#[repr(C)]pub struct Matrix<T, R, C, S> {
pub data: S,
/* private fields */
}
Expand description
The most generic column-major matrix (and vector) type.
§Methods summary
Because Matrix
is the most generic types used as a common representation of all matrices 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
(
Vector3
,Matrix3x6
…) - Constructors of fully dynamic matrices (
DMatrix
) - Constructors of dynamic vectors and matrices with a dynamic number of rows
(
DVector
,MatrixXx3
…) - Constructors of matrices with a dynamic number of columns
(
Matrix2xX
…) - Generic constructors (For code generic wrt. the vectors or matrices dimensions.)
§Computer graphics utilities for transformations
- 2D transformations as a Matrix3
new_rotation
… - 3D transformations as a Matrix4
new_rotation
,new_perspective
,look_at_rh
… - Translation and scaling in any dimension
new_scaling
,new_translation
… - Append/prepend translation and scaling
append_scaling
,prepend_translation_mut
… - Transformation of vectors and points
transform_vector
,transform_point
…
§Common math operations
- Componentwise operations
component_mul
,component_div
,inf
… - Special multiplications
tr_mul
,ad_mul
,kronecker
… - Dot/scalar product
dot
,dotc
,tr_dot
… - Cross product
cross
,perp
… - Magnitude and norms
norm
,normalize
,metric_distance
… - In-place normalization
normalize_mut
,try_normalize_mut
… - Interpolation
lerp
,slerp
… - BLAS functions
gemv
,gemm
,syger
… - Swizzling
xx
,yxz
… - Triangular matrix extraction
upper_triangle
,lower_triangle
§Statistics
- Common operations
row_sum
,column_mean
,variance
… - Find the min and max components
min
,max
,amin
,amax
,camin
,cmax
… - Find the min and max components (vector-specific methods)
argmin
,argmax
,icamin
,icamax
…
§Iteration, map, and fold
- Iteration on components, rows, and columns
iter
,column_iter
… - Parallel iterators using rayon
par_column_iter
,par_column_iter_mut
… - Elementwise mapping and folding
map
,fold
,zip_map
… - Folding or columns and rows
compress_rows
,compress_columns
…
§Vector and matrix views
- Creating matrix views from
&[T]
from_slice
,from_slice_with_strides
… - Creating mutable matrix views from
&mut [T]
from_slice_mut
,from_slice_with_strides_mut
… - Views based on index and length
row
,columns
,view
… - Mutable views based on index and length
row_mut
,columns_mut
,view_mut
… - Views based on ranges
rows_range
,columns_range
… - Mutable views based on ranges
rows_range_mut
,columns_range_mut
…
§In-place modification of a single matrix or vector
- In-place filling
fill
,fill_diagonal
,fill_with_identity
… - In-place swapping
swap
,swap_columns
… - Set rows, columns, and diagonal
set_column
,set_diagonal
…
§Vector and matrix size modification
- Rows and columns insertion
insert_row
,insert_column
… - Rows and columns removal
remove_row
,remove column
… - Rows and columns extraction
select_rows
,select_columns
… - Resizing and reshaping
resize
,reshape_generic
… - In-place resizing
resize_mut
,resize_vertically_mut
…
§Matrix decomposition
- Rectangular matrix decomposition
qr
,lu
,svd
… - Square matrix decomposition
cholesky
,symmetric_eigen
…
§Vector basis computation
§Type parameters
The generic Matrix
type has four type parameters:
T
: for the matrix components scalar type.R
: for the matrix number of rows.C
: for the matrix number of columns.S
: for the matrix data storage, i.e., the buffer that actually contains the matrix components.
The matrix dimensions parameters R
and C
can either be:
- type-level unsigned integer constants (e.g.
U1
,U124
) from thenalgebra::
root module. All numbers from 0 to 127 are defined that way. - type-level unsigned integer constants (e.g.
U1024
,U10000
) from thetypenum::
crate. Using those, you will not get error messages as nice as for numbers smaller than 128 defined on thenalgebra::
module. - the special value
Dyn
from thenalgebra::
root module. This indicates that the specified dimension is not known at compile-time. Note that this will generally imply that the matrix data storageS
performs a dynamic allocation and contains extra metadata for the matrix shape.
Note that mixing Dyn
with type-level unsigned integers is allowed. Actually, a
dynamically-sized column vector should be represented as a Matrix<T, Dyn, U1, S>
(given
some concrete types for T
and a compatible data storage type S
).
Fields§
§data: S
The data storage that contains all the matrix components. Disappointed?
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:
let mut vec = Vector3::new(1.0, 2.0, 3.0);
vec.x = 10.0;
vec.y += 30.0;
assert_eq!(vec.x, 10.0);
assert_eq!(vec.y + 100.0, 132.0);
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.
Implementations§
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Dot/scalar product
sourcepub fn dot<R2, C2, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
pub fn dot<R2, C2, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
The dot product between two vectors or matrices (seen as vectors).
This is equal to self.transpose() * rhs
. For the sesquilinear complex dot product, use
self.dotc(rhs)
.
Note that this is not the matrix multiplication as in, e.g., numpy. For matrix
multiplication, use one of: .gemm
, .mul_to
, .mul
, the *
operator.
§Example
let vec1 = Vector3::new(1.0, 2.0, 3.0);
let vec2 = Vector3::new(0.1, 0.2, 0.3);
assert_eq!(vec1.dot(&vec2), 1.4);
let mat1 = Matrix2x3::new(1.0, 2.0, 3.0,
4.0, 5.0, 6.0);
let mat2 = Matrix2x3::new(0.1, 0.2, 0.3,
0.4, 0.5, 0.6);
assert_eq!(mat1.dot(&mat2), 9.1);
sourcepub fn dotc<R2, C2, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> Twhere
R2: Dim,
C2: Dim,
T: SimdComplexField,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: DimEq<R, R2> + DimEq<C, C2>,
pub fn dotc<R2, C2, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> Twhere
R2: Dim,
C2: Dim,
T: SimdComplexField,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: DimEq<R, R2> + DimEq<C, C2>,
The conjugate-linear dot product between two vectors or matrices (seen as vectors).
This is equal to self.adjoint() * rhs
.
For real vectors, this is identical to self.dot(&rhs)
.
Note that this is not the matrix multiplication as in, e.g., numpy. For matrix
multiplication, use one of: .gemm
, .mul_to
, .mul
, the *
operator.
§Example
let vec1 = Vector2::new(Complex::new(1.0, 2.0), Complex::new(3.0, 4.0));
let vec2 = Vector2::new(Complex::new(0.4, 0.3), Complex::new(0.2, 0.1));
assert_eq!(vec1.dotc(&vec2), Complex::new(2.0, -1.0));
// Note that for complex vectors, we generally have:
// vec1.dotc(&vec2) != vec2.dot(&vec2)
assert_ne!(vec1.dotc(&vec2), vec1.dot(&vec2));
sourcepub fn tr_dot<R2, C2, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
pub fn tr_dot<R2, C2, SB>(&self, rhs: &Matrix<T, R2, C2, SB>) -> T
The dot product between the transpose of self
and rhs
.
§Example
let vec1 = Vector3::new(1.0, 2.0, 3.0);
let vec2 = RowVector3::new(0.1, 0.2, 0.3);
assert_eq!(vec1.tr_dot(&vec2), 1.4);
let mat1 = Matrix2x3::new(1.0, 2.0, 3.0,
4.0, 5.0, 6.0);
let mat2 = Matrix3x2::new(0.1, 0.4,
0.2, 0.5,
0.3, 0.6);
assert_eq!(mat1.tr_dot(&mat2), 9.1);
source§impl<T, D, S> Matrix<T, D, Const<1>, S>
impl<T, D, S> Matrix<T, D, Const<1>, S>
§BLAS functions
sourcepub fn axcpy<D2, SB>(
&mut self,
a: T,
x: &Matrix<T, D2, Const<1>, SB>,
c: T,
b: T,
)
pub fn axcpy<D2, SB>( &mut self, a: T, x: &Matrix<T, D2, Const<1>, SB>, c: T, b: T, )
Computes self = a * x * c + b * self
.
If b
is zero, self
is never read from.
§Example
let mut vec1 = Vector3::new(1.0, 2.0, 3.0);
let vec2 = Vector3::new(0.1, 0.2, 0.3);
vec1.axcpy(5.0, &vec2, 2.0, 5.0);
assert_eq!(vec1, Vector3::new(6.0, 12.0, 18.0));
sourcepub fn axpy<D2, SB>(&mut self, a: T, x: &Matrix<T, D2, Const<1>, SB>, b: T)
pub fn axpy<D2, SB>(&mut self, a: T, x: &Matrix<T, D2, Const<1>, SB>, b: T)
Computes self = a * x + b * self
.
If b
is zero, self
is never read from.
§Example
let mut vec1 = Vector3::new(1.0, 2.0, 3.0);
let vec2 = Vector3::new(0.1, 0.2, 0.3);
vec1.axpy(10.0, &vec2, 5.0);
assert_eq!(vec1, Vector3::new(6.0, 12.0, 18.0));
sourcepub fn gemv<R2, C2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
D3: Dim,
T: One,
SB: Storage<T, R2, C2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, R2> + AreMultipliable<R2, C2, D3, Const<1>>,
pub fn gemv<R2, C2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
D3: Dim,
T: One,
SB: Storage<T, R2, C2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, R2> + AreMultipliable<R2, C2, D3, Const<1>>,
Computes self = alpha * a * x + beta * self
, where a
is a matrix, x
a vector, and
alpha, beta
two scalars.
If beta
is zero, self
is never read.
§Example
let mut vec1 = Vector2::new(1.0, 2.0);
let vec2 = Vector2::new(0.1, 0.2);
let mat = Matrix2::new(1.0, 2.0,
3.0, 4.0);
vec1.gemv(10.0, &mat, &vec2, 5.0);
assert_eq!(vec1, Vector2::new(10.0, 21.0));
sourcepub fn sygemv<D2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, D2, D2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
D2: Dim,
D3: Dim,
T: One,
SB: Storage<T, D2, D2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, D2> + AreMultipliable<D2, D2, D3, Const<1>>,
pub fn sygemv<D2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, D2, D2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
D2: Dim,
D3: Dim,
T: One,
SB: Storage<T, D2, D2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, D2> + AreMultipliable<D2, D2, D3, Const<1>>,
Computes self = alpha * a * x + beta * self
, where a
is a symmetric matrix, x
a
vector, and alpha, beta
two scalars.
For hermitian matrices, use .hegemv
instead.
If beta
is zero, self
is never read. If self
is read, only its lower-triangular part
(including the diagonal) is actually read.
§Examples
let mat = Matrix2::new(1.0, 2.0,
2.0, 4.0);
let mut vec1 = Vector2::new(1.0, 2.0);
let vec2 = Vector2::new(0.1, 0.2);
vec1.sygemv(10.0, &mat, &vec2, 5.0);
assert_eq!(vec1, Vector2::new(10.0, 20.0));
// The matrix upper-triangular elements can be garbage because it is never
// read by this method. Therefore, it is not necessary for the caller to
// fill the matrix struct upper-triangle.
let mat = Matrix2::new(1.0, 9999999.9999999,
2.0, 4.0);
let mut vec1 = Vector2::new(1.0, 2.0);
vec1.sygemv(10.0, &mat, &vec2, 5.0);
assert_eq!(vec1, Vector2::new(10.0, 20.0));
sourcepub fn hegemv<D2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, D2, D2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
D2: Dim,
D3: Dim,
T: SimdComplexField,
SB: Storage<T, D2, D2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, D2> + AreMultipliable<D2, D2, D3, Const<1>>,
pub fn hegemv<D2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, D2, D2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
D2: Dim,
D3: Dim,
T: SimdComplexField,
SB: Storage<T, D2, D2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, D2> + AreMultipliable<D2, D2, D3, Const<1>>,
Computes self = alpha * a * x + beta * self
, where a
is an hermitian matrix, x
a
vector, and alpha, beta
two scalars.
If beta
is zero, self
is never read. If self
is read, only its lower-triangular part
(including the diagonal) is actually read.
§Examples
let mat = Matrix2::new(Complex::new(1.0, 0.0), Complex::new(2.0, -0.1),
Complex::new(2.0, 1.0), Complex::new(4.0, 0.0));
let mut vec1 = Vector2::new(Complex::new(1.0, 2.0), Complex::new(3.0, 4.0));
let vec2 = Vector2::new(Complex::new(0.1, 0.2), Complex::new(0.3, 0.4));
vec1.sygemv(Complex::new(10.0, 20.0), &mat, &vec2, Complex::new(5.0, 15.0));
assert_eq!(vec1, Vector2::new(Complex::new(-48.0, 44.0), Complex::new(-75.0, 110.0)));
// The matrix upper-triangular elements can be garbage because it is never
// read by this method. Therefore, it is not necessary for the caller to
// fill the matrix struct upper-triangle.
let mat = Matrix2::new(Complex::new(1.0, 0.0), Complex::new(99999999.9, 999999999.9),
Complex::new(2.0, 1.0), Complex::new(4.0, 0.0));
let mut vec1 = Vector2::new(Complex::new(1.0, 2.0), Complex::new(3.0, 4.0));
let vec2 = Vector2::new(Complex::new(0.1, 0.2), Complex::new(0.3, 0.4));
vec1.sygemv(Complex::new(10.0, 20.0), &mat, &vec2, Complex::new(5.0, 15.0));
assert_eq!(vec1, Vector2::new(Complex::new(-48.0, 44.0), Complex::new(-75.0, 110.0)));
sourcepub fn gemv_tr<R2, C2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
D3: Dim,
T: One,
SB: Storage<T, R2, C2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, C2> + AreMultipliable<C2, R2, D3, Const<1>>,
pub fn gemv_tr<R2, C2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
D3: Dim,
T: One,
SB: Storage<T, R2, C2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, C2> + AreMultipliable<C2, R2, D3, Const<1>>,
Computes self = alpha * a.transpose() * x + beta * self
, where a
is a matrix, x
a vector, and
alpha, beta
two scalars.
If beta
is zero, self
is never read.
§Example
let mat = Matrix2::new(1.0, 3.0,
2.0, 4.0);
let mut vec1 = Vector2::new(1.0, 2.0);
let vec2 = Vector2::new(0.1, 0.2);
let expected = mat.transpose() * vec2 * 10.0 + vec1 * 5.0;
vec1.gemv_tr(10.0, &mat, &vec2, 5.0);
assert_eq!(vec1, expected);
sourcepub fn gemv_ad<R2, C2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
D3: Dim,
T: SimdComplexField,
SB: Storage<T, R2, C2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, C2> + AreMultipliable<C2, R2, D3, Const<1>>,
pub fn gemv_ad<R2, C2, D3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
x: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
D3: Dim,
T: SimdComplexField,
SB: Storage<T, R2, C2>,
SC: Storage<T, D3>,
ShapeConstraint: DimEq<D, C2> + AreMultipliable<C2, R2, D3, Const<1>>,
Computes self = alpha * a.adjoint() * x + beta * self
, where a
is a matrix, x
a vector, and
alpha, beta
two scalars.
For real matrices, this is the same as .gemv_tr
.
If beta
is zero, self
is never read.
§Example
let mat = Matrix2::new(Complex::new(1.0, 2.0), Complex::new(3.0, 4.0),
Complex::new(5.0, 6.0), Complex::new(7.0, 8.0));
let mut vec1 = Vector2::new(Complex::new(1.0, 2.0), Complex::new(3.0, 4.0));
let vec2 = Vector2::new(Complex::new(0.1, 0.2), Complex::new(0.3, 0.4));
let expected = mat.adjoint() * vec2 * Complex::new(10.0, 20.0) + vec1 * Complex::new(5.0, 15.0);
vec1.gemv_ad(Complex::new(10.0, 20.0), &mat, &vec2, Complex::new(5.0, 15.0));
assert_eq!(vec1, expected);
source§impl<T, R1, C1, S> Matrix<T, R1, C1, S>where
R1: Dim,
C1: Dim,
S: StorageMut<T, R1, C1>,
T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
impl<T, R1, C1, S> Matrix<T, R1, C1, S>where
R1: Dim,
C1: Dim,
S: StorageMut<T, R1, C1>,
T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
sourcepub fn ger<D2, D3, SB, SC>(
&mut self,
alpha: T,
x: &Matrix<T, D2, Const<1>, SB>,
y: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)
pub fn ger<D2, D3, SB, SC>( &mut self, alpha: T, x: &Matrix<T, D2, Const<1>, SB>, y: &Matrix<T, D3, Const<1>, SC>, beta: T, )
Computes self = alpha * x * y.transpose() + beta * self
.
If beta
is zero, self
is never read.
§Example
let mut mat = Matrix2x3::repeat(4.0);
let vec1 = Vector2::new(1.0, 2.0);
let vec2 = Vector3::new(0.1, 0.2, 0.3);
let expected = vec1 * vec2.transpose() * 10.0 + mat * 5.0;
mat.ger(10.0, &vec1, &vec2, 5.0);
assert_eq!(mat, expected);
sourcepub fn gerc<D2, D3, SB, SC>(
&mut self,
alpha: T,
x: &Matrix<T, D2, Const<1>, SB>,
y: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)
pub fn gerc<D2, D3, SB, SC>( &mut self, alpha: T, x: &Matrix<T, D2, Const<1>, SB>, y: &Matrix<T, D3, Const<1>, SC>, beta: T, )
Computes self = alpha * x * y.adjoint() + beta * self
.
If beta
is zero, self
is never read.
§Example
let mut mat = Matrix2x3::repeat(Complex::new(4.0, 5.0));
let vec1 = Vector2::new(Complex::new(1.0, 2.0), Complex::new(3.0, 4.0));
let vec2 = Vector3::new(Complex::new(0.6, 0.5), Complex::new(0.4, 0.5), Complex::new(0.2, 0.1));
let expected = vec1 * vec2.adjoint() * Complex::new(10.0, 20.0) + mat * Complex::new(5.0, 15.0);
mat.gerc(Complex::new(10.0, 20.0), &vec1, &vec2, Complex::new(5.0, 15.0));
assert_eq!(mat, expected);
sourcepub fn gemm<R2, C2, R3, C3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
T: One,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C3> + AreMultipliable<R2, C2, R3, C3>,
pub fn gemm<R2, C2, R3, C3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
T: One,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C3> + AreMultipliable<R2, C2, R3, C3>,
Computes self = alpha * a * b + beta * self
, where a, b, self
are matrices.
alpha
and beta
are scalar.
If beta
is zero, self
is never read.
§Example
let mut mat1 = Matrix2x4::identity();
let mat2 = Matrix2x3::new(1.0, 2.0, 3.0,
4.0, 5.0, 6.0);
let mat3 = Matrix3x4::new(0.1, 0.2, 0.3, 0.4,
0.5, 0.6, 0.7, 0.8,
0.9, 1.0, 1.1, 1.2);
let expected = mat2 * mat3 * 10.0 + mat1 * 5.0;
mat1.gemm(10.0, &mat2, &mat3, 5.0);
assert_relative_eq!(mat1, expected);
sourcepub fn gemm_tr<R2, C2, R3, C3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
T: One,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, C2> + SameNumberOfColumns<C1, C3> + AreMultipliable<C2, R2, R3, C3>,
pub fn gemm_tr<R2, C2, R3, C3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
T: One,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, C2> + SameNumberOfColumns<C1, C3> + AreMultipliable<C2, R2, R3, C3>,
Computes self = alpha * a.transpose() * b + beta * self
, where a, b, self
are matrices.
alpha
and beta
are scalar.
If beta
is zero, self
is never read.
§Example
let mut mat1 = Matrix2x4::identity();
let mat2 = Matrix3x2::new(1.0, 4.0,
2.0, 5.0,
3.0, 6.0);
let mat3 = Matrix3x4::new(0.1, 0.2, 0.3, 0.4,
0.5, 0.6, 0.7, 0.8,
0.9, 1.0, 1.1, 1.2);
let expected = mat2.transpose() * mat3 * 10.0 + mat1 * 5.0;
mat1.gemm_tr(10.0, &mat2, &mat3, 5.0);
assert_eq!(mat1, expected);
sourcepub fn gemm_ad<R2, C2, R3, C3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
T: SimdComplexField,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, C2> + SameNumberOfColumns<C1, C3> + AreMultipliable<C2, R2, R3, C3>,
pub fn gemm_ad<R2, C2, R3, C3, SB, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
T: SimdComplexField,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, C2> + SameNumberOfColumns<C1, C3> + AreMultipliable<C2, R2, R3, C3>,
Computes self = alpha * a.adjoint() * b + beta * self
, where a, b, self
are matrices.
alpha
and beta
are scalar.
If beta
is zero, self
is never read.
§Example
let mut mat1 = Matrix2x4::identity();
let mat2 = Matrix3x2::new(Complex::new(1.0, 4.0), Complex::new(7.0, 8.0),
Complex::new(2.0, 5.0), Complex::new(9.0, 10.0),
Complex::new(3.0, 6.0), Complex::new(11.0, 12.0));
let mat3 = Matrix3x4::new(Complex::new(0.1, 1.3), Complex::new(0.2, 1.4), Complex::new(0.3, 1.5), Complex::new(0.4, 1.6),
Complex::new(0.5, 1.7), Complex::new(0.6, 1.8), Complex::new(0.7, 1.9), Complex::new(0.8, 2.0),
Complex::new(0.9, 2.1), Complex::new(1.0, 2.2), Complex::new(1.1, 2.3), Complex::new(1.2, 2.4));
let expected = mat2.adjoint() * mat3 * Complex::new(10.0, 20.0) + mat1 * Complex::new(5.0, 15.0);
mat1.gemm_ad(Complex::new(10.0, 20.0), &mat2, &mat3, Complex::new(5.0, 15.0));
assert_eq!(mat1, expected);
source§impl<T, R1, C1, S> Matrix<T, R1, C1, S>where
R1: Dim,
C1: Dim,
S: StorageMut<T, R1, C1>,
T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
impl<T, R1, C1, S> Matrix<T, R1, C1, S>where
R1: Dim,
C1: Dim,
S: StorageMut<T, R1, C1>,
T: Scalar + Zero + ClosedAddAssign + ClosedMulAssign,
sourcepub fn ger_symm<D2, D3, SB, SC>(
&mut self,
alpha: T,
x: &Matrix<T, D2, Const<1>, SB>,
y: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)
👎Deprecated: This is renamed syger
to match the original BLAS terminology.
pub fn ger_symm<D2, D3, SB, SC>( &mut self, alpha: T, x: &Matrix<T, D2, Const<1>, SB>, y: &Matrix<T, D3, Const<1>, SC>, beta: T, )
syger
to match the original BLAS terminology.Computes self = alpha * x * y.transpose() + beta * self
, where self
is a symmetric
matrix.
If beta
is zero, self
is never read. The result is symmetric. Only the lower-triangular
(including the diagonal) part of self
is read/written.
