Talk Open sprinting space

Presented by Admin Istrator in Scientific track 2010 on 2010/07/10 from 10:00 to 18:00

A room will be dedicated to open collaboration and sprinting.

At the same time

A Speech Recognition Toolkit based on Python

MDP: Modular toolkit for Data Processing (and its new features)

A Python Software Framework for Photonics Integrated Circuits

pyMetris : a flexible endoscope tracker

Topographica: Python simulator for computational neuroscience

Lightning talks

VisuAlea: Towards a Scientific Modelling Environment using Visual Programming

Automated tracking of computational experiments using Sumatra

Keynote: Konrad Hinsen, Python in Science, the next 15 years

Playdoh: a lightweight Python library for distributed computing and optimisation

Connectome Viewer - Visualization and Analysis of Connectome Data with Python

Algorithmic Differentiation in Python with Application Examples

Contribution of Python to the LMGC90 platform

Visualizing and segmenting large synchrotron-tomography datasets with the scientific-Python stack

WatchMan Project - A Python CASE framework for High Energy Physics data analysis in the LHC era

Computing with polynomials in SymPy

Tools for developing a Fortran library

Using Python and the GIS to Analyze the Spatial Localization of Firms in Cities

DANA, Distributed (Asynchronous) Numerical & Adaptive computing framework

Pre and post-processing with Salome

SfePy - Introduction, Examples, and Plans

Teaching Scientific computing in Developing countries


ObsPy: A Python Toolbox for Seismology

Sage: Creating a viable free open source alternative to Magma, Maple, Mathematica and Matlab

Python and geographic information systems: current applications and future potential in landscape ecology

High-throughput structural bioinformatics using Python and p3d

SciPy for Design for Six Sigma

GPU computing for machine learning with Theano

The Foundation for Mathematical and Scientific Computing

Multi-Physic Simulations in an Open Environment

A comparison of different approaches used to seek maintainability, performance and scalability in Python scientific code