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Diffcode

Automatic differentiation
(443 downloads for this version - 18020 downloads for all versions)
Details
Version
1.2
A more recent valid version exists: 1.3
Authors
DIGITEO - Michael Baudin
INRIA - Xavier Jonsson
INRIA - Serge Steer
Owner Organization
DIGITEO - INRIA
Maintainers
Michael Baudin
Vincent Couvert
John Gliksberg
Categories
License
Dependencies
Creation Date
December 2, 2014
Source created on
Scilab 5.4.x
Binaries available on
This toolbox is in the process of being built
Description
            This toolbox provides forward automatic differentiation. It is based on
operators and functions overloading.

Given a Scilab code computing a variable y depending on a variable x and a
direction dx it allow evaluation of y together with the directional derivative
Grad(y)*dx.

The module supports common arithmetic operations, common elementary functions
and several matrix functions, including matrix inversion.

Type : 

help diffcode_overview

for a quick start.

Features
--------

The following is a list of the current functions :
 * diffcode_der -  Create a new code differentiation object.
 * diffcode_CDcost -  Objective function for optim.
 * diffcode_hessian - Compute the Hessian of the function.
 * diffcode_jacobian - Compute the Jacobian of the function.

            
Files (1)
[33.93 kB]
Source code archive

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