§Example
let mut mat = Matrix2::identity();
let vec1 = Vector2::new(1.0, 2.0);
let vec2 = Vector2::new(0.1, 0.2);
let expected = vec1 * vec2.transpose() * 10.0 + mat * 5.0;
mat.m12 = 99999.99999; // This component is on the upper-triangular part and will not be read/written.
mat.ger_symm(10.0, &vec1, &vec2, 5.0);
assert_eq!(mat.lower_triangle(), expected.lower_triangle());
assert_eq!(mat.m12, 99999.99999); // This was untouched.
sourcepub fn syger<D2, D3, SB, SC>(
&mut self,
alpha: T,
x: &Matrix<T, D2, Const<1>, SB>,
y: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)
pub fn syger<D2, D3, SB, SC>( &mut self, alpha: T, x: &Matrix<T, D2, Const<1>, SB>, y: &Matrix<T, D3, Const<1>, SC>, beta: T, )
Computes self = alpha * x * y.transpose() + beta * self
, where self
is a symmetric
matrix.
For hermitian complex matrices, use .hegerc
instead.
If beta
is zero, self
is never read. The result is symmetric. Only the lower-triangular
(including the diagonal) part of self
is read/written.
§Example
let mut mat = Matrix2::identity();
let vec1 = Vector2::new(1.0, 2.0);
let vec2 = Vector2::new(0.1, 0.2);
let expected = vec1 * vec2.transpose() * 10.0 + mat * 5.0;
mat.m12 = 99999.99999; // This component is on the upper-triangular part and will not be read/written.
mat.syger(10.0, &vec1, &vec2, 5.0);
assert_eq!(mat.lower_triangle(), expected.lower_triangle());
assert_eq!(mat.m12, 99999.99999); // This was untouched.
sourcepub fn hegerc<D2, D3, SB, SC>(
&mut self,
alpha: T,
x: &Matrix<T, D2, Const<1>, SB>,
y: &Matrix<T, D3, Const<1>, SC>,
beta: T,
)
pub fn hegerc<D2, D3, SB, SC>( &mut self, alpha: T, x: &Matrix<T, D2, Const<1>, SB>, y: &Matrix<T, D3, Const<1>, SC>, beta: T, )
Computes self = alpha * x * y.adjoint() + beta * self
, where self
is an hermitian
matrix.
If beta
is zero, self
is never read. The result is symmetric. Only the lower-triangular
(including the diagonal) part of self
is read/written.
§Example
let mut mat = Matrix2::identity();
let vec1 = Vector2::new(Complex::new(1.0, 3.0), Complex::new(2.0, 4.0));
let vec2 = Vector2::new(Complex::new(0.2, 0.4), Complex::new(0.1, 0.3));
let expected = vec1 * vec2.adjoint() * Complex::new(10.0, 20.0) + mat * Complex::new(5.0, 15.0);
mat.m12 = Complex::new(99999.99999, 88888.88888); // This component is on the upper-triangular part and will not be read/written.
mat.hegerc(Complex::new(10.0, 20.0), &vec1, &vec2, Complex::new(5.0, 15.0));
assert_eq!(mat.lower_triangle(), expected.lower_triangle());
assert_eq!(mat.m12, Complex::new(99999.99999, 88888.88888)); // This was untouched.
source§impl<T, D1, S> Matrix<T, D1, D1, S>where
D1: Dim,
S: StorageMut<T, D1, D1>,
T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
impl<T, D1, S> Matrix<T, D1, D1, S>where
D1: Dim,
S: StorageMut<T, D1, D1>,
T: Scalar + Zero + One + ClosedAddAssign + ClosedMulAssign,
sourcepub fn quadform_tr_with_workspace<D2, S2, R3, C3, S3, D4, S4>(
&mut self,
work: &mut Matrix<T, D2, Const<1>, S2>,
alpha: T,
lhs: &Matrix<T, R3, C3, S3>,
mid: &Matrix<T, D4, D4, S4>,
beta: T,
)
pub fn quadform_tr_with_workspace<D2, S2, R3, C3, S3, D4, S4>( &mut self, work: &mut Matrix<T, D2, Const<1>, S2>, alpha: T, lhs: &Matrix<T, R3, C3, S3>, mid: &Matrix<T, D4, D4, S4>, beta: T, )
Computes the quadratic form self = alpha * lhs * mid * lhs.transpose() + beta * self
.
This uses the provided workspace work
to avoid allocations for intermediate results.
§Example
// Note that all those would also work with statically-sized matrices.
// We use DMatrix/DVector since that's the only case where pre-allocating the
// workspace is actually useful (assuming the same workspace is re-used for
// several computations) because it avoids repeated dynamic allocations.
let mut mat = DMatrix::identity(2, 2);
let lhs = DMatrix::from_row_slice(2, 3, &[1.0, 2.0, 3.0,
4.0, 5.0, 6.0]);
let mid = DMatrix::from_row_slice(3, 3, &[0.1, 0.2, 0.3,
0.5, 0.6, 0.7,
0.9, 1.0, 1.1]);
// The random shows that values on the workspace do not
// matter as they will be overwritten.
let mut workspace = DVector::new_random(2);
let expected = &lhs * &mid * lhs.transpose() * 10.0 + &mat * 5.0;
mat.quadform_tr_with_workspace(&mut workspace, 10.0, &lhs, &mid, 5.0);
assert_relative_eq!(mat, expected);
sourcepub fn quadform_tr<R3, C3, S3, D4, S4>(
&mut self,
alpha: T,
lhs: &Matrix<T, R3, C3, S3>,
mid: &Matrix<T, D4, D4, S4>,
beta: T,
)
pub fn quadform_tr<R3, C3, S3, D4, S4>( &mut self, alpha: T, lhs: &Matrix<T, R3, C3, S3>, mid: &Matrix<T, D4, D4, S4>, beta: T, )
Computes the quadratic form self = alpha * lhs * mid * lhs.transpose() + beta * self
.
This allocates a workspace vector of dimension D1 for intermediate results.
If D1
is a type-level integer, then the allocation is performed on the stack.
Use .quadform_tr_with_workspace(...)
instead to avoid allocations.
§Example
let mut mat = Matrix2::identity();
let lhs = Matrix2x3::new(1.0, 2.0, 3.0,
4.0, 5.0, 6.0);
let mid = Matrix3::new(0.1, 0.2, 0.3,
0.5, 0.6, 0.7,
0.9, 1.0, 1.1);
let expected = lhs * mid * lhs.transpose() * 10.0 + mat * 5.0;
mat.quadform_tr(10.0, &lhs, &mid, 5.0);
assert_relative_eq!(mat, expected);
sourcepub fn quadform_with_workspace<D2, S2, D3, S3, R4, C4, S4>(
&mut self,
work: &mut Matrix<T, D2, Const<1>, S2>,
alpha: T,
mid: &Matrix<T, D3, D3, S3>,
rhs: &Matrix<T, R4, C4, S4>,
beta: T,
)where
D2: Dim,
D3: Dim,
R4: Dim,
C4: Dim,
S2: StorageMut<T, D2>,
S3: Storage<T, D3, D3>,
S4: Storage<T, R4, C4>,
ShapeConstraint: DimEq<D3, R4> + DimEq<D1, C4> + DimEq<D2, D3> + AreMultipliable<C4, R4, D2, Const<1>>,
pub fn quadform_with_workspace<D2, S2, D3, S3, R4, C4, S4>(
&mut self,
work: &mut Matrix<T, D2, Const<1>, S2>,
alpha: T,
mid: &Matrix<T, D3, D3, S3>,
rhs: &Matrix<T, R4, C4, S4>,
beta: T,
)where
D2: Dim,
D3: Dim,
R4: Dim,
C4: Dim,
S2: StorageMut<T, D2>,
S3: Storage<T, D3, D3>,
S4: Storage<T, R4, C4>,
ShapeConstraint: DimEq<D3, R4> + DimEq<D1, C4> + DimEq<D2, D3> + AreMultipliable<C4, R4, D2, Const<1>>,
Computes the quadratic form self = alpha * rhs.transpose() * mid * rhs + beta * self
.
This uses the provided workspace work
to avoid allocations for intermediate results.
§Example
// Note that all those would also work with statically-sized matrices.
// We use DMatrix/DVector since that's the only case where pre-allocating the
// workspace is actually useful (assuming the same workspace is re-used for
// several computations) because it avoids repeated dynamic allocations.
let mut mat = DMatrix::identity(2, 2);
let rhs = DMatrix::from_row_slice(3, 2, &[1.0, 2.0,
3.0, 4.0,
5.0, 6.0]);
let mid = DMatrix::from_row_slice(3, 3, &[0.1, 0.2, 0.3,
0.5, 0.6, 0.7,
0.9, 1.0, 1.1]);
// The random shows that values on the workspace do not
// matter as they will be overwritten.
let mut workspace = DVector::new_random(3);
let expected = rhs.transpose() * &mid * &rhs * 10.0 + &mat * 5.0;
mat.quadform_with_workspace(&mut workspace, 10.0, &mid, &rhs, 5.0);
assert_relative_eq!(mat, expected);
sourcepub fn quadform<D2, S2, R3, C3, S3>(
&mut self,
alpha: T,
mid: &Matrix<T, D2, D2, S2>,
rhs: &Matrix<T, R3, C3, S3>,
beta: T,
)where
D2: Dim,
R3: Dim,
C3: Dim,
S2: Storage<T, D2, D2>,
S3: Storage<T, R3, C3>,
ShapeConstraint: DimEq<D2, R3> + DimEq<D1, C3> + AreMultipliable<C3, R3, D2, Const<1>>,
DefaultAllocator: Allocator<D2>,
pub fn quadform<D2, S2, R3, C3, S3>(
&mut self,
alpha: T,
mid: &Matrix<T, D2, D2, S2>,
rhs: &Matrix<T, R3, C3, S3>,
beta: T,
)where
D2: Dim,
R3: Dim,
C3: Dim,
S2: Storage<T, D2, D2>,
S3: Storage<T, R3, C3>,
ShapeConstraint: DimEq<D2, R3> + DimEq<D1, C3> + AreMultipliable<C3, R3, D2, Const<1>>,
DefaultAllocator: Allocator<D2>,
Computes the quadratic form self = alpha * rhs.transpose() * mid * rhs + beta * self
.
This allocates a workspace vector of dimension D2 for intermediate results.
If D2
is a type-level integer, then the allocation is performed on the stack.
Use .quadform_with_workspace(...)
instead to avoid allocations.
§Example
let mut mat = Matrix2::identity();
let rhs = Matrix3x2::new(1.0, 2.0,
3.0, 4.0,
5.0, 6.0);
let mid = Matrix3::new(0.1, 0.2, 0.3,
0.5, 0.6, 0.7,
0.9, 1.0, 1.1);
let expected = rhs.transpose() * mid * rhs * 10.0 + mat * 5.0;
mat.quadform(10.0, &mid, &rhs, 5.0);
assert_relative_eq!(mat, expected);
source§impl<T, R1, C1, SA> Matrix<T, R1, C1, SA>
impl<T, R1, C1, SA> Matrix<T, R1, C1, SA>
sourcepub fn add_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> + SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3>,
pub fn add_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> + SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3>,
Equivalent to self + rhs
but stores the result into out
to avoid allocations.
source§impl<T, R1, C1, SA> Matrix<T, R1, C1, SA>
impl<T, R1, C1, SA> Matrix<T, R1, C1, SA>
sourcepub fn sub_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> + SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3>,
pub fn sub_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> + SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3>,
Equivalent to self + rhs
but stores the result into out
to avoid allocations.
source§impl<T, R1, C1, SA> Matrix<T, R1, C1, SA>
impl<T, R1, C1, SA> Matrix<T, R1, C1, SA>
§Special multiplications.
sourcepub fn tr_mul<R2, C2, SB>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, C1, C2, <DefaultAllocator as Allocator<C1, C2>>::Buffer<T>>where
R2: Dim,
C2: Dim,
SB: Storage<T, R2, C2>,
DefaultAllocator: Allocator<C1, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2>,
pub fn tr_mul<R2, C2, SB>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, C1, C2, <DefaultAllocator as Allocator<C1, C2>>::Buffer<T>>where
R2: Dim,
C2: Dim,
SB: Storage<T, R2, C2>,
DefaultAllocator: Allocator<C1, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2>,
Equivalent to self.transpose() * rhs
.
sourcepub fn ad_mul<R2, C2, SB>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, C1, C2, <DefaultAllocator as Allocator<C1, C2>>::Buffer<T>>where
R2: Dim,
C2: Dim,
T: SimdComplexField,
SB: Storage<T, R2, C2>,
DefaultAllocator: Allocator<C1, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2>,
pub fn ad_mul<R2, C2, SB>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, C1, C2, <DefaultAllocator as Allocator<C1, C2>>::Buffer<T>>where
R2: Dim,
C2: Dim,
T: SimdComplexField,
SB: Storage<T, R2, C2>,
DefaultAllocator: Allocator<C1, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2>,
Equivalent to self.adjoint() * rhs
.
sourcepub fn tr_mul_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + DimEq<C1, R3> + DimEq<C2, C3>,
pub fn tr_mul_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + DimEq<C1, R3> + DimEq<C2, C3>,
Equivalent to self.transpose() * rhs
but stores the result into out
to avoid
allocations.
sourcepub fn ad_mul_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
T: SimdComplexField,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + DimEq<C1, R3> + DimEq<C2, C3>,
pub fn ad_mul_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
T: SimdComplexField,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + DimEq<C1, R3> + DimEq<C2, C3>,
Equivalent to self.adjoint() * rhs
but stores the result into out
to avoid
allocations.
sourcepub fn mul_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R3, R1> + SameNumberOfColumns<C3, C2> + AreMultipliable<R1, C1, R2, C2>,
pub fn mul_to<R2, C2, SB, R3, C3, SC>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
out: &mut Matrix<T, R3, C3, SC>,
)where
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SB: Storage<T, R2, C2>,
SC: StorageMut<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R3, R1> + SameNumberOfColumns<C3, C2> + AreMultipliable<R1, C1, R2, C2>,
Equivalent to self * rhs
but stores the result into out
to avoid allocations.
sourcepub fn kronecker<R2, C2, SB>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, <R1 as DimMul<R2>>::Output, <C1 as DimMul<C2>>::Output, <DefaultAllocator as Allocator<<R1 as DimMul<R2>>::Output, <C1 as DimMul<C2>>::Output>>::Buffer<T>>
pub fn kronecker<R2, C2, SB>( &self, rhs: &Matrix<T, R2, C2, SB>, ) -> Matrix<T, <R1 as DimMul<R2>>::Output, <C1 as DimMul<C2>>::Output, <DefaultAllocator as Allocator<<R1 as DimMul<R2>>::Output, <C1 as DimMul<C2>>::Output>>::Buffer<T>>
The kronecker product of two matrices (aka. tensor product of the corresponding linear maps).
source§impl<T, D> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
impl<T, D> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
§Translation and scaling in any dimension
sourcepub fn new_scaling(
scaling: T,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
pub fn new_scaling( scaling: T, ) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
Creates a new homogeneous matrix that applies the same scaling factor on each dimension.
sourcepub fn new_nonuniform_scaling<SB>(
scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
pub fn new_nonuniform_scaling<SB>( scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>, ) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
Creates a new homogeneous matrix that applies a distinct scaling factor for each dimension.
sourcepub fn new_translation<SB>(
translation: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
pub fn new_translation<SB>( translation: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>, ) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
Creates a new homogeneous matrix that applies a pure translation.
source§impl<T> Matrix<T, Const<3>, Const<3>, ArrayStorage<T, 3, 3>>where
T: RealField,
impl<T> Matrix<T, Const<3>, Const<3>, ArrayStorage<T, 3, 3>>where
T: RealField,
§2D transformations as a Matrix3
sourcepub fn new_rotation(
angle: T,
) -> Matrix<T, Const<3>, Const<3>, ArrayStorage<T, 3, 3>>
pub fn new_rotation( angle: T, ) -> Matrix<T, Const<3>, Const<3>, ArrayStorage<T, 3, 3>>
Builds a 2 dimensional homogeneous rotation matrix from an angle in radian.
sourcepub fn new_nonuniform_scaling_wrt_point(
scaling: &Matrix<T, Const<2>, Const<1>, ArrayStorage<T, 2, 1>>,
pt: &OPoint<T, Const<2>>,
) -> Matrix<T, Const<3>, Const<3>, ArrayStorage<T, 3, 3>>
pub fn new_nonuniform_scaling_wrt_point( scaling: &Matrix<T, Const<2>, Const<1>, ArrayStorage<T, 2, 1>>, pt: &OPoint<T, Const<2>>, ) -> Matrix<T, Const<3>, Const<3>, ArrayStorage<T, 3, 3>>
Creates a new homogeneous matrix that applies a scaling factor for each dimension with respect to point.
Can be used to implement zoom_to
functionality.
source§impl<T> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>where
T: RealField,
impl<T> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>where
T: RealField,
§3D transformations as a Matrix4
sourcepub fn new_rotation(
axisangle: Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn new_rotation( axisangle: Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Builds a 3D homogeneous rotation matrix from an axis and an angle (multiplied together).
Returns the identity matrix if the given argument is zero.
sourcepub fn new_rotation_wrt_point(
axisangle: Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>,
pt: OPoint<T, Const<3>>,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn new_rotation_wrt_point( axisangle: Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>, pt: OPoint<T, Const<3>>, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Builds a 3D homogeneous rotation matrix from an axis and an angle (multiplied together).
Returns the identity matrix if the given argument is zero.
sourcepub fn new_nonuniform_scaling_wrt_point(
scaling: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>,
pt: &OPoint<T, Const<3>>,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn new_nonuniform_scaling_wrt_point( scaling: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>, pt: &OPoint<T, Const<3>>, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Creates a new homogeneous matrix that applies a scaling factor for each dimension with respect to point.
Can be used to implement zoom_to
functionality.
sourcepub fn from_scaled_axis(
axisangle: Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn from_scaled_axis( axisangle: Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Builds a 3D homogeneous rotation matrix from an axis and an angle (multiplied together).
Returns the identity matrix if the given argument is zero.
This is identical to Self::new_rotation
.
sourcepub fn from_euler_angles(
roll: T,
pitch: T,
yaw: T,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn from_euler_angles( roll: T, pitch: T, yaw: T, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Creates a new rotation from Euler angles.
The primitive rotations are applied in order: 1 roll − 2 pitch − 3 yaw.
sourcepub fn from_axis_angle(
axis: &Unit<Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>>,
angle: T,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn from_axis_angle( axis: &Unit<Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>>, angle: T, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Builds a 3D homogeneous rotation matrix from an axis and a rotation angle.
sourcepub fn new_orthographic(
left: T,
right: T,
bottom: T,
top: T,
znear: T,
zfar: T,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn new_orthographic( left: T, right: T, bottom: T, top: T, znear: T, zfar: T, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Creates a new homogeneous matrix for an orthographic projection.
sourcepub fn new_perspective(
aspect: T,
fovy: T,
znear: T,
zfar: T,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn new_perspective( aspect: T, fovy: T, znear: T, zfar: T, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Creates a new homogeneous matrix for a perspective projection.
sourcepub fn face_towards(
eye: &OPoint<T, Const<3>>,
target: &OPoint<T, Const<3>>,
up: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn face_towards( eye: &OPoint<T, Const<3>>, target: &OPoint<T, Const<3>>, up: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Creates an isometry that corresponds to the local frame of an observer standing at the
point eye
and looking toward target
.
It maps the view direction target - eye
to the positive z
axis and the origin to the
eye
.
sourcepub fn new_observer_frame(
eye: &OPoint<T, Const<3>>,
target: &OPoint<T, Const<3>>,
up: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
👎Deprecated: renamed to face_towards
pub fn new_observer_frame( eye: &OPoint<T, Const<3>>, target: &OPoint<T, Const<3>>, up: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
face_towards
Deprecated: Use Matrix4::face_towards
instead.
sourcepub fn look_at_rh(
eye: &OPoint<T, Const<3>>,
target: &OPoint<T, Const<3>>,
up: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn look_at_rh( eye: &OPoint<T, Const<3>>, target: &OPoint<T, Const<3>>, up: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Builds a right-handed look-at view matrix.
sourcepub fn look_at_lh(
eye: &OPoint<T, Const<3>>,
target: &OPoint<T, Const<3>>,
up: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>,
) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
pub fn look_at_lh( eye: &OPoint<T, Const<3>>, target: &OPoint<T, Const<3>>, up: &Matrix<T, Const<3>, Const<1>, ArrayStorage<T, 3, 1>>, ) -> Matrix<T, Const<4>, Const<4>, ArrayStorage<T, 4, 4>>
Builds a left-handed look-at view matrix.
source§impl<T, D, S> Matrix<T, D, D, S>
impl<T, D, S> Matrix<T, D, D, S>
§Append/prepend translation and scaling
sourcepub fn append_scaling(
&self,
scaling: T,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
pub fn append_scaling( &self, scaling: T, ) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
Computes the transformation equal to self
followed by an uniform scaling factor.
sourcepub fn prepend_scaling(
&self,
scaling: T,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
pub fn prepend_scaling( &self, scaling: T, ) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
Computes the transformation equal to an uniform scaling factor followed by self
.
sourcepub fn append_nonuniform_scaling<SB>(
&self,
scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<D, D>,
pub fn append_nonuniform_scaling<SB>(
&self,
scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<D, D>,
Computes the transformation equal to self
followed by a non-uniform scaling factor.
sourcepub fn prepend_nonuniform_scaling<SB>(
&self,
scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<D, D>,
pub fn prepend_nonuniform_scaling<SB>(
&self,
scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<D, D>,
Computes the transformation equal to a non-uniform scaling factor followed by self
.
sourcepub fn append_translation<SB>(
&self,
shift: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<D, D>,
pub fn append_translation<SB>(
&self,
shift: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<D, D>,
Computes the transformation equal to self
followed by a translation.
sourcepub fn prepend_translation<SB>(
&self,
shift: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<D, D> + Allocator<<D as DimNameSub<Const<1>>>::Output>,
pub fn prepend_translation<SB>(
&self,
shift: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<D, D> + Allocator<<D as DimNameSub<Const<1>>>::Output>,
Computes the transformation equal to a translation followed by self
.
sourcepub fn append_scaling_mut(&mut self, scaling: T)
pub fn append_scaling_mut(&mut self, scaling: T)
Computes in-place the transformation equal to self
followed by an uniform scaling factor.
sourcepub fn prepend_scaling_mut(&mut self, scaling: T)
pub fn prepend_scaling_mut(&mut self, scaling: T)
Computes in-place the transformation equal to an uniform scaling factor followed by self
.
sourcepub fn append_nonuniform_scaling_mut<SB>(
&mut self,
scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
)where
S: StorageMut<T, D, D>,
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
pub fn append_nonuniform_scaling_mut<SB>(
&mut self,
scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
)where
S: StorageMut<T, D, D>,
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
Computes in-place the transformation equal to self
followed by a non-uniform scaling factor.
sourcepub fn prepend_nonuniform_scaling_mut<SB>(
&mut self,
scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
)where
S: StorageMut<T, D, D>,
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
pub fn prepend_nonuniform_scaling_mut<SB>(
&mut self,
scaling: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
)where
S: StorageMut<T, D, D>,
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
Computes in-place the transformation equal to a non-uniform scaling factor followed by self
.
sourcepub fn append_translation_mut<SB>(
&mut self,
shift: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
)where
S: StorageMut<T, D, D>,
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
pub fn append_translation_mut<SB>(
&mut self,
shift: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
)where
S: StorageMut<T, D, D>,
D: DimNameSub<Const<1>>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
Computes the transformation equal to self
followed by a translation.
sourcepub fn prepend_translation_mut<SB>(
&mut self,
shift: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
)where
D: DimNameSub<Const<1>>,
S: StorageMut<T, D, D>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<<D as DimNameSub<Const<1>>>::Output>,
pub fn prepend_translation_mut<SB>(
&mut self,
shift: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, SB>,
)where
D: DimNameSub<Const<1>>,
S: StorageMut<T, D, D>,
SB: Storage<T, <D as DimNameSub<Const<1>>>::Output>,
DefaultAllocator: Allocator<<D as DimNameSub<Const<1>>>::Output>,
Computes the transformation equal to a translation followed by self
.
source§impl<T, D, S> Matrix<T, D, D, S>where
T: RealField,
D: DimNameSub<Const<1>>,
S: Storage<T, D, D>,
DefaultAllocator: Allocator<D, D> + Allocator<<D as DimNameSub<Const<1>>>::Output> + Allocator<<D as DimNameSub<Const<1>>>::Output, <D as DimNameSub<Const<1>>>::Output>,
impl<T, D, S> Matrix<T, D, D, S>where
T: RealField,
D: DimNameSub<Const<1>>,
S: Storage<T, D, D>,
DefaultAllocator: Allocator<D, D> + Allocator<<D as DimNameSub<Const<1>>>::Output> + Allocator<<D as DimNameSub<Const<1>>>::Output, <D as DimNameSub<Const<1>>>::Output>,
§Transformation of vectors and points
sourcepub fn transform_vector(
&self,
v: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, <DefaultAllocator as Allocator<<D as DimNameSub<Const<1>>>::Output>>::Buffer<T>>,
) -> Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, <DefaultAllocator as Allocator<<D as DimNameSub<Const<1>>>::Output>>::Buffer<T>>
pub fn transform_vector( &self, v: &Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, <DefaultAllocator as Allocator<<D as DimNameSub<Const<1>>>::Output>>::Buffer<T>>, ) -> Matrix<T, <D as DimNameSub<Const<1>>>::Output, Const<1>, <DefaultAllocator as Allocator<<D as DimNameSub<Const<1>>>::Output>>::Buffer<T>>
Transforms the given vector, assuming the matrix self
uses homogeneous coordinates.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
source§impl<T, R1, C1, SA> Matrix<T, R1, C1, SA>
impl<T, R1, C1, SA> Matrix<T, R1, C1, SA>
§Componentwise operations
sourcepub fn component_mul<R2, C2, SB>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C1, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C1, C2>>::Representative>>::Buffer<T>>where
T: ClosedMulAssign,
R2: Dim,
C2: Dim,
SB: Storage<T, R2, C2>,
DefaultAllocator: SameShapeAllocator<R1, C1, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
pub fn component_mul<R2, C2, SB>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C1, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C1, C2>>::Representative>>::Buffer<T>>where
T: ClosedMulAssign,
R2: Dim,
C2: Dim,
SB: Storage<T, R2, C2>,
DefaultAllocator: SameShapeAllocator<R1, C1, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
Componentwise matrix or vector multiplication.
