-Yates
.Take(quantity) // pick N
.ToArray(); // into an int[]
if (results.Length < quantity)
{
// not enough true values in input
}
If you have 10 indices to choose from, you could generate a random number from 0 to 2^10 - 1, and use that as you mask.
IMPORTANT NOTE
To the people who flagged this as a duplicate, please understand we do NOT want a LINQ-based solution. Our real-world example has several original lists in the tens-of-thousands range and LINQ-based solutions are not performant enough for our needs since they have to walk the lists several times to perform their function, expanding with each new source list.
That is why we are specifically looking for a non-LINQ algorithm, such as the one suggested in this answer below where they walk all lists simultaneously, and only once, via enumerators. That seems to be the best so far, but I am wondering if there are others.
Now back to the question...
For the sake of explaining our issue, consider this hypothetical problem:
I have multiple lists, but to keep this example simple, let's limit it to two, ListA and ListB, both of which are of type List<int>. Their data is as follows:
List A List B
1 2
2 3
4 4
5 6
6 8
8 9
9 10
...however the real lists can have tens of thousands of rows.
We next have a class called ListPairing that's simply defined as follows:
public class ListPairing
{
public int? ASide{ get; set; }
public int? BSide{ get; set; }
}
where each 'side' parameter really represents one of the lists. (i.e. if there were four lists, it would also have a CSide and a DSide.)
We are trying to do is construct a List<ListPairing> with the data initialized as follows:
A Side B Side
1 -
2 2
- 3
4 4
5 -
6 6
8 8
9 9
- 10
Again, note there is no row with '7'
As you can see, the results look like a full outer join. However, please see the update below.
Now to get things started, we can simply do this...
var finalList = ListA.Select(valA => new ListPairing(){ ASide = valA} );
Which yields...
A Side B Side
1 -
2 -
4 -
5 -
6 -
8 -
9 -
and now we want to go back-fill the values from List B. This requires checking first if there is an already existing ListPairing with ASide that matches BSide and if so, setting the BSide.
If there is no existing ListPairing with a matching ASide, a new ListPairing is instantiated with only the BSide set (ASide is blank.)
However, I get the feeling that's not the most efficient way to do this considering all of the required 'FindFirst' calls it would take. (These lists can be tens of thousands of items long.)
However, taking a union of those lists once up front yields the following values...
1, 2, 3, 4, 5, 6, 8, 9, 10 (Note there is no #7)
My thinking was to somehow use that ordered union of the values, then 'walking' both lists simultaneously, building up ListPairings as needed. That eliminates repeated calls to FindFirst, but I'm wondering if that's the most efficient way to do this.
Thoughts?
Update
People have suggested this is a duplicate of getting a full outer join using LINQ because the results are the same...
I am not after a LINQ full outer join. I'm after a performant algorithm.
As such, I have updated the question.
The reason I bring this up is the LINQ needed to perform that functionality is much too slow for our needs. In our model, there are actually four lists, and each can be in the tens of thousands of rows. That's why I suggested the 'Union' approach of the IDs at the very end to get the list of unique 'keys' to walk through, but I think the posted answer on doing the same but with the enumerators is an even better approach as you don't need the list of IDs up front. This would yield a single pass through all items in the lists simultaneously which would easily out-perform the LINQ-based approach.
This didn't turn out as neat as I'd hoped, but if both input lists are sorted then you can just walk through them together comparing the head elements of each one: if they're equal then you have a pair, else emit the smallest one on its own and advance that list.
public static IEnumerable<ListPairing> PairUpLists(IEnumerable<int> sortedAList,
IEnumerable<int> sortedBList)
{
// Should wrap these two in using() per Servy's comment with braces around
// the rest of the method.
var aEnum = sortedAList.GetEnumerator();
var bEnum = sortedBList.GetEnumerator();
bool haveA = aEnum.MoveNext();
bool haveB = bEnum.MoveNext();
while (haveA && haveB)
{
// We still have values left on both lists.
int comparison = aEnum.Current.CompareTo(bEnum.Current);
if (comparison < 0)
{
// The heads of the two remaining sequences do not match and A's is
// lower. Generate a partial pair with the head of A and advance the
// enumerator.
