.. Copyright (c) 2015, Ecole Polytechnique Federale de Lausanne, Blue Brain Project All rights reserved. This file is part of NeuroM Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Reporting issues ================ Issues should be reported to the `NeuroM github repository issue tracker `_. The ability and speed with which issues can be resolved depends on how complete and succinct the report is. For this reason, it is recommended that reports be accompanied with * A minimal but self-contained code sample that reproduces the issue. Minimal means no code that is irrelevant to the issue should be included. Self-contained means it should be possible to run the code without modifications and reproduce the problem. * The observed and expected output and/or behaviour. If the issue is an error, the python error stack trace is extremely useful. * The commit ID of the version used. This is particularly important if reporting an error from an older version of NeuroM. * If reporting a regression, the commit ID of the change that introduced the problem * If the issue depends on data, a data sample which reproduces the problem should be up-loaded. But check first whether the error can be reproduced with any of the data samples available in the ``test_data`` directory.