§Example
let a = Matrix2::new(0.0, 1.0, 2.0, 3.0);
let b = Matrix2::new(4.0, 5.0, 6.0, 7.0);
let expected = Matrix2::new(0.0, 5.0, 12.0, 21.0);
assert_eq!(a.component_mul(&b), expected);
sourcepub fn cmpy<R2, C2, SB, R3, C3, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
T: ClosedMulAssign<Output = T> + Zero<Output = T> + Mul + Add,
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> + SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3>,
pub fn cmpy<R2, C2, SB, R3, C3, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
T: ClosedMulAssign<Output = T> + Zero<Output = T> + Mul + Add,
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> + SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3>,
Computes componentwise self[i] = alpha * a[i] * b[i] + beta * self[i]
.
§Example
let mut m = Matrix2::new(0.0, 1.0, 2.0, 3.0);
let a = Matrix2::new(0.0, 1.0, 2.0, 3.0);
let b = Matrix2::new(4.0, 5.0, 6.0, 7.0);
let expected = (a.component_mul(&b) * 5.0) + m * 10.0;
m.cmpy(5.0, &a, &b, 10.0);
assert_eq!(m, expected);
sourcepub fn component_mul_assign<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)where
T: ClosedMulAssign,
R2: Dim,
C2: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
pub fn component_mul_assign<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)where
T: ClosedMulAssign,
R2: Dim,
C2: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
Inplace componentwise matrix or vector multiplication.
§Example
let mut a = Matrix2::new(0.0, 1.0, 2.0, 3.0);
let b = Matrix2::new(4.0, 5.0, 6.0, 7.0);
let expected = Matrix2::new(0.0, 5.0, 12.0, 21.0);
a.component_mul_assign(&b);
assert_eq!(a, expected);
sourcepub fn component_mul_mut<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)where
T: ClosedMulAssign,
R2: Dim,
C2: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
👎Deprecated: This is renamed using the _assign
suffix instead of the _mut
suffix.
pub fn component_mul_mut<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)where
T: ClosedMulAssign,
R2: Dim,
C2: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
_assign
suffix instead of the _mut
suffix.Inplace componentwise matrix or vector multiplication.
§Example
let mut a = Matrix2::new(0.0, 1.0, 2.0, 3.0);
let b = Matrix2::new(4.0, 5.0, 6.0, 7.0);
let expected = Matrix2::new(0.0, 5.0, 12.0, 21.0);
a.component_mul_assign(&b);
assert_eq!(a, expected);
sourcepub fn component_div<R2, C2, SB>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C1, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C1, C2>>::Representative>>::Buffer<T>>where
T: ClosedDivAssign,
R2: Dim,
C2: Dim,
SB: Storage<T, R2, C2>,
DefaultAllocator: SameShapeAllocator<R1, C1, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
pub fn component_div<R2, C2, SB>(
&self,
rhs: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C1, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C1, C2>>::Representative>>::Buffer<T>>where
T: ClosedDivAssign,
R2: Dim,
C2: Dim,
SB: Storage<T, R2, C2>,
DefaultAllocator: SameShapeAllocator<R1, C1, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
Componentwise matrix or vector division.
§Example
let a = Matrix2::new(0.0, 1.0, 2.0, 3.0);
let b = Matrix2::new(4.0, 5.0, 6.0, 7.0);
let expected = Matrix2::new(0.0, 1.0 / 5.0, 2.0 / 6.0, 3.0 / 7.0);
assert_eq!(a.component_div(&b), expected);
sourcepub fn cdpy<R2, C2, SB, R3, C3, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
T: ClosedDivAssign + Zero<Output = T> + Mul<Output = T> + Add,
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> + SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3>,
pub fn cdpy<R2, C2, SB, R3, C3, SC>(
&mut self,
alpha: T,
a: &Matrix<T, R2, C2, SB>,
b: &Matrix<T, R3, C3, SC>,
beta: T,
)where
T: ClosedDivAssign + Zero<Output = T> + Mul<Output = T> + Add,
R2: Dim,
C2: Dim,
R3: Dim,
C3: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
SC: Storage<T, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> + SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3>,
Computes componentwise self[i] = alpha * a[i] / b[i] + beta * self[i]
.
§Example
let mut m = Matrix2::new(0.0, 1.0, 2.0, 3.0);
let a = Matrix2::new(4.0, 5.0, 6.0, 7.0);
let b = Matrix2::new(4.0, 5.0, 6.0, 7.0);
let expected = (a.component_div(&b) * 5.0) + m * 10.0;
m.cdpy(5.0, &a, &b, 10.0);
assert_eq!(m, expected);
sourcepub fn component_div_assign<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)where
T: ClosedDivAssign,
R2: Dim,
C2: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
pub fn component_div_assign<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)where
T: ClosedDivAssign,
R2: Dim,
C2: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
Inplace componentwise matrix or vector division.
§Example
let mut a = Matrix2::new(0.0, 1.0, 2.0, 3.0);
let b = Matrix2::new(4.0, 5.0, 6.0, 7.0);
let expected = Matrix2::new(0.0, 1.0 / 5.0, 2.0 / 6.0, 3.0 / 7.0);
a.component_div_assign(&b);
assert_eq!(a, expected);
sourcepub fn component_div_mut<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)where
T: ClosedDivAssign,
R2: Dim,
C2: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
👎Deprecated: This is renamed using the _assign
suffix instead of the _mut
suffix.
pub fn component_div_mut<R2, C2, SB>(&mut self, rhs: &Matrix<T, R2, C2, SB>)where
T: ClosedDivAssign,
R2: Dim,
C2: Dim,
SA: StorageMut<T, R1, C1>,
SB: Storage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
_assign
suffix instead of the _mut
suffix.Inplace componentwise matrix or vector division.
§Example
let mut a = Matrix2::new(0.0, 1.0, 2.0, 3.0);
let b = Matrix2::new(4.0, 5.0, 6.0, 7.0);
let expected = Matrix2::new(0.0, 1.0 / 5.0, 2.0 / 6.0, 3.0 / 7.0);
a.component_div_assign(&b);
assert_eq!(a, expected);
sourcepub fn inf(
&self,
other: &Matrix<T, R1, C1, SA>,
) -> Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>where
T: SimdPartialOrd,
DefaultAllocator: Allocator<R1, C1>,
pub fn inf(
&self,
other: &Matrix<T, R1, C1, SA>,
) -> Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>where
T: SimdPartialOrd,
DefaultAllocator: Allocator<R1, C1>,
Computes the infimum (aka. componentwise min) of two matrices/vectors.
§Example
let u = Matrix2::new(4.0, 2.0, 1.0, -2.0);
let v = Matrix2::new(2.0, 4.0, -2.0, 1.0);
let expected = Matrix2::new(2.0, 2.0, -2.0, -2.0);
assert_eq!(u.inf(&v), expected)
sourcepub fn sup(
&self,
other: &Matrix<T, R1, C1, SA>,
) -> Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>where
T: SimdPartialOrd,
DefaultAllocator: Allocator<R1, C1>,
pub fn sup(
&self,
other: &Matrix<T, R1, C1, SA>,
) -> Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>where
T: SimdPartialOrd,
DefaultAllocator: Allocator<R1, C1>,
Computes the supremum (aka. componentwise max) of two matrices/vectors.
§Example
let u = Matrix2::new(4.0, 2.0, 1.0, -2.0);
let v = Matrix2::new(2.0, 4.0, -2.0, 1.0);
let expected = Matrix2::new(4.0, 4.0, 1.0, 1.0);
assert_eq!(u.sup(&v), expected)
sourcepub fn inf_sup(
&self,
other: &Matrix<T, R1, C1, SA>,
) -> (Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>, Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>)where
T: SimdPartialOrd,
DefaultAllocator: Allocator<R1, C1>,
pub fn inf_sup(
&self,
other: &Matrix<T, R1, C1, SA>,
) -> (Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>, Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>)where
T: SimdPartialOrd,
DefaultAllocator: Allocator<R1, C1>,
Computes the (infimum, supremum) of two matrices/vectors.
§Example
let u = Matrix2::new(4.0, 2.0, 1.0, -2.0);
let v = Matrix2::new(2.0, 4.0, -2.0, 1.0);
let expected = (Matrix2::new(2.0, 2.0, -2.0, -2.0), Matrix2::new(4.0, 4.0, 1.0, 1.0));
assert_eq!(u.inf_sup(&v), expected)
sourcepub fn add_scalar(
&self,
rhs: T,
) -> Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>where
T: ClosedAddAssign,
DefaultAllocator: Allocator<R1, C1>,
pub fn add_scalar(
&self,
rhs: T,
) -> Matrix<T, R1, C1, <DefaultAllocator as Allocator<R1, C1>>::Buffer<T>>where
T: ClosedAddAssign,
DefaultAllocator: Allocator<R1, C1>,
Adds a scalar to self
.
§Example
let u = Matrix2::new(1.0, 2.0, 3.0, 4.0);
let s = 10.0;
let expected = Matrix2::new(11.0, 12.0, 13.0, 14.0);
assert_eq!(u.add_scalar(s), expected)
sourcepub fn add_scalar_mut(&mut self, rhs: T)where
T: ClosedAddAssign,
SA: StorageMut<T, R1, C1>,
pub fn add_scalar_mut(&mut self, rhs: T)where
T: ClosedAddAssign,
SA: StorageMut<T, R1, C1>,
Adds a scalar to self
in-place.
§Example
let mut u = Matrix2::new(1.0, 2.0, 3.0, 4.0);
let s = 10.0;
u.add_scalar_mut(s);
let expected = Matrix2::new(11.0, 12.0, 13.0, 14.0);
assert_eq!(u, expected)
source§impl<T, R, C> Matrix<MaybeUninit<T>, R, C, <DefaultAllocator as Allocator<R, C>>::BufferUninit<T>>
impl<T, R, C> Matrix<MaybeUninit<T>, R, C, <DefaultAllocator as Allocator<R, C>>::BufferUninit<T>>
sourcepub fn uninit(
nrows: R,
ncols: C,
) -> Matrix<MaybeUninit<T>, R, C, <DefaultAllocator as Allocator<R, C>>::BufferUninit<T>>
pub fn uninit( nrows: R, ncols: C, ) -> Matrix<MaybeUninit<T>, R, C, <DefaultAllocator as Allocator<R, C>>::BufferUninit<T>>
Builds a matrix with uninitialized elements of type MaybeUninit<T>
.
source§impl<T, R, C> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
impl<T, R, C> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
§Generic constructors
This set of matrix and vector construction functions are all generic 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.
sourcepub fn from_element_generic(
nrows: R,
ncols: C,
elem: T,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_element_generic( nrows: R, ncols: C, elem: T, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix with all its elements set to elem
.
sourcepub fn repeat_generic(
nrows: R,
ncols: C,
elem: T,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn repeat_generic( nrows: R, ncols: C, elem: T, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix with all its elements set to elem
.
Same as from_element_generic
.
sourcepub fn zeros_generic(
nrows: R,
ncols: C,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
T: Zero,
pub fn zeros_generic(
nrows: R,
ncols: C,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
T: Zero,
Creates a matrix with all its elements set to 0.
sourcepub fn from_iterator_generic<I>(
nrows: R,
ncols: C,
iter: I,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_iterator_generic<I>(
nrows: R,
ncols: C,
iter: I,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix with all its elements filled by an iterator.
sourcepub fn from_row_iterator_generic<I>(
nrows: R,
ncols: C,
iter: I,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_row_iterator_generic<I>(
nrows: R,
ncols: C,
iter: I,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix with all its elements filled by an row-major order iterator.
sourcepub fn from_row_slice_generic(
nrows: R,
ncols: C,
slice: &[T],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_row_slice_generic( nrows: R, ncols: C, slice: &[T], ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice in row-major order.
The order of elements in the slice must follow the usual mathematic writing, i.e., row-by-row.
sourcepub fn from_column_slice_generic(
nrows: R,
ncols: C,
slice: &[T],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_column_slice_generic( nrows: R, ncols: C, slice: &[T], ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice. The components must have the same layout as the matrix data storage (i.e. column-major).
sourcepub fn from_fn_generic<F>(
nrows: R,
ncols: C,
f: F,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_fn_generic<F>( nrows: R, ncols: C, f: F, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix filled with the results of a function applied to each of its component coordinates.
sourcepub fn identity_generic(
nrows: R,
ncols: C,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn identity_generic( nrows: R, ncols: C, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a new identity matrix.
If the matrix is not square, the largest square submatrix starting at index (0, 0)
is set
to the identity matrix. All other entries are set to zero.
sourcepub fn from_diagonal_element_generic(
nrows: R,
ncols: C,
elt: T,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_diagonal_element_generic( nrows: R, ncols: C, elt: T, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a new matrix with its diagonal filled with copies of elt
.
If the matrix is not square, the largest square submatrix starting at index (0, 0)
is set
to the identity matrix. All other entries are set to zero.
sourcepub fn from_partial_diagonal_generic(
nrows: R,
ncols: C,
elts: &[T],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
T: Zero,
pub fn from_partial_diagonal_generic(
nrows: R,
ncols: C,
elts: &[T],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
T: Zero,
Creates a new matrix that may be rectangular. The first elts.len()
diagonal elements are
filled with the content of elts
. Others are set to 0.
Panics if elts.len()
is larger than the minimum among nrows
and ncols
.
sourcepub fn from_rows<SB>(
rows: &[Matrix<T, Const<1>, C, SB>],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
SB: RawStorage<T, Const<1>, C>,
pub fn from_rows<SB>(
rows: &[Matrix<T, Const<1>, C, SB>],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
SB: RawStorage<T, Const<1>, C>,
Builds a new matrix from its rows.
Panics if not enough rows are provided (for statically-sized matrices), or if all rows do not have the same dimensions.
§Example
let m = Matrix3::from_rows(&[ RowVector3::new(1.0, 2.0, 3.0), RowVector3::new(4.0, 5.0, 6.0), RowVector3::new(7.0, 8.0, 9.0) ]);
assert!(m.m11 == 1.0 && m.m12 == 2.0 && m.m13 == 3.0 &&
m.m21 == 4.0 && m.m22 == 5.0 && m.m23 == 6.0 &&
m.m31 == 7.0 && m.m32 == 8.0 && m.m33 == 9.0);
sourcepub fn from_columns<SB>(
columns: &[Matrix<T, R, Const<1>, SB>],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
SB: RawStorage<T, R>,
pub fn from_columns<SB>(
columns: &[Matrix<T, R, Const<1>, SB>],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
SB: RawStorage<T, R>,
Builds a new matrix from its columns.
Panics if not enough columns are provided (for statically-sized matrices), or if all columns do not have the same dimensions.
§Example
let m = Matrix3::from_columns(&[ Vector3::new(1.0, 2.0, 3.0), Vector3::new(4.0, 5.0, 6.0), Vector3::new(7.0, 8.0, 9.0) ]);
assert!(m.m11 == 1.0 && m.m12 == 4.0 && m.m13 == 7.0 &&
m.m21 == 2.0 && m.m22 == 5.0 && m.m23 == 8.0 &&
m.m31 == 3.0 && m.m32 == 6.0 && m.m33 == 9.0);
sourcepub fn from_vec_generic(
nrows: R,
ncols: C,
data: Vec<T>,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_vec_generic( nrows: R, ncols: C, data: Vec<T>, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix backed by a given Vec
.
The output matrix is filled column-by-column.
§Example
let vec = vec![0, 1, 2, 3, 4, 5];
let vec_ptr = vec.as_ptr();
let matrix = Matrix::from_vec_generic(Dyn(vec.len()), Const::<1>, vec);
let matrix_storage_ptr = matrix.data.as_vec().as_ptr();
// `matrix` is backed by exactly the same `Vec` as it was constructed from.
assert_eq!(matrix_storage_ptr, vec_ptr);
source§impl<T, D> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
impl<T, D> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>
sourcepub fn from_diagonal<SB>(
diag: &Matrix<T, D, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
SB: RawStorage<T, D>,
T: Zero,
pub fn from_diagonal<SB>(
diag: &Matrix<T, D, Const<1>, SB>,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
SB: RawStorage<T, D>,
T: Zero,
Creates a square matrix with its diagonal set to diag
and all other entries set to 0.
§Example
let m = Matrix3::from_diagonal(&Vector3::new(1.0, 2.0, 3.0));
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_diagonal(&DVector::from_row_slice(&[1.0, 2.0, 3.0]));
assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 2.0 && m.m23 == 0.0 &&
m.m31 == 0.0 && m.m32 == 0.0 && m.m33 == 3.0);
assert!(dm[(0, 0)] == 1.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 0.0 &&
dm[(2, 0)] == 0.0 && dm[(2, 1)] == 0.0 && dm[(2, 2)] == 3.0);
source§impl<T, R, C> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
impl<T, R, C> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
§Constructors of statically-sized vectors or statically-sized matrices
sourcepub fn from_element(
elem: T,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_element( elem: T, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix or vector with all its elements set to elem
.
§Example
let v = Vector3::from_element(2.0);
// The additional argument represents the vector dimension.
let dv = DVector::from_element(3, 2.0);
let m = Matrix2x3::from_element(2.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_element(2, 3, 2.0);
assert!(v.x == 2.0 && v.y == 2.0 && v.z == 2.0);
assert!(dv[0] == 2.0 && dv[1] == 2.0 && dv[2] == 2.0);
assert!(m.m11 == 2.0 && m.m12 == 2.0 && m.m13 == 2.0 &&
m.m21 == 2.0 && m.m22 == 2.0 && m.m23 == 2.0);
assert!(dm[(0, 0)] == 2.0 && dm[(0, 1)] == 2.0 && dm[(0, 2)] == 2.0 &&
dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
sourcepub fn repeat(
elem: T,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn repeat( elem: T, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix or vector with all its elements set to elem
.
Same as .from_element
.
§Example
let v = Vector3::repeat(2.0);
// The additional argument represents the vector dimension.
let dv = DVector::repeat(3, 2.0);
let m = Matrix2x3::repeat(2.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::repeat(2, 3, 2.0);
assert!(v.x == 2.0 && v.y == 2.0 && v.z == 2.0);
assert!(dv[0] == 2.0 && dv[1] == 2.0 && dv[2] == 2.0);
assert!(m.m11 == 2.0 && m.m12 == 2.0 && m.m13 == 2.0 &&
m.m21 == 2.0 && m.m22 == 2.0 && m.m23 == 2.0);
assert!(dm[(0, 0)] == 2.0 && dm[(0, 1)] == 2.0 && dm[(0, 2)] == 2.0 &&
dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
sourcepub fn zeros() -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
T: Zero,
pub fn zeros() -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
T: Zero,
Creates a matrix or vector with all its elements set to 0
.
§Example
let v = Vector3::<f32>::zeros();
// The argument represents the vector dimension.
let dv = DVector::<f32>::zeros(3);
let m = Matrix2x3::<f32>::zeros();
// The two arguments represent the matrix dimensions.
let dm = DMatrix::<f32>::zeros(2, 3);
assert!(v.x == 0.0 && v.y == 0.0 && v.z == 0.0);
assert!(dv[0] == 0.0 && dv[1] == 0.0 && dv[2] == 0.0);
assert!(m.m11 == 0.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 0.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 0.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 0.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_iterator<I>(
iter: I,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_iterator<I>(
iter: I,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix or vector with all its elements filled by an iterator.
The output matrix is filled column-by-column.
§Example
let v = Vector3::from_iterator((0..3).into_iter());
// The additional argument represents the vector dimension.
let dv = DVector::from_iterator(3, (0..3).into_iter());
let m = Matrix2x3::from_iterator((0..6).into_iter());
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_iterator(2, 3, (0..6).into_iter());
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
sourcepub fn from_row_iterator<I>(
iter: I,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_row_iterator<I>(
iter: I,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix or vector with all its elements filled by a row-major iterator.
The output matrix is filled row-by-row.
