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Bug#790803: marked as done (ITP: Amp -- atomistic machine-learning potentials)

Your message dated Tue, 19 Sep 2017 13:00:10 +0000
with message-id <E1duI8I-000CNB-6I@fasolo.debian.org>
and subject line Bug#790803: fixed in amp 0.6-1
has caused the Debian Bug report #790803,
regarding ITP: Amp -- atomistic machine-learning potentials
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.

(NB: If you are a system administrator and have no idea what this
message is talking about, this may indicate a serious mail system
misconfiguration somewhere. Please contact owner@bugs.debian.org
immediately.)


-- 
790803: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=790803
Debian Bug Tracking System
Contact owner@bugs.debian.org with problems
--- Begin Message --- 
Package: wnpp
Severity: wishlist
Owner: Graham Inggs <graham@nerve.org.za>
X-Debbugs-CC: debian-devel@lists.debian.org

* Package name    : neural
  Version         : 1.0
  Upstream Author : Andrew Peterson, Alireza Khorshidi
* URL             : https://bitbucket.org/andrewpeterson/neural
* License         : GPL-3.0+
  Programming Lang: Python
  Description     : Machine Learning for Atomistics
 Neural is an open-source code designed to easily bring machine-learning to
 atomistic calculations. This allows one to predict (or really, interpolate)
 calculations on the potential energy surface, by optimizing a neural network
 representation of a "training set" of atomic images. The code works by
 learning from any other calculator (usually DFT) that can provide energy as
 a function of atomic coordinates. In theory, these predictions can take place
 with arbitrary accuracy approaching that of the original calculator.
 .
 Neural is designed to integrate closely with the Atomic Simulation
 Environment (ASE). As such, the interface is in pure python, although several
 compute-heavy parts of the underlying code also have fortran versions to
 accelerate the calculations. The close integration with ASE means that any
 calculator that works with ASE ─ including EMT, GPAW, DACAPO, VASP, NWChem,
 and Gaussian ─ can easily be used as the parent method.

--- End Message ---
--- Begin Message --- 
Source: amp
Source-Version: 0.6-1

We believe that the bug you reported is fixed in the latest version of
amp, 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 790803@bugs.debian.org,
and the maintainer will reopen the bug report if appropriate.

Debian distribution maintenance software
pp.
Muammar El Khatib <muammar@debian.org> (supplier of updated amp 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 ftpmaster@ftp-master.debian.org)


-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256

Format: 1.8
Date: Sat, 29 Jul 2017 21:12:31 -0400
Source: amp
Binary: python3-amp
Architecture: source amd64
Version: 0.6-1
Distribution: unstable
Urgency: medium
Maintainer: Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
Changed-By: Muammar El Khatib <muammar@debian.org>
Description:
 python3-amp - Atomistic Machine-learning Package (python 3)
Closes: 790803
Changes:
 amp (0.6-1) unstable; urgency=medium
 .
   * Initial release (Closes: #790803)
Checksums-Sha1:
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 6bb88003be352f9c3a2610a3675ef37a1c3632ae 3222959 amp_0.6.orig.tar.gz
 1bd1122ad32bb2f8d51032c281e963a0daf9b58c 2912 amp_0.6-1.debian.tar.xz
 3926a2b4c60f9bb02aca33a447f9e6ee0abb6738 8302 amp_0.6-1_amd64.buildinfo
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 b0ed00e19174afe44635a198035f8ffb908179b4dc0e46418a40f1ab338610f3 8302 amp_0.6-1_amd64.buildinfo
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Files:
 befed29b2bc8466e2e8b4e65b619c486 2114 science optional amp_0.6-1.dsc
 cb5b79b15eaba0703f1ccd698b406e7a 3222959 science optional amp_0.6.orig.tar.gz
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 ebaec299ca536c19a7b4f1934e98f255 8302 science optional amp_0.6-1_amd64.buildinfo
 cb64cc0cf1a686522a568baf3d085853 482888 debug extra python3-amp-dbgsym_0.6-1_amd64.deb
 7b793310322763ec1b75a43f70295b56 225644 science optional python3-amp_0.6-1_amd64.deb

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