Reorganize matrix construction macros.

This commit is contained in:
Crozet Sébastien 2020-11-13 18:34:47 +01:00
parent 4c2192d9e0
commit 9a4cf0b69f
2 changed files with 316 additions and 269 deletions

View File

@ -22,11 +22,12 @@ use crate::base::dimension::{Dim, DimName, Dynamic, U1, U2, U3, U4, U5, U6};
use crate::base::storage::Storage; use crate::base::storage::Storage;
use crate::base::{DefaultAllocator, Matrix, MatrixMN, MatrixN, Scalar, Unit, Vector, VectorN}; use crate::base::{DefaultAllocator, Matrix, MatrixMN, MatrixN, Scalar, Unit, Vector, VectorN};
/* /// # Generic constructors
* /// This set of matrix and vector construction functions are all generic
* Generic constructors. /// with-regard to the matrix dimensions. They all expect to be given
* /// the dimension as inputs.
*/ ///
/// These functions should only be used when working on dimension-generic code.
impl<N: Scalar, R: Dim, C: Dim> MatrixMN<N, R, C> impl<N: Scalar, R: Dim, C: Dim> MatrixMN<N, R, C>
where where
DefaultAllocator: Allocator<N, R, C>, DefaultAllocator: Allocator<N, R, C>,
@ -350,9 +351,6 @@ where
*/ */
macro_rules! impl_constructors( macro_rules! impl_constructors(
($($Dims: ty),*; $(=> $DimIdent: ident: $DimBound: ident),*; $($gargs: expr),*; $($args: ident),*) => { ($($Dims: ty),*; $(=> $DimIdent: ident: $DimBound: ident),*; $($gargs: expr),*; $($args: ident),*) => {
impl<N: Scalar, $($DimIdent: $DimBound, )*> MatrixMN<N $(, $Dims)*>
where DefaultAllocator: Allocator<N $(, $Dims)*> {
/// Creates a new uninitialized matrix or vector. /// Creates a new uninitialized matrix or vector.
#[inline] #[inline]
pub unsafe fn new_uninitialized($($args: usize),*) -> Self { pub unsafe fn new_uninitialized($($args: usize),*) -> Self {
@ -577,48 +575,66 @@ macro_rules! impl_constructors(
) -> Self { ) -> Self {
Self::from_distribution_generic($($gargs, )* distribution, rng) Self::from_distribution_generic($($gargs, )* distribution, rng)
} }
}
impl<N: Scalar, $($DimIdent: $DimBound, )*> MatrixMN<N $(, $Dims)*>
where
DefaultAllocator: Allocator<N $(, $Dims)*>,
Standard: Distribution<N> {
/// Creates a matrix filled with random values. /// Creates a matrix filled with random values.
#[inline] #[inline]
#[cfg(feature = "std")] #[cfg(feature = "std")]
pub fn new_random($($args: usize),*) -> Self { pub fn new_random($($args: usize),*) -> Self
where Standard: Distribution<N> {
Self::new_random_generic($($gargs),*) Self::new_random_generic($($gargs),*)
} }
} }
}
); );
// FIXME: this is not very pretty. We could find a better call syntax. /// # Constructors of statically-sized vectors or statically-sized matrices
impl_constructors!(R, C; // Arguments for Matrix<N, ..., S> impl<N: Scalar, R: DimName, C: DimName> MatrixMN<N, R, C>
=> R: DimName, => C: DimName; // Type parameters for impl<N, ..., S> where
R::name(), C::name(); // Arguments for `_generic` constructors. DefaultAllocator: Allocator<N, R, C>,
); // Arguments for non-generic constructors. {
// FIXME: this is not very pretty. We could find a better call syntax.
impl_constructors!(R, C; // Arguments for Matrix<N, ..., S>
=> R: DimName, => C: DimName; // Type parameters for impl<N, ..., S>
R::name(), C::name(); // Arguments for `_generic` constructors.
); // Arguments for non-generic constructors.
}
impl_constructors!(R, Dynamic; /// # Constructors of matrices with a dynamic number of columns
impl<N: Scalar, R: DimName> MatrixMN<N, R, Dynamic>
where
DefaultAllocator: Allocator<N, R, Dynamic>,
{
impl_constructors!(R, Dynamic;
=> R: DimName; => R: DimName;
R::name(), Dynamic::new(ncols); R::name(), Dynamic::new(ncols);
ncols); ncols);
}
impl_constructors!(Dynamic, C; /// # Constructors of dynamic vectors and matrices with a dynamic number of rows
impl<N: Scalar, C: DimName> MatrixMN<N, Dynamic, C>
where
DefaultAllocator: Allocator<N, Dynamic, C>,
{
impl_constructors!(Dynamic, C;
=> C: DimName; => C: DimName;
Dynamic::new(nrows), C::name(); Dynamic::new(nrows), C::name();
nrows); nrows);
}
impl_constructors!(Dynamic, Dynamic; /// # Constructors of fully dynamic matrices
impl<N: Scalar> MatrixMN<N, Dynamic, Dynamic>
where
DefaultAllocator: Allocator<N, Dynamic, Dynamic>,
{
impl_constructors!(Dynamic, Dynamic;
; ;
Dynamic::new(nrows), Dynamic::new(ncols); Dynamic::new(nrows), Dynamic::new(ncols);
nrows, ncols); nrows, ncols);
}
/* /*
* *
* Constructors that don't necessarily require all dimensions * Constructors that don't necessarily require all dimensions
* to be specified whon one dimension is already known. * to be specified when one dimension is already known.
* *
*/ */
macro_rules! impl_constructors_from_data( macro_rules! impl_constructors_from_data(

