Your message dated Wed, 17 Jun 2026 06:01:02 +0000
with message-id <[email protected]>
and subject line Bug#1139702: fixed in adept-math 2.1.3+dfsg-1
has caused the Debian Bug report #1139702,
regarding ITP: adept-math -- combined automatic differentiation and array
library
to be marked as done.
This means that you claim that the problem has been dealt with.
If this is not the case it is now your responsibility to reopen the
Bug report if necessary, and/or fix the problem forthwith.
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--
1139702: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=1139702
Debian Bug Tracking System
Contact [email protected] with problems
--- Begin Message ---
Package: wnpp
Severity: wishlist
Owner: Pierre Gruet <[email protected]>
X-Debbugs-Cc: [email protected]
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Hash: SHA512
* Package name : adept-math
Version : 2.1.3
Upstream Contact: University of Reading
* URL : https://www.met.reading.ac.uk/clouds/adept/
* License : Apache-2.0
Programming Lang: C++
Description : combined automatic differentiation and array library
Adept enables C++ algorithms to be automatically differentiated. For each
mathematical statement involving scalars or arrays of a special "active" type,
Adept stores the corresponding differential statement symbolically on a stack.
The stack may then be used to perform the following computations:
- Full Jacobian matrix. Given the non-linear function y=f(x) coded in C or
C++, Adept will compute the matrix H, where the element at row i and column
j of H is the partial derivative of y_i with respect to x_j. This matrix
will be computed much more rapidly and accurately than if you simply
recompute the function multiple times perturbing each element of x one by
one. The Jacobian matrix is used in the Gauss-Newton and Levenberg-Marquardt
minimization algorithms;
- Reverse-mode differentiation. This is a key component in optimization
problems where a non-linear function needs to be minimized but the state
vector x is too large for it to make sense to compute the full Jacobian
matrix. Atmospheric data assimilation is the canonical example in
Meteorology. Given a non-linear function y=f(x) and a vector of adjoints,
Adept will compute the vector of adjoints, without computing the full
Jacobian matrix H. The adjoint may then be used in a quasi-Newton
minimization scheme.
- Forward-mode differentiation. Given the non-linear function y=f(x) and a
vector of perturbations, Adept will compute the corresponding vector arising
from a linearization of the function f. Formally, the perturbed output is
given by the matrix-vector product, but it is computed here without computing
the full Jacobian matrix H. Note that Adept is optimized for the reverse
case, so might not be as fast (and will certainly not be as economical in
memory) in the forward mode as libraries written especially for that purpose.
This is a package I am using myself, and a dependency of the new upstream
version of stopt.
I plan to maintain it in the Debian-Math team.
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--- Begin Message ---
Source: adept-math
Source-Version: 2.1.3+dfsg-1
Done: Pierre Gruet <[email protected]>
We believe that the bug you reported is fixed in the latest version of
adept-math, which is due to be installed in the Debian FTP archive.
A summary of the changes between this version and the previous one is
attached.
Thank you for reporting the bug, which will now be closed. If you
have further comments please address them to [email protected],
and the maintainer will reopen the bug report if appropriate.
Debian distribution maintenance software
pp.
Pierre Gruet <[email protected]> (supplier of updated adept-math package)
(This message was generated automatically at their request; if you
believe that there is a problem with it please contact the archive
administrators by mailing [email protected])
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Format: 1.8
Date: Mon, 15 Jun 2026 21:06:24 +0200
Source: adept-math
Binary: libadept-dev libadept0 libadept0-dbgsym
Architecture: source amd64
Version: 2.1.3+dfsg-1
Distribution: experimental
Urgency: medium
Maintainer: Debian Math Team <[email protected]>
Changed-By: Pierre Gruet <[email protected]>
Description:
libadept-dev - combined automatic differentiation and array library
(development
libadept0 - combined automatic differentiation and array library (shared libr
Closes: 1139702
Changes:
adept-math (2.1.3+dfsg-1) experimental; urgency=medium
.
* Initial release (Closes: #1139702)
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