Numeripack is a library containing several mathematical algorithms.
- CollectionPermutator
- ExtremumIterator
- MinimalHamiltonianPathSeeker
- PermutationTree
- GenericPermutator
- PositionalIncrementer
- EnumStateMachine
From the set of input elements creates every possible combination of sets. The number of output sets can be any. For example:
Input elements type: int
Input elements set: [1, 2, 3]
Output sets identifier type: string
Output sets identifiers: ["first", "second"]
It generates:
1st iteration:
"first": [1, 2, 3]
"second": []
2nd iteration:
"first": [2,3]
"second": [1]
3rd iteration:
"first": [1,3]
"second": [2]
4th iteration:
"first": [3]
"second": [1,2]
5th iteration:
"first": [1,2]
"second": [3]
6th iteration:
"first": [2]
"second": [1,3]
7th iteration:
"first": [1]
"second": [2,3]
8th iteration:
"first": []
"second": [1,2,3]
Code below writes to console something similiar to example in previous section.
var outputIdentifiers = new[] { "first", "second" };
var inputElements = new[] { 1, 2, 3 };
var permutator = new CollectionPermutator<int, string>(inputElements, outputIdentifiers);
while (permutator.Permute())
{
var outputSets = permutator.Current;
foreach (var outputSet in outputSets)
{
var joinedElements = string.Join(",", outputSet);
Console.WriteLine($"{outputSet.Identifier}: [{joinedElements}]");
}
}Tries to find minimum, maximum or value closest to zero of specified function. The value is searched step by step with step function definied by user.
Let's find minimum of quadratic function:
internal class QuadraticFunction
{
private readonly double _a;
private readonly double _b;
private readonly double _c;
public double Argument { get; set; } = 0.0;
public QuadraticFunction(double a, double b, double c)
{
_a = a;
_b = b;
_c = c;
}
public double GetValue()
{
return (_a * Argument * Argument) + (_b * Argument) + _c;
}
public double GetDerivative()
{
return (2 * _a * Argument) + _b;
}
}With argument property named Argument and value of that argument: GetValue().
We will find maximum of this function for [a, b, c] = [-4.2, 4.6, -12.3]
var qFunction = new QuadraticFunction(-4.2, 4.6, -12.3)
{
Argument = -23.3 //x0 for our search
};
var iterator = new ExtremumIteratorBuilder()
.Find(Extremum.Maximum) // may be Minimum or Zero
.ForObject(qFunction)
.SelectArgument(qf => qf.Argument)
.WithStep(ctx =>
{
var qf = ctx.Object;
var derivative = qe.GetDerivative();
qe.Argument += derivative * 0.01;
return qe.GetValue();
})
.WithMaximumSteps(1000)
.Build();
var result = iterator.FindResult();Result will be f(x) = -11.0404... with argument x = 0.5476...
Or intead of calling FindResult() we can iterate step by step to final value:
while (iterator.Next())
{
var current = iterator.Current;
Console.WriteLine($"{iterator.StepNumber}. f({current.Argument}) = {current.Value}");
}It will write to the console:
1. f(-21,2968) = -2015,1907790080002
2. f(-19,4618688) = -1692,6348126713365
3. f(-17,7810718208) = -1421,992293780761
4. f(-16,241461787852803) = -1194,9080644505104
5. f(-14,831178997673167) = -1004,3716793255874
6. f(-13,53935996186862) = -844,5009821682099
7. f(-12,356053725071655) = -710,3605144941296
8. f(-11,272145212165636) = -597,8091502493863
9. f(-10,279285014343722) = -503,37225277164913
10. f(-9,36982507313885) = -424,13440732156886
11. f(-8,536759766995187) = -357,64941766960635
...
