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Classy Library Documentation

Classy library provides a class like interface and collection of data structure classes and utilities, implemented in Lua, to facilitate complex programming tasks. Below, you'll find detailed documentation on each class, including its instance methods and class-level "static" methods.

Setup

Using the Makefile

This section provides a concise guide to using the Makefile to build and bundle the Lua Classy Library.

Prerequisites

  • GNU Make and Curl should be installed on your system.

Makefile Overview

The Makefile automates:

  • Building the Lua interpreter from source.
  • Creating two bundled Lua files:
    • classy.bundle.lua (without UnitTests.lua).
    • classy.bundle.tests.lua (with UnitTests.lua appended).
  • Cleaning up build artifacts and bundled files.

Targets

default

Builds all bundles.

  • Usage: make

all

Builds all bundles and Lua.

  • Usage: make all

bundle

Creates classy.bundle.lua by bundling all source files without UnitTests.lua.

  • Usage: make bundle

bundle-with-tests

Creates classy.bundle.tests.lua by bundling all source files with UnitTests.lua appended.

  • Usage: make bundle-with-tests

bundle-neural

Creates neural-network.lua by bundling classy.bundle.lua with src/NeuralNetwork/NeuralNetwork.lua.

  • Usage: make bundle-neural

clean-lua

Removes the Lua binary and source directory.

  • Usage: make clean-lua

clean

Removes the output directory and bundled files.

  • Usage: make clean

clean-all

Cleans both the bundled files and lua binary.

  • Usage: make clean-all

Usage Summary

  1. Build all bundles: Run make.
  2. Build Lua: Run make lua.
  3. Build Lua and all bundles: Run make all.
  4. Clean bundled files: Run make clean.
  5. Clean Lua build: Run make clean-lua.
  6. Clean all files: Run make clean-all.

Classes

Array

The Array class provides methods to work with arrays, including sorting, cloning, and performing operations like map and forEach.

Instance Methods

  • length(self) - Returns the number of elements in the array.
  • clone(self) - Returns a simple copy of the internal array.
  • copy(self) - Returns a new instance of Classy.Array containing a copy of the internal data.
  • equals(self, arrayClass) - Compares two arrays for equality.
  • sort(self, compareFunction) - Sorts the array using an optional comparison function.
  • isEmpty(self) - Returns true if the array is empty.
  • contains(self, value) - Checks if the array contains a specific value.
  • forEach(self, func, errorHandler, ...) - Iterates over each element, invoking the provided function.
  • map(self, handler, ...) - Returns a new array with the results of applying the handler function to each element.

BinaryTree

The BinaryTree class implements a binary tree structure, supporting basic operations like insertion, searching, and traversals.

Instance Methods

  • getRoot(self) - Returns the root node of the binary tree.
  • insert(self, value) - Inserts a value into the binary tree.
  • find(self, value) - Finds and returns a node with the specified value.
  • inOrderTraversal(self, visit) - Performs an in-order traversal of the tree.
  • preOrderTraversal(self, visit) - Performs a pre-order traversal of the tree.
  • postOrderTraversal(self, visit) - Performs a post-order traversal of the tree.

Node Class

  • getChildren(self) - Returns the left and right children of the node.
  • setChildren(self, leftChild, rightChild) - Sets the left and right children of the node.
  • getLeft(self) - Returns the left child of the node.
  • setLeft(self, child) - Sets the left child of the node.
  • getRight(self) - Returns the right child of the node.
  • setRight(self, child) - Sets the right child of the node.
  • getValue(self) - Returns the value of the node.
  • setValue(self, value) - Sets the value of the node.

Collection

The Collection class provides a double-ended queue (deque) functionality, allowing elements to be added or removed from both ends.

Instance Methods

  • reset(self) - Resets the collection to its initial empty state.
  • pushleft(self, value) - Adds an element to the front of the collection.
  • pushright(self, value) - Adds an element to the end of the collection.
  • popleft(self) - Removes and returns the element from the front of the collection.
  • popright(self) - Removes and returns the element from the end of the collection.
  • isEmpty(self) - Returns true if the collection is empty.

