API
API for TaylorDiff.
TaylorDiff.TaylorScalar
— TypeTaylorScalar{T, N}
Representation of Taylor polynomials.
Fields
value::NTuple{N, T}
: i-th element of this stores the (i-1)-th derivative
TaylorDiff.TaylorScalar
— MethodTaylorScalar{T, N}(x::T, d::T) where {T, N}
Construct a Taylor polynomial with zeroth and first order coefficient, acting as a seed.
TaylorDiff.TaylorScalar
— MethodTaylorScalar{T, N}(x::T) where {T, N}
Construct a Taylor polynomial with zeroth order coefficient.
TaylorDiff.derivative
— Functionderivative(f, x::T, order::Int64)
+API · TaylorDiff.jl API
API for TaylorDiff.
TaylorDiff.TaylorScalar
— TypeTaylorScalar{T, N}
Representation of Taylor polynomials.
Fields
value::NTuple{N, T}
: i-th element of this stores the (i-1)-th derivative
sourceTaylorDiff.TaylorScalar
— MethodTaylorScalar{T, N}(x::T, d::T) where {T, N}
Construct a Taylor polynomial with zeroth and first order coefficient, acting as a seed.
sourceTaylorDiff.TaylorScalar
— MethodTaylorScalar{T, N}(x::T) where {T, N}
Construct a Taylor polynomial with zeroth order coefficient.
sourceTaylorDiff.derivative
— Functionderivative(f, x::T, order::Int64)
derivative(f, x::T, ::Val{N})
Computes order
-th derivative of f
w.r.t. scalar x
.
derivative(f, x::AbstractVector{T}, l::AbstractVector{T}, order::Int64)
derivative(f, x::AbstractVector{T}, l::AbstractVector{T}, ::Val{N})
Computes order
-th directional derivative of f
w.r.t. vector x
in direction l
.
derivative(f, x::AbstractMatrix{T}, order::Int64)
derivative(f, x::AbstractMatrix{T}, ::Val{N})
derivative(f, x::AbstractMatrix{T}, l::AbstractVector{T}, order::Int64)
-derivative(f, x::AbstractMatrix{T}, l::AbstractVector{T}, ::Val{N})
Shorthand notations for multiple calculations. For a M-by-N matrix, calculate the directional derivative for each column. For a 1-by-N matrix (row vector), calculate the derivative for each scalar.
sourceSettings
This document was generated with Documenter.jl version 0.27.25 on Monday 11 September 2023. Using Julia version 1.9.3.
+derivative(f, x::AbstractMatrix{T}, l::AbstractVector{T}, ::Val{N})
Shorthand notations for multiple calculations. For a M-by-N matrix, calculate the directional derivative for each column. For a 1-by-N matrix (row vector), calculate the derivative for each scalar.