Proceedings of SciPy 2012
SciPy 2012, the 11th annual Scientific Computing with Python conference, was held July 16-21, 2012 in Austin, Texas. 13 peer reviewed articles were published in the conference proceedings. Full proceedings and organizing committee can be found at https://
In many large-scale computations, systems of equations arise in the form , where is a linear operation to be performed on the unknown data , producing the known right-hand side, , which represents some constraint of known or assumed behavior of the system being modeled.
Modern processor architectures, in addition to having still more cores, also require still more consideration to memory-layout in order to run at full capacity. The usefulness of most languages is deprecating as their abstractions, structures or objects are hard to map onto modern processor architectures efficiently.
We present QuTiP (http://www.qutip.org), an object-oriented, open-source framework for solving the dynamics of open quantum systems. Written in Python, and using a combination of Cython, NumPy, SciPy, and matplotlib, QuTiP provides an environment for computational quantum mechanics that is both easy and efficient to use.
We add a random variable type to a mathematical modeling language. We demonstrate through examples how this is a highly separable way to introduce uncertainty and produce and query stochastic models. We motivate the use of symbolics and thin compilers in scientific computing.
Flow cytometry has the ability to measure multiple parameters of a heterogeneous mix of cells at single cell resolution. This has lead flow cytometry to become an integral tool in immunology and biology.
The Reference Model for disease progression is based on a modeling framework written in Python. It is a prototype that demonstrates the use of computing power to aid in chronic disease forecast. The model uses references to publicly available data as a source of information, hence the name for the model.
In this paper, I describe the workings of my personal hobby project - a self-driving lego mindstorms robot. The body of the robot is built with Lego Mindstorms. An Android smartphone is used to capture the view in front of the robot.
PythonTeX is a new LaTeX package that provides access to the full power of Python from within LaTeX documents. It allows Python code entered within a LaTeX document to be executed, and provides access to the output.
VisIt is an open source, turnkey application for scientific data analysis and visualization that runs on a wide variety of platforms from desktops to petascale class supercomputers. VisIt's core software infrastructure is written in C++, however Python plays a vital role in enabling custom workflows.
FLASH is a high-performance computing (HPC) multi-physics code which is used to perform astrophysical and high-energy density physics simulations. To run a FLASH simulation, the user must go through three basic steps: setup, build, and execution.
This work describes the use some scientific Python tools to solve information gathering problems using Reinforcement Learning. In particular, we focus on the problem of designing an agent able to learn how to gather information in linked datasets.
Basic principles in biosensing and nanomaterials precede the introduction of a novel fiber optic sensor. Software limitations in the biosensing domain are presented, followed by the development of a Python-based simulation environment.
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