§Example
let v = Vector3::from_row_iterator((0..3).into_iter());
// The additional argument represents the vector dimension.
let dv = DVector::from_row_iterator(3, (0..3).into_iter());
let m = Matrix2x3::from_row_iterator((0..6).into_iter());
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_row_iterator(2, 3, (0..6).into_iter());
// For Vectors from_row_iterator is identical to from_iterator
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn from_fn<F>(
f: F,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_fn<F>( f: F, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix or vector filled with the results of a function applied to each of its component coordinates.
§Example
let v = Vector3::from_fn(|i, _| i);
// The additional argument represents the vector dimension.
let dv = DVector::from_fn(3, |i, _| i);
let m = Matrix2x3::from_fn(|i, j| i * 3 + j);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_fn(2, 3, |i, j| i * 3 + j);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn identity() -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn identity() -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates an identity matrix. If the matrix is not square, the largest square submatrix (starting at the first row and column) is set to the identity while all other entries are set to zero.
§Example
let m = Matrix2x3::<f32>::identity();
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::<f32>::identity(2, 3);
assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 1.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 1.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 1.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_diagonal_element(
elt: T,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_diagonal_element( elt: T, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix filled with its diagonal filled with elt
and all other
components set to zero.
§Example
let m = Matrix2x3::from_diagonal_element(5.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_diagonal_element(2, 3, 5.0);
assert!(m.m11 == 5.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 5.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 5.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 5.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_partial_diagonal(
elts: &[T],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
T: Zero,
pub fn from_partial_diagonal(
elts: &[T],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
T: Zero,
Creates a new matrix that may be rectangular. The first elts.len()
diagonal
elements are filled with the content of elts
. Others are set to 0.
Panics if elts.len()
is larger than the minimum among nrows
and ncols
.
§Example
let m = Matrix3::from_partial_diagonal(&[1.0, 2.0]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_partial_diagonal(3, 3, &[1.0, 2.0]);
assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 2.0 && m.m23 == 0.0 &&
m.m31 == 0.0 && m.m32 == 0.0 && m.m33 == 0.0);
assert!(dm[(0, 0)] == 1.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 0.0 &&
dm[(2, 0)] == 0.0 && dm[(2, 1)] == 0.0 && dm[(2, 2)] == 0.0);
source§impl<T, R> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
impl<T, R> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
§Constructors of matrices with a dynamic number of columns
sourcepub fn from_element(
ncols: usize,
elem: T,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn from_element( ncols: usize, elem: T, ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Creates a matrix or vector with all its elements set to elem
.
§Example
let v = Vector3::from_element(2.0);
// The additional argument represents the vector dimension.
let dv = DVector::from_element(3, 2.0);
let m = Matrix2x3::from_element(2.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_element(2, 3, 2.0);
assert!(v.x == 2.0 && v.y == 2.0 && v.z == 2.0);
assert!(dv[0] == 2.0 && dv[1] == 2.0 && dv[2] == 2.0);
assert!(m.m11 == 2.0 && m.m12 == 2.0 && m.m13 == 2.0 &&
m.m21 == 2.0 && m.m22 == 2.0 && m.m23 == 2.0);
assert!(dm[(0, 0)] == 2.0 && dm[(0, 1)] == 2.0 && dm[(0, 2)] == 2.0 &&
dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
sourcepub fn repeat(
ncols: usize,
elem: T,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn repeat( ncols: usize, elem: T, ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Creates a matrix or vector with all its elements set to elem
.
Same as .from_element
.
§Example
let v = Vector3::repeat(2.0);
// The additional argument represents the vector dimension.
let dv = DVector::repeat(3, 2.0);
let m = Matrix2x3::repeat(2.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::repeat(2, 3, 2.0);
assert!(v.x == 2.0 && v.y == 2.0 && v.z == 2.0);
assert!(dv[0] == 2.0 && dv[1] == 2.0 && dv[2] == 2.0);
assert!(m.m11 == 2.0 && m.m12 == 2.0 && m.m13 == 2.0 &&
m.m21 == 2.0 && m.m22 == 2.0 && m.m23 == 2.0);
assert!(dm[(0, 0)] == 2.0 && dm[(0, 1)] == 2.0 && dm[(0, 2)] == 2.0 &&
dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
sourcepub fn zeros(
ncols: usize,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
T: Zero,
pub fn zeros(
ncols: usize,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
T: Zero,
Creates a matrix or vector with all its elements set to 0
.
§Example
let v = Vector3::<f32>::zeros();
// The argument represents the vector dimension.
let dv = DVector::<f32>::zeros(3);
let m = Matrix2x3::<f32>::zeros();
// The two arguments represent the matrix dimensions.
let dm = DMatrix::<f32>::zeros(2, 3);
assert!(v.x == 0.0 && v.y == 0.0 && v.z == 0.0);
assert!(dv[0] == 0.0 && dv[1] == 0.0 && dv[2] == 0.0);
assert!(m.m11 == 0.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 0.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 0.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 0.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_iterator<I>(
ncols: usize,
iter: I,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_iterator<I>(
ncols: usize,
iter: I,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix or vector with all its elements filled by an iterator.
The output matrix is filled column-by-column.
§Example
let v = Vector3::from_iterator((0..3).into_iter());
// The additional argument represents the vector dimension.
let dv = DVector::from_iterator(3, (0..3).into_iter());
let m = Matrix2x3::from_iterator((0..6).into_iter());
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_iterator(2, 3, (0..6).into_iter());
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
sourcepub fn from_row_iterator<I>(
ncols: usize,
iter: I,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_row_iterator<I>(
ncols: usize,
iter: I,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix or vector with all its elements filled by a row-major iterator.
The output matrix is filled row-by-row.
§Example
let v = Vector3::from_row_iterator((0..3).into_iter());
// The additional argument represents the vector dimension.
let dv = DVector::from_row_iterator(3, (0..3).into_iter());
let m = Matrix2x3::from_row_iterator((0..6).into_iter());
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_row_iterator(2, 3, (0..6).into_iter());
// For Vectors from_row_iterator is identical to from_iterator
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn from_fn<F>(
ncols: usize,
f: F,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn from_fn<F>( ncols: usize, f: F, ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Creates a matrix or vector filled with the results of a function applied to each of its component coordinates.
§Example
let v = Vector3::from_fn(|i, _| i);
// The additional argument represents the vector dimension.
let dv = DVector::from_fn(3, |i, _| i);
let m = Matrix2x3::from_fn(|i, j| i * 3 + j);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_fn(2, 3, |i, j| i * 3 + j);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn identity(
ncols: usize,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn identity( ncols: usize, ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Creates an identity matrix. If the matrix is not square, the largest square submatrix (starting at the first row and column) is set to the identity while all other entries are set to zero.
§Example
let m = Matrix2x3::<f32>::identity();
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::<f32>::identity(2, 3);
assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 1.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 1.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 1.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_diagonal_element(
ncols: usize,
elt: T,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn from_diagonal_element( ncols: usize, elt: T, ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Creates a matrix filled with its diagonal filled with elt
and all other
components set to zero.
§Example
let m = Matrix2x3::from_diagonal_element(5.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_diagonal_element(2, 3, 5.0);
assert!(m.m11 == 5.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 5.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 5.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 5.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_partial_diagonal(
ncols: usize,
elts: &[T],
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
T: Zero,
pub fn from_partial_diagonal(
ncols: usize,
elts: &[T],
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
T: Zero,
Creates a new matrix that may be rectangular. The first elts.len()
diagonal
elements are filled with the content of elts
. Others are set to 0.
Panics if elts.len()
is larger than the minimum among nrows
and ncols
.
§Example
let m = Matrix3::from_partial_diagonal(&[1.0, 2.0]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_partial_diagonal(3, 3, &[1.0, 2.0]);
assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 2.0 && m.m23 == 0.0 &&
m.m31 == 0.0 && m.m32 == 0.0 && m.m33 == 0.0);
assert!(dm[(0, 0)] == 1.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 0.0 &&
dm[(2, 0)] == 0.0 && dm[(2, 1)] == 0.0 && dm[(2, 2)] == 0.0);
source§impl<T, C> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
impl<T, C> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
§Constructors of dynamic vectors and matrices with a dynamic number of rows
sourcepub fn from_element(
nrows: usize,
elem: T,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn from_element( nrows: usize, elem: T, ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Creates a matrix or vector with all its elements set to elem
.
§Example
let v = Vector3::from_element(2.0);
// The additional argument represents the vector dimension.
let dv = DVector::from_element(3, 2.0);
let m = Matrix2x3::from_element(2.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_element(2, 3, 2.0);
assert!(v.x == 2.0 && v.y == 2.0 && v.z == 2.0);
assert!(dv[0] == 2.0 && dv[1] == 2.0 && dv[2] == 2.0);
assert!(m.m11 == 2.0 && m.m12 == 2.0 && m.m13 == 2.0 &&
m.m21 == 2.0 && m.m22 == 2.0 && m.m23 == 2.0);
assert!(dm[(0, 0)] == 2.0 && dm[(0, 1)] == 2.0 && dm[(0, 2)] == 2.0 &&
dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
sourcepub fn repeat(
nrows: usize,
elem: T,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn repeat( nrows: usize, elem: T, ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Creates a matrix or vector with all its elements set to elem
.
Same as .from_element
.
§Example
let v = Vector3::repeat(2.0);
// The additional argument represents the vector dimension.
let dv = DVector::repeat(3, 2.0);
let m = Matrix2x3::repeat(2.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::repeat(2, 3, 2.0);
assert!(v.x == 2.0 && v.y == 2.0 && v.z == 2.0);
assert!(dv[0] == 2.0 && dv[1] == 2.0 && dv[2] == 2.0);
assert!(m.m11 == 2.0 && m.m12 == 2.0 && m.m13 == 2.0 &&
m.m21 == 2.0 && m.m22 == 2.0 && m.m23 == 2.0);
assert!(dm[(0, 0)] == 2.0 && dm[(0, 1)] == 2.0 && dm[(0, 2)] == 2.0 &&
dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
sourcepub fn zeros(
nrows: usize,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
T: Zero,
pub fn zeros(
nrows: usize,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
T: Zero,
Creates a matrix or vector with all its elements set to 0
.
§Example
let v = Vector3::<f32>::zeros();
// The argument represents the vector dimension.
let dv = DVector::<f32>::zeros(3);
let m = Matrix2x3::<f32>::zeros();
// The two arguments represent the matrix dimensions.
let dm = DMatrix::<f32>::zeros(2, 3);
assert!(v.x == 0.0 && v.y == 0.0 && v.z == 0.0);
assert!(dv[0] == 0.0 && dv[1] == 0.0 && dv[2] == 0.0);
assert!(m.m11 == 0.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 0.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 0.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 0.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_iterator<I>(
nrows: usize,
iter: I,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_iterator<I>(
nrows: usize,
iter: I,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix or vector with all its elements filled by an iterator.
The output matrix is filled column-by-column.
§Example
let v = Vector3::from_iterator((0..3).into_iter());
// The additional argument represents the vector dimension.
let dv = DVector::from_iterator(3, (0..3).into_iter());
let m = Matrix2x3::from_iterator((0..6).into_iter());
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_iterator(2, 3, (0..6).into_iter());
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
sourcepub fn from_row_iterator<I>(
nrows: usize,
iter: I,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_row_iterator<I>(
nrows: usize,
iter: I,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix or vector with all its elements filled by a row-major iterator.
The output matrix is filled row-by-row.
§Example
let v = Vector3::from_row_iterator((0..3).into_iter());
// The additional argument represents the vector dimension.
let dv = DVector::from_row_iterator(3, (0..3).into_iter());
let m = Matrix2x3::from_row_iterator((0..6).into_iter());
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_row_iterator(2, 3, (0..6).into_iter());
// For Vectors from_row_iterator is identical to from_iterator
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn from_fn<F>(
nrows: usize,
f: F,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn from_fn<F>( nrows: usize, f: F, ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Creates a matrix or vector filled with the results of a function applied to each of its component coordinates.
§Example
let v = Vector3::from_fn(|i, _| i);
// The additional argument represents the vector dimension.
let dv = DVector::from_fn(3, |i, _| i);
let m = Matrix2x3::from_fn(|i, j| i * 3 + j);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_fn(2, 3, |i, j| i * 3 + j);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn identity(
nrows: usize,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn identity( nrows: usize, ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Creates an identity matrix. If the matrix is not square, the largest square submatrix (starting at the first row and column) is set to the identity while all other entries are set to zero.
§Example
let m = Matrix2x3::<f32>::identity();
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::<f32>::identity(2, 3);
assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 1.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 1.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 1.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_diagonal_element(
nrows: usize,
elt: T,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn from_diagonal_element( nrows: usize, elt: T, ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Creates a matrix filled with its diagonal filled with elt
and all other
components set to zero.
§Example
let m = Matrix2x3::from_diagonal_element(5.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_diagonal_element(2, 3, 5.0);
assert!(m.m11 == 5.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 5.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 5.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 5.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_partial_diagonal(
nrows: usize,
elts: &[T],
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
T: Zero,
pub fn from_partial_diagonal(
nrows: usize,
elts: &[T],
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
T: Zero,
Creates a new matrix that may be rectangular. The first elts.len()
diagonal
elements are filled with the content of elts
. Others are set to 0.
Panics if elts.len()
is larger than the minimum among nrows
and ncols
.
§Example
let m = Matrix3::from_partial_diagonal(&[1.0, 2.0]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_partial_diagonal(3, 3, &[1.0, 2.0]);
assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 2.0 && m.m23 == 0.0 &&
m.m31 == 0.0 && m.m32 == 0.0 && m.m33 == 0.0);
assert!(dm[(0, 0)] == 1.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 0.0 &&
dm[(2, 0)] == 0.0 && dm[(2, 1)] == 0.0 && dm[(2, 2)] == 0.0);
source§impl<T> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
impl<T> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
§Constructors of fully dynamic matrices
sourcepub fn from_element(
nrows: usize,
ncols: usize,
elem: T,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
pub fn from_element( nrows: usize, ncols: usize, elem: T, ) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
Creates a matrix or vector with all its elements set to elem
.
§Example
let v = Vector3::from_element(2.0);
// The additional argument represents the vector dimension.
let dv = DVector::from_element(3, 2.0);
let m = Matrix2x3::from_element(2.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_element(2, 3, 2.0);
assert!(v.x == 2.0 && v.y == 2.0 && v.z == 2.0);
assert!(dv[0] == 2.0 && dv[1] == 2.0 && dv[2] == 2.0);
assert!(m.m11 == 2.0 && m.m12 == 2.0 && m.m13 == 2.0 &&
m.m21 == 2.0 && m.m22 == 2.0 && m.m23 == 2.0);
assert!(dm[(0, 0)] == 2.0 && dm[(0, 1)] == 2.0 && dm[(0, 2)] == 2.0 &&
dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
sourcepub fn repeat(
nrows: usize,
ncols: usize,
elem: T,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
pub fn repeat( nrows: usize, ncols: usize, elem: T, ) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
Creates a matrix or vector with all its elements set to elem
.
Same as .from_element
.
§Example
let v = Vector3::repeat(2.0);
// The additional argument represents the vector dimension.
let dv = DVector::repeat(3, 2.0);
let m = Matrix2x3::repeat(2.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::repeat(2, 3, 2.0);
assert!(v.x == 2.0 && v.y == 2.0 && v.z == 2.0);
assert!(dv[0] == 2.0 && dv[1] == 2.0 && dv[2] == 2.0);
assert!(m.m11 == 2.0 && m.m12 == 2.0 && m.m13 == 2.0 &&
m.m21 == 2.0 && m.m22 == 2.0 && m.m23 == 2.0);
assert!(dm[(0, 0)] == 2.0 && dm[(0, 1)] == 2.0 && dm[(0, 2)] == 2.0 &&
dm[(1, 0)] == 2.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 2.0);
sourcepub fn zeros(
nrows: usize,
ncols: usize,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
T: Zero,
pub fn zeros(
nrows: usize,
ncols: usize,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
T: Zero,
Creates a matrix or vector with all its elements set to 0
.
§Example
let v = Vector3::<f32>::zeros();
// The argument represents the vector dimension.
let dv = DVector::<f32>::zeros(3);
let m = Matrix2x3::<f32>::zeros();
// The two arguments represent the matrix dimensions.
let dm = DMatrix::<f32>::zeros(2, 3);
assert!(v.x == 0.0 && v.y == 0.0 && v.z == 0.0);
assert!(dv[0] == 0.0 && dv[1] == 0.0 && dv[2] == 0.0);
assert!(m.m11 == 0.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 0.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 0.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 0.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_iterator<I>(
nrows: usize,
ncols: usize,
iter: I,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_iterator<I>(
nrows: usize,
ncols: usize,
iter: I,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix or vector with all its elements filled by an iterator.
The output matrix is filled column-by-column.
§Example
let v = Vector3::from_iterator((0..3).into_iter());
// The additional argument represents the vector dimension.
let dv = DVector::from_iterator(3, (0..3).into_iter());
let m = Matrix2x3::from_iterator((0..6).into_iter());
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_iterator(2, 3, (0..6).into_iter());
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
sourcepub fn from_row_iterator<I>(
nrows: usize,
ncols: usize,
iter: I,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = T>,
pub fn from_row_iterator<I>(
nrows: usize,
ncols: usize,
iter: I,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = T>,
Creates a matrix or vector with all its elements filled by a row-major iterator.
The output matrix is filled row-by-row.
§Example
let v = Vector3::from_row_iterator((0..3).into_iter());
// The additional argument represents the vector dimension.
let dv = DVector::from_row_iterator(3, (0..3).into_iter());
let m = Matrix2x3::from_row_iterator((0..6).into_iter());
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_row_iterator(2, 3, (0..6).into_iter());
// For Vectors from_row_iterator is identical to from_iterator
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn from_fn<F>(
nrows: usize,
ncols: usize,
f: F,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
pub fn from_fn<F>( nrows: usize, ncols: usize, f: F, ) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
Creates a matrix or vector filled with the results of a function applied to each of its component coordinates.
§Example
let v = Vector3::from_fn(|i, _| i);
// The additional argument represents the vector dimension.
let dv = DVector::from_fn(3, |i, _| i);
let m = Matrix2x3::from_fn(|i, j| i * 3 + j);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_fn(2, 3, |i, j| i * 3 + j);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn identity(
nrows: usize,
ncols: usize,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
pub fn identity( nrows: usize, ncols: usize, ) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
Creates an identity matrix. If the matrix is not square, the largest square submatrix (starting at the first row and column) is set to the identity while all other entries are set to zero.
§Example
let m = Matrix2x3::<f32>::identity();
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::<f32>::identity(2, 3);
assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 1.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 1.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 1.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_diagonal_element(
nrows: usize,
ncols: usize,
elt: T,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
pub fn from_diagonal_element( nrows: usize, ncols: usize, elt: T, ) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
Creates a matrix filled with its diagonal filled with elt
and all other
components set to zero.
§Example
let m = Matrix2x3::from_diagonal_element(5.0);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_diagonal_element(2, 3, 5.0);
assert!(m.m11 == 5.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 5.0 && m.m23 == 0.0);
assert!(dm[(0, 0)] == 5.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 5.0 && dm[(1, 2)] == 0.0);
sourcepub fn from_partial_diagonal(
nrows: usize,
ncols: usize,
elts: &[T],
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
T: Zero,
pub fn from_partial_diagonal(
nrows: usize,
ncols: usize,
elts: &[T],
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
T: Zero,
Creates a new matrix that may be rectangular. The first elts.len()
diagonal
elements are filled with the content of elts
. Others are set to 0.
Panics if elts.len()
is larger than the minimum among nrows
and ncols
.
§Example
let m = Matrix3::from_partial_diagonal(&[1.0, 2.0]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_partial_diagonal(3, 3, &[1.0, 2.0]);
assert!(m.m11 == 1.0 && m.m12 == 0.0 && m.m13 == 0.0 &&
m.m21 == 0.0 && m.m22 == 2.0 && m.m23 == 0.0 &&
m.m31 == 0.0 && m.m32 == 0.0 && m.m33 == 0.0);
assert!(dm[(0, 0)] == 1.0 && dm[(0, 1)] == 0.0 && dm[(0, 2)] == 0.0 &&
dm[(1, 0)] == 0.0 && dm[(1, 1)] == 2.0 && dm[(1, 2)] == 0.0 &&
dm[(2, 0)] == 0.0 && dm[(2, 1)] == 0.0 && dm[(2, 2)] == 0.0);
source§impl<T, R, C> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
impl<T, R, C> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
sourcepub fn from_row_slice(
data: &[T],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_row_slice( data: &[T], ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice in row-major order.
The order of elements in the slice must follow the usual mathematic writing, i.e., row-by-row.
§Example
let v = Vector3::from_row_slice(&[0, 1, 2]);
// The additional argument represents the vector dimension.
let dv = DVector::from_row_slice(&[0, 1, 2]);
let m = Matrix2x3::from_row_slice(&[0, 1, 2, 3, 4, 5]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_row_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn from_column_slice(
data: &[T],
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_column_slice( data: &[T], ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice in column-major order.
§Example
let v = Vector3::from_column_slice(&[0, 1, 2]);
// The additional argument represents the vector dimension.
let dv = DVector::from_column_slice(&[0, 1, 2]);
let m = Matrix2x3::from_column_slice(&[0, 1, 2, 3, 4, 5]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_column_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
sourcepub fn from_vec(
data: Vec<T>,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn from_vec( data: Vec<T>, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Creates a matrix backed by a given Vec
.
The output matrix is filled column-by-column.
§Example
let m = Matrix2x3::from_vec(vec![0, 1, 2, 3, 4, 5]);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_vec(2, 3, vec![0, 1, 2, 3, 4, 5]);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
source§impl<T, R> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
impl<T, R> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
sourcepub fn from_row_slice(
data: &[T],
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn from_row_slice( data: &[T], ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice in row-major order.
The order of elements in the slice must follow the usual mathematic writing, i.e., row-by-row.
§Example
let v = Vector3::from_row_slice(&[0, 1, 2]);
// The additional argument represents the vector dimension.
let dv = DVector::from_row_slice(&[0, 1, 2]);
let m = Matrix2x3::from_row_slice(&[0, 1, 2, 3, 4, 5]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_row_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn from_column_slice(
data: &[T],
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn from_column_slice( data: &[T], ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice in column-major order.
§Example
let v = Vector3::from_column_slice(&[0, 1, 2]);
// The additional argument represents the vector dimension.
let dv = DVector::from_column_slice(&[0, 1, 2]);
let m = Matrix2x3::from_column_slice(&[0, 1, 2, 3, 4, 5]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_column_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
sourcepub fn from_vec(
data: Vec<T>,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn from_vec( data: Vec<T>, ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Creates a matrix backed by a given Vec
.
The output matrix is filled column-by-column.
§Example
let m = Matrix2x3::from_vec(vec![0, 1, 2, 3, 4, 5]);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_vec(2, 3, vec![0, 1, 2, 3, 4, 5]);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
source§impl<T, C> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
impl<T, C> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
sourcepub fn from_row_slice(
data: &[T],
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn from_row_slice( data: &[T], ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice in row-major order.
The order of elements in the slice must follow the usual mathematic writing, i.e., row-by-row.
