"It's a tough galaxy. If you want to survive, you've gotta know... where your towel is." - Ford Prefect
Towel is a C# .Net Standard libary intended to add core functionality that is missing in the language and to make advanced programming topics as clean and simple as possible.
Topic | Info |
---|---|
GitHub | https://github.com/ZacharyPatten/Towel |
Status | |
NuGet | |
License | |
Discord |
Many features are coded and working, but Towel is still in heavy development. There will be actual NuGet package releases (not just pre-releases) of the code when ready, but note that the project has a goal of keeping as up-to-date as possible on modern C# practices rather than maintaining backwards compatibility.
How It Works [click to expand]
public static T Addition<T>(T a, T b)
{
return AdditionImplementation<T>.Function(a, b);
}
internal static class AdditionImplementation<T>
{
internal static Func<T, T, T> Function = (T a, T b) =>
{
ParameterExpression A = Expression.Parameter(typeof(T));
ParameterExpression B = Expression.Parameter(typeof(T));
Expression BODY = Expression.Add(A, B);
Function = Expression.Lambda<Func<T, T, T>>(BODY, A, B).Compile();
return Function(a, b);
};
}
You can break type safe-ness using generic types and runtime compilation, and you can store the runtime compilation in a delegate so the only overhead is the invocation of the delegate.
// Logic Fundamentals
bool EqualTo<T>(T a , T b);
bool LessThan<T>(T a, T b);
bool GreaterThan<T>(T a, T b);
CompareResult Compare<T>(T a, T b);
// Mathematics Fundamentals
T Negation<T>(T a);
T Addition<T>(T a, T b);
T Subtraction<T>(T a, T b);
T Multiplication<T>(T a, T b);
T Division<T>(T a, T b);
T Remainder<T>(T a, T b);
// More Logic
bool IsPrime<T>(T a);
bool IsEven<T>(T a);
bool IsOdd<T>(T a);
T Minimum<T>(T a, T b);
T Maximum<T>(T a, T b);
T Clamp<T>(T value, T floor, T ceiling);
T AbsoluteValue<T>(T a);
bool EqualityLeniency<T>(T a, T b, T leniency);
// More Numerics
void FactorPrimes<T>(T a, Step<T> step);
T Factorial<T>(T a);
T LinearInterpolation<T>(T x, T x0, T x1, T y0, T y1);
T LeastCommonMultiple<T>(T a, T b, params T[] c);
T GreatestCommonFactor<T>(T a, T b, params T[] c);
LinearRegression2D<T>(Stepper<T, T> points, out T slope, out T y_intercept);
// Statistics
T Mean<T>(T a, params T[] b);
T Median<T>(params T[] values);
Heap<Link<T, int>> Mode<T>(T a, params T[] b);
void Range<T>(out T minimum, out T maximum, Stepper<T> stepper);
T[] Quantiles<T>(int quantiles, Stepper<T> stepper);
T GeometricMean<T>(Stepper<T> stepper);
T Variance<T>(Stepper<T> stepper);
T StandardDeviation<T>(Stepper<T> stepper);
T MeanDeviation<T>(Stepper<T> stepper);
// Vectors
Vector<T> V1 = new Vector<T>(params T[] vector);
Vector<T> V2 = new Vector<T>(params T[] vector);
Vector<T> V3;
T scalar;
V3 = -V1; // Negate
V3 = V1 + V2; // Add
V3 = V1 - V2; // Subtract
V3 = V1 * scalar; // Multiply
V3 = V1 / scalar; // Divide
scalar = V1.DotProduct(V2); // Dot Product
V3 = V1.CrossProduct(V2); // Cross Product
V1.Magnitude; // Magnitude
V3 = V1.Normalize(); // Normalize
bool equal = V1 == V2; // Equal
// Matrices
Matrix<T> M1 = new Matrix<T>(int rows, int columns);
Matrix<T> M2 = new Matrix<T>(int rows, int columns);
Matrix<T> M3;
Vector<T> V2 = new Vector<T>(params T[] vector);
Vector<T> V3;
T scalar;
M3 = -M1; // Negate
M3 = M1 + M2; // Add
M3 = M1 - M2; // Subtract
M3 = M1 * M2; // Multiply
V3 = M1 * V2; // Multiply (vector)
M3 = M1 * scalar; // Multiply (scalar)
M3 = M1 / scalar; // Divide
M3 = M1 ^ 3; // Power
scalar = M1.Determinent(); // Determinent
M3 = M1.Minor(int row, int column); // Minor
M3 = M1.Echelon(); // Echelon Form (REF)
M3 = M1.ReducedEchelon(); // Reduced Echelon Form (RREF)
M3 = M1.Inverse(); // Inverse
