VectorMath is a Swift library for Mac and iOS that implements common 2D and 3D vector and matrix functions, useful for games or vector-based graphics.
VectorMath takes advantage of Swift language features such as function and operator overloading and struct methods to provide a more elegant interface than most C, C++ or Cocoa-based graphics APIs.
VectorMath also provides a handy replacement for the GLKit vector math types and functions, which are not available yet in Swift due to their reliance on union types.
VectorMath is a completely standalone library, relying only on the Foundation framework. However, it provides optional compatibility extensions for SceneKit and Quartz (CoreGraphics/CoreAnimation) for interoperability with UIKit, AppKit, SpriteKit and SceneKit.
VectorMath is designed to be efficient, but has not been heavily optimized yet, and does not yet take advantage of architecture-specific hardware acceleration using the Accelerate framework.
Supported OS & SDK Versions
Supported build target - iOS 12.0, Mac OS 10.14 (Xcode 11.1)
Earliest supported deployment target - iOS 9.0, Mac OS 10.13
Earliest compatible deployment target - iOS 7.0, Mac OS 10.9
NOTE: ‘Supported’ means that the library has been tested with this version. ‘Compatible’ means that the library should work on this OS version (i.e. it doesn’t rely on any unavailable SDK features) but is no longer being tested for compatibility and may require tweaking or bug fixes to run correctly.
Installation
To use the VectorMath functions in an app, drag the VectorMath.swift file (demo/test files and assets are not needed) into your project. You may also wish to include the VectorMath+SceneKit.swift and/or VectorMath+Quartz.swift compatibility extensions.
Types
VectorMath declares the following types:
Scalar
This is a typealias used for the scalar floating point values in the VectorMath library. It is set to Float by default, but you can change it to Double or CGFloat to improve performance for your specific application.
Vector2
Vector3
Vector4
These represent 2D, 3D and 4D vectors, respectively.
Matrix3
Matrix4
These represent homogenous 3x3 and 4x4 transform matrices, respectively.
Quaternion
This represents a rotation in 3D space. It has the same structure as Vector4D, but is defined as a different type due to the different use cases and methods.
All the VectorMath types conform to Equatable and Hashable, so they can be stored in Swift dictionaries.
Constants
VectorMath declares a number of namespaced constants for your convenience. They are as follows:
Conversion factors between degrees and radians. E.g. to convert 40 degrees to radians, you would say let r = 40 * .degreesPerRadian, or to convert Pi/2 radians to degrees, say let d = .halfPi * .radiansPerDegree
Scalar.epsilon = 0.0001
This is a floating point error value used by the approx-equal operator. You can change this if it’s insufficiently (or excessively) precise for your needs.
These are identity matrices, which have the property that multiplying them by another matrix or vector has no effect.
Methods
The complete list of VectorMath properties and methods is given below. These are mostly self-explanatory. If you can’t find a method you are looking for (e.g. a method to rotate a vector using a quaternion), it’s probably implemented as an operator (see “Operators” below).
VectorMath makes extensive use of operator overloading, but I’ve tried not to go overboard with custom operators. The only nonstandard operator defined is ~=, meaning “approximately equal”, which is extremely useful for comparing Scalar, Vector or Matrix values for equality, as, due to floating point imprecision, they are rarely identical.
The *, /, +, - and == operators are implemented for most of the included types. * in particular is useful for matrix and vector transforms. For example, to apply a matrix transform “m” to a vector “v” you can write m * v. * can also be used in conjunction with a Scalar value to scale a vector.
Unary minus is supported for inversion/negation on vectors and matrices.
Dot product, cross product and normalization are not available in operator form, but are supplied as methods on the various types.
Purpose
VectorMath is a Swift library for Mac and iOS that implements common 2D and 3D vector and matrix functions, useful for games or vector-based graphics.
VectorMath takes advantage of Swift language features such as function and operator overloading and struct methods to provide a more elegant interface than most C, C++ or Cocoa-based graphics APIs.
VectorMath also provides a handy replacement for the GLKit vector math types and functions, which are not available yet in Swift due to their reliance on union types.
VectorMath is a completely standalone library, relying only on the Foundation framework. However, it provides optional compatibility extensions for SceneKit and Quartz (CoreGraphics/CoreAnimation) for interoperability with UIKit, AppKit, SpriteKit and SceneKit.
VectorMath is designed to be efficient, but has not been heavily optimized yet, and does not yet take advantage of architecture-specific hardware acceleration using the Accelerate framework.
Supported OS & SDK Versions
NOTE: ‘Supported’ means that the library has been tested with this version. ‘Compatible’ means that the library should work on this OS version (i.e. it doesn’t rely on any unavailable SDK features) but is no longer being tested for compatibility and may require tweaking or bug fixes to run correctly.
Installation
To use the VectorMath functions in an app, drag the VectorMath.swift file (demo/test files and assets are not needed) into your project. You may also wish to include the VectorMath+SceneKit.swift and/or VectorMath+Quartz.swift compatibility extensions.
Types
VectorMath declares the following types:
This is a typealias used for the scalar floating point values in the VectorMath library. It is set to Float by default, but you can change it to Double or CGFloat to improve performance for your specific application.
These represent 2D, 3D and 4D vectors, respectively.
These represent homogenous 3x3 and 4x4 transform matrices, respectively.
This represents a rotation in 3D space. It has the same structure as Vector4D, but is defined as a different type due to the different use cases and methods.
All the VectorMath types conform to Equatable and Hashable, so they can be stored in Swift dictionaries.
Constants
VectorMath declares a number of namespaced constants for your convenience. They are as follows:
These should be self-explanatory.
Conversion factors between degrees and radians. E.g. to convert 40 degrees to radians, you would say
let r = 40 * .degreesPerRadian
, or to convert Pi/2 radians to degrees, saylet d = .halfPi * .radiansPerDegree
This is a floating point error value used by the approx-equal operator. You can change this if it’s insufficiently (or excessively) precise for your needs.
These are zero vector constants, useful as default values for vectors
These are unit vectors along various axes. For example Vector3.z has the value
Vector3(0, 0, 1)
These are identity matrices, which have the property that multiplying them by another matrix or vector has no effect.
Methods
The complete list of VectorMath properties and methods is given below. These are mostly self-explanatory. If you can’t find a method you are looking for (e.g. a method to rotate a vector using a quaternion), it’s probably implemented as an operator (see “Operators” below).
Operators
VectorMath makes extensive use of operator overloading, but I’ve tried not to go overboard with custom operators. The only nonstandard operator defined is
~=
, meaning “approximately equal”, which is extremely useful for comparing Scalar, Vector or Matrix values for equality, as, due to floating point imprecision, they are rarely identical.The *, /, +, - and == operators are implemented for most of the included types. * in particular is useful for matrix and vector transforms. For example, to apply a matrix transform “m” to a vector “v” you can write
m * v
. * can also be used in conjunction with a Scalar value to scale a vector.Unary minus is supported for inversion/negation on vectors and matrices.
Dot product, cross product and normalization are not available in operator form, but are supplied as methods on the various types.
Acknowledgements
Many of the algorithms used in VectorMath were ported or adapted from the Kazmath vector math library for C (https://github.com/Kazade/kazmath), or derived from the awesome Matrix and Quaternion FAQ (http://www.j3d.org/matrix_faq/matrfaq_latest.html).
In addition, the following people have contributed directly to the project:
(Full list of contributors)