996. f(0,5476190332922326) = -11,040476190476191
997. f(0,5476190332922326) = -11,040476190476191
998. f(0,5476190332922326) = -11,040476190476191
999. f(0,5476190332922326) = -11,040476190476191
Additionally, you can use functions:
-
to limit argument to specified domain:
.WithArgumentDomain(arg => arg > -100 && arg < 100) -
to specify when iterator should stop working:
.EndsIf(ctx => ctx.CurrentExtremum.Value > 10000)
Finds hamiltonian graph path that has minimum value. Hamiltonian graph is an undirected or directed graph that visits each vertex exactly once.
Let's find minimal hamiltonian path for cost values:
| A | B | C | D | E | F | G | |
|---|---|---|---|---|---|---|---|
| A | - | x | x | x | x | x | x |
| B | 2 | - | x | x | x | x | x |
| C | 6 | 3 | - | x | x | x | x |
| D | 4 | 7 | 3 | - | x | x | x |
| E | 5 | 1 | 6 | 8 | - | x | x |
| F | 8 | 3 | 1 | 7 | 4 | - | x |
| G | 9 | 3 | 5 | 6 | 1 | 4 | - |
It means that going from point A to B costs 2, B to C costs 3, ...
Our graph point is pair of its name and index.
public class PathPoint
{
public PathPoint(string name, int index)
{
Name = name;
Index = index;
}
public string Name { get; set; }
public int Index { get; set; }
}Filling elements array with PathPoint objects and costValues with values from table.
var elements = new[]
{
new PathPoint("A", 0),
new PathPoint("B", 1),
new PathPoint("C", 2),
new PathPoint("D", 3),
new PathPoint("E", 4),
new PathPoint("F", 5),
new PathPoint("G", 6),
};
var costValues = new[,]
{
{ 0, 2, 6, 4, 5, 8, 9 },
{ 2, 0, 3, 7, 1, 3, 3 },
{ 6, 3, 0, 3, 6, 1, 5 },
{ 4, 7, 3, 0, 8, 7, 6 },
{ 5, 1, 6, 8, 0, 4, 1 },
{ 8, 3, 1, 7, 4, 0, 4 },
{ 9, 3, 5, 6, 1, 4, 0 }
};Finding minimum:
var seeker = new MinimalHamiltonianCycleSeekerBuilder<PathPoint>()
.ForElements(elements)
.WithCostFunction((first, second, order) =>
{
return costValues[first.Index, second.Index];
})
.Build();
var result = seeker.FindResult();Result will be: A -> B -> C -> F -> E -> G -> D with cost 17
cost(A -> B) + cost (B -> C) + cost(C -> F) + cost(F -> E) + cost(E -> G) + cost(G -> D) =
= 2 + 3 + 1 + 4 + 1 + 6 = 17
-
Directed graph can be used. You should change the cost values over diagonal in the table. The effect will be that for example
cost(B -> C) = 3 != 4 = cost(C -> B) -
The cost function may depend on the order of the transition. For example,
cost (A-> B)may be different if it is the first and fourth transition. Use the third parameter in the lamda function (order):
.WithCostFunction((first, second, order) =>
{
...
})Allows you to traverse any permutation of the Hamilton graph composed of elements given by the user.
