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@@ -5,7 +5,7 @@ b'Symbolic computing with sympy'@b'Ondrej Certik'@[email protected]@t@s | |
| b'Statistics with Scipy'@b'Robert Kern'@[email protected]@t@s | ||
| b'Cython'@b'Dag Sverre Seljebotn'@[email protected]@t@s | ||
| b'Using GPUs with PyCUDA'@b'Nicolas Pinto'@[email protected]@t@s | ||
| b'Designing scientific interfaces with Traits'@b'Enthought'@U@-1.00@t@s | ||
| b'Designing scientific interfaces with Traits'@b'Enthought'@M@-1.00@t@s | ||
| b'Mayavi/TVTK'@b'Prabhu Ramachandran'@[email protected]@t@s | ||
| b'The conference talks are held at the Beckman institute'@b'map.'@[email protected]@n@s | ||
| b'Welcome'@b'Jarrod Millman & Gael Varoquaux'@[email protected]@n@s | ||
|
|
@@ -41,7 +41,7 @@ b'ESPResSo++: A Python-controlled, Parallel Simulation Software for Soft Matter | |
| b'ESPResSo++: A Python-controlled, Parallel Simulation Software for Soft Matter Research'@b'Germany'@[email protected]@n@s | ||
| b'Sympy'@b'Ondrej Certik'@[email protected]@n@s | ||
| b'Sympy'@b'University of Nevada'@[email protected]@n@s | ||
| b'Sympy'@b'Reno'@M@1.00@n@s | ||
| b'Sympy'@b'Reno'@U@-1.00@n@s | ||
| b'Python implementation of weno interpolation and reconstruction'@b'Adrian Townsend'@[email protected]@n@s | ||
| b'Python implementation of weno interpolation and reconstruction'@b'University of Washington'@[email protected]@n@s | ||
| b'Writing Safer NumPy Extensions in C++ with Templates and TooN'@b'Damian Eads'@[email protected]@n@s | ||
|
|
@@ -56,13 +56,13 @@ b'Keynote:Modeling of Materials with Python'@b'Jonathan Guyer'@[email protected]@k@s | |
| b'Keynote:Modeling of Materials with Python'@b'NIST'@[email protected]@k@s | ||
| b'Hermes and FEMhub Project'@b'Pavel Solin'@[email protected]@n@s | ||
| b'Hermes and FEMhub Project'@b'University of Nevada'@[email protected]@n@s | ||
| b'Hermes and FEMhub Project'@b'Reno'@M@1.00@n@s | ||
| b'Hermes and FEMhub Project'@b'Reno'@U@-1.00@n@s | ||
| b'The PyMca Application and Toolkit'@b'Armando Sole'@[email protected]@n@s | ||
| b'The PyMca Application and Toolkit'@b'ESRF'@[email protected]@n@s | ||
| b'The PyMca Application and Toolkit'@b'France'@F@1.00@n@s | ||
| b'The PyMca Application and Toolkit'@b'France'@U@-1.00@n@s | ||
| b'Implementation of automatic script recording and network control for Mayavi'@b'Prabhu Ramachandran'@[email protected]@n@s | ||
| b'Implementation of automatic script recording and network control for Mayavi'@b'IIT Bombay'@[email protected]@n@s | ||
| b'Implementation of automatic script recording and network control for Mayavi'@b'India'@F@1.00@n@s | ||
| b'Implementation of automatic script recording and network control for Mayavi'@b'India'@U@-1.00@n@s | ||
| b'Fast numerical computations with Cython'@b'Dag Sverre Seljebotn'@[email protected]@n@s | ||
| b'Fast numerical computations with Cython'@b'University of Oslo'@[email protected]@n@s | ||
| b'Fast numerical computations with Cython'@b'Norway'@[email protected]@n@s | ||
|
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@@ -85,8 +85,8 @@ b'NumPy and SciPy Documentation in 2009 and Beyond'@b'Joe Harrington'@[email protected]@n@s | |
| b'NumPy and SciPy Documentation in 2009 and Beyond'@b'U. Central Florida'@[email protected]@n@s | ||
| b'Python in science and engineering education in India'@b'Prabhu Ramachandran'@[email protected]@n@s | ||
| b'Python in science and engineering education in India'@b'IIT Bombay'@[email protected]@n@s | ||
| b'Python in science and engineering education in India'@b'India'@F@1.00@n@s | ||
| b'Python in science and engineering education in India'@b'India'@U@-1.00@n@s | ||
| b'Next challenges for Python in Science'@b'Jarrod Millman'@[email protected]@n@s | ||
| b'Sprints'@b'Rooms Powell Booth 100 and Powell Booth 120 -map'@[email protected]@n@s | ||
| b'Sprints'@b'Rooms Powell Booth 100 and Powell Booth 120 -map'@[email protected]@n@s | ||
| ##2009 51 3 48 40 Pexpect: 0.240000 Nexpect: 13 Pobs: 0.000120 Pover: 0.454785 | ||
| ##2009 47 0 47 44 Pexpect: 0.240000 Nexpect: 12 Pobs: 0.000000 Pover: 0.458287 | ||
