Search Results for "domain"

pandas is a Python data analysis library that provides high-performance, user friendly data structures and data analysis tools for the Python programming language. It enables you to carry out entire data analysis workflows in Python without having to switch to a more domain specific language. With pandas, performance, productivity and collaboration in doing data analysis in Python can significantly increase. pandas is continuously being developed to be a fundamental high-level building block for doing practical, real world data analysis in Python, as well as powerful and flexible open source data analysis/ manipulation tool for any language.

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! And we're not talking...

...Take a look at the advanced tour notebook to learn how to make the package more flexible, how to deal with categorical parameters, how to use observers, and more. Explore the options exemplifying the balance between exploration and exploitation and how to control it. Explore the domain reduction notebook to learn more about how search can be sped up by dynamically changing parameters' bounds.

...It supports exponential curve fitting for the calculation of the R1 and R2 relaxation rates, calculation of the NOE, reduced spectral density mapping, the Lipari and Szabo model-free analysis, study of domain motions via the N-state model and frame order dynamics theories using anisotropic NMR parameters such as RDCs and PCSs, the investigation of stereochemistry in dynamic ensembles, and the analysis of relaxation dispersion data.

The purpose of the SCiDA Pro program is to help with processing solar cell production data. It has the following features: - Able to handle large data sets in a fast way (e.g. plotting 100k cell data takes a few seconds) - Easy data filtering - Easy generation of a data summary report - Extensive data plotting features - Cross-platform (Windows/Linux/MacOS) - Supports multiple languages

Avogadro is an advanced molecular editor designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science and related areas. It offers a flexible rendering framework and a powerful plugin architecture.

Small python script that can visualize Inter Process Communication on Linux. It can create a graph of TCP and Unix sockets, pipes and also process hierarchy. Short (59 sec) demo visualizing ssh client connecting to ssh server on the same Ubuntu host: http://youtu.be/8XFKwzkexQY Longer (2 min 13 sec) demo visualizing ZoneMinder surveillance solution operation (stopping, starting, enabling and viewing camera): http://youtu.be/kM7klE61Ibk Tested on Ubuntu 14.10 and Debian...

A group a subprojects for Data Cleaning projects, mainly as a step of a Data Mining Project. Visit www.datacleaningopensource.com to review our current applications or if you want to add yours. NOTE: PROGRAMMING SKILLS ARE REQUIRED.

An object-oriented partial differential equation (PDE) solver, written in Python, based on a standard finite volume approach and includes interface tracking algorithms. *WARNING* The project is no longer using Sourceforge to maintain its repository.

idyuts is \"I Dare You to Use This Shell\"; a pre-hibernate approach to replacing an ORM written with jython functors into a pure-Java language command pattern. The \"pipeline codegen artifacts\" are simple IoC templates, and trivial to adapt