The Python Papers Anthology
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Mapping Relational Operations onto Hypergraph Model
Get PDFThe relational model is the most commonly used data model for storing large datasets, perhaps due to the simplicity of the tabular format which had revolutionized database management systems. However, many real world objects are recursive and associative in nature which makes storage in the relational model difficult. The hypergraph model is a generalization of a graph model, where each hypernode can be made up of other nodes or graphs and each hyperedge can be made up of one or more edges. It may address the recursive and associative limitations of relational model. However, the hypergraph model is non-tabular; thus, loses the simplicity of the relational model. In this study, we consider the means to convert a relational model into a hypergraph model in two layers. At the bottom layer, each relational tuple can be considered as a star graph centered where the primary key node is surrounded by non-primary key attributes. At the top layer, each tuple is a hypernode, and a relation is a set of hypernodes. We presented a reference implementation of relational operators (project, rename, select, inner join, natural join, left join, right join, outer join and Cartesian join) on a hypergraph model. Using a simple example, we demonstrate that a relation and relational operators can be implemented on this hypergraph model
Bactome II: Analyzing Gene List for Gene Ontology Over-Representation
Get PDFMicroarray is an experimental tool that allows for the screening of several thousand genes in a single experiment and the analysis of which often requires mapping onto biological processes. This allows for the examination of processes that are over-represented. A number of tools have been developed but each differed in terms of organisms that can be analyzed (not sure what you mean here). Gene Ontology website has a list of up-to-date annotation files for different organisms that can be used for over-representation analysis. Each file maps each gene of the organism to its ontological terms. It is a simple tool that allows users to use the up-to-date annotation files to generate the expected and observed counts for each GO identifier (GO ID) from a given gene list for further statistical analyses
Python GUI Scripting Interface for Running Atomic Physics Applications
Get PDFWe create a Python GUI scripting interface working under Windows in addition to (UNIX/ Linux). The GUI has been built around the Python open-source programming language. We use the Python's GUI library that so called Python Mega Widgets (PMW) and based on Tkinter Python module (http://www.freenetpages.co.uk/hp/alan.gauld/tutgui.htm). The new GUI was motivated primarily by the desire of more updated operations, more flexibility incorporating future and current improvements in producing atomic data. Furthermore it will be useful for a variety of applications of atomic physics, plasma physics and astrophysics and will help in calculating various atomic properties
Key-value Storage Systems (and Beyond) with Python
Get PDFWeb application developers often use RDBMS systems such as MySql or PostgreSql but there are many other types of databases out there. Key-value storage, schema and schema-less document storage, and column-oriented DBMS systems abound. These kind of database systems are becoming more popular when developing scalable web applications but many developers are unsure how to integrate them into their projects. This talk will focus on the key-value class of data storage systems, weigh the strengths and drawbacks of each and discuss typical use cases for key value storage
Python Experiment Suite Implementation
Get PDFThis manuscript describes the implementation of a generic experiment management tool called Python Experiment Suite, an open source software framework written in Python, that supports scientists, engineers and others to conduct automated software experiments on a larger scale with features like parameter evaluations in grid search manner, result logging and support for multiple cores, amongst others
A Python Experiment Suite
Get PDFWe introduce the Python Experiment Suite, an open source software tool written in Python, that supports scientists, engineers and others to conduct automated generic software experiments on a larger scale with numerous features: parameter ranges and combinations can be evaluated automatically, where different experiment architectures (e.g. grid search) are available. The suite also takes care of logging results into files, can handle experiment interruption and continuation, for instance after process termination by power failure, supports execution on multiple cores and contains a convenient Python interface to retrieve the stored results. Configuration files ease the setup of complex experiments without modifying code, and various run-time options allow for a variety of use cases
Python for Collective Intelligence and Collaborative Filtering
Get PDFThis paper will define the two terms Collective Intelligence and Collaborative Filtering and discuss how these two ideas can be used to create personally relevant filters allowing end users more personalized access to information on their chosen topics of interest. In addition various mathematical models used to filter data and compare preferences and their corresponding pythonic implementations will be discussed. Finally a simple example using web APIs and Collective Intelligence algorithms will be demonstrated to provide an idea of the type of things that can be achieved, relatively easily, using python for Collective Intelligence and Collaborative Filtering. This short abstract will be accompanied by a talk given at PyCon Asia 2010