Proceedings of SciPy 2014

X-ray astronomy is an important tool in the astrophysicist's toolkit to investigate high-energy astrophysical phenomena. Theoretical numerical simulations of astrophysical sources are fully three-dimensional representations of physical quantities such as density, temperature, and pressure, whereas astronomical observations are two-dimensional projections of the emission generated via mechanisms dependent on these quantities.

We present the motivation and architecture of Blaze, a library for cross-backend data-oriented computation. Blaze provides a standard interface to connect users familiar with NumPy and Pandas to other data analytics libraries like SQLAlchemy and Spark.

This paper presents a brief, semi-technical comparison of the essential features of the frequentist and Bayesian approaches to statistical inference, with several illustrative examples implemented in Python.

Numerical Lagrangian trajectory modeling is a natural method of investigating transport in a circulation system and understanding the physics on the wide range of length scales that are actually experienced by a drifter.

With laptops and tablets becoming more powerful and more ubiquitous in the classroom, traditional computer labs with rows of expensive desktop computers are slowly beginning to lose their relevance. An alternative approach for teaching Python is to use a browser-based virtual computer lab, with a notebook interface.

We introduce the ValidiPy package for validated numerics in Python. This suite of tools, which includes interval arithmetic and automatic differentiation, enables rigorous and guaranteed results using floating-point arithmetic.

Together with theory and experimentation, computational modeling and simulation has become a “third pillar” of scientific inquiry. I am developing a curriculum for a three part, graduate level course on computational methods designed to increase the exposure of graduate students and researchers in the School of Economics at the University of Edinburgh to basic techniques used in computational modeling and simulation using the Python programming language.

This article explains an approach to promote Information Technology (IT) literacy in India, which has evolved into a pyramid structure. We begin this article by explaining the design decisions, such as the use of FOSS and being a friendly interface between beginners and experts, in undertaking this activity.

Adjacency and neighbor structures play an essential role in many spatial analytical tasks. The computation of adjacenecy structures is non-trivial and can form a significant processing bottleneck as the total number of observations increases.

Python has powerful capabilities for coding elements of Web-based mapping applications. This paper highlights examples of analytical geospatial processing services that we have implemented for several Open Source-based development projects, including the Eastern Interconnection States' Planning Council (EISPC) Energy Zones Mapping Tool (http://eispctools.

Hyperopt-sklearn is a new software project that provides automatic algorithm configuration of the Scikit-learn machine learning library. Following Auto-Weka, we take the view that the choice of classifier and even the choice of preprocessing module can be taken together to represent a single large hyperparameter optimization problem.

This paper presents an overview of a project-based course in computing for physics majors using Python and the IPython Notebook that was developed at Cal Poly San Luis Obispo. The course materials are made freely available on GitHub as a project under the Computing4Physics C4P organization.

A course in numerical methods should teach both the mathematical theory of numerical analysis and the craft of implementing numerical algorithms. The IPython notebook provides a single medium in which mathematics, explanations, executable code, and visualizations can be combined, and with which the student can interact in order to learn both the theory and the craft of numerical methods.

Remote sensing data is complicated, very complicated! It is not only geometrically tricky but also, unlike in-situ methods, indirect as the sensor measures the interaction of the scattering media (eg raindrops) with the probing radiation, not the geophysics.

There are numerous barriers to the use of scientific computing toolsets. These barriers are becoming more apparent as we increasingly see mixing of different academic backgrounds, and compute ranging from laptops to cloud platforms.

The physics community is working to improve the undergraduate curriculum to include computer skills that graduates will need in the workforce. At Penn State Erie, The Behrend College, we have added computational tools to our Junior/Senior physics laboratory, PHYS421w Research Methods.

SciPy 2014, the thirteenth annual Scientific Computing with Python conference, was held July 6–12th in Austin, Texas. SciPyis a community dedicated to the advancement of scientific computing through open source Python software for mathematics,science, and engineering