Fun.Collections.UniJagged
6.0.0
See the version list below for details.
dotnet add package Fun.Collections.UniJagged --version 6.0.0
NuGet\Install-Package Fun.Collections.UniJagged -Version 6.0.0
<PackageReference Include="Fun.Collections.UniJagged" Version="6.0.0" />
paket add Fun.Collections.UniJagged --version 6.0.0
#r "nuget: Fun.Collections.UniJagged, 6.0.0"
// Install Fun.Collections.UniJagged as a Cake Addin #addin nuget:?package=Fun.Collections.UniJagged&version=6.0.0 // Install Fun.Collections.UniJagged as a Cake Tool #tool nuget:?package=Fun.Collections.UniJagged&version=6.0.0
Fun.Collections.UniJagged
This library provides jagged array types enabling access by indices. The jagged array types wraps different representations to achieve a unified representation.
Currently, from one-dimensional to eight-dimensional jagged arrays are supported.
Complete auto-generated documentation can be found here: sandcastle-documentation.
Addressed Problem
Consider the following method that requires a two dimensional (2D) jagged array to read from.
Path CalculateShortestPath(double[][] distanceMatrix, int origin, int destination)
{
// the method creates the shortest path from origin to destination
// reading required distances from teh distance matrix, where
// distanceMatrix[i][j] -> distance from i to j.
}
Note that, there exist other relevant representations to enable access by indices:
1. Other Standard Collections
For the 2D double example above, some alternatives are List<List<double>>
, List<double[]>
, IList<double>[]
, IEnumerable<IEnumerable<double>>
, etc.
2. Functions: On Demand Computation
One example case for using functions is as follows. The CalculateShortestPath
method might not require all entries of the jagged array. It might be computationally expensive to compute all distances beforehand; or memory-wise expensive to store all entries.
Consider the following on-request distance provider for instance:
double GetEuclideanDistance(int tail, int head)
{
var (x1, y1) = GetCoordinatesOf(tail);
var (x2, y2) = GetCoordinatesOf(head);
return Math.Sqrt((Math.Pow(x1 - x2, 2) + Math.Pow(y1 - y2, 2)));
}
This function, although not storing the elements, fits into the requirement; it provides indexed access to data.
3. Functions: Immutability
A second case for using functions could be related to the limited language support for immutability. Simply, one would prefer to pass the closure (i, j) => distanceMatrix[i][j]
rather than passing directly the array double[][] distanceMatrix
to prevent the consumer from mutating the array.
4. Scalars
Consider a collection that might have different values at different elements; or exactly the same constant/scalar value at every element. One general representation for this case is to replicate the scalar value for each entry; however, this solution would be memory inefficient. A better general representation could be to handle these variants separately.
For the above example; assume we want to call CalculateShortestPath
method with two different distance matrices:
- the first distance matrix represents distances among physical locations; and hence, contains heterogeneous distances;
- and every element of the second distance matrix is exactly one, so that the
CalculateShortestPath
provides the path with the minimum number of edges/connections.
The first case is clear. To call CalculateShortestPath
method to handle the second case, one needs to populate a jagged array, all entries of which are 1.
var distanceMatrix = new double[n][];
for (int i = 0; i < distanceMatrix.Length; i++)
{
distanceMatrix[i] = new double[GetOutDegree(i)];
for (int j = 0; j < distanceMatrix[i].Length; j++)
distanceMatrix[i][j] = 1;
}
// lots of code & memory, just to return 1.
Proposed Solution
Consider now the alternative implementation of the CalculateShortestPath
method, which is completely identical to the original, except for:
- instead of a specific
double[][]
, it expectsUniJaggedD2<double>
which can be any of many possible representations that allows access by indices; - instead of using
distanceMatrix[i][j]
to access the (i,j)-th element, we usedistanceMatrix[i, j]
.
Path CalculateShortestPath(UniJaggedD2<double> distanceMatrix, int origin, int destination)
{
// distanceMatrix[i, j] -> distance from i to j.
}
Now the caller can freely choose the underlying data type without having to change the method signature or implementation. For instance, all below examples are valid calls for the implementation accepting the unified jagged array.
int origin = 0;
int destination = 10;
// array
double[][] distMatArr = ... // get the data as array of arrays
var shortestPath = CalculateShortestPath(new(distMatArr), origin, destination);
// list
List<List<double>> distMatList = ... // get the data as list of lists
var shortestPath = CalculateShortestPath(new(distMatList), origin, destination);
// scalar
UniJaggedD2<double> distMatOne = new(1); // distMatOne[i, j] = 1 for every i, j
var shortestPath = CalculateShortestPath(distMatOne, origin, destination);
// scalar - brief version
var shortestPath = CalculateShortestPath(new(1), origin, destination);
// functional - on demand computation
record Location(double X, double Y);
record DistanceProvider(Location[] Locations)
{
public double GetEuclideanDistance(int tailIndex, int headIndex)
{
var tail = Locations[tailIndex];
var head = Locations[headIndex];
return Math.Sqrt((Math.Pow(tail.X - head.X, 2) + Math.Pow(tail.Y - head.Y, 2)));
}
}
DistanceProvider provider = new(GetLocations());
UniJaggedD2<double> distMatFun = new((i,j) => provider.GetEuclideanDistance(i, j));
UniJaggedD2<double> distMatFun = new(provider.GetEuclideanDistance); // more briefly
var shortestPath = CalculateShortestPath(distMatFun, origin, destination);
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net6.0 is compatible. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 was computed. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 was computed. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. |
-
net6.0
- OptRes (>= 6.1.2)
NuGet packages
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