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@@ -23,23 +23,23 @@ b'IPython-powered Slideshow Reveal-ed'@b'Damian Avila'@[email protected]@n@s | |
| b'A Gentle Introduction To Machine Learning'@b'Kyle Kastner'@[email protected]@n@s | ||
| b'PyOP2: a Framework for Performance-Portable Unstructured Mesh-based Simulations and its Application to Finite-Element Computations'@b'Florian, Imperial College London, UK Rathgeber'@[email protected]@n@s | ||
| b'PyOP2: a Framework for Performance-Portable Unstructured Mesh-based Simulations and its Application to Finite-Element Computations'@b'Markall'@[email protected]@n@s | ||
| b'PyOP2: a Framework for Performance-Portable Unstructured Mesh-based Simulations and its Application to Finite-Element Computations'@b'Mi'@F@1.00@n@s | ||
| b'PyOP2: a Framework for Performance-Portable Unstructured Mesh-based Simulations and its Application to Finite-Element Computations'@b'Mi'@M@-1.00@n@s | ||
| b'Writing Reproducible Papers with Dexy'@b'Ana Nelson'@[email protected]@n@s | ||
| b'Hyperopt: A Python library for optimizing the hyperparameters of machine learning algorithms'@b'James Bergstra'@[email protected]@n@s | ||
| b'Hyperopt: A Python library for optimizing the hyperparameters of machine learning algorithms'@b'Dan Yamins'@[email protected]@n@s | ||
| b'Hyperopt: A Python library for optimizing the hyperparameters of machine learning algorithms'@b'Cox, David D., Harvard University'@U@-1.00@n@s | ||
| b'Hyperopt: A Python library for optimizing the hyperparameters of machine learning algorithms'@b'Cox, David D., Harvard University'@M@-1.00@n@s | ||
| b'Julia and Python: a dynamic duo for scientific computing'@b'Jeff Bezanson'@[email protected]@n@s | ||
| b'Julia and Python: a dynamic duo for scientific computing'@b'Stefan Karpinski'@[email protected]@n@s | ||
| b'GraphTerm: A notebook-like graphical terminal interface for collaboration and inline data visualization'@b'Ramalingam Saravanan'@[email protected]@n@s | ||
| b'Using Python for Structured Prediction'@b'Rob Zinkov'@[email protected]@n@s | ||
| b'Pythran: Enabling Static Optimization of Scientific Python Programs'@b'Serge Guelton'@[email protected]@n@s | ||
| b'Pythran: Enabling Static Optimization of Scientific Python Programs'@b'Pierrick Brunet'@U@-1.00@n@s | ||
| b'Pythran: Enabling Static Optimization of Scientific Python Programs'@b'Pierrick Brunet'@M@-1.00@n@s | ||
| b'Pythran: Enabling Static Optimization of Scientific Python Programs'@b'Alan Raynaud'@[email protected]@n@s | ||
| b'Pythran: Enabling Static Optimization of Scientific Python Programs'@b'Adrien Merlini'@[email protected]@n@s | ||
| b'Pythran: Enabling Static Optimization of Scientific Python Programs'@b'Mehdi Amini'@[email protected]@n@s | ||
| b'The advantages of a scientific IDE'@b'Carlos Cordoba'@[email protected]@n@s | ||
| b'Processing biggish data on commodity hardware: simple Python patterns'@b'Gael Varoquaux Institution: INRIA'@[email protected]@n@s | ||
| b'XDress - Type, But Verify'@b'Anthony, The University of Chicago & NumFOCUS, Inc. Scopatz'@U@-1.00@n@s | ||
| b'XDress - Type, But Verify'@b'Anthony, The University of Chicago & NumFOCUS, Inc. Scopatz'@M@-1.00@n@s | ||
| b'An efficient workflow for reproducible science'@b'Trevor Bekolay'@[email protected]@n@s | ||
| b'Python Tools for Coding and Feature Learning'@b'Leif Johnson'@[email protected]@n@s | ||
| b'Keynote: Trends in Machine Learning and the SciPy community'@b'Olivier Grisel'@[email protected]@k@s | ||
|
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@@ -48,28 +48,28 @@ b'Complex Experiment Configuration, Control, Automation, and Analysis using Robo | |
| b'Complex Experiment Configuration, Control, Automation, and Analysis using Robot Operating System (ROS)'@b'Andrew Straw'@[email protected]@n@s | ||
| b'mystic: a framework for predictive science'@b'Michael McKerns @ California Institute of Technology'@[email protected]@n@s | ||
| b'Modeling the Earth with Fatiando a Terra'@b'Leonardo Uieda'@[email protected]@n@s | ||
| b'Modeling the Earth with Fatiando a Terra'@b'Oliveira Jr'@U@-1.00@n@s | ||
| b'Modeling the Earth with Fatiando a Terra'@b'Barbosa'@U@-1.00@n@s | ||
| b'Modeling the Earth with Fatiando a Terra'@b'Oliveira Jr'@M@-1.00@n@s | ||
