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WPSS stands for Web Panel Sample Service. It is a web application paired with the Qualtrics survey platform to meet the specific needs of high quality cross-national web surveys. WPSS enables: - a centralised management of survey fielding orchestration (publishing, sending invites and reminders), - and decentralised and privacy-compliant handling of panelist data. WPSS has been specified and developped within the framework of SSHOC, the Social Sciences and Humanities Open Cloud H2020, as part of the Work Package "Innovations in data production", led by ESS-ERIC. The software was developped by the CDSP's IT team at Sciences Po. Use cases can be found in the Social Sciences and Humanities but may extend to broader contexts as well. From October 2021 to June 2023, WPSS supports its first full-scale use case, within the frame of the European Social Survey for the web panel spinoff of ESS round 10, "Opinion Survey for (Country) "also known as the CRONOS-2 project.

fairgraph is an experimental Python library for working with metadata in the HBP/EBRAINS Knowledge Graph, with a particular focus on data reuse, although it is also useful in metadata registration/curation. This is v0.5.1 of fairgraph.

PyNN (pronounced 'pine') is a simulator-independent language for building neuronal network models.In other words, you can write the code for a model once, using the PyNN API and the Python programming language, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST and Brian) and on a number of neuromorphic hardware systems.Home page: http://neuralensemble.org/PyNN/Documentation: http://neuralensemble.org/docs/PyNN/Mailing list: https://groups.google.com/forum/?fromgroups#!forum/neuralensembleBug reports: https://github.com/NeuralEnsemble/PyNN/issuesThis is version 0.9.6. of PyNN

Givaro main features are implementations of the basic arithmetic of many mathematical entities: Primes fields, Extensions Fields, Finite Fields, Finite Rings, Polynomials, Algebraic numbers, Arbitrary precision integers and rationals (C++ wrappers over gmp), fixed precision integers. It also provides data-structures and templated classes for the manipulation of basic algebraic objects, such as vectors, matrices, univariate polynomials (and therefore recursive multivariate). It contains different program modules and is fully compatible with the FFLAS-FFPACK and LinBox linear algebra libraries.

The code of this toolbox is distributed under the terms of the GNU Public License version 3 (http://www.gnu.org/licenses/gpl.txt).The data files are distributed under specific licenses as stated in the related .txt files in the directory 'Data/'.; A toolbox to reproduce audio inpainting experiments from the paper Amir Adler, Valentin Emiya, Maria Jafari, Michael Elad, Rémi Gribonval, et al.. Audio Inpainting. IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2012, 20 (3), pp.922 - 932. ⟨10.1109/TASL.2011.2168211⟩. ⟨inria-00577079⟩

A SystemC simulator able to simulate embedded applications described using the AMALTHEA application model on top of crossbar-based manycore architectures in a cycle accurate way. This simulator has been developed by the LIRMM laboratory of Montpellier.Webpage: https://github.com/DreamCloud-Project/McSim-Cycle-accurate-Xbar

The Graph Sampling Toolbox is a Matlab toolbox implementing routines to reproduce experiments from the paper:Random Sampling for Bandlimited Graph Signals", by G. Puy, N. Tremblay, P. Vandergheynst and R. Gribonval,

Format converter from NEMO model to NetCDF standard (fcNEMOtoStd) What's new in fcNEMOtoStd? v1.5 - Added the masks conversion v1.4 - Improved loading of NetCDF files v1.3 - Introduced compression level for NetCDF files v1.2 - Improves the export of NetCDF files v1.1 - Set reference time in NetCDF files The authors acknowledges the TRIATLAS project, which has received funding from the European Union's Horizon 2020 Research and Innovation Program under grant agreement no. 817578 and to the International Joint Laboratory TAPIOCA (IRD-UFPE-UFRPE)

Année de la première version : 2014Interface utilisateur : interface WebMode de diffusion : service en ligne; Common european tree species sampled in Gascony hills in South-West of France.

Neo is a Python package for working with electrophysiology data in Python, together with support for reading a wide range of neurophysiology file formats, including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, Igor Pro, and support for writing to a subset of these formats plus non-proprietary formats including Kwik and HDF5. The goal of Neo is to improve interoperability between Python tools for analyzing, visualizing and generating electrophysiology data, by providing a common, shared object model. In order to be as lightweight a dependency as possible, Neo is deliberately limited to represention of data, with no functions for data analysis or visualization. Neo is used by a number of other software tools, including SpykeViewer (data analysis and visualization), Elephant (data analysis), the G-node suite (databasing), PyNN (simulations), tridesclous (spike sorting) and ephyviewer (data visualization). OpenElectrophy (data analysis and visualization) used an older version of Neo. Neo implements a hierarchical data model well adapted to intracellular and extracellular electrophysiology and EEG data with support for multi-electrodes (for example tetrodes). Neo’s data objects build on the quantities package, which in turn builds on NumPy by adding support for physical dimensions. Thus Neo objects behave just like normal NumPy arrays, but with additional metadata, checks for dimensional consistency and automatic unit conversion. This is version 0.9.0 of Neo. Release notes are available at https://neo.readthedocs.io/en/stable/releases/0.9.0.html