§Example
let v = Vector3::from_row_slice(&[0, 1, 2]);
// The additional argument represents the vector dimension.
let dv = DVector::from_row_slice(&[0, 1, 2]);
let m = Matrix2x3::from_row_slice(&[0, 1, 2, 3, 4, 5]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_row_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn from_column_slice(
data: &[T],
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn from_column_slice( data: &[T], ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice in column-major order.
§Example
let v = Vector3::from_column_slice(&[0, 1, 2]);
// The additional argument represents the vector dimension.
let dv = DVector::from_column_slice(&[0, 1, 2]);
let m = Matrix2x3::from_column_slice(&[0, 1, 2, 3, 4, 5]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_column_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
sourcepub fn from_vec(
data: Vec<T>,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn from_vec( data: Vec<T>, ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Creates a matrix backed by a given Vec
.
The output matrix is filled column-by-column.
§Example
let m = Matrix2x3::from_vec(vec![0, 1, 2, 3, 4, 5]);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_vec(2, 3, vec![0, 1, 2, 3, 4, 5]);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
source§impl<T> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
impl<T> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
sourcepub fn from_row_slice(
nrows: usize,
ncols: usize,
data: &[T],
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
pub fn from_row_slice( nrows: usize, ncols: usize, data: &[T], ) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice in row-major order.
The order of elements in the slice must follow the usual mathematic writing, i.e., row-by-row.
§Example
let v = Vector3::from_row_slice(&[0, 1, 2]);
// The additional argument represents the vector dimension.
let dv = DVector::from_row_slice(&[0, 1, 2]);
let m = Matrix2x3::from_row_slice(&[0, 1, 2, 3, 4, 5]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_row_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 1 && m.m13 == 2 &&
m.m21 == 3 && m.m22 == 4 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 1 && dm[(0, 2)] == 2 &&
dm[(1, 0)] == 3 && dm[(1, 1)] == 4 && dm[(1, 2)] == 5);
sourcepub fn from_column_slice(
nrows: usize,
ncols: usize,
data: &[T],
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
pub fn from_column_slice( nrows: usize, ncols: usize, data: &[T], ) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
Creates a matrix with its elements filled with the components provided by a slice in column-major order.
§Example
let v = Vector3::from_column_slice(&[0, 1, 2]);
// The additional argument represents the vector dimension.
let dv = DVector::from_column_slice(&[0, 1, 2]);
let m = Matrix2x3::from_column_slice(&[0, 1, 2, 3, 4, 5]);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_column_slice(2, 3, &[0, 1, 2, 3, 4, 5]);
assert!(v.x == 0 && v.y == 1 && v.z == 2);
assert!(dv[0] == 0 && dv[1] == 1 && dv[2] == 2);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
sourcepub fn from_vec(
nrows: usize,
ncols: usize,
data: Vec<T>,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
pub fn from_vec( nrows: usize, ncols: usize, data: Vec<T>, ) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
Creates a matrix backed by a given Vec
.
The output matrix is filled column-by-column.
§Example
let m = Matrix2x3::from_vec(vec![0, 1, 2, 3, 4, 5]);
assert!(m.m11 == 0 && m.m12 == 2 && m.m13 == 4 &&
m.m21 == 1 && m.m22 == 3 && m.m23 == 5);
// The two additional arguments represent the matrix dimensions.
let dm = DMatrix::from_vec(2, 3, vec![0, 1, 2, 3, 4, 5]);
assert!(dm[(0, 0)] == 0 && dm[(0, 1)] == 2 && dm[(0, 2)] == 4 &&
dm[(1, 0)] == 1 && dm[(1, 1)] == 3 && dm[(1, 2)] == 5);
source§impl<T> Matrix<T, Const<5>, Const<5>, ArrayStorage<T, 5, 5>>
impl<T> Matrix<T, Const<5>, Const<5>, ArrayStorage<T, 5, 5>>
sourcepub const fn new(
m11: T,
m12: T,
m13: T,
m14: T,
m15: T,
m21: T,
m22: T,
m23: T,
m24: T,
m25: T,
m31: T,
m32: T,
m33: T,
m34: T,
m35: T,
m41: T,
m42: T,
m43: T,
m44: T,
m45: T,
m51: T,
m52: T,
m53: T,
m54: T,
m55: T,
) -> Matrix<T, Const<5>, Const<5>, ArrayStorage<T, 5, 5>>
pub const fn new( m11: T, m12: T, m13: T, m14: T, m15: T, m21: T, m22: T, m23: T, m24: T, m25: T, m31: T, m32: T, m33: T, m34: T, m35: T, m41: T, m42: T, m43: T, m44: T, m45: T, m51: T, m52: T, m53: T, m54: T, m55: T, ) -> Matrix<T, Const<5>, Const<5>, ArrayStorage<T, 5, 5>>
Initializes this matrix from its components.
source§impl<T> Matrix<T, Const<6>, Const<6>, ArrayStorage<T, 6, 6>>
impl<T> Matrix<T, Const<6>, Const<6>, ArrayStorage<T, 6, 6>>
sourcepub const fn new(
m11: T,
m12: T,
m13: T,
m14: T,
m15: T,
m16: T,
m21: T,
m22: T,
m23: T,
m24: T,
m25: T,
m26: T,
m31: T,
m32: T,
m33: T,
m34: T,
m35: T,
m36: T,
m41: T,
m42: T,
m43: T,
m44: T,
m45: T,
m46: T,
m51: T,
m52: T,
m53: T,
m54: T,
m55: T,
m56: T,
m61: T,
m62: T,
m63: T,
m64: T,
m65: T,
m66: T,
) -> Matrix<T, Const<6>, Const<6>, ArrayStorage<T, 6, 6>>
pub const fn new( m11: T, m12: T, m13: T, m14: T, m15: T, m16: T, m21: T, m22: T, m23: T, m24: T, m25: T, m26: T, m31: T, m32: T, m33: T, m34: T, m35: T, m36: T, m41: T, m42: T, m43: T, m44: T, m45: T, m46: T, m51: T, m52: T, m53: T, m54: T, m55: T, m56: T, m61: T, m62: T, m63: T, m64: T, m65: T, m66: T, ) -> Matrix<T, Const<6>, Const<6>, ArrayStorage<T, 6, 6>>
Initializes this matrix from its components.
source§impl<T> Matrix<T, Const<4>, Const<6>, ArrayStorage<T, 4, 6>>
impl<T> Matrix<T, Const<4>, Const<6>, ArrayStorage<T, 4, 6>>
sourcepub const fn new(
m11: T,
m12: T,
m13: T,
m14: T,
m15: T,
m16: T,
m21: T,
m22: T,
m23: T,
m24: T,
m25: T,
m26: T,
m31: T,
m32: T,
m33: T,
m34: T,
m35: T,
m36: T,
m41: T,
m42: T,
m43: T,
m44: T,
m45: T,
m46: T,
) -> Matrix<T, Const<4>, Const<6>, ArrayStorage<T, 4, 6>>
pub const fn new( m11: T, m12: T, m13: T, m14: T, m15: T, m16: T, m21: T, m22: T, m23: T, m24: T, m25: T, m26: T, m31: T, m32: T, m33: T, m34: T, m35: T, m36: T, m41: T, m42: T, m43: T, m44: T, m45: T, m46: T, ) -> Matrix<T, Const<4>, Const<6>, ArrayStorage<T, 4, 6>>
Initializes this matrix from its components.
source§impl<T> Matrix<T, Const<5>, Const<6>, ArrayStorage<T, 5, 6>>
impl<T> Matrix<T, Const<5>, Const<6>, ArrayStorage<T, 5, 6>>
sourcepub const fn new(
m11: T,
m12: T,
m13: T,
m14: T,
m15: T,
m16: T,
m21: T,
m22: T,
m23: T,
m24: T,
m25: T,
m26: T,
m31: T,
m32: T,
m33: T,
m34: T,
m35: T,
m36: T,
m41: T,
m42: T,
m43: T,
m44: T,
m45: T,
m46: T,
m51: T,
m52: T,
m53: T,
m54: T,
m55: T,
m56: T,
) -> Matrix<T, Const<5>, Const<6>, ArrayStorage<T, 5, 6>>
pub const fn new( m11: T, m12: T, m13: T, m14: T, m15: T, m16: T, m21: T, m22: T, m23: T, m24: T, m25: T, m26: T, m31: T, m32: T, m33: T, m34: T, m35: T, m36: T, m41: T, m42: T, m43: T, m44: T, m45: T, m46: T, m51: T, m52: T, m53: T, m54: T, m55: T, m56: T, ) -> Matrix<T, Const<5>, Const<6>, ArrayStorage<T, 5, 6>>
Initializes this matrix from its components.
source§impl<T> Matrix<T, Const<6>, Const<4>, ArrayStorage<T, 6, 4>>
impl<T> Matrix<T, Const<6>, Const<4>, ArrayStorage<T, 6, 4>>
sourcepub const fn new(
m11: T,
m12: T,
m13: T,
m14: T,
m21: T,
m22: T,
m23: T,
m24: T,
m31: T,
m32: T,
m33: T,
m34: T,
m41: T,
m42: T,
m43: T,
m44: T,
m51: T,
m52: T,
m53: T,
m54: T,
m61: T,
m62: T,
m63: T,
m64: T,
) -> Matrix<T, Const<6>, Const<4>, ArrayStorage<T, 6, 4>>
pub const fn new( m11: T, m12: T, m13: T, m14: T, m21: T, m22: T, m23: T, m24: T, m31: T, m32: T, m33: T, m34: T, m41: T, m42: T, m43: T, m44: T, m51: T, m52: T, m53: T, m54: T, m61: T, m62: T, m63: T, m64: T, ) -> Matrix<T, Const<6>, Const<4>, ArrayStorage<T, 6, 4>>
Initializes this matrix from its components.
source§impl<T> Matrix<T, Const<6>, Const<5>, ArrayStorage<T, 6, 5>>
impl<T> Matrix<T, Const<6>, Const<5>, ArrayStorage<T, 6, 5>>
sourcepub const fn new(
m11: T,
m12: T,
m13: T,
m14: T,
m15: T,
m21: T,
m22: T,
m23: T,
m24: T,
m25: T,
m31: T,
m32: T,
m33: T,
m34: T,
m35: T,
m41: T,
m42: T,
m43: T,
m44: T,
m45: T,
m51: T,
m52: T,
m53: T,
m54: T,
m55: T,
m61: T,
m62: T,
m63: T,
m64: T,
m65: T,
) -> Matrix<T, Const<6>, Const<5>, ArrayStorage<T, 6, 5>>
pub const fn new( m11: T, m12: T, m13: T, m14: T, m15: T, m21: T, m22: T, m23: T, m24: T, m25: T, m31: T, m32: T, m33: T, m34: T, m35: T, m41: T, m42: T, m43: T, m44: T, m45: T, m51: T, m52: T, m53: T, m54: T, m55: T, m61: T, m62: T, m63: T, m64: T, m65: T, ) -> Matrix<T, Const<6>, Const<5>, ArrayStorage<T, 6, 5>>
Initializes this matrix from its components.
source§impl<T, R> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
impl<T, R> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
sourcepub fn ith(
i: usize,
val: T,
) -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
pub fn ith( i: usize, val: T, ) -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
The column vector with val
as its i-th component.
sourcepub fn ith_axis(
i: usize,
) -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
pub fn ith_axis( i: usize, ) -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
The column unit vector with T::one()
as its i-th component.
sourcepub fn x() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
pub fn x() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
The column vector with a 1 as its first component, and zero elsewhere.
sourcepub fn y() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
pub fn y() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
The column vector with a 1 as its second component, and zero elsewhere.
sourcepub fn z() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
pub fn z() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
The column vector with a 1 as its third component, and zero elsewhere.
sourcepub fn w() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
pub fn w() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
The column vector with a 1 as its fourth component, and zero elsewhere.
sourcepub fn a() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
pub fn a() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
The column vector with a 1 as its fifth component, and zero elsewhere.
sourcepub fn b() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
pub fn b() -> Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>
The column vector with a 1 as its sixth component, and zero elsewhere.
sourcepub fn x_axis() -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
pub fn x_axis() -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
The unit column vector with a 1 as its first component, and zero elsewhere.
sourcepub fn y_axis() -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
pub fn y_axis() -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
The unit column vector with a 1 as its second component, and zero elsewhere.
sourcepub fn z_axis() -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
pub fn z_axis() -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
The unit column vector with a 1 as its third component, and zero elsewhere.
sourcepub fn w_axis() -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
pub fn w_axis() -> Unit<Matrix<T, R, Const<1>, <DefaultAllocator as Allocator<R>>::Buffer<T>>>
The unit column vector with a 1 as its fourth component, and zero elsewhere.
source§impl<'a, T, R, C, RStride, CStride> Matrix<T, R, C, ViewStorage<'a, T, R, C, RStride, CStride>>
impl<'a, T, R, C, RStride, CStride> Matrix<T, R, C, ViewStorage<'a, T, R, C, RStride, CStride>>
§Creating matrix views from &[T]
sourcepub unsafe fn from_slice_with_strides_generic_unchecked(
data: &'a [T],
start: usize,
nrows: R,
ncols: C,
rstride: RStride,
cstride: CStride,
) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, RStride, CStride>>
pub unsafe fn from_slice_with_strides_generic_unchecked( data: &'a [T], start: usize, nrows: R, ncols: C, rstride: RStride, cstride: CStride, ) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, RStride, CStride>>
Creates, without bounds checking, a matrix view from an array and with dimensions and strides specified by generic types instances.
§Safety
This method is unsafe because the input data array is not checked to contain enough elements.
The generic types R
, C
, RStride
, CStride
can either be type-level integers or integers wrapped with Dyn()
.
sourcepub fn from_slice_with_strides_generic(
data: &'a [T],
nrows: R,
ncols: C,
rstride: RStride,
cstride: CStride,
) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, RStride, CStride>>
pub fn from_slice_with_strides_generic( data: &'a [T], nrows: R, ncols: C, rstride: RStride, cstride: CStride, ) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, RStride, CStride>>
Creates a matrix view from an array and with dimensions and strides specified by generic types instances.
Panics if the input data array dose not contain enough elements.
The generic types R
, C
, RStride
, CStride
can either be type-level integers or integers wrapped with Dyn()
.
source§impl<'a, T, R, C> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
impl<'a, T, R, C> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
sourcepub unsafe fn from_slice_generic_unchecked(
data: &'a [T],
start: usize,
nrows: R,
ncols: C,
) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
pub unsafe fn from_slice_generic_unchecked( data: &'a [T], start: usize, nrows: R, ncols: C, ) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
Creates, without bound-checking, a matrix view from an array and with dimensions specified by generic types instances.
§Safety
This method is unsafe because the input data array is not checked to contain enough elements.
The generic types R
and C
can either be type-level integers or integers wrapped with Dyn()
.
sourcepub fn from_slice_generic(
data: &'a [T],
nrows: R,
ncols: C,
) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
pub fn from_slice_generic( data: &'a [T], nrows: R, ncols: C, ) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
Creates a matrix view from an array and with dimensions and strides specified by generic types instances.
Panics if the input data array dose not contain enough elements.
The generic types R
and C
can either be type-level integers or integers wrapped with Dyn()
.
source§impl<'a, T, R, C> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
impl<'a, T, R, C> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
sourcepub fn from_slice(
data: &'a [T],
) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
pub fn from_slice( data: &'a [T], ) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
Creates a new matrix view from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_unchecked(
data: &'a [T],
start: usize,
) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
pub unsafe fn from_slice_unchecked( data: &'a [T], start: usize, ) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Const<1>, R>>
Creates, without bound checking, a new matrix view from the given data array.
§Safety
data[start..start+rstride * cstride]
must be within bounds.
source§impl<'a, T, R, C> Matrix<T, R, C, ViewStorage<'a, T, R, C, Dyn, Dyn>>
impl<'a, T, R, C> Matrix<T, R, C, ViewStorage<'a, T, R, C, Dyn, Dyn>>
sourcepub fn from_slice_with_strides(
data: &'a [T],
rstride: usize,
cstride: usize,
) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Dyn, Dyn>>
pub fn from_slice_with_strides( data: &'a [T], rstride: usize, cstride: usize, ) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Dyn, Dyn>>
Creates a new matrix view with the specified strides from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_with_strides_unchecked(
data: &'a [T],
start: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Dyn, Dyn>>
pub unsafe fn from_slice_with_strides_unchecked( data: &'a [T], start: usize, rstride: usize, cstride: usize, ) -> Matrix<T, R, C, ViewStorage<'a, T, R, C, Dyn, Dyn>>
Creates, without bound checking, a new matrix view with the specified strides from the given data array.
§Safety
start
, rstride
, and cstride
, with the given matrix size will not index
outside of data
.
source§impl<'a, T, R> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Const<1>, R>>
impl<'a, T, R> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Const<1>, R>>
sourcepub fn from_slice(
data: &'a [T],
ncols: usize,
) -> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Const<1>, R>>
pub fn from_slice( data: &'a [T], ncols: usize, ) -> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Const<1>, R>>
Creates a new matrix view from the given data array.
Panics if data
does not contain enough elements.
source§impl<'a, T, R> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Dyn, Dyn>>
impl<'a, T, R> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Dyn, Dyn>>
sourcepub fn from_slice_with_strides(
data: &'a [T],
ncols: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Dyn, Dyn>>
pub fn from_slice_with_strides( data: &'a [T], ncols: usize, rstride: usize, cstride: usize, ) -> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Dyn, Dyn>>
Creates a new matrix view with the specified strides from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_with_strides_unchecked(
data: &'a [T],
start: usize,
ncols: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Dyn, Dyn>>
pub unsafe fn from_slice_with_strides_unchecked( data: &'a [T], start: usize, ncols: usize, rstride: usize, cstride: usize, ) -> Matrix<T, R, Dyn, ViewStorage<'a, T, R, Dyn, Dyn, Dyn>>
Creates, without bound checking, a new matrix view with the specified strides from the given data array.
§Safety
start
, rstride
, and cstride
, with the given matrix size will not index
outside of data
.
source§impl<'a, T, C> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Const<1>, Dyn>>
impl<'a, T, C> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Const<1>, Dyn>>
sourcepub fn from_slice(
data: &'a [T],
nrows: usize,
) -> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Const<1>, Dyn>>
pub fn from_slice( data: &'a [T], nrows: usize, ) -> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Const<1>, Dyn>>
Creates a new matrix view from the given data array.
Panics if data
does not contain enough elements.
source§impl<'a, T, C> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Dyn, Dyn>>
impl<'a, T, C> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Dyn, Dyn>>
sourcepub fn from_slice_with_strides(
data: &'a [T],
nrows: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Dyn, Dyn>>
pub fn from_slice_with_strides( data: &'a [T], nrows: usize, rstride: usize, cstride: usize, ) -> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Dyn, Dyn>>
Creates a new matrix view with the specified strides from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_with_strides_unchecked(
data: &'a [T],
start: usize,
nrows: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Dyn, Dyn>>
pub unsafe fn from_slice_with_strides_unchecked( data: &'a [T], start: usize, nrows: usize, rstride: usize, cstride: usize, ) -> Matrix<T, Dyn, C, ViewStorage<'a, T, Dyn, C, Dyn, Dyn>>
Creates, without bound checking, a new matrix view with the specified strides from the given data array.
§Safety
start
, rstride
, and cstride
, with the given matrix size will not index
outside of data
.
source§impl<'a, T> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Const<1>, Dyn>>where
T: Scalar,
impl<'a, T> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Const<1>, Dyn>>where
T: Scalar,
sourcepub fn from_slice(
data: &'a [T],
nrows: usize,
ncols: usize,
) -> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Const<1>, Dyn>>
pub fn from_slice( data: &'a [T], nrows: usize, ncols: usize, ) -> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Const<1>, Dyn>>
Creates a new matrix view from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_unchecked(
data: &'a [T],
start: usize,
nrows: usize,
ncols: usize,
) -> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Const<1>, Dyn>>
pub unsafe fn from_slice_unchecked( data: &'a [T], start: usize, nrows: usize, ncols: usize, ) -> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Const<1>, Dyn>>
Creates, without bound checking, a new matrix view from the given data array.
§Safety
data[start..start+rstride * cstride]
must be within bounds.
source§impl<'a, T> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Dyn, Dyn>>where
T: Scalar,
impl<'a, T> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Dyn, Dyn>>where
T: Scalar,
sourcepub fn from_slice_with_strides(
data: &'a [T],
nrows: usize,
ncols: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Dyn, Dyn>>
pub fn from_slice_with_strides( data: &'a [T], nrows: usize, ncols: usize, rstride: usize, cstride: usize, ) -> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Dyn, Dyn>>
Creates a new matrix view with the specified strides from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_with_strides_unchecked(
data: &'a [T],
start: usize,
nrows: usize,
ncols: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Dyn, Dyn>>
pub unsafe fn from_slice_with_strides_unchecked( data: &'a [T], start: usize, nrows: usize, ncols: usize, rstride: usize, cstride: usize, ) -> Matrix<T, Dyn, Dyn, ViewStorage<'a, T, Dyn, Dyn, Dyn, Dyn>>
Creates, without bound checking, a new matrix view with the specified strides from the given data array.
§Safety
start
, rstride
, and cstride
, with the given matrix size will not index
outside of data
.
source§impl<'a, T, R, C, RStride, CStride> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, RStride, CStride>>
impl<'a, T, R, C, RStride, CStride> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, RStride, CStride>>
§Creating mutable matrix views from &mut [T]
sourcepub unsafe fn from_slice_with_strides_generic_unchecked(
data: &'a mut [T],
start: usize,
nrows: R,
ncols: C,
rstride: RStride,
cstride: CStride,
) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, RStride, CStride>>
pub unsafe fn from_slice_with_strides_generic_unchecked( data: &'a mut [T], start: usize, nrows: R, ncols: C, rstride: RStride, cstride: CStride, ) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, RStride, CStride>>
Creates, without bound-checking, a mutable matrix view from an array and with dimensions and strides specified by generic types instances.
§Safety
This method is unsafe because the input data array is not checked to contain enough elements.
The generic types R
, C
, RStride
, CStride
can either be type-level integers or integers wrapped with Dyn()
.
sourcepub fn from_slice_with_strides_generic(
data: &'a mut [T],
nrows: R,
ncols: C,
rstride: RStride,
cstride: CStride,
) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, RStride, CStride>>
pub fn from_slice_with_strides_generic( data: &'a mut [T], nrows: R, ncols: C, rstride: RStride, cstride: CStride, ) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, RStride, CStride>>
Creates a mutable matrix view from an array and with dimensions and strides specified by generic types instances.
Panics if the input data array dose not contain enough elements.
The generic types R
, C
, RStride
, CStride
can either be type-level integers or integers wrapped with Dyn()
.
source§impl<'a, T, R, C> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
impl<'a, T, R, C> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
sourcepub unsafe fn from_slice_generic_unchecked(
data: &'a mut [T],
start: usize,
nrows: R,
ncols: C,
) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
pub unsafe fn from_slice_generic_unchecked( data: &'a mut [T], start: usize, nrows: R, ncols: C, ) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
Creates, without bound-checking, a mutable matrix view from an array and with dimensions specified by generic types instances.
§Safety
This method is unsafe because the input data array is not checked to contain enough elements.