M1.DecomposeLowerUpper(ref M2, ref M3); // Lower Upper Decomposition
bool equal = M1 == M2; // Equal
// Parsing From Linq Expression
Expression<Func<double, double>> exp1 = (x) => 2 * (x / 7);
Symbolics.Expression symExp1 = Symbolics.Parse(exp1);
// Parsing From String
Symbolics.Expression symExp2 = Symbolics.Parse("2 * ([x] / 7)");
// Mathematical Simplification
Symbolics.Expression simplified = symExp1.Simplify();
// Variable Substitution
symExp1.Substitute("x", 5);
Supported Measurements [click to expand]
Here are the currently supported measurement types:
// Acceleration: Length/Time/Time
// AngularAcceleration: Angle/Time/Time
// Angle: Angle
// AngularSpeed: Angle/Time
// Area: Length*Length
// AreaDensity: Mass/Length/Length
// Density: Mass/Length/Length/Length
// ElectricCharge: ElectricCharge
// ElectricCurrent: ElectricCharge/Time
// Energy: Mass*Length*Length/Time/Time
// Force: Mass*Length/Time/Time
// Length: Length
// LinearDensity: Mass/Length
// LinearMass: Mass*Length
// LinearMassFlow: Mass*Length/Time
// Mass: Mass
// MassRate: Mass/Time
// Power: Mass*Length*Length/Time/Time/Time
// Pressure: Mass/Length/Time/Time
// Speed: Length/Time
// Tempurature: Tempurature
// Time: Time
// TimeArea: Time*Time
// Volume: Length*Length*Length
// VolumeRate: Length*Length*Length/Time
The measurement types are generated in the Towel/Measurements/MeasurementTypes.tt T4 text template file. The unit (enum) definitions are in the Towel/Measurements/MeasurementUnitDefinitions.cs file. Both measurment types and unit definitions can be easily added. If you think a measurement type or unit type should be added, please submit an enhancement issue.
// Towel has measurement types to help write scientific code: Acceleration<T>, Angle<T>, Area<T>,
// Density<T>, Length<T>, Mass<T>, Speed<T>, Time<T>, Volume<T>, etc.
// Automatic Unit Conversion
// When you perform mathematical operations on measurements, any necessary unit conversions will
// be automatically performed by the relative measurement type (in this case "Angle<T>").
Angle<double> angle1 = (90d, Degrees);
Angle<double> angle2 = (.5d, Turns);
Angle<double> result1 = angle1 + angle2; // 270°
// Type Safeness
// The type safe-ness of the measurement types prevents the miss-use of the measurements. You cannot
// add "Length<T>" to "Angle<T>" because that is mathematically invalid (no operator exists).
Length<double> length1 = (2d, Yards);
object result2 = angle1 + length1; // WILL NOT COMPILE!!!
// Simplify The Syntax Even Further
// You can use alias to remove the generic type if you want to simplify the syntax even further.
using Speedf = Towel.Measurements.Speed<float>; // at top of file
Speedf speed1 = (5, Meters / Seconds);
// Vector + Measurements
// You can use the measurement types inside Towel Vectors.
Vector<Speed<float>> velocity1 = new Vector<Speed<float>>(
(1f, Meters / Seconds),
(2f, Meters / Seconds),
(3f, Meters / Seconds));
Vector<Speedf> velocity2 = new Vector<Speedf>(
(1f, Centimeters / Seconds),
(2f, Centimeters / Seconds),
(3f, Centimeters / Seconds));
Vector<Speed<float>> velocity3 = velocity1 + velocity2;
// Manual Unit Conversions
// 1. Index Operator On Measurement Type
double angle1_inRadians = angle1[Radians];
float speed1_inMilesPerHour = speed1[Miles / Hours];
// 2. Static Conversion Methods
double angle3 = Angle<double>.Convert(7d,
Radians, // from
Degrees); // to
double speed2 = Speed<double>.Convert(8d,
Meters / Seconds, // from
Miles / Hours); // to
double force1 = Force<double>.Convert(9d,
Kilograms * Meters / Seconds / Seconds, // from
Grams * Miles / Hours / Hours); // to
double angle4 = Measurement.Convert(10d,
Radians, // from
Degrees); // to
// Note: The unit conversion on the Measurement class
// is still compile-time-safe.
