Abstract is missing.
- A Technical Anatomy of SPM.Python, a Scalable, Parallel Version of PythonMinesh B. Amin. 1-9 [doi]
- Fitting and Estimating Parameter Confidence Limits with SherpaBrian Refsdal, Stephen Doe, Dan Nguyen, Aneta Siemiginowska. 10-16 [doi]
- Crab: A Recommendation Engine Framework for PythonMarcel Caraciolo, Bruno Melo, Ricardo Caspirro. 17-23 [doi]
- gpustats: GPU Library for Statistical Computing in PythonAndrew Cron, Wes McKinney. 24-28 [doi]
- Using the Global Arrays Toolkit to Reimplement NumPy for Distributed ComputationJeff Daily, Robert R. Lewis. 29-35 [doi]
- Vision Spreadsheet: An Environment for Computer VisionScott Determan. 36-39 [doi]
- Constructing scientific programs using SymPyMark Dewing. 40-43 [doi]
- Using Python, Partnerships, Standards and Web Services to provide Water Data for TexansDharhas Pothina, Andrew Wilson. 44-47 [doi]
- PyModel: Model-based testing in PythonJonathan Jacky. 48-52 [doi]
- Automation of Inertial Fusion Target Design with PythonMatthew Terry, Joseph Koning. 53-57 [doi]
- Hurricane Prediction with PythonMinwoo Lee, Charles W. Anderson, Mark DeMaria. 58-62 [doi]
- IMUSim - Simulating inertial and magnetic sensor systems in PythonMartin J. Ling, Alexander D. Young. 63-69 [doi]
- Using Python to Construct a Scalable Parallel Nonlinear Wave SolverKyle T. Mandli, Amal Alghamdi, Aron J. Ahmadia, David I. Ketcheson, William Scullin. 70-75 [doi]
- Building a Framework for Predictive ScienceMichael M. McKerns, Leif Strand, Tim Sullivan, Alta Fang, Michael A. G. Aivazis. 76-86 [doi]
- PyStream: Compiling Python onto the GPUNick Bray. 87-90 [doi]
- Bringing Parallel Performance to Python with Domain-Specific Selective Embedded Just-in-Time SpecializationShoaib Kamil 0001, Derrick Coetzee, Armando Fox. 91-97 [doi]
- N-th-order Accurate, Distributed Interpolation LibraryStephen M. McQuay, Steven E. Gorrell. 98-103 [doi]
- Google App Engine PythonDouglas A. Starnes. 104-106 [doi]
- Time Series Analysis in Python with statsmodelsWes McKinney, Josef Perktold, Skipper Seabold. 107-113 [doi]
- Improving efficiency and repeatability of lake volume estimates using PythonTyler McEwen, Dharhas Pothina, Solomon Negusse. 114 [doi]