The generic types R
and C
can either be type-level integers or integers wrapped with Dyn()
.
sourcepub fn from_slice_generic(
data: &'a mut [T],
nrows: R,
ncols: C,
) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
pub fn from_slice_generic( data: &'a mut [T], nrows: R, ncols: C, ) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
Creates a mutable matrix view from an array and with dimensions and strides specified by generic types instances.
Panics if the input data array dose not contain enough elements.
The generic types R
and C
can either be type-level integers or integers wrapped with Dyn()
.
source§impl<'a, T, R, C> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
impl<'a, T, R, C> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
sourcepub fn from_slice(
data: &'a mut [T],
) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
pub fn from_slice( data: &'a mut [T], ) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
Creates a new mutable matrix view from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_unchecked(
data: &'a mut [T],
start: usize,
) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
pub unsafe fn from_slice_unchecked( data: &'a mut [T], start: usize, ) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Const<1>, R>>
Creates, without bound checking, a new mutable matrix view from the given data array.
§Safety
data[start..start+(R * C)]
must be within bounds.
source§impl<'a, T, R, C> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Dyn, Dyn>>
impl<'a, T, R, C> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Dyn, Dyn>>
sourcepub fn from_slice_with_strides_mut(
data: &'a mut [T],
rstride: usize,
cstride: usize,
) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Dyn, Dyn>>
pub fn from_slice_with_strides_mut( data: &'a mut [T], rstride: usize, cstride: usize, ) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Dyn, Dyn>>
Creates a new mutable matrix view with the specified strides from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_with_strides_unchecked(
data: &'a mut [T],
start: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Dyn, Dyn>>
pub unsafe fn from_slice_with_strides_unchecked( data: &'a mut [T], start: usize, rstride: usize, cstride: usize, ) -> Matrix<T, R, C, ViewStorageMut<'a, T, R, C, Dyn, Dyn>>
Creates, without bound checking, a new mutable matrix view with the specified strides from the given data array.
§Safety
data[start..start+rstride * cstride]
must be within bounds.
source§impl<'a, T, R> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Const<1>, R>>
impl<'a, T, R> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Const<1>, R>>
sourcepub fn from_slice(
data: &'a mut [T],
ncols: usize,
) -> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Const<1>, R>>
pub fn from_slice( data: &'a mut [T], ncols: usize, ) -> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Const<1>, R>>
Creates a new mutable matrix view from the given data array.
Panics if data
does not contain enough elements.
source§impl<'a, T, R> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Dyn, Dyn>>
impl<'a, T, R> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Dyn, Dyn>>
sourcepub fn from_slice_with_strides_mut(
data: &'a mut [T],
ncols: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Dyn, Dyn>>
pub fn from_slice_with_strides_mut( data: &'a mut [T], ncols: usize, rstride: usize, cstride: usize, ) -> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Dyn, Dyn>>
Creates a new mutable matrix view with the specified strides from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_with_strides_unchecked(
data: &'a mut [T],
start: usize,
ncols: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Dyn, Dyn>>
pub unsafe fn from_slice_with_strides_unchecked( data: &'a mut [T], start: usize, ncols: usize, rstride: usize, cstride: usize, ) -> Matrix<T, R, Dyn, ViewStorageMut<'a, T, R, Dyn, Dyn, Dyn>>
Creates, without bound checking, a new mutable matrix view with the specified strides from the given data array.
§Safety
data[start..start+rstride * cstride]
must be within bounds.
source§impl<'a, T, C> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Const<1>, Dyn>>
impl<'a, T, C> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Const<1>, Dyn>>
sourcepub fn from_slice(
data: &'a mut [T],
nrows: usize,
) -> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Const<1>, Dyn>>
pub fn from_slice( data: &'a mut [T], nrows: usize, ) -> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Const<1>, Dyn>>
Creates a new mutable matrix view from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_unchecked(
data: &'a mut [T],
start: usize,
nrows: usize,
) -> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Const<1>, Dyn>>
pub unsafe fn from_slice_unchecked( data: &'a mut [T], start: usize, nrows: usize, ) -> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Const<1>, Dyn>>
Creates, without bound checking, a new mutable matrix view from the given data array.
§Safety
data[start..start+(R * C)]
must be within bounds.
source§impl<'a, T, C> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Dyn, Dyn>>
impl<'a, T, C> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Dyn, Dyn>>
sourcepub fn from_slice_with_strides_mut(
data: &'a mut [T],
nrows: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Dyn, Dyn>>
pub fn from_slice_with_strides_mut( data: &'a mut [T], nrows: usize, rstride: usize, cstride: usize, ) -> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Dyn, Dyn>>
Creates a new mutable matrix view with the specified strides from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_with_strides_unchecked(
data: &'a mut [T],
start: usize,
nrows: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Dyn, Dyn>>
pub unsafe fn from_slice_with_strides_unchecked( data: &'a mut [T], start: usize, nrows: usize, rstride: usize, cstride: usize, ) -> Matrix<T, Dyn, C, ViewStorageMut<'a, T, Dyn, C, Dyn, Dyn>>
Creates, without bound checking, a new mutable matrix view with the specified strides from the given data array.
§Safety
data[start..start+rstride * cstride]
must be within bounds.
source§impl<'a, T> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Const<1>, Dyn>>where
T: Scalar,
impl<'a, T> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Const<1>, Dyn>>where
T: Scalar,
sourcepub fn from_slice(
data: &'a mut [T],
nrows: usize,
ncols: usize,
) -> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Const<1>, Dyn>>
pub fn from_slice( data: &'a mut [T], nrows: usize, ncols: usize, ) -> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Const<1>, Dyn>>
Creates a new mutable matrix view from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_unchecked(
data: &'a mut [T],
start: usize,
nrows: usize,
ncols: usize,
) -> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Const<1>, Dyn>>
pub unsafe fn from_slice_unchecked( data: &'a mut [T], start: usize, nrows: usize, ncols: usize, ) -> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Const<1>, Dyn>>
Creates, without bound checking, a new mutable matrix view from the given data array.
§Safety
data[start..start+(R * C)]
must be within bounds.
source§impl<'a, T> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Dyn, Dyn>>where
T: Scalar,
impl<'a, T> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Dyn, Dyn>>where
T: Scalar,
sourcepub fn from_slice_with_strides_mut(
data: &'a mut [T],
nrows: usize,
ncols: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Dyn, Dyn>>
pub fn from_slice_with_strides_mut( data: &'a mut [T], nrows: usize, ncols: usize, rstride: usize, cstride: usize, ) -> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Dyn, Dyn>>
Creates a new mutable matrix view with the specified strides from the given data array.
Panics if data
does not contain enough elements.
sourcepub unsafe fn from_slice_with_strides_unchecked(
data: &'a mut [T],
start: usize,
nrows: usize,
ncols: usize,
rstride: usize,
cstride: usize,
) -> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Dyn, Dyn>>
pub unsafe fn from_slice_with_strides_unchecked( data: &'a mut [T], start: usize, nrows: usize, ncols: usize, rstride: usize, cstride: usize, ) -> Matrix<T, Dyn, Dyn, ViewStorageMut<'a, T, Dyn, Dyn, Dyn, Dyn>>
Creates, without bound checking, a new mutable matrix view with the specified strides from the given data array.
§Safety
data[start..start+rstride * cstride]
must be within bounds.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Triangular matrix extraction
sourcepub fn upper_triangle(
&self,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
pub fn upper_triangle(
&self,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
Extracts the upper triangular part of this matrix (including the diagonal).
sourcepub fn lower_triangle(
&self,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
pub fn lower_triangle(
&self,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
Extracts the lower triangular part of this matrix (including the diagonal).
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Rows and columns extraction
sourcepub fn select_rows<'a, I>(
&self,
irows: I,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
I: IntoIterator<Item = &'a usize>,
<I as IntoIterator>::IntoIter: ExactSizeIterator + Clone,
DefaultAllocator: Allocator<Dyn, C>,
pub fn select_rows<'a, I>(
&self,
irows: I,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>where
I: IntoIterator<Item = &'a usize>,
<I as IntoIterator>::IntoIter: ExactSizeIterator + Clone,
DefaultAllocator: Allocator<Dyn, C>,
Creates a new matrix by extracting the given set of rows from self
.
sourcepub fn select_columns<'a, I>(
&self,
icols: I,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = &'a usize>,
<I as IntoIterator>::IntoIter: ExactSizeIterator,
DefaultAllocator: Allocator<R, Dyn>,
pub fn select_columns<'a, I>(
&self,
icols: I,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>where
I: IntoIterator<Item = &'a usize>,
<I as IntoIterator>::IntoIter: ExactSizeIterator,
DefaultAllocator: Allocator<R, Dyn>,
Creates a new matrix by extracting the given set of columns from self
.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Set rows, columns, and diagonal
sourcepub fn set_diagonal<R2, S2>(&mut self, diag: &Matrix<T, R2, Const<1>, S2>)where
R2: Dim,
R: DimMin<C>,
S2: RawStorage<T, R2>,
ShapeConstraint: DimEq<<R as DimMin<C>>::Output, R2>,
pub fn set_diagonal<R2, S2>(&mut self, diag: &Matrix<T, R2, Const<1>, S2>)where
R2: Dim,
R: DimMin<C>,
S2: RawStorage<T, R2>,
ShapeConstraint: DimEq<<R as DimMin<C>>::Output, R2>,
Fills the diagonal of this matrix with the content of the given vector.
sourcepub fn set_partial_diagonal(&mut self, diag: impl Iterator<Item = T>)
pub fn set_partial_diagonal(&mut self, diag: impl Iterator<Item = T>)
Fills the diagonal of this matrix with the content of the given iterator.
This will fill as many diagonal elements as the iterator yields, up to the
minimum of the number of rows and columns of self
, and starting with the
diagonal element at index (0, 0).
sourcepub fn set_row<C2, S2>(&mut self, i: usize, row: &Matrix<T, Const<1>, C2, S2>)
pub fn set_row<C2, S2>(&mut self, i: usize, row: &Matrix<T, Const<1>, C2, S2>)
Fills the selected row of this matrix with the content of the given vector.
sourcepub fn set_column<R2, S2>(
&mut self,
i: usize,
column: &Matrix<T, R2, Const<1>, S2>,
)
pub fn set_column<R2, S2>( &mut self, i: usize, column: &Matrix<T, R2, Const<1>, S2>, )
Fills the selected column of this matrix with the content of the given vector.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§In-place filling
sourcepub fn fill_with(&mut self, val: impl Fn() -> T)
pub fn fill_with(&mut self, val: impl Fn() -> T)
Sets all the elements of this matrix to the value returned by the closure.
sourcepub fn fill_with_identity(&mut self)
pub fn fill_with_identity(&mut self)
Fills self
with the identity matrix.
sourcepub fn fill_diagonal(&mut self, val: T)where
T: Scalar,
pub fn fill_diagonal(&mut self, val: T)where
T: Scalar,
Sets all the diagonal elements of this matrix to val
.
sourcepub fn fill_row(&mut self, i: usize, val: T)where
T: Scalar,
pub fn fill_row(&mut self, i: usize, val: T)where
T: Scalar,
Sets all the elements of the selected row to val
.
sourcepub fn fill_column(&mut self, j: usize, val: T)where
T: Scalar,
pub fn fill_column(&mut self, j: usize, val: T)where
T: Scalar,
Sets all the elements of the selected column to val
.
sourcepub fn fill_lower_triangle(&mut self, val: T, shift: usize)where
T: Scalar,
pub fn fill_lower_triangle(&mut self, val: T, shift: usize)where
T: Scalar,
Sets all the elements of the lower-triangular part of this matrix to val
.
The parameter shift
allows some subdiagonals to be left untouched:
- If
shift = 0
then the diagonal is overwritten as well. - If
shift = 1
then the diagonal is left untouched. - If
shift > 1
, then the diagonal and the firstshift - 1
subdiagonals are left untouched.
sourcepub fn fill_upper_triangle(&mut self, val: T, shift: usize)where
T: Scalar,
pub fn fill_upper_triangle(&mut self, val: T, shift: usize)where
T: Scalar,
Sets all the elements of the lower-triangular part of this matrix to val
.
The parameter shift
allows some superdiagonals to be left untouched:
- If
shift = 0
then the diagonal is overwritten as well. - If
shift = 1
then the diagonal is left untouched. - If
shift > 1
, then the diagonal and the firstshift - 1
superdiagonals are left untouched.
source§impl<T, D, S> Matrix<T, D, D, S>
impl<T, D, S> Matrix<T, D, D, S>
sourcepub fn fill_lower_triangle_with_upper_triangle(&mut self)
pub fn fill_lower_triangle_with_upper_triangle(&mut self)
Copies the upper-triangle of this matrix to its lower-triangular part.
This makes the matrix symmetric. Panics if the matrix is not square.
sourcepub fn fill_upper_triangle_with_lower_triangle(&mut self)
pub fn fill_upper_triangle_with_lower_triangle(&mut self)
Copies the upper-triangle of this matrix to its upper-triangular part.
This makes the matrix symmetric. Panics if the matrix is not square.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Rows and columns removal
sourcepub fn remove_column(
self,
i: usize,
) -> Matrix<T, R, <C as DimSub<Const<1>>>::Output, <DefaultAllocator as Allocator<R, <C as DimSub<Const<1>>>::Output>>::Buffer<T>>where
C: DimSub<Const<1>>,
DefaultAllocator: Reallocator<T, R, C, R, <C as DimSub<Const<1>>>::Output>,
pub fn remove_column(
self,
i: usize,
) -> Matrix<T, R, <C as DimSub<Const<1>>>::Output, <DefaultAllocator as Allocator<R, <C as DimSub<Const<1>>>::Output>>::Buffer<T>>where
C: DimSub<Const<1>>,
DefaultAllocator: Reallocator<T, R, C, R, <C as DimSub<Const<1>>>::Output>,
Removes the i
-th column from this matrix.
sourcepub fn remove_columns_at(
self,
indices: &[usize],
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn remove_columns_at( self, indices: &[usize], ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Removes all columns in indices
sourcepub fn remove_rows_at(
self,
indices: &[usize],
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn remove_rows_at( self, indices: &[usize], ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Removes all rows in indices
sourcepub fn remove_fixed_columns<const D: usize>(
self,
i: usize,
) -> Matrix<T, R, <C as DimSub<Const<D>>>::Output, <DefaultAllocator as Allocator<R, <C as DimSub<Const<D>>>::Output>>::Buffer<T>>where
C: DimSub<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, R, <C as DimSub<Const<D>>>::Output>,
pub fn remove_fixed_columns<const D: usize>(
self,
i: usize,
) -> Matrix<T, R, <C as DimSub<Const<D>>>::Output, <DefaultAllocator as Allocator<R, <C as DimSub<Const<D>>>::Output>>::Buffer<T>>where
C: DimSub<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, R, <C as DimSub<Const<D>>>::Output>,
Removes D::dim()
consecutive columns from this matrix, starting with the i
-th
(included).
sourcepub fn remove_columns(
self,
i: usize,
n: usize,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn remove_columns( self, i: usize, n: usize, ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Removes n
consecutive columns from this matrix, starting with the i
-th (included).
sourcepub fn remove_columns_generic<D>(
self,
i: usize,
nremove: D,
) -> Matrix<T, R, <C as DimSub<D>>::Output, <DefaultAllocator as Allocator<R, <C as DimSub<D>>::Output>>::Buffer<T>>
pub fn remove_columns_generic<D>( self, i: usize, nremove: D, ) -> Matrix<T, R, <C as DimSub<D>>::Output, <DefaultAllocator as Allocator<R, <C as DimSub<D>>::Output>>::Buffer<T>>
Removes nremove.value()
columns from this matrix, starting with the i
-th (included).
This is the generic implementation of .remove_columns(...)
and
.remove_fixed_columns(...)
which have nicer API interfaces.
sourcepub fn remove_row(
self,
i: usize,
) -> Matrix<T, <R as DimSub<Const<1>>>::Output, C, <DefaultAllocator as Allocator<<R as DimSub<Const<1>>>::Output, C>>::Buffer<T>>where
R: DimSub<Const<1>>,
DefaultAllocator: Reallocator<T, R, C, <R as DimSub<Const<1>>>::Output, C>,
pub fn remove_row(
self,
i: usize,
) -> Matrix<T, <R as DimSub<Const<1>>>::Output, C, <DefaultAllocator as Allocator<<R as DimSub<Const<1>>>::Output, C>>::Buffer<T>>where
R: DimSub<Const<1>>,
DefaultAllocator: Reallocator<T, R, C, <R as DimSub<Const<1>>>::Output, C>,
Removes the i
-th row from this matrix.
sourcepub fn remove_fixed_rows<const D: usize>(
self,
i: usize,
) -> Matrix<T, <R as DimSub<Const<D>>>::Output, C, <DefaultAllocator as Allocator<<R as DimSub<Const<D>>>::Output, C>>::Buffer<T>>where
R: DimSub<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, <R as DimSub<Const<D>>>::Output, C>,
pub fn remove_fixed_rows<const D: usize>(
self,
i: usize,
) -> Matrix<T, <R as DimSub<Const<D>>>::Output, C, <DefaultAllocator as Allocator<<R as DimSub<Const<D>>>::Output, C>>::Buffer<T>>where
R: DimSub<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, <R as DimSub<Const<D>>>::Output, C>,
Removes D::dim()
consecutive rows from this matrix, starting with the i
-th (included).
sourcepub fn remove_rows(
self,
i: usize,
n: usize,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn remove_rows( self, i: usize, n: usize, ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Removes n
consecutive rows from this matrix, starting with the i
-th (included).
sourcepub fn remove_rows_generic<D>(
self,
i: usize,
nremove: D,
) -> Matrix<T, <R as DimSub<D>>::Output, C, <DefaultAllocator as Allocator<<R as DimSub<D>>::Output, C>>::Buffer<T>>
pub fn remove_rows_generic<D>( self, i: usize, nremove: D, ) -> Matrix<T, <R as DimSub<D>>::Output, C, <DefaultAllocator as Allocator<<R as DimSub<D>>::Output, C>>::Buffer<T>>
Removes nremove.value()
rows from this matrix, starting with the i
-th (included).
This is the generic implementation of .remove_rows(...)
and .remove_fixed_rows(...)
which have nicer API interfaces.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Rows and columns insertion
sourcepub fn insert_column(
self,
i: usize,
val: T,
) -> Matrix<T, R, <C as DimAdd<Const<1>>>::Output, <DefaultAllocator as Allocator<R, <C as DimAdd<Const<1>>>::Output>>::Buffer<T>>where
C: DimAdd<Const<1>>,
DefaultAllocator: Reallocator<T, R, C, R, <C as DimAdd<Const<1>>>::Output>,
pub fn insert_column(
self,
i: usize,
val: T,
) -> Matrix<T, R, <C as DimAdd<Const<1>>>::Output, <DefaultAllocator as Allocator<R, <C as DimAdd<Const<1>>>::Output>>::Buffer<T>>where
C: DimAdd<Const<1>>,
DefaultAllocator: Reallocator<T, R, C, R, <C as DimAdd<Const<1>>>::Output>,
Inserts a column filled with val
at the i-th
position.
sourcepub fn insert_fixed_columns<const D: usize>(
self,
i: usize,
val: T,
) -> Matrix<T, R, <C as DimAdd<Const<D>>>::Output, <DefaultAllocator as Allocator<R, <C as DimAdd<Const<D>>>::Output>>::Buffer<T>>where
C: DimAdd<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, R, <C as DimAdd<Const<D>>>::Output>,
pub fn insert_fixed_columns<const D: usize>(
self,
i: usize,
val: T,
) -> Matrix<T, R, <C as DimAdd<Const<D>>>::Output, <DefaultAllocator as Allocator<R, <C as DimAdd<Const<D>>>::Output>>::Buffer<T>>where
C: DimAdd<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, R, <C as DimAdd<Const<D>>>::Output>,
Inserts D
columns filled with val
starting at the i-th
position.
sourcepub fn insert_columns(
self,
i: usize,
n: usize,
val: T,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn insert_columns( self, i: usize, n: usize, val: T, ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Inserts n
columns filled with val
starting at the i-th
position.
sourcepub unsafe fn insert_columns_generic_uninitialized<D>(
self,
i: usize,
ninsert: D,
) -> Matrix<MaybeUninit<T>, R, <C as DimAdd<D>>::Output, <DefaultAllocator as Allocator<R, <C as DimAdd<D>>::Output>>::BufferUninit<T>>
pub unsafe fn insert_columns_generic_uninitialized<D>( self, i: usize, ninsert: D, ) -> Matrix<MaybeUninit<T>, R, <C as DimAdd<D>>::Output, <DefaultAllocator as Allocator<R, <C as DimAdd<D>>::Output>>::BufferUninit<T>>
Inserts ninsert.value()
columns starting at the i-th
place of this matrix.
§Safety
The output matrix has all its elements initialized except for the the components of the added columns.
sourcepub fn insert_row(
self,
i: usize,
val: T,
) -> Matrix<T, <R as DimAdd<Const<1>>>::Output, C, <DefaultAllocator as Allocator<<R as DimAdd<Const<1>>>::Output, C>>::Buffer<T>>where
R: DimAdd<Const<1>>,
DefaultAllocator: Reallocator<T, R, C, <R as DimAdd<Const<1>>>::Output, C>,
pub fn insert_row(
self,
i: usize,
val: T,
) -> Matrix<T, <R as DimAdd<Const<1>>>::Output, C, <DefaultAllocator as Allocator<<R as DimAdd<Const<1>>>::Output, C>>::Buffer<T>>where
R: DimAdd<Const<1>>,
DefaultAllocator: Reallocator<T, R, C, <R as DimAdd<Const<1>>>::Output, C>,
Inserts a row filled with val
at the i-th
position.
sourcepub fn insert_fixed_rows<const D: usize>(
self,
i: usize,
val: T,
) -> Matrix<T, <R as DimAdd<Const<D>>>::Output, C, <DefaultAllocator as Allocator<<R as DimAdd<Const<D>>>::Output, C>>::Buffer<T>>where
R: DimAdd<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, <R as DimAdd<Const<D>>>::Output, C>,
pub fn insert_fixed_rows<const D: usize>(
self,
i: usize,
val: T,
) -> Matrix<T, <R as DimAdd<Const<D>>>::Output, C, <DefaultAllocator as Allocator<<R as DimAdd<Const<D>>>::Output, C>>::Buffer<T>>where
R: DimAdd<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, <R as DimAdd<Const<D>>>::Output, C>,
Inserts D::dim()
rows filled with val
starting at the i-th
position.
sourcepub fn insert_rows(
self,
i: usize,
n: usize,
val: T,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn insert_rows( self, i: usize, n: usize, val: T, ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Inserts n
rows filled with val
starting at the i-th
position.
sourcepub unsafe fn insert_rows_generic_uninitialized<D>(
self,
i: usize,
ninsert: D,
) -> Matrix<MaybeUninit<T>, <R as DimAdd<D>>::Output, C, <DefaultAllocator as Allocator<<R as DimAdd<D>>::Output, C>>::BufferUninit<T>>
pub unsafe fn insert_rows_generic_uninitialized<D>( self, i: usize, ninsert: D, ) -> Matrix<MaybeUninit<T>, <R as DimAdd<D>>::Output, C, <DefaultAllocator as Allocator<<R as DimAdd<D>>::Output, C>>::BufferUninit<T>>
Inserts ninsert.value()
rows at the i-th
place of this matrix.