yield return new ListPairing() {ASide = aEnum.Current};
haveA = aEnum.MoveNext();
}
else if (comparison == 0)
{
// The heads of the two sequences match. Generate a pair.
yield return new ListPairing() {
ASide = aEnum.Current,
BSide = bEnum.Current
};
// Advance both enumerators
haveA = aEnum.MoveNext();
haveB = bEnum.MoveNext();
}
else
{
// No match and B is the lowest. Generate a partial pair with B.
yield return new ListPairing() {BSide = bEnum.Current};
// and advance the enumerator
haveB = bEnum.MoveNext();
}
}
if (haveA)
{
// We still have elements on list A but list B is exhausted.
do
{
// Generate a partial pair for all remaining A elements.
yield return new ListPairing() { ASide = aEnum.Current };
} while (aEnum.MoveNext());
}
else if (haveB)
{
// List A is exhausted but we still have elements on list B.
do
{
// Generate a partial pair for all remaining B elements.
yield return new ListPairing() { BSide = bEnum.Current };
} while (bEnum.MoveNext());
}
}
var list1 = new List<int?>(){1,2,4,5,6,8,9};
var list2 = new List<int?>(){2,3,4,6,8,9,10};
var left = from i in list1
join k in list2 on i equals k
into temp
from k in temp.DefaultIfEmpty()
select new {a = i, b = (i == k) ? k : (int?)null};
var right = from k in list2
join i in list1 on k equals i
into temp
from i in temp.DefaultIfEmpty()
select new {a = (i == k) ? i : (int?)i , b = k};
var result = left.Union(right);
If you need the ordering to be same as your example, then you will need to provide an index and order by that (then remove duplicates)
var result = left.Select((o,i) => new {o.a, o.b, i}).Union(right.Select((o, i) => new {o.a, o.b, i})).OrderBy( o => o.i);
result.Select( o => new {o.a, o.b}).Distinct();
Is there a way, with LINQ, to check if a list of integers are "sequential" - ie 1,2,3,4,5 or 14,15,16,17,18?
You could do this via Enumerable.Zip:
bool sequential = values.Zip(values.Skip(1), (a,b) => (a+1) == b).All(x => x);
This works by taking each pair of values, and checking to see if the second is 1 more than the first, and returning booleans. If all pairs fit the criteria, the values are sequential.
Given that this is a list of integers, you can do this slightly more efficiently using:
bool sequential = values.Skip(1).Select((v,i) => v == (values[i]+1)).All(v => v);
This will only work on sequences which can be accessed by index. Note that we use values[i], not values[i-1], as the Skip call effectively shifts the indices.
bool isSequential = Enumerable.Range(values.Min(), values.Count())
.SequenceEqual(values);
One more option is to use Aggregate to iterate sequence only once.
Note that unlike All suggested by Reed Copsey Aggregate can't stop in the middle when condition fails...
var s = new int[] {3,4,5,6}.ToList();
var isSequential = s.Aggregate
(
new {PrevValue = 0, isFirst = true, Success = true} ,
(acc, current) =>
new {
PrevValue = current,
isFirst = false,
Success = acc.Success && (acc.isFirst || (acc.PrevValue == current - 1))
}
)
.Success;
Fancier version would be to have iterator that carries previous value along or special code that would split iterator on "First and the rest" allowing to implement Reed's solution with single iteration for any enumerable.
If you already know that the numbers you have in your list is unique, and also sorted, then the simplest check for sequential is just
lst[lst.Count - 1] - lst[0] == lst.Count - 1
Assume atleast 1 element in list.
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I have read an article about various shuffle algorithms over at Coding Horror. I have seen that somewhere people have done this to shuffle a list:
var r = new Random();
var shuffled = ordered.OrderBy(x => r.Next());
Is this a good shuffle algorithm? How does it work exactly? Is it an acceptable way of doing this?
It's not a way of shuffling that I like, mostly on the grounds that it's O(n log n) for no good reason when it's easy to implement an O(n) shuffle. The code in the question "works" by basically giving a random (hopefully unique!) number to each element, then ordering the elements according to that number.