| b'Modeling the Earth with Fatiando a Terra'@b'Barbosa'@F@-1.00@n@s | ||
| b'vIPer, a new tool to work with IPython notebooks'@b'Damian Avila'@[email protected]@n@s | ||
| b'Skdata: Data seets and algorithm evaluation protocols in Python'@b'Nicolas Pinto'@[email protected]@n@s | ||
| b'Skdata: Data seets and algorithm evaluation protocols in Python'@b'Cox, David D., Harvard University'@U@-1.00@n@s | ||
| b'Skdata: Data seets and algorithm evaluation protocols in Python'@b'Cox, David D., Harvard University'@M@-1.00@n@s | ||
| b'Scientific Computing and the Materials Genome Initiative'@b'Andrew Reid'@[email protected]@n@s | ||
| b'OS deduplication with SIDUS (single-instance distributing universal system)'@b'Emmanuel, Centre Blaise Pascal (Lyon, France) Quemener'@U@-1.00@n@s | ||
| b'OS deduplication with SIDUS (single-instance distributing universal system)'@b'Emmanuel, Centre Blaise Pascal (Lyon, France) Quemener'@M@-1.00@n@s | ||
| b'OS deduplication with SIDUS (single-instance distributing universal system)'@b'Marianne Corvellec'@[email protected]@n@s | ||
| b'Infer.py: Probabilistic Programming and Bayesian Inference from Python'@b'Rob Zinkov'@[email protected]@n@s | ||
| b'Multidimensional Data Exploration with Glue'@b'Christopher Beaumont'@[email protected]@n@s | ||
| b'Multidimensional Data Exploration with Glue'@b'Thomas Robitaille'@[email protected]@n@s | ||
| b'Multidimensional Data Exploration with Glue'@b'Michelle Borkin'@[email protected]@n@s | ||
| b'Multidimensional Data Exploration with Glue'@b'Goodman'@U@-1.00@n@s | ||
| b'lpEdit: An editor to facilitate reproducible analysis via literate programming'@b'Adam, Duke University, CNRS France Richards'@U@-1.00@n@s | ||
| b'lpEdit: An editor to facilitate reproducible analysis via literate programming'@b'Kosinski Andrzej'@U@-1.00@n@s | ||
| b'Multidimensional Data Exploration with Glue'@b'Goodman'@F@-1.00@n@s | ||
| b'lpEdit: An editor to facilitate reproducible analysis via literate programming'@b'Adam, Duke University, CNRS France Richards'@M@-1.00@n@s | ||
| b'lpEdit: An editor to facilitate reproducible analysis via literate programming'@b'Kosinski Andrzej'@M@-1.00@n@s | ||
| b'lpEdit: An editor to facilitate reproducible analysis via literate programming'@b'Camille Bonneaud'@[email protected]@n@s | ||
| b'Roadmap to a Sentience Stack'@b'Eric Neuman'@[email protected]@n@s | ||
| b'Exploring disease genetics from thousands of individual genomes with Gemini'@b'Aaron Quinlan'@[email protected]@n@s | ||
| b'Exploring disease genetics from thousands of individual genomes with Gemini'@b'Uma Paila'@[email protected]@n@s | ||
| b'Exploring disease genetics from thousands of individual genomes with Gemini'@b'Brad Chapman'@[email protected]@n@s | ||
| b'Exploring disease genetics from thousands of individual genomes with Gemini'@b'Rory Kirchner'@[email protected]@n@s | ||
| b'metaseq: a Python framework for integrating high-throughput sequencing analyses'@b'Ryan, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Dale'@U@-1.00@n@s | ||
| b'metaseq: a Python framework for integrating high-throughput sequencing analyses'@b'Ryan, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Dale'@M@-1.00@n@s | ||
| b'Stuff to do with your genomic intervals'@b'Brent Pedersen'@[email protected]@n@s | ||
| b'Stuff to do with your genomic intervals'@b'University of Colorado'@[email protected]@n@s | ||
| b'All-by-all learning of protein complexes from mass spectrometry data'@b'Blake Borgeson'@[email protected]@n@s | ||
|
|
@@ -164,4 +164,4 @@ b'Diving into NumPy code'@b'David Cournapeau'@[email protected]@t@s | |
| b'Statistical Data Analysis in Python'@b'Christopher Fonnesbeck'@[email protected]@t@s | ||
| b'Using geospatial data with python'@b'Kelsey Jordahl'@[email protected]@t@s | ||
| b'An Introduction to scikit-learn (II)'@b'Ga\xc3\x83\xc2\xabl Varoquaux'@[email protected]@t@s | ||
| ##2013 131 12 119 35 Pexpect: 0.240000 Nexpect: 32 Pobs: 0.000003 Pover: 0.488004 | ||
| ##2013 142 13 129 24 Pexpect: 0.240000 Nexpect: 35 Pobs: 0.000001 Pover: 0.460394 | ||
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