Crates.io | vectrix-macro |
lib.rs | vectrix-macro |
version | 0.3.0 |
source | src |
created_at | 2021-01-15 21:09:11.584077 |
updated_at | 2022-11-13 11:32:32.518348 |
description | A macro for composing matrices |
homepage | |
repository | https://github.com/rossmacarthur/vectrix |
max_upload_size | |
id | 342554 |
size | 12,292 |
This crate provides a stack-allocated, constant-size Matrix<T, M, N>
type implemented using const generics.
Add this crate to your Cargo manifest.
cargo add vectrix
no_std
is also supported by disabling the default std feature.
cargo add vectrix --no-default-features --features=macro
The base Matrix<T, M, N>
type represents a matrix with M
rows and N
columns. This type is a backed by an array of arrays. The data is stored in
column-major order. Some convenient aliases are provided for common
matrices, like vectors.
Matrix<T, M, N>
→ a generic matrix type with M
rows and N
columns.Vector<T, M>
→ a column vector with M
rows.RowVector<T, N>
→ a row vector with N
columns.Macros are provided for easy construction of the provided types. These
macros will also work in const
contexts.
The matrix!
macro can be used to construct a new Matrix
of any
size.
let m = matrix![
1, 3, 5;
2, 4, 6;
];
In the above example matrix
is a Matrix<_, 2, 3>
type, having 2 rows and
3 columns.
The vector!
and row_vector!
macros can be used to to construct
column and row vectors respectively.
let v = vector![1, 3, 3, 7];
// ^ type `Vector<_, 4>`
assert_eq!(v, matrix![1; 3; 3; 7]);
let v = row_vector![1, 3, 3, 7];
// ^^^^^^ type `RowVector<_, 4>`
assert_eq!(v, matrix![1, 3, 3, 7]);
Commonly used constructors are listed below.
::zero()
→ constructs a new matrix filled with
T::zero()
.::identity()
→ constructs a new identity matrix.::repeat(..)
→ constructs a new matrix filled with
the provided value.::repeat_with(..)
→ constructs a new matrix
filled with values computed by the provided closure.::from_iter(..)
→ constructs a
new matrix from an iterator.::new(..)
→ constructs a new vector using the
provided components.Three types of element access are available.
usize
indexing selects the nth element in the matrix as viewed in
column-major order.
let m = matrix![
1, 2, 3;
4, 5, 6;
];
assert_eq!(m[1], 4);
(usize, usize)
indexing selects the element at a particular row and
column position.
let m = matrix![
1, 2, 3;
4, 5, 6;
];
assert_eq!(m[(1, 0)], 4);
Component accessors are available for small vectors using traditional names.
let mut v = vector![1, 2, 3, 4, 0, 0];
v.y = 3;
v.w = 7;
assert_eq!(v.x, 1);
assert_eq!(v.y, 3);
assert_eq!(v.z, 3);
assert_eq!(v.w, 7);
assert_eq!(v.a, 0);
assert_eq!(v.b, 0);
You can get a reference to particular row or column using the
.row()
or .column()
methods. You
can get a mutable reference using the _mut
variants.
let mut m = matrix![
1, 2, 3;
4, 7, 6;
];
let row = m.row_mut(1);
row[1] = 5;
assert_eq!(m.column(1), &[2, 5]);
Element-wise, column-major order iteration is provided using the following methods.
.into_iter()
→ consumes the matrix and returns
an owned iterator over each element..iter()
→ returns an iterator over a reference to
each element..iter_mut()
→ returns an iterator over a mutable
reference to each element.Iteration over rows and columns is provide using the following methods.
.iter_rows()
→ returns an iterator over a
reference to each row..iter_rows_mut()
→ returns an iterator over
mutable reference to each row..iter_columns()
→ returns an iterator over a
reference to each column..iter_columns_mut()
→ returns an
iterator over a mutable reference to each column.A slice view of the underlying data is provided using
.as_slice()
and
.as_mut_slice()
.
let mut m = matrix![
1, 3, 5;
2, 3, 6;
];
m.as_mut_slice()[3] = 4;
assert_eq!(m.as_slice(), &[1, 2, 3, 4, 5, 6]);
The Debug
implementation will print out vectors as
lists and matrices as a list of lists in column-major order.
let v = vector![1.1, 2.0];
let m = matrix![1, 2; 3, 4];
println!("vector: {:.2?}", v);
println!("matrix: {:?}", m);
This will output:
vector: [1.10, 2.00]
matrix: [[1, 3], [2, 4]]
The Display
implementation will print out the
matrix in the traditional box bracket format. Precision is supported as well
as most of the other formatting traits like
LowerHex
.
let cv = vector![1.1, 2.0];
let rv = row_vector![1.1, 2.0];
let m = matrix![1, 2; 3, 4];
println!("column vector: {:.2}", cv);
println!("row vector: {:.1}", rv);
println!("matrix: {:b}", m);
This will output:
column vector:
┌ ┐
│ 1.10 │
│ 2.00 │
└ ┘
row vector:
┌ ┐
│ 1.1 2.0 │
└ ┘
matrix:
┌ ┐
│ 1 10 │
│ 11 100 │
└ ┘
Matrix
implements many built-in operators. With scalar operands almost
all operators are implemented and they simply apply the operation to each
element in the matrix. Unary operators will do the equivalent. In the
following example each element in the matrix is multiplied by 2.
let m = matrix![
1, -3;
3, -7;
];
let exp = matrix![
2, -6;
6, -14;
];
assert_eq!(m * 2, exp);
Matrix
supports addition and subtraction with same size matrices for
element-wise addition and subtraction. In the following example a matrix
is added to itself.
let m = matrix![
1, -3;
3, -7;
];
let exp = matrix![
2, -6;
6, -14;
];
assert_eq!(m + m, exp);
Licensed under either of
at your option.