// Measurement Parsing
Speed<float>.TryParse("20.5 Meters / Seconds",
out Speed<float> parsedSpeed);
Force<decimal>.TryParse(".1234 Kilograms * Meters / Seconds / Seconds",
out Force<decimal> parsedForce);
Heap [click to expand]
// A heap is a binary tree that is sorted vertically using comparison methods. This is different
// from AVL Trees or Red-Black Trees that keep their contents stored horizontally. The rule
// of a heap is that no parent can be less than either of its children. A Heap using "sifting up"
// and "sifting down" algorithms to move values vertically through the tree to keep items sorted.
IHeap<T> heapArray = new HeapArray<T>();
// Visualization:
//
// Binary Tree
//
// -7
// / \
// / \
// / \
// / \
// / \
// / \
// / \
// / \
// -4 1
// / \ / \
// / \ / \
// / \ / \
// -1 3 6 4
// / \ / \ / \ / \
// 30 10 17 51 45 22 19 7
//
// Flattened into an Array
//
// Root = 1
// Left Child = 2 * Index
// Right Child = 2* Index + 1
// __________________________________________________________________________
// |0 |-7 |-4 |1 |-1 |3 |6 |4 |30 |10 |17 |51 |45 |22 |19 |7 |0 |0 |0 ...
// ‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾
// 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
AVL Tree [click to expand]
// An AVL tree is a binary tree that is sorted using comparison methods and automatically balances
// itself by tracking the heights of nodes and performing one of four specific algorithms: rotate
// right, rotate left, double rotate right, or double rotate left. Any parent in an AVL Tree must
// be greater than its left child but less than its right child (if the children exist). An AVL
// tree is sorted in the same manor as a Red-Black Tree, but uses different algorithms to maintain
// the balance of the tree.
IAvlTree<int> avlTree = new AvlTreeLinked<int>();
// Visualization:
//
// Binary Tree
//
// Depth 0 ------------------> 7
// / \
// / \
// / \
// / \
// / \
// / \
// / \
// / \
// Depth 1 ---------> 1 22
// / \ / \
// / \ / \
// / \ / \
// Depth 2 ----> -4 4 17 45
// / \ / \ / \ / \
// Depth 3 ---> -7 -1 3 6 10 19 30 51
//
// Flattened into an Array
//
// Root = 1
// Left Child = 2 * Index
// Right Child = 2* Index + 1
// __________________________________________________________________________
// |0 |7 |1 |22 |-4 |4 |17 |45 |-7 |-1 |3 |6 |10 |19 |30 |51 |0 |0 |0 ...
// ‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾
// 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Red Black Tree [click to expand]
// A Red-Black treeis a binary tree that is sorted using comparison methods and automatically
// balances itself. Any parent in an Red-Black Tree must be greater than its left child but less
// than its right child (if the children exist). A Red-Black tree is sorted in the same manor as
// an AVL Tree, but uses different algorithms to maintain the balance of the tree.
IRedBlackTree<int> redBlackTree = new RedBlackTreeLinked<int>();
// Visualization:
//
// Binary Tree
//
// Color Black ----------------> 7
// / \
// / \
// / \
// / \
// / \
// / \
// / \
// / \
// Color Red ---------> 1 22
// / \ / \
// / \ / \
// / \ / \
// Color Black ---> -4 4 17 45
// / \ / \ / \ / \
// Color Red ---> -7 -1 3 6 10 19 30 51
//
// Flattened into an Array
//
// Root = 1
// Left Child = 2 * Index
// Right Child = 2* Index + 1
// __________________________________________________________________________
// |0 |7 |1 |22 |-4 |4 |17 |45 |-7 |-1 |3 |6 |10 |19 |30 |51 |0 |0 |0 ...
// ‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾
// 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Omnitree [click to expand]
// An Omnitree is a Spacial Partitioning Tree (SPT) that works on an arbitrary number of dimensions.
// It stores items sorted along multiple dimensions by dividing spaces into sub-spaces. A 3D
// version of an SPT is often called an "Octree" and a 2D version of an SPT is often called a
// "Quadtree." There are two versions of the Omnitree: Points and Bounds. The Points version stores
// vectors while the Bounds version stores spaces with a minimum and maximum vector.