If there are three vertex defined in graph: A, B, C a result of traversal will be:
A
A -> B
A -> B -> C
A -> C
A -> C -> B
B
B -> C
B -> C -> A
B -> A
B -> A -> C
C
C -> A
C -> A -> B
C -> B
C -> B -> A
Algorithm allows to skip any part of the traversal. For example if you need to skip A and C -> A a result of the traversal will be:
B
B -> C
B -> C -> A
B -> A
B -> A -> C
C
C -> B
C -> B -> A
var elements = new[] { "A", "B", "C" };
var permutationTree = new TreePermutator<string>(elements);
while (permutationTree.MoveNext())
{
Console.WriteLine(string.Join(" -> ", permutationTree.Current.Elements));
}Full graph traversal will be writed to console. After traversal method GetResult() may be called to get every path that was found:
var result = permutationTree.GetResult();
foreach (var path in result)
{
Console.WriteLine(string.Join(" -> ", path));
}It will write to the console:
A -> B -> C
A -> C -> B
B -> C -> A
B -> A -> C
C -> A -> B
C -> B -> A
Let's say we want to skip A and C -> A branches as in the first paragraph. The code will be:
while (permutationTree.MoveNext())
{
var currentElements = permutationTree.Current.Elements;
if (currentElements.Count == 1 && currentElements[0] == "A")
{
permutationTree.Current.SkipBranch();
}
if (currentElements.Count == 2 && currentElements[0] == "C" && currentElements[1] == "A")
{
permutationTree.Current.SkipBranch();
}
else
{
Console.WriteLine(string.Join(" -> ", permutationTree.Current.Elements));
}
}Output will be:
B
B -> C
B -> C -> A
B -> A
B -> A -> C
C
C -> B
C -> B -> A
Print result to console:
var result = permutationTree.GetResult();
foreach (var path in result)
{
Console.WriteLine(string.Join(" -> ", path));
}B -> C -> A
B -> A -> C
C -> B -> A
Generates all permutations of objects of a given type. Heap's algorithm is used.
Let's generate permutation of three objects of type string: ["one", "two", "three"].
var elements = new[] { "one", "two", "three" };
var permutator = new GenericPermutator<string>(elements);
foreach (var permutation in permutator)
{
Console.WriteLine(string.Join(", ", permutation));
}Console will print:
one, two, three
two, one, three
three, one, two
one, three, two
two, three, one
three, two, one
Counter with base and number of items given by the user.
Code for positional incrementator with: base = 3, positions = 4
const int baseNumber = 3;
const int positions = 4;
var incrementer = new PositionalIncrementer(baseNumber, positions);
foreach (var value in incrementer)
{
Console.WriteLine(string.Join(" ", value));
}Output:
0 0 0 0
1 0 0 0
2 0 0 0
0 1 0 0
1 1 0 0
2 1 0 0
0 2 0 0
1 2 0 0
2 2 0 0
0 0 1 0
1 0 1 0
2 0 1 0
...
1 1 2 2
2 1 2 2
0 2 2 2
1 2 2 2
2 2 2 2
Similarly for a generic incrementer with elements: ["one", "two", "three", "four"]
var elements = new[] { "one", "two", "three", "four" };
const int positions = 4;
var incrementer = new PositionalIncrementer<string>(elements, positions);
foreach (var value in incrementer)
{
Console.WriteLine(string.Join(" ", value));
}Output:
one one one one
two one one one
three one one one
four one one one
one two one one
two two one one
...
four three four four
one four four four
two four four four
three four four four
four four four four
It allows you to build a state machine with specific transitions. Uses enum type to define a state. Transition throws exception InvalidOperationException if operation is not allowed.
Let's build state machine for some process:
Define enum type (values must be powers of 2):
enum ProcessState
{
Standby = 1,
Active = 2,
Suspect = 4,
Failed = 8
}Build state machine, define allowed transitions and assign starting state:
var builder = new EnumStateMachineBuilder<ProcessState>();
builder.For(ProcessState.Active)
.AllowTransitionTo(ProcessState.Standby)
.AllowTransitionTo(ProcessState.Suspect);
builder.For(ProcessState.Standby)
.AllowTransitionTo(ProcessState.Active)
.AllowTransitionTo(ProcessState.Suspect);
builder.For(ProcessState.Suspect)
.AllowTransitionTo(ProcessState.Standby)
.AllowTransitionTo(ProcessState.Failed);
builder.For(ProcessState.Failed)
.AllowTransitionTo(ProcessState.Suspect);
var processState = builder.Build(ProcessState.Standby);Object processState provides methods and properties:
ProcessState CurrentState { get; }
IReadOnlyList<ProcessState> GetAllowedTransitions();
void GotoState(ProcessState state);
bool IsTransitionAllowed(ProcessState state);You can track changes of state with StateChanged event.