DataSet

The DataSet class ensures each value exists only once, supporting set operations like union, intersection, and difference.

Instance Methods

  • add(self, value) - Adds a unique value to the dataset.
  • remove(self, value) - Removes a value from the dataset.
  • get(self, index) - Retrieves a value by its index.
  • find(self, value) - Finds the index of a value in the dataset.
  • union(self, dataSet) - Returns a new DataSet containing all unique elements from both datasets.
  • intersection(self, dataSet) - Returns a new DataSet containing elements common to both datasets.
  • difference(self, dataSet) - Returns a new DataSet containing elements unique to each dataset.

Field

The Field class is an abstract base class for managing a 2D array of values.

Instance Methods

  • set(self, x, y, value) - Sets a value at position (x, y) in the 2D array.
  • get(self, x, y) - Gets a value at position (x, y) in the 2D array.
  • clear(self) - Clears the entire 2D array.

Hashtable

The Hashtable class provides a key-value store with unique keys.

Instance Methods

  • size(self) - Returns the number of key-value pairs in the hashtable.
  • clear(self) - Clears all key-value pairs in the hashtable.
  • put(self, key, value) - Adds or updates a key-value pair in the hashtable.
  • get(self, key, default) - Retrieves the value associated with a key.
  • remove(self, key) - Removes a key-value pair from the hashtable by key.
  • containsKey(self, key) - Checks if a given key exists in the hashtable.
  • containsValue(self, value) - Checks if a given value exists in the hashtable.
  • getKeys(self, sort) - Returns a list of all keys in the hashtable, optionally sorted.
  • getValues(self, sort) - Returns a list of all values in the hashtable, optionally sorted.
  • equals(self, otherHashtable) - Checks if two hashtables are equal.
  • forEach(self, func, errorHandler, ...) - Iterates over each key-value pair, applying the given function.

LinkedList

The LinkedList class implements a doubly-linked list.

Instance Methods

  • add(self, value) - Adds a new node with the specified value.
  • insertAfter(self, refNode, value) - Inserts a new node after the specified reference node.
  • insertBefore(self, refNode, value) - Inserts a new node before the specified reference node.
  • remove(self, node) - Removes the specified node from the linked list.
  • findFirst(self, value) - Returns the first node that has the specified value.
  • findAll(self, value) - Returns all nodes with the specified value.
  • firstNode(self) - Returns the first node in the list.
  • lastNode(self) - Returns the last node in the list.
  • first(self) - Returns the value of the first node in the list.
  • last(self) - Returns the value of the last node in the list.
  • current(self) - Returns the value of the current node in the list.
  • next(self) - Moves to and returns the value of the next node in the list.
  • previous(self) - Moves to and returns the value of the previous node in the list.
  • stop(self) - Stops iteration over the list.

Node Class

  • get(self) - Returns the value of the node.
  • set(self, value) - Sets the value of the node.
  • getChildren(self) - Returns the left and right children of the node.
  • setChildren(self, leftChild, rightChild) - Sets the left and right children of the node.

Matrix

The Matrix class provides operations for working with matrices, including addition, subtraction, multiplication, transposition, and inversion.

Instance Methods

  • initialize(self, rows, cols, initialValue) - Initializes the matrix with a specific size and initial value.
  • add(self, matrix) - Adds another matrix to the current matrix.
  • subtract(self, matrix) - Subtracts another matrix from the current matrix.
  • multiply(self, matrixOrScalar) - Multiplies the current matrix by another matrix or a scalar.
  • transpose(self) - Transposes the current matrix.
  • determinant(self) - Calculates the determinant of the matrix (only for square matrices).
  • inverse(self) - Calculates the inverse of the matrix (only for square matrices).
  • toString(self) - Returns a string representation of the matrix.

Observable

The Observable class allows for observing changes to a value, notifying subscribed listeners when the value changes.