I prefer Durstenfeld's variant of the Fisher-Yates shuffle which swaps elements.
Implementing a simple Shuffle extension method would basically consist of calling ToList or ToArray on the input then using an existing implementation of Fisher-Yates. (Pass in the Random as a parameter to make life generally nicer.) There are plenty of implementations around... I've probably got one in an answer somewhere.
The nice thing about such an extension method is that it would then be very clear to the reader what you're actually trying to do.
EDIT: Here's a simple implementation (no error checking!):
public static IEnumerable<T> Shuffle<T>(this IEnumerable<T> source, Random rng)
{
T[] elements = source.ToArray();
// Note i > 0 to avoid final pointless iteration
for (int i = elements.Length-1; i > 0; i--)
{
// Swap element "i" with a random earlier element it (or itself)
int swapIndex = rng.Next(i + 1);
T tmp = elements[i];
elements[i] = elements[swapIndex];
elements[swapIndex] = tmp;
}
// Lazily yield (avoiding aliasing issues etc)
foreach (T element in elements)
{
yield return element;
}
}
EDIT: Comments on performance below reminded me that we can actually return the elements as we shuffle them:
public static IEnumerable<T> Shuffle<T>(this IEnumerable<T> source, Random rng)
{
T[] elements = source.ToArray();
for (int i = elements.Length - 1; i >= 0; i--)
{
// Swap element "i" with a random earlier element it (or itself)
// ... except we don't really need to swap it fully, as we can
// return it immediately, and afterwards it's irrelevant.
int swapIndex = rng.Next(i + 1);
yield return elements[swapIndex];
elements[swapIndex] = elements[i];
}
}
This will now only do as much work as it needs to.
Note that in both cases, you need to be careful about the instance of Random you use as:
Creating two instances of Random at roughly the same time will yield the same sequence of random numbers (when used in the same way)
Random isn't thread-safe.
I have an article on Random which goes into more detail on these issues and provides solutions.
This is based on Jon Skeet's answer.
In that answer, the array is shuffled, then returned using yield. The net result is that the array is kept in memory for the duration of foreach, as well as objects necessary for iteration, and yet the cost is all at the beginning - the yield is basically an empty loop.
This algorithm is used a lot in games, where the first three items are picked, and the others will only be needed later if at all. My suggestion is to yield the numbers as soon as they are swapped. This will reduce the start-up cost, while keeping the iteration cost at O(1) (basically 5 operations per iteration). The total cost would remain the same, but the shuffling itself would be quicker. In cases where this is called as collection.Shuffle().ToArray() it will theoretically make no difference, but in the aforementioned use cases it will speed start-up. Also, this would make the algorithm useful for cases where you only need a few unique items. For example, if you need to pull out three cards from a deck of 52, you can call deck.Shuffle().Take(3) and only three swaps will take place (although the entire array would have to be copied first).
public static IEnumerable<T> Shuffle<T>(this IEnumerable<T> source, Random rng)
{
T[] elements = source.ToArray();
// Note i > 0 to avoid final pointless iteration
for (int i = elements.Length - 1; i > 0; i--)
{
// Swap element "i" with a random earlier element it (or itself)
int swapIndex = rng.Next(i + 1);
yield return elements[swapIndex];
elements[swapIndex] = elements[i];
// we don't actually perform the swap, we can forget about the
// swapped element because we already returned it.
}
// there is one item remaining that was not returned - we return it now
yield return elements[0];
}
Starting from this quote of Skeet:
It's not a way of shuffling that I like, mostly on the grounds that it's O(n log n) for no good reason when it's easy to implement an O(n) shuffle. The code in the question "works" by basically giving a random (hopefully unique!) number to each element, then ordering the elements according to that number.
I'll go on a little explaining the reason for the hopefully unique!
Now, from the Enumerable.OrderBy:
This method performs a stable sort; that is, if the keys of two elements are equal, the order of the elements is preserved
This is very important! What happens if two elements "receive" the same random number? It happens that they remain in the same order they are in the array. Now, what is the possibility for this to happen? It is difficult to calculate exactly, but there is the Birthday Problem that is exactly this problem.
