Crate truck_geometry::base::cgmath

Expand description

A low-dimensional linear algebra library, targeted at computer graphics.

Trait overview

In order to make a clean, composable API, we divide operations into traits that are roughly based on mathematical properties. The main ones that we concern ourselves with are listed below:

VectorSpace: Specifies the main operators for vectors, quaternions, and matrices.
MetricSpace: For types that have a distance function implemented.
InnerSpace: For types that have a dot (or inner) product - ie. vectors or quaternions. This also allows for the definition of operations that are based on the dot product, like finding the magnitude or normalizing.
EuclideanSpace: Points in euclidean space, with an associated space of displacement vectors.
Matrix: Common operations for matrices of arbitrary dimensions.
SquareMatrix: A special trait for matrices where the number of columns equal the number of rows.

Other traits are included for practical convenience, for example:

Array: For contiguous, indexable arrays of elements, specifically vectors.
ElementWise: For element-wise addition, subtraction, multiplication, division, and remainder operations.

The prelude

Importing each trait individually can become a chore, so we provide a prelude module to allow you to import the main traits all at once. For example:

use cgmath::prelude::*;

Modules

Constrained conversion functions for assisting in situations where type inference is difficult.

Numeric traits for generic mathematics

This module contains the most common traits used in cgmath. By glob-importing this module, you can avoid the need to import each trait individually, while still being selective about what types you import.

Macros

Approximate equality of using the absolute difference.

Approximate inequality of using the absolute difference.

assert_abs_diff_eq

An assertion that delegates to [abs_diff_eq!], and panics with a helpful error on failure.

assert_abs_diff_ne

An assertion that delegates to [abs_diff_ne!], and panics with a helpful error on failure.

assert_relative_eq

An assertion that delegates to [relative_eq!], and panics with a helpful error on failure.

assert_relative_ne

An assertion that delegates to [relative_ne!], and panics with a helpful error on failure.

An assertion that delegates to [ulps_eq!], and panics with a helpful error on failure.

An assertion that delegates to [ulps_ne!], and panics with a helpful error on failure.

Approximate equality using both the absolute difference and relative based comparisons.

Approximate inequality using both the absolute difference and relative based comparisons.

Approximate equality using both the absolute difference and ULPs (Units in Last Place).

Approximate inequality using both the absolute difference and ULPs (Units in Last Place).

Structs

The requisite parameters for testing for approximate equality using a absolute difference based comparison.

A two-dimensional rotation matrix.

A three-dimensional rotation matrix.

A generic transformation consisting of a rotation, displacement vector and scale amount.

An angle, in degrees.

A set of Euler angles representing a rotation in three-dimensional space.

A 2 x 2, column major matrix

A 3 x 3, column major matrix

A 4 x 4, column major matrix

An orthographic projection with arbitrary left/right/bottom/top distances

A perspective projection with arbitrary left/right/bottom/top distances

A perspective projection based on a vertical field-of-view angle.

A point in 1-dimensional space.

A point in 2-dimensional space.

A point in 3-dimensional space.

A quaternion in scalar/vector form.

An angle, in radians.

The requisite parameters for testing for approximate equality using a relative based comparison.

The requisite parameters for testing for approximate equality using an ULPs based comparison.

A 1-dimensional vector.

A 2-dimensional vector.

A 3-dimensional vector.

A 4-dimensional vector.

Traits

Equality that is defined using the absolute difference of two numbers.

Angles and their associated trigonometric functions.

An array containing elements of type Element

Base floating point types

Base numeric types with partial ordering

Numbers which have upper and lower bounds

Element-wise arithmetic operations. These are supplied for pragmatic reasons, but will usually fall outside of traditional algebraic properties.

Points in a Euclidean space with an associated space of displacement vectors.

Vectors that also have a dot (or inner) product.

A column-major matrix of arbitrary dimensions.

A type with a distance function between values.

Defines a multiplicative identity element for Self.

Equality comparisons between two numbers using both the absolute difference and relative based comparisons.

A trait for a generic rotation. A rotation is a transformation that creates a circular motion, and preserves at least one point in the space.

A two-dimensional rotation.

A three-dimensional rotation.

A column-major major matrix where the rows and column vectors are of the same dimensions.

A trait representing an affine transformation that can be applied to points or vectors. An affine transformation is one which

Equality comparisons between two numbers using both the absolute difference and ULPs (Units in Last Place) based comparisons.

Vectors that can be added together and multiplied by scalars.

Defines an additive identity element for Self.

Functions

Dot product of two vectors.

Create a perspective matrix from a view frustum.

Create an orthographic projection matrix.

Create a perspective projection matrix.

The short constructor.

The short constructor.

The short constructor.

The short constructor.

The short constructor.

The short constructor.

The short constructor.