§Safety
The added rows values are not initialized.
This is the generic implementation of .insert_rows(...)
and
.insert_fixed_rows(...)
which have nicer API interfaces.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Resizing and reshaping
sourcepub fn resize(
self,
new_nrows: usize,
new_ncols: usize,
val: T,
) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
pub fn resize( self, new_nrows: usize, new_ncols: usize, val: T, ) -> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>
Resizes this matrix so that it contains new_nrows
rows and new_ncols
columns.
The values are copied such that self[(i, j)] == result[(i, j)]
. If the result has more
rows and/or columns than self
, then the extra rows or columns are filled with val
.
sourcepub fn resize_vertically(
self,
new_nrows: usize,
val: T,
) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
pub fn resize_vertically( self, new_nrows: usize, val: T, ) -> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
Resizes this matrix vertically, i.e., so that it contains new_nrows
rows while keeping the same number of columns.
The values are copied such that self[(i, j)] == result[(i, j)]
. If the result has more
rows than self
, then the extra rows are filled with val
.
sourcepub fn resize_horizontally(
self,
new_ncols: usize,
val: T,
) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
pub fn resize_horizontally( self, new_ncols: usize, val: T, ) -> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
Resizes this matrix horizontally, i.e., so that it contains new_ncolumns
columns while keeping the same number of columns.
The values are copied such that self[(i, j)] == result[(i, j)]
. If the result has more
columns than self
, then the extra columns are filled with val
.
sourcepub fn fixed_resize<const R2: usize, const C2: usize>(
self,
val: T,
) -> Matrix<T, Const<R2>, Const<C2>, <DefaultAllocator as Allocator<Const<R2>, Const<C2>>>::Buffer<T>>
pub fn fixed_resize<const R2: usize, const C2: usize>( self, val: T, ) -> Matrix<T, Const<R2>, Const<C2>, <DefaultAllocator as Allocator<Const<R2>, Const<C2>>>::Buffer<T>>
Resizes this matrix so that it contains R2::value()
rows and C2::value()
columns.
The values are copied such that self[(i, j)] == result[(i, j)]
. If the result has more
rows and/or columns than self
, then the extra rows or columns are filled with val
.
sourcepub fn resize_generic<R2, C2>(
self,
new_nrows: R2,
new_ncols: C2,
val: T,
) -> Matrix<T, R2, C2, <DefaultAllocator as Allocator<R2, C2>>::Buffer<T>>
pub fn resize_generic<R2, C2>( self, new_nrows: R2, new_ncols: C2, val: T, ) -> Matrix<T, R2, C2, <DefaultAllocator as Allocator<R2, C2>>::Buffer<T>>
Resizes self
such that it has dimensions new_nrows × new_ncols
.
The values are copied such that self[(i, j)] == result[(i, j)]
. If the result has more
rows and/or columns than self
, then the extra rows or columns are filled with val
.
sourcepub fn reshape_generic<R2, C2>(
self,
new_nrows: R2,
new_ncols: C2,
) -> Matrix<T, R2, C2, <S as ReshapableStorage<T, R, C, R2, C2>>::Output>
pub fn reshape_generic<R2, C2>( self, new_nrows: R2, new_ncols: C2, ) -> Matrix<T, R2, C2, <S as ReshapableStorage<T, R, C, R2, C2>>::Output>
Reshapes self
such that it has dimensions new_nrows × new_ncols
.
This will reinterpret self
as if it is a matrix with new_nrows
rows and new_ncols
columns. The arrangements of the component in the output matrix are the same as what
would be obtained by Matrix::from_slice_generic(self.as_slice(), new_nrows, new_ncols)
.
If self
is a dynamically-sized matrix, then its components are neither copied nor moved.
If self
is staticyll-sized, then a copy may happen in some situations.
This function will panic if the given dimensions are such that the number of elements of
the input matrix are not equal to the number of elements of the output matrix.
§Examples
let m1 = Matrix2x3::new(
1.1, 1.2, 1.3,
2.1, 2.2, 2.3
);
let m2 = Matrix3x2::new(
1.1, 2.2,
2.1, 1.3,
1.2, 2.3
);
let reshaped = m1.reshape_generic(Const::<3>, Const::<2>);
assert_eq!(reshaped, m2);
let dm1 = DMatrix::from_row_slice(
4,
3,
&[
1.0, 0.0, 0.0,
0.0, 0.0, 1.0,
0.0, 0.0, 0.0,
0.0, 1.0, 0.0
],
);
let dm2 = DMatrix::from_row_slice(
6,
2,
&[
1.0, 0.0,
0.0, 1.0,
0.0, 0.0,
0.0, 1.0,
0.0, 0.0,
0.0, 0.0,
],
);
let reshaped = dm1.reshape_generic(Dyn(6), Dyn(2));
assert_eq!(reshaped, dm2);
source§impl<T> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
T: Scalar,
impl<T> Matrix<T, Dyn, Dyn, <DefaultAllocator as Allocator<Dyn, Dyn>>::Buffer<T>>where
T: Scalar,
§In-place resizing
sourcepub fn resize_mut(&mut self, new_nrows: usize, new_ncols: usize, val: T)
pub fn resize_mut(&mut self, new_nrows: usize, new_ncols: usize, val: T)
Resizes this matrix in-place.
The values are copied such that self[(i, j)] == result[(i, j)]
. If the result has more
rows and/or columns than self
, then the extra rows or columns are filled with val
.
Defined only for owned fully-dynamic matrices, i.e., DMatrix
.
source§impl<T, C> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
impl<T, C> Matrix<T, Dyn, C, <DefaultAllocator as Allocator<Dyn, C>>::Buffer<T>>
sourcepub fn resize_vertically_mut(&mut self, new_nrows: usize, val: T)
pub fn resize_vertically_mut(&mut self, new_nrows: usize, val: T)
Changes the number of rows of this matrix in-place.
The values are copied such that self[(i, j)] == result[(i, j)]
. If the result has more
rows than self
, then the extra rows are filled with val
.
Defined only for owned matrices with a dynamic number of rows (for example, DVector
).
source§impl<T, R> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
impl<T, R> Matrix<T, R, Dyn, <DefaultAllocator as Allocator<R, Dyn>>::Buffer<T>>
sourcepub fn resize_horizontally_mut(&mut self, new_ncols: usize, val: T)
pub fn resize_horizontally_mut(&mut self, new_ncols: usize, val: T)
Changes the number of column of this matrix in-place.
The values are copied such that self[(i, j)] == result[(i, j)]
. If the result has more
columns than self
, then the extra columns are filled with val
.
Defined only for owned matrices with a dynamic number of columns (for example, DVector
).
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Views based on ranges
§Indices to Individual Elements
§Two-Dimensional Indices
let matrix = Matrix2::new(0, 2,
1, 3);
assert_eq!(matrix.index((0, 0)), &0);
assert_eq!(matrix.index((1, 0)), &1);
assert_eq!(matrix.index((0, 1)), &2);
assert_eq!(matrix.index((1, 1)), &3);
§Linear Address Indexing
let matrix = Matrix2::new(0, 2,
1, 3);
assert_eq!(matrix.get(0), Some(&0));
assert_eq!(matrix.get(1), Some(&1));
assert_eq!(matrix.get(2), Some(&2));
assert_eq!(matrix.get(3), Some(&3));
§Indices to Individual Rows and Columns
§Index to a Row
let matrix = Matrix2::new(0, 2,
1, 3);
assert!(matrix.index((0, ..))
.eq(&Matrix1x2::new(0, 2)));
§Index to a Column
let matrix = Matrix2::new(0, 2,
1, 3);
assert!(matrix.index((.., 0))
.eq(&Matrix2x1::new(0,
1)));
§Indices to Parts of Individual Rows and Columns
§Index to a Partial Row
let matrix = Matrix3::new(0, 3, 6,
1, 4, 7,
2, 5, 8);
assert!(matrix.index((0, ..2))
.eq(&Matrix1x2::new(0, 3)));
§Index to a Partial Column
let matrix = Matrix3::new(0, 3, 6,
1, 4, 7,
2, 5, 8);
assert!(matrix.index((..2, 0))
.eq(&Matrix2x1::new(0,
1)));
assert!(matrix.index((Const::<1>.., 0))
.eq(&Matrix2x1::new(1,
2)));
§Indices to Ranges of Rows and Columns
§Index to a Range of Rows
let matrix = Matrix3::new(0, 3, 6,
1, 4, 7,
2, 5, 8);
assert!(matrix.index((1..3, ..))
.eq(&Matrix2x3::new(1, 4, 7,
2, 5, 8)));
§Index to a Range of Columns
let matrix = Matrix3::new(0, 3, 6,
1, 4, 7,
2, 5, 8);
assert!(matrix.index((.., 1..3))
.eq(&Matrix3x2::new(3, 6,
4, 7,
5, 8)));
sourcepub fn get<'a, I>(
&'a self,
index: I,
) -> Option<<I as MatrixIndex<'a, T, R, C, S>>::Output>where
I: MatrixIndex<'a, T, R, C, S>,
pub fn get<'a, I>(
&'a self,
index: I,
) -> Option<<I as MatrixIndex<'a, T, R, C, S>>::Output>where
I: MatrixIndex<'a, T, R, C, S>,
Produces a view of the data at the given index, or
None
if the index is out of bounds.
sourcepub fn get_mut<'a, I>(
&'a mut self,
index: I,
) -> Option<<I as MatrixIndexMut<'a, T, R, C, S>>::OutputMut>where
S: RawStorageMut<T, R, C>,
I: MatrixIndexMut<'a, T, R, C, S>,
pub fn get_mut<'a, I>(
&'a mut self,
index: I,
) -> Option<<I as MatrixIndexMut<'a, T, R, C, S>>::OutputMut>where
S: RawStorageMut<T, R, C>,
I: MatrixIndexMut<'a, T, R, C, S>,
Produces a mutable view of the data at the given index, or
None
if the index is out of bounds.
sourcepub fn index<'a, I>(
&'a self,
index: I,
) -> <I as MatrixIndex<'a, T, R, C, S>>::Outputwhere
I: MatrixIndex<'a, T, R, C, S>,
pub fn index<'a, I>(
&'a self,
index: I,
) -> <I as MatrixIndex<'a, T, R, C, S>>::Outputwhere
I: MatrixIndex<'a, T, R, C, S>,
Produces a view of the data at the given index, or panics if the index is out of bounds.
sourcepub fn index_mut<'a, I>(
&'a mut self,
index: I,
) -> <I as MatrixIndexMut<'a, T, R, C, S>>::OutputMutwhere
S: RawStorageMut<T, R, C>,
I: MatrixIndexMut<'a, T, R, C, S>,
pub fn index_mut<'a, I>(
&'a mut self,
index: I,
) -> <I as MatrixIndexMut<'a, T, R, C, S>>::OutputMutwhere
S: RawStorageMut<T, R, C>,
I: MatrixIndexMut<'a, T, R, C, S>,
Produces a mutable view of the data at the given index, or panics if the index is out of bounds.
sourcepub unsafe fn get_unchecked<'a, I>(
&'a self,
index: I,
) -> <I as MatrixIndex<'a, T, R, C, S>>::Outputwhere
I: MatrixIndex<'a, T, R, C, S>,
pub unsafe fn get_unchecked<'a, I>(
&'a self,
index: I,
) -> <I as MatrixIndex<'a, T, R, C, S>>::Outputwhere
I: MatrixIndex<'a, T, R, C, S>,
Produces a view of the data at the given index, without doing any bounds checking.
§Safety
index
must within bounds of the array.
sourcepub unsafe fn get_unchecked_mut<'a, I>(
&'a mut self,
index: I,
) -> <I as MatrixIndexMut<'a, T, R, C, S>>::OutputMutwhere
S: RawStorageMut<T, R, C>,
I: MatrixIndexMut<'a, T, R, C, S>,
pub unsafe fn get_unchecked_mut<'a, I>(
&'a mut self,
index: I,
) -> <I as MatrixIndexMut<'a, T, R, C, S>>::OutputMutwhere
S: RawStorageMut<T, R, C>,
I: MatrixIndexMut<'a, T, R, C, S>,
Returns a mutable view of the data at the given index, without doing any bounds checking.
§Safety
index
must within bounds of the array.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
sourcepub const unsafe fn from_data_statically_unchecked(
data: S,
) -> Matrix<T, R, C, S>
pub const unsafe fn from_data_statically_unchecked( data: S, ) -> Matrix<T, R, C, S>
Creates a new matrix with the given data without statically checking that the matrix dimension matches the storage dimension.
§Safety
The storage dimension must match the given dimensions.
source§impl<T, const R: usize, const C: usize> Matrix<T, Const<R>, Const<C>, ArrayStorage<T, R, C>>
impl<T, const R: usize, const C: usize> Matrix<T, Const<R>, Const<C>, ArrayStorage<T, R, C>>
sourcepub const fn from_array_storage(
storage: ArrayStorage<T, R, C>,
) -> Matrix<T, Const<R>, Const<C>, ArrayStorage<T, R, C>>
pub const fn from_array_storage( storage: ArrayStorage<T, R, C>, ) -> Matrix<T, Const<R>, Const<C>, ArrayStorage<T, R, C>>
Creates a new statically-allocated matrix from the given ArrayStorage
.
This method exists primarily as a workaround for the fact that from_data
can not
work in const fn
contexts.
source§impl<T> Matrix<T, Dyn, Dyn, VecStorage<T, Dyn, Dyn>>
impl<T> Matrix<T, Dyn, Dyn, VecStorage<T, Dyn, Dyn>>
sourcepub const fn from_vec_storage(
storage: VecStorage<T, Dyn, Dyn>,
) -> Matrix<T, Dyn, Dyn, VecStorage<T, Dyn, Dyn>>
pub const fn from_vec_storage( storage: VecStorage<T, Dyn, Dyn>, ) -> Matrix<T, Dyn, Dyn, VecStorage<T, Dyn, Dyn>>
Creates a new heap-allocated matrix from the given VecStorage
.
This method exists primarily as a workaround for the fact that from_data
can not
work in const fn
contexts.
source§impl<T> Matrix<T, Dyn, Const<1>, VecStorage<T, Dyn, Const<1>>>
impl<T> Matrix<T, Dyn, Const<1>, VecStorage<T, Dyn, Const<1>>>
sourcepub const fn from_vec_storage(
storage: VecStorage<T, Dyn, Const<1>>,
) -> Matrix<T, Dyn, Const<1>, VecStorage<T, Dyn, Const<1>>>
pub const fn from_vec_storage( storage: VecStorage<T, Dyn, Const<1>>, ) -> Matrix<T, Dyn, Const<1>, VecStorage<T, Dyn, Const<1>>>
Creates a new heap-allocated matrix from the given VecStorage
.
This method exists primarily as a workaround for the fact that from_data
can not
work in const fn
contexts.
source§impl<T> Matrix<T, Const<1>, Dyn, VecStorage<T, Const<1>, Dyn>>
impl<T> Matrix<T, Const<1>, Dyn, VecStorage<T, Const<1>, Dyn>>
sourcepub const fn from_vec_storage(
storage: VecStorage<T, Const<1>, Dyn>,
) -> Matrix<T, Const<1>, Dyn, VecStorage<T, Const<1>, Dyn>>
pub const fn from_vec_storage( storage: VecStorage<T, Const<1>, Dyn>, ) -> Matrix<T, Const<1>, Dyn, VecStorage<T, Const<1>, Dyn>>
Creates a new heap-allocated matrix from the given VecStorage
.
This method exists primarily as a workaround for the fact that from_data
can not
work in const fn
contexts.
source§impl<T, R, C> Matrix<MaybeUninit<T>, R, C, <DefaultAllocator as Allocator<R, C>>::BufferUninit<T>>
impl<T, R, C> Matrix<MaybeUninit<T>, R, C, <DefaultAllocator as Allocator<R, C>>::BufferUninit<T>>
sourcepub unsafe fn assume_init(
self,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub unsafe fn assume_init( self, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Assumes a matrix’s entries to be initialized. This operation should be near zero-cost.
§Safety
The user must make sure that every single entry of the buffer has been initialized, or Undefined Behavior will immediately occur.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
sourcepub fn shape(&self) -> (usize, usize)
pub fn shape(&self) -> (usize, usize)
The shape of this matrix returned as the tuple (number of rows, number of columns).
§Example
let mat = Matrix3x4::<f32>::zeros();
assert_eq!(mat.shape(), (3, 4));
sourcepub fn shape_generic(&self) -> (R, C)
pub fn shape_generic(&self) -> (R, C)
The shape of this matrix wrapped into their representative types (Const
or Dyn
).
sourcepub fn nrows(&self) -> usize
pub fn nrows(&self) -> usize
The number of rows of this matrix.
§Example
let mat = Matrix3x4::<f32>::zeros();
assert_eq!(mat.nrows(), 3);
sourcepub fn ncols(&self) -> usize
pub fn ncols(&self) -> usize
The number of columns of this matrix.
§Example
let mat = Matrix3x4::<f32>::zeros();
assert_eq!(mat.ncols(), 4);
sourcepub fn strides(&self) -> (usize, usize)
pub fn strides(&self) -> (usize, usize)
The strides (row stride, column stride) of this matrix.
§Example
let mat = DMatrix::<f32>::zeros(10, 10);
let view = mat.view_with_steps((0, 0), (5, 3), (1, 2));
// The column strides is the number of steps (here 2) multiplied by the corresponding dimension.
assert_eq!(mat.strides(), (1, 10));
sourcepub fn vector_to_matrix_index(&self, i: usize) -> (usize, usize)
pub fn vector_to_matrix_index(&self, i: usize) -> (usize, usize)
Computes the row and column coordinates of the i-th element of this matrix seen as a vector.
§Example
let m = Matrix2::new(1, 2,
3, 4);
let i = m.vector_to_matrix_index(3);
assert_eq!(i, (1, 1));
assert_eq!(m[i], m[3]);
sourcepub fn as_ptr(&self) -> *const T
pub fn as_ptr(&self) -> *const T
Returns a pointer to the start of the matrix.
If the matrix is not empty, this pointer is guaranteed to be aligned and non-null.
§Example
let m = Matrix2::new(1, 2,
3, 4);
let ptr = m.as_ptr();
assert_eq!(unsafe { *ptr }, m[0]);
sourcepub fn relative_eq<R2, C2, SB>(
&self,
other: &Matrix<T, R2, C2, SB>,
eps: <T as AbsDiffEq>::Epsilon,
max_relative: <T as AbsDiffEq>::Epsilon,
) -> boolwhere
T: RelativeEq + Scalar,
R2: Dim,
C2: Dim,
SB: Storage<T, R2, C2>,
<T as AbsDiffEq>::Epsilon: Clone,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
pub fn relative_eq<R2, C2, SB>(
&self,
other: &Matrix<T, R2, C2, SB>,
eps: <T as AbsDiffEq>::Epsilon,
max_relative: <T as AbsDiffEq>::Epsilon,
) -> boolwhere
T: RelativeEq + Scalar,
R2: Dim,
C2: Dim,
SB: Storage<T, R2, C2>,
<T as AbsDiffEq>::Epsilon: Clone,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
Tests whether self
and rhs
are equal up to a given epsilon.
See relative_eq
from the RelativeEq
trait for more details.
sourcepub fn eq<R2, C2, SB>(&self, other: &Matrix<T, R2, C2, SB>) -> boolwhere
T: PartialEq,
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
pub fn eq<R2, C2, SB>(&self, other: &Matrix<T, R2, C2, SB>) -> boolwhere
T: PartialEq,
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
Tests whether self
and rhs
are exactly equal.
sourcepub fn into_owned(
self,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn into_owned( self, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Moves this matrix into one that owns its data.
sourcepub fn into_owned_sum<R2, C2>(
self,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative>>::Buffer<T>>where
T: Scalar,
S: Storage<T, R, C>,
R2: Dim,
C2: Dim,
DefaultAllocator: SameShapeAllocator<R, C, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
pub fn into_owned_sum<R2, C2>(
self,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative>>::Buffer<T>>where
T: Scalar,
S: Storage<T, R, C>,
R2: Dim,
C2: Dim,
DefaultAllocator: SameShapeAllocator<R, C, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
Moves this matrix into one that owns its data. The actual type of the result depends on matrix storage combination rules for addition.
sourcepub fn clone_owned(
&self,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
pub fn clone_owned( &self, ) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>
Clones this matrix to one that owns its data.
sourcepub fn clone_owned_sum<R2, C2>(
&self,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative>>::Buffer<T>>where
T: Scalar,
S: Storage<T, R, C>,
R2: Dim,
C2: Dim,
DefaultAllocator: SameShapeAllocator<R, C, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
pub fn clone_owned_sum<R2, C2>(
&self,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative>>::Buffer<T>>where
T: Scalar,
S: Storage<T, R, C>,
R2: Dim,
C2: Dim,
DefaultAllocator: SameShapeAllocator<R, C, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
Clones this matrix into one that owns its data. The actual type of the result depends on matrix storage combination rules for addition.
sourcepub fn transpose_to<R2, C2, SB>(&self, out: &mut Matrix<T, R2, C2, SB>)where
T: Scalar,
R2: Dim,
C2: Dim,
SB: RawStorageMut<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, C2> + SameNumberOfColumns<C, R2>,
pub fn transpose_to<R2, C2, SB>(&self, out: &mut Matrix<T, R2, C2, SB>)where
T: Scalar,
R2: Dim,
C2: Dim,
SB: RawStorageMut<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, C2> + SameNumberOfColumns<C, R2>,
Transposes self
and store the result into out
.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Elementwise mapping and folding
sourcepub fn map<T2, F>(
&self,
f: F,
) -> Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>
pub fn map<T2, F>( &self, f: F, ) -> Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>
Returns a matrix containing the result of f
applied to each of its entries.
sourcepub fn cast<T2>(
self,
) -> Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>where
T2: Scalar,
T: Scalar,
Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>: SupersetOf<Matrix<T, R, C, S>>,
DefaultAllocator: Allocator<R, C>,
pub fn cast<T2>(
self,
) -> Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>where
T2: Scalar,
T: Scalar,
Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>: SupersetOf<Matrix<T, R, C, S>>,
DefaultAllocator: Allocator<R, C>,
Cast the components of self
to another type.
§Example
let q = Vector3::new(1.0f64, 2.0, 3.0);
let q2 = q.cast::<f32>();
assert_eq!(q2, Vector3::new(1.0f32, 2.0, 3.0));
sourcepub fn try_cast<T2>(
self,
) -> Option<Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>>where
T2: Scalar,
T: Scalar,
Matrix<T, R, C, S>: SupersetOf<Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>>,
DefaultAllocator: Allocator<R, C>,
pub fn try_cast<T2>(
self,
) -> Option<Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>>where
T2: Scalar,
T: Scalar,
Matrix<T, R, C, S>: SupersetOf<Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>>,
DefaultAllocator: Allocator<R, C>,
Attempts to cast the components of self
to another type.
