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ORCID10th SciPy 2011, Austin, Texas
- Stéfan van der Walt, Jarrod Millman:
Proceedings of the 10th Python in Science Conference 2011 (SciPy 2011), Austin, Texas, July 11 - 16, 2011. scipy.org 2011 - Minesh B. Amin:
A Technical Anatomy of SPM.Python, a Scalable, Parallel Version of Python. 1-9 - Brian Refsdal, Stephen Doe, Dan Nguyen, Aneta Siemiginowska:
Fitting and Estimating Parameter Confidence Limits with Sherpa. 10-16 - Marcel Caraciolo, Bruno Melo, Ricardo Caspirro:
Crab: A Recommendation Engine Framework for Python. 17-23 - Andrew Cron, Wes McKinney:
gpustats: GPU Library for Statistical Computing in Python. 24-28 - Jeff Daily, Robert R. Lewis:
Using the Global Arrays Toolkit to Reimplement NumPy for Distributed Computation. 29-35 - Scott Determan:
Vision Spreadsheet: An Environment for Computer Vision. 36-39 - Mark Dewing
:
Constructing scientific programs using SymPy. 40-43 - Dharhas Pothina, Andrew Wilson:
Using Python, Partnerships, Standards and Web Services to provide Water Data for Texans. 44-47 - Jonathan Jacky:
PyModel: Model-based testing in Python. 48-52 - Matthew Terry, Joseph Koning:
Automation of Inertial Fusion Target Design with Python. 53-57 - Minwoo Lee, Charles W. Anderson, Mark DeMaria:
Hurricane Prediction with Python. 58-62 - Martin J. Ling, Alexander D. Young:
IMUSim - Simulating inertial and magnetic sensor systems in Python. 63-69 - Kyle T. Mandli, Amal Alghamdi, Aron J. Ahmadia, David I. Ketcheson, William Scullin:
Using Python to Construct a Scalable Parallel Nonlinear Wave Solver. 70-75 - Michael M. McKerns, Leif Strand, Tim Sullivan, Alta Fang, Michael A. G. Aivazis:
Building a Framework for Predictive Science. 76-86 - Nick Bray:
PyStream: Compiling Python onto the GPU. 87-90 - Shoaib Kamil, Derrick Coetzee, Armando Fox:
Bringing Parallel Performance to Python with Domain-Specific Selective Embedded Just-in-Time Specialization. 91-97 - Stephen M. McQuay, Steven E. Gorrell:
N-th-order Accurate, Distributed Interpolation Library. 98-103 - Douglas A. Starnes:
Google App Engine Python. 104-106 - Wes McKinney, Josef Perktold, Skipper Seabold:
Time Series Analysis in Python with statsmodels. 107-113 - Tyler McEwen, Dharhas Pothina, Solomon Negusse:
Improving efficiency and repeatability of lake volume estimates using Python. 114-
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