IOmnitreePoints<T, A1, A2, A3...> omnitreePoints =
new OmnitreePointsLinked<T, A1, A2, A3...>(
(T value, out A1 a1, out A2 a2, out A3 a3...) => { ... });
IOmnitreeBounds<T, A1, A2, A3...> omnitreeBounds =
new OmnitreeBoundsLinked<T, A1, A2, A3...>(
(T value,
out A1 min1, out A1 max1,
out A2 min2, out A2 max2,
out A3 min3, out A3 max3...) => { ... });
// The maximum number of children any node can have is 2 ^ N where N is the number
// of dimensions of the tree.
//
// -------------------------------
// | Dimensions | Max # Children |
// |============|================|
// | 1 | 2 ^ 1 = 2 |
// | 2 | 2 ^ 2 = 4 |
// | 3 | 2 ^ 3 = 8 |
// | 4 | 2 ^ 4 = 16 |
// | ... | ... |
// -------------------------------
//
// Visualizations
//
// 1 Dimensional:
//
// -1D |-----------|-----------| +1D Children Indexes:
// -1D: 0
// <--- 0 ---> <--- 1 ---> +1D: 1
//
// 2 Dimensional:
// _____________________
// | | | +2D
// | | | ^
// | 2 | 3 | | Children Indexes:
// | | | | -2D -1D: 0
// |----------|----------| | -2D +1D: 1
// | | | | +2D -1D: 2
// | | | | +2D +1D: 3
// | 0 | 1 | |
// | | | v
// |__________|__________| -2D
//
// -1D <-----------> +1D
//
// 3 Dimensional:
//
// +3D _____________________
// 7 / / /|
// / / 6 / 7 / |
// / /---------/----------/ | Children Indexes:
// / / 2 / 3 /| | -3D -2D -1D: 0
// L /_________/__________/ | | -3D -2D +1D: 1
// -3D | | | | /| +2D -3D +2D -1D: 2
// | | | |/ | ^ -3D +2D +1D: 3
// | 2 | 3 | / | | +3D -2D -1D: 4
// | | |/| | <-- 5 | +3D -2D +1D: 5
// |----------|----------| | | | +3D +2D -1D: 6
// | | | | / | +3D +2D +1D: 7
// | | | | / |
// | 0 | 1 | |/ |
// | | | / v
// |__________|__________|/ -2D
//
// ^
// |
// 4 (behind 0)
//
// -1D <-----------> +1D
//
// 4 Dimensional:
//
// +1D +2D +3D +4D Children Indexes:
// ^ ^ ^ ^
// | | | | -4D -3D -2D -1D: 0 +4D -3D -2D -1D: 8
// | | | | -4D -3D -2D +1D: 1 +4D -3D -2D +1D: 9
// | | | | -4D -3D +2D -1D: 2 +4D -3D +2D -1D: 10
// | | | | -4D -3D +2D +1D: 3 +4D -3D +2D +1D: 11
// | | | | -4D +3D -2D -1D: 4 +4D +3D -2D -1D: 12
// --- --- --- --- -4D +3D -2D +1D: 5 +4D +3D -2D +1D: 13
// | | | | -4D +3D +2D -1D: 6 +4D +3D +2D -1D: 14
// | | | | -4D +3D +2D +1D: 7 +4D +3D +2D +1D: 15
// | | | |
// | | | |
// | | | |
// v v v v
// -1D -2D -3D -4D
//
// With a value that is in the (+1D, -2D, -3D, +4D)[Index 9] child:
//
// +1D +2D +3D +4D
// ^ ^ ^ ^
// | | | |
// | | | |
// O--- | | ---O
// | \ | | / |
// | \ | | / |
// --- \ --- --- / ---
// | \ | | / |
// | \ | | / |
// | ---O-----------O--- |
// | | | |
// | | | |
// v v v v
// -1D -2D -3D -4D
// By default, the omnitree will sort items along each axis and use the median algorithm to determine
// the point of divisions. However, you can override the subdivision algorithm. For numerical values,
// the mean algorithm can be used (and is much faster than median). If you know the data set will be
// relatively evenly distributed within a sub-space, you can even set the subdivision algorithm to
// calculate the subdivision from parent spaces rather than looking at the current contents of the
// space. Note: In a future enhancement I will automatically detect if the mean algorithm is possible
// for a given type, and then the default will depend on the type in use.