View File

@ -54,7 +54,34 @@ pub type MatrixCross<N, R1, C1, R2, C2> =
/// The most generic column-major matrix (and vector) type. /// The most generic column-major matrix (and vector) type.
/// ///
/// It combines four type parameters: /// # Methods summary
/// Because `Matrix` is the most generic types that groups all matrix and vectors of **nalgebra**
/// this documentation page contains every single matrix/vector-related method. In order to make
/// browsing this page simpler, the next subsections contain direct links to groups of methods
/// related to a specific topic.
///
/// #### Vector and matrix construction
/// - [Constructors of statically-sized vectors or statically-sized matrices](#constructors-of-statically-sized-vectors-or-statically-sized-matrices)
/// (`Vector3`, `Matrix3x6`, etc.)
/// - [Constructors of fully dynamic matrices](#constructors-of-fully-dynamic-matrices) (`DMatrix`)
/// - [Constructors of dynamic vectors and matrices with a dynamic number of rows](#constructors-of-dynamic-vectors-and-matrices-with-a-dynamic-number-of-rows)
/// (`DVector`, `MatrixXx3`, etc.)
/// - [Constructors of matrices with a dynamic number of columns](#constructors-of-matrices-with-a-dynamic-number-of-columns)
/// (`Matrix2xX`, etc.)
/// - [Generic constructors](#generic-constructors)
/// (For code generic wrt. the vectors or matrices dimensions.)
/// #### Matrix decomposition
/// - [Rectangular matrix decomposition](#rectangular-matrix-decomposition) (Applicable to square matrices too)
/// - [Square matrix decomposition](#square-matrix-decomposition)
///
/// #### Vector and matrix slicing
/// - [Slicing based on index and length](#slicing-based-on-index-and-length)
/// - [Mutable slicing based on index and length](#mutable-slicing-based-on-index-and-length)
/// - [Slicing based on ranges](#slicing-based-on-ranges)
/// - [Mutable slicing based on ranges](#mutable-slicing-based-on-ranges)
///
/// # Type parameters
/// The generic `Matrix` type has four type parameters:
/// - `N`: for the matrix components scalar type. /// - `N`: for the matrix components scalar type.
/// - `R`: for the matrix number of rows. /// - `R`: for the matrix number of rows.
/// - `C`: for the matrix number of columns. /// - `C`: for the matrix number of columns.
@ -75,26 +102,30 @@ pub type MatrixCross<N, R1, C1, R2, C2> =
/// Note that mixing `Dynamic` with type-level unsigned integers is allowed. Actually, a /// Note that mixing `Dynamic` with type-level unsigned integers is allowed. Actually, a
/// dynamically-sized column vector should be represented as a `Matrix<N, Dynamic, U1, S>` (given /// dynamically-sized column vector should be represented as a `Matrix<N, Dynamic, U1, S>` (given
/// some concrete types for `N` and a compatible data storage type `S`). /// some concrete types for `N` and a compatible data storage type `S`).
///
/// # Documentation by feature
/// Because `Matrix` is the most generic types that groups all matrix and vectors of **nalgebra**
/// this documentation page contains every single matrix/vector-related method. In order to make
/// browsing this page simpler, the next subsections contain direct links to groups of methods
/// related to a specific topic.
///
/// #### Matrix decomposition
/// - [Rectangular matrix decomposition](#rectangular-matrix-decomposition).
/// - [Square matrix decomposition](#square-matrix-decomposition).
///
/// #### Matrix slicing
/// - [Slicing](#slicing)
/// - [Mutable slicing](#mutable-slicing)
/// - [Range-based slicing](#range-based-slicing), [mutable range-based slicing](#mutable-range-based-slicing).
#[repr(C)] #[repr(C)]
#[derive(Clone, Copy)] #[derive(Clone, Copy)]
pub struct Matrix<N: Scalar, R: Dim, C: Dim, S> { pub struct Matrix<N: Scalar, R: Dim, C: Dim, S> {
/// The data storage that contains all the matrix components and informations about its number /// The data storage that contains all the matrix components. Disappointed?
/// of rows and column (if needed). ///
/// Well, if you came here to see how you can access the matrix components,
/// you may be in luck: you can access the individual components of all vectors with compile-time
/// dimensions <= 6 using field notation like this:
/// `vec.x`, `vec.y`, `vec.z`, `vec.w`, `vec.a`, `vec.b`. Reference and assignation work too:
/// ```.ignore
/// let mut v = Vector3::new(1.0, 2.0, 3.0);
/// vec.x = 10.0;
/// my_function(&vec.z);
/// println!("{}", vec.y + 30.0);
/// ```
/// Similarly, for matrices with compile-time dimensions <= 6, you can use field notation
/// like this: `mat.m11`, `mat.m42`, etc. The first digit identifies the row to address
/// and the second digit identifies the column to address. So `mat.m13` identifies the component
/// at the first row and third column (note that the count of rows and columns start at 1 instead
/// of 0 here. This is so we match the mathematical notation).
///
/// For all matrices and vectors, independently from their size, individual components can
/// be accessed and modified using indexing: `vec[20]`, `mat[(20, 19)]`. Here the indexing
/// starts at 0 as you would expect.
pub data: S, pub data: S,
_phantoms: PhantomData<(N, R, C)>, _phantoms: PhantomData<(N, R, C)>,