§Example
let q = Vector3::new(1.0f64, 2.0, 3.0);
let q2 = q.try_cast::<i32>();
assert_eq!(q2, Some(Vector3::new(1, 2, 3)));
sourcepub fn fold_with<T2>(
&self,
init_f: impl FnOnce(Option<&T>) -> T2,
f: impl FnMut(T2, &T) -> T2,
) -> T2where
T: Scalar,
pub fn fold_with<T2>(
&self,
init_f: impl FnOnce(Option<&T>) -> T2,
f: impl FnMut(T2, &T) -> T2,
) -> T2where
T: Scalar,
Similar to self.iter().fold(init, f)
except that init
is replaced by a closure.
The initialization closure is given the first component of this matrix:
- If the matrix has no component (0 rows or 0 columns) then
init_f
is called withNone
and its return value is the value returned by this method. - If the matrix has has least one component, then
init_f
is called with the first component to compute the initial value. Folding then continues on all the remaining components of the matrix.
sourcepub fn map_with_location<T2, F>(
&self,
f: F,
) -> Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>
pub fn map_with_location<T2, F>( &self, f: F, ) -> Matrix<T2, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T2>>
Returns a matrix containing the result of f
applied to each of its entries. Unlike map
,
f
also gets passed the row and column index, i.e. f(row, col, value)
.
sourcepub fn zip_map<T2, N3, S2, F>(
&self,
rhs: &Matrix<T2, R, C, S2>,
f: F,
) -> Matrix<N3, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<N3>>where
T: Scalar,
T2: Scalar,
N3: Scalar,
S2: RawStorage<T2, R, C>,
F: FnMut(T, T2) -> N3,
DefaultAllocator: Allocator<R, C>,
pub fn zip_map<T2, N3, S2, F>(
&self,
rhs: &Matrix<T2, R, C, S2>,
f: F,
) -> Matrix<N3, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<N3>>where
T: Scalar,
T2: Scalar,
N3: Scalar,
S2: RawStorage<T2, R, C>,
F: FnMut(T, T2) -> N3,
DefaultAllocator: Allocator<R, C>,
Returns a matrix containing the result of f
applied to each entries of self
and
rhs
.
sourcepub fn zip_zip_map<T2, N3, N4, S2, S3, F>(
&self,
b: &Matrix<T2, R, C, S2>,
c: &Matrix<N3, R, C, S3>,
f: F,
) -> Matrix<N4, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<N4>>where
T: Scalar,
T2: Scalar,
N3: Scalar,
N4: Scalar,
S2: RawStorage<T2, R, C>,
S3: RawStorage<N3, R, C>,
F: FnMut(T, T2, N3) -> N4,
DefaultAllocator: Allocator<R, C>,
pub fn zip_zip_map<T2, N3, N4, S2, S3, F>(
&self,
b: &Matrix<T2, R, C, S2>,
c: &Matrix<N3, R, C, S3>,
f: F,
) -> Matrix<N4, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<N4>>where
T: Scalar,
T2: Scalar,
N3: Scalar,
N4: Scalar,
S2: RawStorage<T2, R, C>,
S3: RawStorage<N3, R, C>,
F: FnMut(T, T2, N3) -> N4,
DefaultAllocator: Allocator<R, C>,
Returns a matrix containing the result of f
applied to each entries of self
and
b
, and c
.
sourcepub fn fold<Acc>(&self, init: Acc, f: impl FnMut(Acc, T) -> Acc) -> Accwhere
T: Scalar,
pub fn fold<Acc>(&self, init: Acc, f: impl FnMut(Acc, T) -> Acc) -> Accwhere
T: Scalar,
Folds a function f
on each entry of self
.
sourcepub fn zip_fold<T2, R2, C2, S2, Acc>(
&self,
rhs: &Matrix<T2, R2, C2, S2>,
init: Acc,
f: impl FnMut(Acc, T, T2) -> Acc,
) -> Accwhere
T: Scalar,
T2: Scalar,
R2: Dim,
C2: Dim,
S2: RawStorage<T2, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
pub fn zip_fold<T2, R2, C2, S2, Acc>(
&self,
rhs: &Matrix<T2, R2, C2, S2>,
init: Acc,
f: impl FnMut(Acc, T, T2) -> Acc,
) -> Accwhere
T: Scalar,
T2: Scalar,
R2: Dim,
C2: Dim,
S2: RawStorage<T2, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
Folds a function f
on each pairs of entries from self
and rhs
.
sourcepub fn zip_apply<T2, R2, C2, S2>(
&mut self,
rhs: &Matrix<T2, R2, C2, S2>,
f: impl FnMut(&mut T, T2),
)where
S: RawStorageMut<T, R, C>,
T2: Scalar,
R2: Dim,
C2: Dim,
S2: RawStorage<T2, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
pub fn zip_apply<T2, R2, C2, S2>(
&mut self,
rhs: &Matrix<T2, R2, C2, S2>,
f: impl FnMut(&mut T, T2),
)where
S: RawStorageMut<T, R, C>,
T2: Scalar,
R2: Dim,
C2: Dim,
S2: RawStorage<T2, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
Replaces each component of self
by the result of a closure f
applied on its components
joined with the components from rhs
.
sourcepub fn zip_zip_apply<T2, R2, C2, S2, N3, R3, C3, S3>(
&mut self,
b: &Matrix<T2, R2, C2, S2>,
c: &Matrix<N3, R3, C3, S3>,
f: impl FnMut(&mut T, T2, N3),
)where
S: RawStorageMut<T, R, C>,
T2: Scalar,
R2: Dim,
C2: Dim,
S2: RawStorage<T2, R2, C2>,
N3: Scalar,
R3: Dim,
C3: Dim,
S3: RawStorage<N3, R3, C3>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
pub fn zip_zip_apply<T2, R2, C2, S2, N3, R3, C3, S3>(
&mut self,
b: &Matrix<T2, R2, C2, S2>,
c: &Matrix<N3, R3, C3, S3>,
f: impl FnMut(&mut T, T2, N3),
)where
S: RawStorageMut<T, R, C>,
T2: Scalar,
R2: Dim,
C2: Dim,
S2: RawStorage<T2, R2, C2>,
N3: Scalar,
R3: Dim,
C3: Dim,
S3: RawStorage<N3, R3, C3>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
Replaces each component of self
by the result of a closure f
applied on its components
joined with the components from b
and c
.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
§Iteration on components, rows, and columns
sourcepub fn iter(&self) -> MatrixIter<'_, T, R, C, S> ⓘ
pub fn iter(&self) -> MatrixIter<'_, T, R, C, S> ⓘ
Iterates through this matrix coordinates in column-major order.
§Example
let mat = Matrix2x3::new(11, 12, 13,
21, 22, 23);
let mut it = mat.iter();
assert_eq!(*it.next().unwrap(), 11);
assert_eq!(*it.next().unwrap(), 21);
assert_eq!(*it.next().unwrap(), 12);
assert_eq!(*it.next().unwrap(), 22);
assert_eq!(*it.next().unwrap(), 13);
assert_eq!(*it.next().unwrap(), 23);
assert!(it.next().is_none());
sourcepub fn row_iter(&self) -> RowIter<'_, T, R, C, S> ⓘ
pub fn row_iter(&self) -> RowIter<'_, T, R, C, S> ⓘ
Iterate through the rows of this matrix.
§Example
let mut a = Matrix2x3::new(1, 2, 3,
4, 5, 6);
for (i, row) in a.row_iter().enumerate() {
assert_eq!(row, a.row(i))
}
sourcepub fn column_iter(&self) -> ColumnIter<'_, T, R, C, S> ⓘ
pub fn column_iter(&self) -> ColumnIter<'_, T, R, C, S> ⓘ
Iterate through the columns of this matrix.
§Example
let mut a = Matrix2x3::new(1, 2, 3,
4, 5, 6);
for (i, column) in a.column_iter().enumerate() {
assert_eq!(column, a.column(i))
}
sourcepub fn iter_mut(&mut self) -> MatrixIterMut<'_, T, R, C, S> ⓘwhere
S: RawStorageMut<T, R, C>,
pub fn iter_mut(&mut self) -> MatrixIterMut<'_, T, R, C, S> ⓘwhere
S: RawStorageMut<T, R, C>,
Mutably iterates through this matrix coordinates.
sourcepub fn row_iter_mut(&mut self) -> RowIterMut<'_, T, R, C, S> ⓘwhere
S: RawStorageMut<T, R, C>,
pub fn row_iter_mut(&mut self) -> RowIterMut<'_, T, R, C, S> ⓘwhere
S: RawStorageMut<T, R, C>,
Mutably iterates through this matrix rows.
§Example
let mut a = Matrix2x3::new(1, 2, 3,
4, 5, 6);
for (i, mut row) in a.row_iter_mut().enumerate() {
row *= (i + 1) * 10;
}
let expected = Matrix2x3::new(10, 20, 30,
80, 100, 120);
assert_eq!(a, expected);
sourcepub fn column_iter_mut(&mut self) -> ColumnIterMut<'_, T, R, C, S> ⓘwhere
S: RawStorageMut<T, R, C>,
pub fn column_iter_mut(&mut self) -> ColumnIterMut<'_, T, R, C, S> ⓘwhere
S: RawStorageMut<T, R, C>,
Mutably iterates through this matrix columns.
§Example
let mut a = Matrix2x3::new(1, 2, 3,
4, 5, 6);
for (i, mut col) in a.column_iter_mut().enumerate() {
col *= (i + 1) * 10;
}
let expected = Matrix2x3::new(10, 40, 90,
40, 100, 180);
assert_eq!(a, expected);
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
sourcepub fn as_mut_ptr(&mut self) -> *mut T
pub fn as_mut_ptr(&mut self) -> *mut T
Returns a mutable pointer to the start of the matrix.
If the matrix is not empty, this pointer is guaranteed to be aligned and non-null.
sourcepub unsafe fn swap_unchecked(
&mut self,
row_cols1: (usize, usize),
row_cols2: (usize, usize),
)
pub unsafe fn swap_unchecked( &mut self, row_cols1: (usize, usize), row_cols2: (usize, usize), )
sourcepub fn swap(&mut self, row_cols1: (usize, usize), row_cols2: (usize, usize))
pub fn swap(&mut self, row_cols1: (usize, usize), row_cols2: (usize, usize))
Swaps two entries.
sourcepub fn copy_from_slice(&mut self, slice: &[T])where
T: Scalar,
pub fn copy_from_slice(&mut self, slice: &[T])where
T: Scalar,
Fills this matrix with the content of a slice. Both must hold the same number of elements.
The components of the slice are assumed to be ordered in column-major order.
sourcepub fn copy_from<R2, C2, SB>(&mut self, other: &Matrix<T, R2, C2, SB>)where
T: Scalar,
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
pub fn copy_from<R2, C2, SB>(&mut self, other: &Matrix<T, R2, C2, SB>)where
T: Scalar,
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
Fills this matrix with the content of another one. Both must have the same shape.
sourcepub fn tr_copy_from<R2, C2, SB>(&mut self, other: &Matrix<T, R2, C2, SB>)where
T: Scalar,
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: DimEq<R, C2> + SameNumberOfColumns<C, R2>,
pub fn tr_copy_from<R2, C2, SB>(&mut self, other: &Matrix<T, R2, C2, SB>)where
T: Scalar,
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: DimEq<R, C2> + SameNumberOfColumns<C, R2>,
Fills this matrix with the content of the transpose another one.
sourcepub fn apply_into<F>(self, f: F) -> Matrix<T, R, C, S>
pub fn apply_into<F>(self, f: F) -> Matrix<T, R, C, S>
Returns self
with each of its components replaced by the result of a closure f
applied on it.
source§impl<T, D, S> Matrix<T, D, Const<1>, S>where
D: Dim,
S: RawStorage<T, D>,
impl<T, D, S> Matrix<T, D, Const<1>, S>where
D: Dim,
S: RawStorage<T, D>,
sourcepub unsafe fn vget_unchecked(&self, i: usize) -> &T
pub unsafe fn vget_unchecked(&self, i: usize) -> &T
Gets a reference to the i-th element of this column vector without bound checking.
§Safety
i
must be less than D
.
source§impl<T, D, S> Matrix<T, D, Const<1>, S>where
D: Dim,
S: RawStorageMut<T, D>,
impl<T, D, S> Matrix<T, D, Const<1>, S>where
D: Dim,
S: RawStorageMut<T, D>,
sourcepub unsafe fn vget_unchecked_mut(&mut self, i: usize) -> &mut T
pub unsafe fn vget_unchecked_mut(&mut self, i: usize) -> &mut T
Gets a mutable reference to the i-th element of this column vector without bound checking.
§Safety
i
must be less than D
.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
sourcepub fn as_mut_slice(&mut self) -> &mut [T]
pub fn as_mut_slice(&mut self) -> &mut [T]
Extracts a mutable slice containing the entire matrix entries ordered column-by-columns.
source§impl<T, D, S> Matrix<T, D, D, S>
impl<T, D, S> Matrix<T, D, D, S>
sourcepub fn transpose_mut(&mut self)
pub fn transpose_mut(&mut self)
Transposes the square matrix self
in-place.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
sourcepub fn adjoint_to<R2, C2, SB>(&self, out: &mut Matrix<T, R2, C2, SB>)where
R2: Dim,
C2: Dim,
SB: RawStorageMut<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, C2> + SameNumberOfColumns<C, R2>,
pub fn adjoint_to<R2, C2, SB>(&self, out: &mut Matrix<T, R2, C2, SB>)where
R2: Dim,
C2: Dim,
SB: RawStorageMut<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, C2> + SameNumberOfColumns<C, R2>,
Takes the adjoint (aka. conjugate-transpose) of self
and store the result into out
.
sourcepub fn adjoint(
&self,
) -> Matrix<T, C, R, <DefaultAllocator as Allocator<C, R>>::Buffer<T>>where
DefaultAllocator: Allocator<C, R>,
pub fn adjoint(
&self,
) -> Matrix<T, C, R, <DefaultAllocator as Allocator<C, R>>::Buffer<T>>where
DefaultAllocator: Allocator<C, R>,
The adjoint (aka. conjugate-transpose) of self
.
sourcepub fn conjugate_transpose_to<R2, C2, SB>(
&self,
out: &mut Matrix<T, R2, C2, SB>,
)where
R2: Dim,
C2: Dim,
SB: RawStorageMut<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, C2> + SameNumberOfColumns<C, R2>,
👎Deprecated: Renamed self.adjoint_to(out)
.
pub fn conjugate_transpose_to<R2, C2, SB>(
&self,
out: &mut Matrix<T, R2, C2, SB>,
)where
R2: Dim,
C2: Dim,
SB: RawStorageMut<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, C2> + SameNumberOfColumns<C, R2>,
self.adjoint_to(out)
.Takes the conjugate and transposes self
and store the result into out
.
sourcepub fn conjugate_transpose(
&self,
) -> Matrix<T, C, R, <DefaultAllocator as Allocator<C, R>>::Buffer<T>>where
DefaultAllocator: Allocator<C, R>,
👎Deprecated: Renamed self.adjoint()
.
pub fn conjugate_transpose(
&self,
) -> Matrix<T, C, R, <DefaultAllocator as Allocator<C, R>>::Buffer<T>>where
DefaultAllocator: Allocator<C, R>,
self.adjoint()
.The conjugate transposition of self
.
sourcepub fn conjugate(
&self,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
pub fn conjugate(
&self,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
The conjugate of self
.
sourcepub fn unscale(
&self,
real: <T as SimdComplexField>::SimdRealField,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
pub fn unscale(
&self,
real: <T as SimdComplexField>::SimdRealField,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
Divides each component of the complex matrix self
by the given real.
sourcepub fn scale(
&self,
real: <T as SimdComplexField>::SimdRealField,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
pub fn scale(
&self,
real: <T as SimdComplexField>::SimdRealField,
) -> Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>where
DefaultAllocator: Allocator<R, C>,
Multiplies each component of the complex matrix self
by the given real.
source§impl<T, R, C, S> Matrix<T, R, C, S>
impl<T, R, C, S> Matrix<T, R, C, S>
sourcepub fn conjugate_mut(&mut self)
pub fn conjugate_mut(&mut self)
The conjugate of the complex matrix self
computed in-place.
sourcepub fn unscale_mut(&mut self, real: <T as SimdComplexField>::SimdRealField)
pub fn unscale_mut(&mut self, real: <T as SimdComplexField>::SimdRealField)
Divides each component of the complex matrix self
by the given real.
source§impl<T, D, S> Matrix<T, D, D, S>where
T: SimdComplexField,
D: Dim,
S: RawStorageMut<T, D, D>,
impl<T, D, S> Matrix<T, D, D, S>where
T: SimdComplexField,
D: Dim,
S: RawStorageMut<T, D, D>,
sourcepub fn conjugate_transform_mut(&mut self)
👎Deprecated: Renamed to self.adjoint_mut()
.
pub fn conjugate_transform_mut(&mut self)
self.adjoint_mut()
.Sets self
to its adjoint.
sourcepub fn adjoint_mut(&mut self)
pub fn adjoint_mut(&mut self)
Sets self
to its adjoint (aka. conjugate-transpose).
source§impl<T, D, S> Matrix<T, D, D, S>
impl<T, D, S> Matrix<T, D, D, S>
sourcepub fn diagonal(
&self,
) -> Matrix<T, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<T>>where
DefaultAllocator: Allocator<D>,
pub fn diagonal(
&self,
) -> Matrix<T, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<T>>where
DefaultAllocator: Allocator<D>,
The diagonal of this matrix.
sourcepub fn map_diagonal<T2>(
&self,
f: impl FnMut(T) -> T2,
) -> Matrix<T2, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<T2>>
pub fn map_diagonal<T2>( &self, f: impl FnMut(T) -> T2, ) -> Matrix<T2, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<T2>>
Apply the given function to this matrix’s diagonal and returns it.
This is a more efficient version of self.diagonal().map(f)
since this
allocates only once.
source§impl<T, D, S> Matrix<T, D, D, S>
impl<T, D, S> Matrix<T, D, D, S>
sourcepub fn symmetric_part(
&self,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
DefaultAllocator: Allocator<D, D>,
pub fn symmetric_part(
&self,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
DefaultAllocator: Allocator<D, D>,
The symmetric part of self
, i.e., 0.5 * (self + self.transpose())
.
sourcepub fn hermitian_part(
&self,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
DefaultAllocator: Allocator<D, D>,
pub fn hermitian_part(
&self,
) -> Matrix<T, D, D, <DefaultAllocator as Allocator<D, D>>::Buffer<T>>where
DefaultAllocator: Allocator<D, D>,
The hermitian part of self
, i.e., 0.5 * (self + self.adjoint())
.
source§impl<T, D, S> Matrix<T, D, D, S>
impl<T, D, S> Matrix<T, D, D, S>
sourcepub fn to_homogeneous(
&self,
) -> Matrix<T, <D as DimAdd<Const<1>>>::Output, <D as DimAdd<Const<1>>>::Output, <DefaultAllocator as Allocator<<D as DimAdd<Const<1>>>::Output, <D as DimAdd<Const<1>>>::Output>>::Buffer<T>>
pub fn to_homogeneous( &self, ) -> Matrix<T, <D as DimAdd<Const<1>>>::Output, <D as DimAdd<Const<1>>>::Output, <DefaultAllocator as Allocator<<D as DimAdd<Const<1>>>::Output, <D as DimAdd<Const<1>>>::Output>>::Buffer<T>>
Yields the homogeneous matrix for this matrix, i.e., appending an additional dimension and
and setting the diagonal element to 1
.
source§impl<T, D, S> Matrix<T, D, Const<1>, S>
impl<T, D, S> Matrix<T, D, Const<1>, S>
sourcepub fn to_homogeneous(
&self,
) -> Matrix<T, <D as DimAdd<Const<1>>>::Output, Const<1>, <DefaultAllocator as Allocator<<D as DimAdd<Const<1>>>::Output>>::Buffer<T>>
pub fn to_homogeneous( &self, ) -> Matrix<T, <D as DimAdd<Const<1>>>::Output, Const<1>, <DefaultAllocator as Allocator<<D as DimAdd<Const<1>>>::Output>>::Buffer<T>>
Computes the coordinates in projective space of this vector, i.e., appends a 0
to its
coordinates.
sourcepub fn from_homogeneous<SB>(
v: Matrix<T, <D as DimAdd<Const<1>>>::Output, Const<1>, SB>,
) -> Option<Matrix<T, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<T>>>
pub fn from_homogeneous<SB>( v: Matrix<T, <D as DimAdd<Const<1>>>::Output, Const<1>, SB>, ) -> Option<Matrix<T, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<T>>>
Constructs a vector from coordinates in projective space, i.e., removes a 0
at the end of
self
. Returns None
if this last component is not zero.
source§impl<T, D, S> Matrix<T, D, Const<1>, S>
impl<T, D, S> Matrix<T, D, Const<1>, S>
source§impl<T, R, C, S> Matrix<T, R, C, S>where
T: Scalar + ClosedAddAssign + ClosedSubAssign + ClosedMulAssign,
R: Dim,
C: Dim,
S: RawStorage<T, R, C>,
impl<T, R, C, S> Matrix<T, R, C, S>where
T: Scalar + ClosedAddAssign + ClosedSubAssign + ClosedMulAssign,
R: Dim,
C: Dim,
S: RawStorage<T, R, C>,
§Cross product
sourcepub fn perp<R2, C2, SB>(&self, b: &Matrix<T, R2, C2, SB>) -> Twhere
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, Const<2>> + SameNumberOfColumns<C, Const<1>> + SameNumberOfRows<R2, Const<2>> + SameNumberOfColumns<C2, Const<1>>,
pub fn perp<R2, C2, SB>(&self, b: &Matrix<T, R2, C2, SB>) -> Twhere
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, Const<2>> + SameNumberOfColumns<C, Const<1>> + SameNumberOfRows<R2, Const<2>> + SameNumberOfColumns<C2, Const<1>>,
The perpendicular product between two 2D column vectors, i.e. a.x * b.y - a.y * b.x
.
sourcepub fn cross<R2, C2, SB>(
&self,
b: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative>>::Buffer<T>>where
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
DefaultAllocator: SameShapeAllocator<R, C, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
pub fn cross<R2, C2, SB>(
&self,
b: &Matrix<T, R2, C2, SB>,
) -> Matrix<T, <ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<C, C2>>::Representative>>::Buffer<T>>where
R2: Dim,
C2: Dim,
SB: RawStorage<T, R2, C2>,
DefaultAllocator: SameShapeAllocator<R, C, R2, C2>,
ShapeConstraint: SameNumberOfRows<R, R2> + SameNumberOfColumns<C, C2>,
The 3D cross product between two vectors.
Panics if the shape is not 3D vector. In the future, this will be implemented only for dynamically-sized matrices and statically-sized 3D matrices.
source§impl<T, S> Matrix<T, Const<3>, Const<1>, S>
impl<T, S> Matrix<T, Const<3>, Const<1>, S>
sourcepub fn cross_matrix(
&self,
) -> Matrix<T, Const<3>, Const<3>, <DefaultAllocator as Allocator<Const<3>, Const<3>>>::Buffer<T>>
pub fn cross_matrix( &self, ) -> Matrix<T, Const<3>, Const<3>, <DefaultAllocator as Allocator<Const<3>, Const<3>>>::Buffer<T>>
Computes the matrix M
such that for all vector v
we have M * v == self.cross(&v)
.