Now, is it real? Is it true?
As always, when in doubt, write some lines of program: http://pastebin.com/5CDnUxPG
This little block of code shuffles an array of 3 elements a certain number of times using the Fisher-Yates algorithm done backward, the Fisher-Yates algorithm done forward (in the wiki page there are two pseudo-code algorithms... They produce equivalent results, but one is done from first to last element, while the other is done from last to first element), the naive wrong algorithm of http://blog.codinghorror.com/the-danger-of-naivete/ and using the .OrderBy(x => r.Next()) and the .OrderBy(x => r.Next(someValue)).
Now, Random.Next is
A 32-bit signed integer that is greater than or equal to 0 and less than MaxValue.
so it's equivalent to
OrderBy(x => r.Next(int.MaxValue))
To test if this problem exists, we could enlarge the array (something very slow) or simply reduce the maximum value of the random number generator (int.MaxValue isn't a "special" number... It is simply a very big number). In the end, if the algorithm isn't biased by the stableness of the OrderBy, then any range of values should give the same result.
The program then tests some values, in the range 1...4096. Looking at the result, it's quite clear that for low values (< 128), the algorithm is very biased (4-8%). With 3 values you need at least r.Next(1024). If you make the array bigger (4 or 5), then even r.Next(1024) isn't enough. I'm not an expert in shuffling and in math, but I think that for each extra bit of length of the array, you need 2 extra bits of maximum value (because the birthday paradox is connected to the sqrt(numvalues)), so that if the maximum value is 2^31, I'll say that you should be able to sort arrays up to 2^12/2^13 bits (4096-8192 elements)
It's probablly ok for most purposes, and almost always it generates a truly random distribution (except when Random.Next() produces two identical random integers).
It works by assigning each element of the series a random integer, then ordering the sequence by these integers.
It's totally acceptable for 99.9% of the applications (unless you absolutely need to handle the edge case above). Also, skeet's objection to its runtime is valid, so if you're shuffling a long list you might not want to use it.
This has come up many times before. Search for Fisher-Yates on StackOverflow.
Here is a C# code sample I wrote for this algorithm. You can parameterize it on some other type, if you prefer.
static public class FisherYates
{
// Based on Java code from wikipedia:
// http://en.wikipedia.org/wiki/Fisher-Yates_shuffle
static public void Shuffle(int[] deck)
{
Random r = new Random();
for (int n = deck.Length - 1; n > 0; --n)
{
int k = r.Next(n+1);
int temp = deck[n];
deck[n] = deck[k];
deck[k] = temp;
}
}
}
Seems like a good shuffling algorithm, if you're not too worried on the performance. The only problem I'd point out is that its behavior is not controllable, so you may have a hard time testing it.
One possible option is having a seed to be passed as a parameter to the random number generator (or the random generator as a parameter), so you can have more control and test it more easily.
I found Jon Skeet's answer to be entirely satisfactory, but my client's robo-scanner will report any instance of Random as a security flaw. So I swapped it out for System.Security.Cryptography.RNGCryptoServiceProvider. As a bonus, it fixes that thread-safety issue that was mentioned. On the other hand, RNGCryptoServiceProvider has been measured as 300x slower than using Random.
Usage:
using (var rng = new RNGCryptoServiceProvider())
{
var data = new byte[4];
yourCollection = yourCollection.Shuffle(rng, data);
}
Method:
/// <summary>
/// Shuffles the elements of a sequence randomly.
/// </summary>
/// <param name="source">A sequence of values to shuffle.</param>
/// <param name="rng">An instance of a random number generator.</param>
/// <param name="data">A placeholder to generate random bytes into.</param>
/// <returns>A sequence whose elements are shuffled randomly.</returns>
public static IEnumerable<T> Shuffle<T>(this IEnumerable<T> source, RNGCryptoServiceProvider rng, byte[] data)
{
var elements = source.ToArray();
for (int i = elements.Length - 1; i >= 0; i--)
{
rng.GetBytes(data);
var swapIndex = BitConverter.ToUInt32(data, 0) % (i + 1);
yield return elements[swapIndex];
elements[swapIndex] = elements[i];
}
}
Looking for an algorithm? You can use my ShuffleList class:
class ShuffleList<T> : List<T>
{
public void Shuffle()
{
Random random = new Random();
for (int count = Count; count > 0; count--)
{
int i = random.Next(count);
Add(this[i]);
RemoveAt(i);
}
}
}
Then, use it like this:
ShuffleList<int> list = new ShuffleList<int>();
// Add elements to your list.
list.Shuffle();
How does it work?