Instance Methods

  • get(self) - Returns the current value of the Observable.
  • set(self, value) - Sets a new value for the Observable and notifies listeners if the value has changed.
  • subscribe(self, func) - Subscribes a function to the Observable's value changes.
  • unsubscribe(self, func) - Unsubscribes a function from the Observable's value changes.
  • invokeValueChanged(self, newValue) - Invokes all subscribed listeners when the value changes.
  • invokeErrorHandler(err) - Default error handler for listener invocation errors.

Queue

The Queue class implements a basic first-in, first-out (FIFO) queue.

Instance Methods

  • enqueue(self, arg) - Adds an element to the queue.
  • dequeue(self) - Removes and returns the next element from the queue.
  • peek(self) - Peeks at the next element in the queue without removing it.
  • isEmpty(self) - Returns true if the queue is empty.
  • size(self) - Returns the number of elements in the queue.

Stack

The Stack class implements a basic last-in, first-out (LIFO) stack.

Instance Methods

  • push(self, arg) - Pushes an element onto the stack.
  • pop(self) - Pops and returns the top element from the stack.
  • peek(self) - Peeks at the top element of the stack without removing it.
  • reset(self) - Resets the stack to its initial empty state.
  • isEmpty(self) - Returns true if the stack is empty.
  • size(self) - Returns the number of elements in the stack.

Tree

The Tree class represents a tree structure where each node can have multiple children.

Instance Methods

  • getRoot(self) - Returns the root node of the tree.
  • depthFirstSearch(self, visit) - Traverses the tree using a depth-first search (DFS) approach.
  • breadthFirstSearch(self, visit) - Traverses the tree using a breadth-first search (BFS) approach.

Node Class

  • get(self, child) - Gets the children of the node, or finds specific children if a value is provided.
  • add(self, child) - Adds a child node to the current node.
  • delete(self, child) - Deletes a child node from the current node.
  • getValue(self) - Returns the value of the node.
  • setValue(self, value) - Sets a new value for the node.

Vector

The Vector class represents a mathematical vector and provides methods for common vector operations such as addition, subtraction, dot product, scalar multiplication, and normalization.

Instance Methods

  • dimension(self): Returns the dimension (length) of the vector.
  • add(self, other): Adds another vector to this vector. The vectors must have the same dimension.
  • subtract(self, other): Subtracts another vector from this vector. The vectors must have the same dimension.
  • multiplyByScalar(self, scalar): Multiplies this vector by a scalar value.
  • dotProduct(self, other): Computes the dot product of this vector and another vector. The vectors must have the same dimension.
  • magnitude(self): Computes the magnitude (length) of the vector.
  • normalize(self): Normalizes the vector, making it a unit vector (a vector with a magnitude of 1).
  • getElement(self, index): Retrieves the value at a specific index.
  • toString(self): Converts the vector to a string for easy printing and debugging.

Example Usage

-- Create two vectors
local vec1 = Classy.Vector.new(function(self)
    self:addElement(1)
    self:addElement(2)
    self:addElement(3)
end)

local vec2 = Classy.Vector.new(function(self)
    self:addElement(4)
    self:addElement(5)
    self:addElement(6)
end)

-- Add the vectors
local sum = vec1:add(vec2)
print("Sum: " .. sum:toString())  -- Output: Sum: {5, 7, 9}

-- Subtract the vectors
local difference = vec1:subtract(vec2)
print("Difference: " .. difference:toString())  -- Output: Difference: {-3, -3, -3}

-- Dot product of the vectors
local dot = vec1:dotProduct(vec2)
print("Dot Product: " .. dot)  -- Output: Dot Product: 32

-- Magnitude of a vector
local magnitude = vec1:magnitude()
print("Magnitude of vec1: " .. magnitude)  -- Output: Magnitude of vec1: 3.7416573867739

-- Normalize the vector
local normalizedVec = vec1:normalize()
print("Normalized vec1: " .. normalizedVec:toString())  -- Output: Normalized vec1: {0.26726124191242, 0.53452248382485, 0.80178372573727}

License

This library is open-source and licensed under the MIT License. Feel free to use, modify, and distribute it as needed.

Contributions

Contributions are welcome! Please fork this repository and submit a pull request with your changes. Be sure to add tests and documentation for any new features or bug fixes.