ProceedingsSciPy ProceedingsContent License: Creative Commons Attribution 3.0 Unported (CC-BY-3.0)Credit must be given to the creatorProceedings of the 16th Python in Science ConferenceSciPy 2017, Austin, Texas July 10 - July 16July 10, 2017https://doi.org/10.25080/shinma-7f4c6e7-000Download PDFDownload BibtexSupporting DocumentsOrganizationSponsored StudentsAccepted Papers¶SPORCO: A Python package for standard and convolutional sparse representationsSPORCO: A Python package for standard and convolutional sparse representationsBrendt Wohlberghttps://doi.org/10.25080/shinma-7f4c6e7-001Software Transactional Memory in Pure PythonSoftware Transactional Memory in Pure PythonDillon Niederhuthttps://doi.org/10.25080/shinma-7f4c6e7-002BespON: Extensible config files with multiline strings, lossless round-tripping, and hex floatsBespON: Extensible config files with multiline strings, lossless round-tripping, and hex floatsGeoffrey Poorehttps://doi.org/10.25080/shinma-7f4c6e7-003LabbookDB: A Wet-Work-Tracking Database Application FrameworkLabbookDB: A Wet-Work-Tracking Database Application FrameworkHorea-Ioan Ioanas, Bechara Saab, Markus Rudinhttps://doi.org/10.25080/shinma-7f4c6e7-004pyMolDyn: Identification, structure, and properties of cavities in condensed matter and moleculespyMolDyn: Identification, structure, and properties of cavities in condensed matter and moleculesIngo Heimbach, Florian Rhiem, Fabian Beule, +3https://doi.org/10.25080/shinma-7f4c6e7-005PyHRF: A Python Library for the Analysis of fMRI Data Based on Local Estimation of the Hemodynamic Response FunctionPyHRF: A Python Library for the Analysis of fMRI Data Based on Local Estimation of the Hemodynamic Response FunctionJaime Arias, Philippe Ciuciu, Michel Dojat, +4https://doi.org/10.25080/shinma-7f4c6e7-006SciSheets: Providing the Power of Programming With The Simplicity of SpreadsheetsSciSheets: Providing the Power of Programming With The Simplicity of SpreadsheetsAlicia Clark, Joseph Hellersteinhttps://doi.org/10.25080/shinma-7f4c6e7-007The Sacred Infrastructure for Computational ResearchThe Sacred Infrastructure for Computational ResearchKlaus Greff, Aaron Klein, Martin Chovanec, +2https://doi.org/10.25080/shinma-7f4c6e7-008FigureFirst: A Layout-first Approach for Scientific FiguresFigureFirst: A Layout-first Approach for Scientific FiguresTheodore Lindsay, Peter Weir, Floris van Breugelhttps://doi.org/10.25080/shinma-7f4c6e7-009Parallel Analysis in MDAnalysis using the Dask Parallel Computing LibraryParallel Analysis in MDAnalysis using the Dask Parallel Computing LibraryMahzad Khoshlessan, Ioannis Paraskevakos, Shantenu Jha, +1https://doi.org/10.25080/shinma-7f4c6e7-00aMatchPy: A Pattern Matching LibraryMatchPy: A Pattern Matching LibraryManuel Krebber, Henrik Bartels, Paolo Bientinesihttps://doi.org/10.25080/shinma-7f4c6e7-00bpulse2percept: A Python-based simulation framework for bionic visionpulse2percept: A Python-based simulation framework for bionic visionMichael Beyeler, Geoffrey Boynton, Ione Fine, +1https://doi.org/10.25080/shinma-7f4c6e7-00cOptimised finite difference computation from symbolic equationsOptimised finite difference computation from symbolic equationsMichael Lange, Navjot Kukreja, Fabio Luporini, +4https://doi.org/10.25080/shinma-7f4c6e7-00dPython meets systems neuroscience: affordable, scalable and open-source electrophysiology in awake, behaving rodentsPython meets systems neuroscience: affordable, scalable and open-source electrophysiology in awake, behaving rodentsNarendra Mukherjee, Joseph Wachutka, Donald Katzhttps://doi.org/10.25080/shinma-7f4c6e7-00eAccelerating Scientific Python with Intel OptimizationsAccelerating Scientific Python with Intel OptimizationsOleksandr Pavlyk, Denis Nagorny, Andres Guzman-Ballen, +5https://doi.org/10.25080/shinma-7f4c6e7-00fNEXT: A system to easily connect crowdsourcing and adaptive data collectionNEXT: A system to easily connect crowdsourcing and adaptive data collectionScott Sievert, Daniel Ross, Lalit Jain, +3https://doi.org/10.25080/shinma-7f4c6e7-010ChiantiPy: a Python package for Astrophysical SpectroscopyChiantiPy: a Python package for Astrophysical SpectroscopyWill Barnes, Kenneth Derehttps://doi.org/10.25080/shinma-7f4c6e7-011Proceedings of the 16th Python in Science ConferenceOrganization