Let's take an initial sorted list of the 5 first integers: { 0, 1, 2, 3, 4 }.
The method starts by counting the nubmer of elements and calls it count. Then, with count decreasing on each step, it takes a random number between 0 and count and moves it to the end of the list.
In the following step-by-step example, the items that could be moved are italic, the selected item is bold:
0 1 2 3 4
0 1 2 3 4
0 1 2 4 3
0 1 2 4 3
1 2 4 3 0
1 2 4 3 0
1 2 3 0 4
1 2 3 0 4
2 3 0 4 1
2 3 0 4 1
3 0 4 1 2
This algorithm shuffles by generating a new random value for each value in a list, then ordering the list by those random values. Think of it as adding a new column to an in-memory table, then filling it with GUIDs, then sorting by that column. Looks like an efficient way to me (especially with the lambda sugar!)
Slightly unrelated, but here is an interesting method (that even though it is really excessibe, has REALLY been implemented) for truly random generation of dice rolls!
Dice-O-Matic
The reason I'm posting this here, is that he makes some interesting points about how his users reacted to the idea of using algorithms to shuffle, over actual dice. Of course, in the real world, such a solution is only for the really extreme ends of the spectrum where randomness has such an big impact and perhaps the impact affects money ;).
I would say that many answers here like "This algorithm shuffles by generating a new random value for each value in a list, then ordering the list by those random values" might be very wrong!
I'd think that this DOES NOT assign a random value to each element of the source collection. Instead there might be a sort algorithm running like Quicksort which would call a compare-function approximately n log n times. Some sort algortihm really expect this compare-function to be stable and always return the same result!
Couldn't it be that the IEnumerableSorter calls a compare function for each algorithm step of e.g. quicksort and each time calls the function x => r.Next() for both parameters without caching these!
In that case you might really mess up the sort algorithm and make it much worse than the expectations the algorithm is build up on. Of course, it eventually will become stable and return something.
I might check it later by putting debugging output inside a new "Next" function so see what happens.
In Reflector I could not immediately find out how it works.
It is worth noting that due to the deferred execution of LINQ, using a random number generator instance with OrderBy() can result in a possibly unexpected behavior: The sorting does not happen until the collection is read. This means each time you read or enumerate the collection, the order changes. One would possibly expect the elements to be shuffled once and then to retain the order each time it is accessed thereafter.
Random random = new();
var shuffled = ordered.OrderBy(x => random.Next())
The code above passes a lambda function x => random.Next() as a parameter to OrderBy(). This will capture the instance referred to by random and save it with the lambda by so that it can call Next() on this instance to perform the ordering later which happens right before it is enumerated(when the first element is requested from the collection).
The problem here, is since this execution is saved for later, the ordering happens each time just before the collection is enumerated using new numbers obtained by calling Next() on the same random instance.
Example
To demonstrate this behavior, I have used Visual Studio's C# Interactive Shell:
> List<int> list = new() { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
> Random random = new();
> var shuffled = list.OrderBy(element => random.Next());
> shuffled.ToList()
List<int>(10) { 5, 9, 10, 4, 6, 2, 8, 3, 1, 7 }
> shuffled.ToList()
List<int>(10) { 8, 2, 9, 1, 3, 6, 5, 10, 4, 7 } // Different order
> shuffled.ElementAt(0)
9 // First element is 9
> shuffled.ElementAt(0)
7 // First element is now 7
>
This behavior can even be seen in action by placing a breakpoint just after where the IOrderedEnumerable is created when using Visual Studio's debugger: each time you hover on the variable, the elements show up in a different order.
