Internal documentation
This page documents the internal types and methods of Manifolds.jl
's that might be of use for writing your own manifold.
Functions
Manifolds.eigen_safe
— Functioneigen_safe(x)
Compute the eigendecomposition of x
. If x
is a StaticMatrix
, it is converted to a Matrix
before the decomposition.
Manifolds.isnormal
— Functionisnormal(x; kwargs...) -> Bool
Check if the matrix or number x
is normal, that is, if it commutes with its adjoint:
\[x x^\mathrm{H} = x^\mathrm{H} x.\]
By default, this is an equality check. Provide kwargs
for isapprox
to perform an approximate check.
Manifolds.log_safe
— Functionlog_safe(x)
Compute the matrix logarithm of x
. If x
is a StaticMatrix
, it is converted to a Matrix
before computing the log.
Manifolds.log_safe!
— Functionlog_safe!(y, x)
Compute the matrix logarithm of x
. If the eltype of y
is real, then the imaginary part of x
is ignored, and a DomainError
is raised if real(x)
has no real logarithm.
Manifolds.mul!_safe
— Functionmul!_safe(Y, A, B) -> Y
Call mul!
safely, that is, A
and/or B
are permitted to alias with Y
.
Manifolds.nzsign
— Functionnzsign(z[, absz])
Compute a modified sign(z)
that is always nonzero, i.e. where
\[\operatorname(nzsign)(z) = \begin{cases} 1 & \text{if } z = 0\\ \frac{z}{|z|} & \text{otherwise} \end{cases}\]
Manifolds.realify
— Functionrealify(X::AbstractMatrix{T𝔽}, 𝔽::AbstractNumbers) -> Y::AbstractMatrix{<:Real}
Given a matrix $X ∈ 𝔽^{n×n}$, compute $Y ∈ ℝ^{m×m}$, where $m = n \operatorname{dim}_𝔽$, and $\operatorname{dim}_𝔽$ is the real_dimension
of the number field $𝔽$, using the map $ϕ \colon X ↦ Y$, that preserves the matrix product, so that for all $C,D ∈ 𝔽^{n×n}$,
\[ϕ(C) ϕ(D) = ϕ(CD).\]
See realify!
for an in-place version, and unrealify!
to compute the inverse of $ϕ$.
Manifolds.realify!
— Functionrealify!(Y::AbstractMatrix{<:Real}, X::AbstractMatrix{T𝔽}, 𝔽::AbstractNumbers)
In-place version of realify
.
realify!(Y::AbstractMatrix{<:Real}, X::AbstractMatrix{<:Complex}, ::typeof(ℂ))
Given a complex matrix $X = A + iB ∈ ℂ^{n×n}$, compute its realified matrix $Y ∈ ℝ^{2n×2n}$, written where
\[Y = \begin{pmatrix}A & -B \\ B & A \end{pmatrix}.\]
Manifolds.symmetrize
— Functionsymmetrize(X)
Given a square matrix X
compute 1/2 .* (X' + X)
.
Manifolds.symmetrize!
— Functionsymmetrize!(Y, X)
Given a square matrix X
compute 1/2 .* (X' + X)
in place of Y
.
Manifolds.unrealify!
— Functionunrealify!(X::AbstractMatrix{T𝔽}, Y::AbstractMatrix{<:Real}, 𝔽::AbstractNumbers[, n])
Given a real matrix $Y ∈ ℝ^{m×m}$, where $m = n \operatorname{dim}_𝔽$, and $\operatorname{dim}_𝔽$ is the real_dimension
of the number field $𝔽$, compute in-place its equivalent matrix $X ∈ 𝔽^{n×n}$. Note that this function does not check that $Y$ has a valid structure to be un-realified.
See realify!
for the inverse of this function.
Manifolds.usinc
— Functionusinc(θ::Real)
Unnormalized version of sinc
function, i.e. $\operatorname{usinc}(θ) = \frac{\sin(θ)}{θ}$. This is equivalent to sinc(θ/π)
.
Manifolds.usinc_from_cos
— Functionusinc_from_cos(x::Real)
Unnormalized version of sinc
function, i.e. $\operatorname{usinc}(θ) = \frac{\sin(θ)}{θ}$, computed from $x = cos(θ)$.
Manifolds.vec2skew!
— Functionvec2skew!(X, v, k)
Create a skew symmetric matrix in-place in X
of size $k×k$ from a vector v
, for example for v=[1,2,3]
and k=3
this yields
[ 0 1 2;
-1 0 3;
-2 -3 0
]