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Diffcode

Automatic differentiation
(7154 downloads for this version - 23902 downloads for all versions)
Details
Version
1.1.1
A more recent valid version with binaries for Scilab 5.4 exists: 1.2
Authors
DIGITEO - Michael Baudin
INRIA - Xavier Jonsson
INRIA - Serge Steer
Owner Organization
DIGITEO - INRIA
Maintainers
Michael BAUDIN
Vincent COUVERT
Categories
License
Dependencies
Creation Date
November 24, 2011
Source created on
Scilab 5.4.x
Binaries available on
Scilab 5.4.x:
Windows 64-bit Windows 32-bit Linux 64-bit Linux 32-bit macOS
Scilab 5.5.x:
Windows 64-bit Windows 32-bit Linux 64-bit Linux 32-bit macOS
Install command
--> atomsInstall("diffcode")
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 (3)
[32.17 kB]
Source code archive
Same sources as in previous toolbox version, updated to make it available for
Scilab 5.4.0
[188.63 kB]
OS-independent binary for Scilab 5.4.x
Binary version
Automatically generated by the ATOMS compilation chain

[217.82 kB]
OS-independent binary for Scilab 5.5.x
Binary version (all platforms)
Automatically generated by the ATOMS compilation chain

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