This, of course, does not apply if you immediately enumerate the elements by calling ToList() or an equivalent. However, this behavior can lead to bugs in many cases, one of them being when the shuffled collection is expected to contain a unique element at each index.
Startup time to run on code with clear all threads and cache every new test,
First unsuccessful code. It runs on LINQPad. If you follow to test this code.
Stopwatch st = new Stopwatch();
st.Start();
var r = new Random();
List<string[]> list = new List<string[]>();
list.Add(new String[] {"1","X"});
list.Add(new String[] {"2","A"});
list.Add(new String[] {"3","B"});
list.Add(new String[] {"4","C"});
list.Add(new String[] {"5","D"});
list.Add(new String[] {"6","E"});
//list.OrderBy (l => r.Next()).Dump();
list.OrderBy (l => Guid.NewGuid()).Dump();
st.Stop();
Console.WriteLine(st.Elapsed.TotalMilliseconds);
list.OrderBy(x => r.Next()) uses 38.6528 ms
list.OrderBy(x => Guid.NewGuid()) uses 36.7634 ms (It's recommended from MSDN.)
the after second time both of them use in the same time.
EDIT:
TEST CODE on Intel Core i7 4#2.1GHz, Ram 8 GB DDR3 #1600, HDD SATA 5200 rpm with [Data: www.dropbox.com/s/pbtmh5s9lw285kp/data]
using System;
using System.Runtime;
using System.Diagnostics;
using System.IO;
using System.Collections.Generic;
using System.Collections;
using System.Linq;
using System.Threading;
namespace Algorithm
{
class Program
{
public static void Main(string[] args)
{
try {
int i = 0;
int limit = 10;
var result = GetTestRandomSort(limit);
foreach (var element in result) {
Console.WriteLine();
Console.WriteLine("time {0}: {1} ms", ++i, element);
}
} catch (Exception e) {
Console.WriteLine(e.Message);
} finally {
Console.Write("Press any key to continue . . . ");
Console.ReadKey(true);
}
}
public static IEnumerable<double> GetTestRandomSort(int limit)
{
for (int i = 0; i < 5; i++) {
string path = null, temp = null;
Stopwatch st = null;
StreamReader sr = null;
int? count = null;
List<string> list = null;
Random r = null;
GC.Collect();
GC.WaitForPendingFinalizers();
Thread.Sleep(5000);
st = Stopwatch.StartNew();
#region Import Input Data
path = Environment.CurrentDirectory + "\\data";
list = new List<string>();
sr = new StreamReader(path);
count = 0;
while (count < limit && (temp = sr.ReadLine()) != null) {
// Console.WriteLine(temp);
list.Add(temp);
count++;
}
sr.Close();
#endregion
// Console.WriteLine("--------------Random--------------");
// #region Sort by Random with OrderBy(random.Next())
// r = new Random();
// list = list.OrderBy(l => r.Next()).ToList();
// #endregion
// #region Sort by Random with OrderBy(Guid)
// list = list.OrderBy(l => Guid.NewGuid()).ToList();
// #endregion
// #region Sort by Random with Parallel and OrderBy(random.Next())
// r = new Random();
// list = list.AsParallel().OrderBy(l => r.Next()).ToList();
// #endregion
// #region Sort by Random with Parallel OrderBy(Guid)
// list = list.AsParallel().OrderBy(l => Guid.NewGuid()).ToList();
// #endregion
// #region Sort by Random with User-Defined Shuffle Method
// r = new Random();
// list = list.Shuffle(r).ToList();
// #endregion
// #region Sort by Random with Parallel User-Defined Shuffle Method
// r = new Random();
// list = list.AsParallel().Shuffle(r).ToList();
// #endregion
// Result
//
st.Stop();
yield return st.Elapsed.TotalMilliseconds;
foreach (var element in list) {
Console.WriteLine(element);
}
}
}
}
}
Result Description: https://www.dropbox.com/s/9dw9wl259dfs04g/ResultDescription.PNG
Result Stat: https://www.dropbox.com/s/ewq5ybtsvesme4d/ResultStat.PNG
Conclusion:
Assume: LINQ OrderBy(r.Next()) and OrderBy(Guid.NewGuid()) are not worse than User-Defined Shuffle Method in First Solution.