// The depth of the omnitree is bounded by "ln(count)" the natural log of the current count. When adding
// and item to the tree, if the number of items in the respective child is greater than ln(count) and
// the depth bounding has not been reached, then the child will be subdivided. The goal is to achieve
// Ω(ln(count)) runtime complexity when looking up values.
Tree [click to expand]
Tree<T> treeMap = new TreeMap<T>(...);
Graph [click to expand]
// A graph is a data structure that contains nodes and edges. They are useful
// when you need to model real world scenarios. They also are generally used
// for particular algorithms such as path finding. The GraphSetOmnitree is a
// graph that stores nodes in a hashed set and the edges in a 2D omnitree (aka
// quadtree).
IGraph<int> graph = new GraphSetOmnitree<int>()
{
// add nodes
0,
1,
2,
3,
// add edges
{ 0, 1 },
{ 1, 2 },
{ 2, 3 },
{ 0, 3 },
// visualization
//
// 0 --------> 1
// | |
// | |
// | |
// v v
// 3 <-------- 2
};
Trie [click to expand]
// A trie is a tree that stores values in a way that partial keys may be shared
// amongst values to reduce redundant memory usage. They are generally used with
// large data sets such as storing all the words in the English language. For
// example, the words "farm" and "fart" both have the letters "far" in common.
// A trie takes advantage of that and only stores the necessary letters for
// those words ['f'->'a'->'r'->('t'||'m')]. A trie is not limited to string
// values though. Any key type that can be broken into pieces (and shared),
// could be used in a trie.
//
// There are two versions. One that only stores the values of the trie (ITrie<T>)
// and one that stores the values of the trie plus an additional generic value
// on the leaves (ITrie<T, D>).
ITrie<T> trie = new TrieLinkedHashLinked<T>();
ITrie<T, D> trieWithAdditionalData = new TrieLinkedHashLinked<T, D>();
// Sorting
Sort.Shuffle<T>(...);
Sort.Bubble<T>(...);
Sort.Selection<T>(...);
Sort.Insertion<T>(...);
Sort.Quick<T>(...);
Sort.Merge<T>(...);
Sort.Heap<T>(...);
Sort.OddEven<T>(...);
Sort.Cocktail<T>(...);
Sort.Comb<T>(...);
Sort.Gnome<T>(...);
Sort.Shell<T>(...);
Sort.Bogo<T>(...);
Sort.Slow<T>(...);
// Path Finding (Graph Search)
// Note: overloads for A*, Dijkstra, and Breadth-First-Search algorithms
Search.Graph<Node, Numeric>(...);
Note: Benchmarks are included for the sorting algorithms.
// System.Random extensions to generate more random types
// Note: there are overloads to specify possible ranges
string NextString(this Random random, int length);
char NextChar(this Random random);
decimal NextDecimal(this Random random);
DateTime DateTime(this Random random);
TimeSpan TimeSpan(this Random random);
long NextLong(this Random random);
IEnumerable<int> NextUnique(this Random random, int count, int minValue, int maxValue); // unique values
T Next<T>(this Random random, IEnumerable<(T Value, double Weight)> pool); // weighted values
void Shuffle<T>(this Random random, T[] array); // randomize arrays
// Type conversion to string definition as appears in C# source code
// Note: useful for runtime compilation from strings
string ConvertToCSharpSourceDefinition(this Type type);
// Example: typeof(List<int>) -> "System.Collections.Generic.List<int>"
string ToEnglishWords(this decimal @decimal);
// Example: 12 -> "Twelve"
// Reflection Extensions To Access XML Documentation
string GetDocumentation(this Type type);
string GetDocumentation(this FieldInfo fieldInfo);
string GetDocumentation(this PropertyInfo propertyInfo);
string GetDocumentation(this EventInfo eventInfo);
string GetDocumentation(this ConstructorInfo constructorInfo);
string GetDocumentation(this MethodInfo methodInfo);
string GetDocumentation(this MemberInfo memberInfo);
string GetDocumentation(this ParameterInfo parameterInfo);
// Iterating the permutations of an array
void PermuteRecursive<T>(this T[] array, Step<T[]> step);
void PermuteIterative<T>(this T[] array, Step<T[]> step);
Feel free to chat with the developer(s) via Discord.
Howdy! I'm Zachary Patten. I like making code frameworks and teaching people how to code. I only work on Towel in my free time, but feel free to contact me if you have questions and I will respond when I am able. :)