Numerical Differentiation Toolbox
Numerical Differentiation Toolbox
This toolbox supplies functions and classes to evaluate derivatives, partial derivatives, gradients, directional derivatives, Jacobians, and Hessians using the forward difference, central difference, and complex-step approximations of a derivative.
Installation
- Download the toolbox from File Exchange or GitHub.
- Open the
INSTALL
folder. - Double-click on
Numerical Differentiation Toolbox.mltbx
.
MATLAB will automatically perform the installation and add all the contents of the toolbox
folder to the MATLAB search path. Alternatively, all of the functions in the toolbox
folder can be used independently.
Documentation
Toolbox Documentation
Technical Documentation
To open the home page of the toolbox documentation in MATLAB, type the following in the Command Window:
doc_NDT
To open the documentation of a specific function or class with name name
, type the following in the Command Window:
doc_NDT name
To open the technical documentation PDF (Numerical_Differentiation.pdf), type the following in the Command Window:
doc_NDT tech
Differentiator
Class
D = Differentiator(method)
Central Difference Differentiation Functions
df = cderivative(f,x0)
pf = cpartial(f,x0,k)
g = cgradient(f,x0)
Dv = cdirectional(f,x0,v)
J = cjacobian(f,x0)
H = chessian(f,x0)
H = cvechessian(f,x0)
Forward Difference Differentiation Functions
df = fderivative(f,x0)
pf = fpartial(f,x0,k)
g = fgradient(f,x0)
Dv = fdirectional(f,x0,v)
J = fjacobian(f,x0)
H = fhessian(f,x0)
H = fvechessian(f,x0)
Complex-Step Differentiation Functions
df = iderivative(f,x0)
pf = ipartial(f,x0,k)
g = igradient(f,x0)
Dv = idirectional(f,x0,v)
J = ijacobian(f,x0)
H = ihessian(f,x0)
H = ivechessian(f,x0)
"Complexified" Functions
y = iabs(x)
z = iatan2(y,x)
z = iatan2d(y,x)
z = idot(x,y)
m = imax(x,y)
m = imin(x,y)
r = imod(a,n)
y = inorm(x)
r = irem(a,n)
Citation pour cette source
Tamas Kis (2024). Numerical Differentiation Toolbox (https://github.com/tamaskis/Numerical_Differentiation_Toolbox-MATLAB/releases/tag/v7.1.4), GitHub. Extrait(e) le .
Compatibilité avec les versions de MATLAB
Plateformes compatibles
Windows macOS LinuxTags
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