Answer: They are contradiction.
I am fairly new to C# programming and I am stuck on my little ASP.NET project.
My website currently examines Twitter statuses for URLs and then adds those URLs to an array, all via a regular expression pattern matching procedure. Clearly more than one person will update a with a specific URL so I do not want to list duplicates, and I want to count the number of times a particular URL is mentioned in, say, 100 tweets.
Now I have a List<String> which I can sort so that all duplicate URLs are next to each other. I was under the impression that I could compare list[i] with list[i+1] and if they match, for a counter to be added to (count++), and if they don't match, then for the URL and the count value to be added to a new array, assuming that this is the end of the duplicates.
This would remove duplicates and give me a count of the number of occurrences for each URL. At the moment, what I have is not working, and I do not know why (like I say, I am not very experienced with it all).
With the code below, assume that a JSON feed has been searched for using a keyword into srchResponse.results. The results with URLs in them get added to sList, a string List type, which contains only the URLs, not the message as a whole.
I want to put one of each URL (no duplicates), a count integer (to string) for the number of occurrences of a URL, and the username, message, and user image URL all into my jagged array called 'urls[100][]'. I have made the array 100 rows long to make sure everything can fit but generally, this is too big. Each 'row' will have 5 elements in them.
The debugger gets stuck on the line: if (sList[i] == sList[i + 1]) which is the crux of my idea, so clearly the logic is not working. Any suggestions or anything will be seriously appreciated!
Here is sample code:
var sList = new ArrayList();
string[][] urls = new string[100][];
int ctr = 0;
int j = 1;
foreach (Result res in srchResponse.results)
{
string content = res.text;
string pattern = #"((https?|ftp|gopher|telnet|file|notes|ms-help):((//)|(\\\\))+[\w\d:##%/;$()~_?\+-=\\\.&]*)";
MatchCollection matches = Regex.Matches(content, pattern);
foreach (Match match in matches)
{
GroupCollection groups = match.Groups;
sList.Add(groups[0].Value.ToString());
}
}
sList.Sort();
foreach (Result res in srchResponse.results)
{
for (int i = 0; i < 100; i++)
{
if (sList[i] == sList[i + 1])
{
j++;
}
else
{
urls[ctr][0] = sList[i].ToString();
urls[ctr][1] = j.ToString();
urls[ctr][2] = res.text;
urls[ctr][3] = res.from_user;
urls[ctr][4] = res.profile_image_url;
ctr++;
j = 1;
}
}
}
The code then goes on to add each result into a StringBuilder method with the HTML.
Is now edite
The description of your algorithm seems fine. I don't know what's wrong with the implementation; I haven't read it that carefully. (The fact that you are using an ArrayList is an immediate red flag; why aren't you using a more strongly typed generic collection?)
However, I have a suggestion. This is exactly the sort of problem that LINQ was intended to solve. Instead of writing all that error-prone code yourself, just describe the transformation you're interested in, and let the compiler work it out for you.
Suppose you have a list of strings and you wish to determine the number of occurrences of each:
var notes = new []{ "Do", "Fa", "La", "So", "Mi", "Do", "Re" };
var counts = from note in notes
group note by note into g
select new { Note = g.Key, Count = g.Count() }
foreach(var count in counts)
Console.WriteLine("Note {0} occurs {1} times.", count.Note, count.Count);
Which I hope you agree is much easier to read than all that array logic you wrote. And of course, now you have your sequence of unique items; you have a sequence of counts, and each count contains a unique Note.
I'd recommend using a more sophisticated data structure than an array. A Set will guarantee that you have no duplicates.
Looks like C# collections doesn't include a Set, but there are 3rd party implementations available, like this one.
Your loop fails because when i == 99, (i + 1) == 100 which is outside the bounds of your array.
But as other have pointed out, .Net 3.5 has ways of doing what you want more elegantly.
If you don't need to know how many duplicates a specific entry has you could do the following:
LINQ Extension Methods
.Count()
.Distinct()
.Count()