Open Source Python Information Analysis Software - Page 2

A web-based interface for the Hadoop MapReduce framework that simplifies the process of writing and running MapReduce jobs. Aimed at introducing parallelism concepts in introductory computer science courses.

Dowser is a research tool for the web. It clusters results from search engines, associates words that appear in previous searches, and keeps a local cache of all the results you click on in a searchable database. It helps you keep track of what you find.

Pretty Damn Quick (PDQ) analytically solves queueing network models of computer and manufacturing systems, data networks, etc., written in conventional programming languages. Generic or customized reports of predicted performance measures are output.

IMPORTANT: The project moved over to github! You can find it at: https://github.com/exhuma/python-cluster

This is a Python-based efficient implementation of several semantic similarity measures. The target is to enable fast and easy calculation of similarity between proteins and genes using the Gene Ontology (GO).

A graphical tool to create Finite Impulse Response (FIR) filters.

KML is a knowledge base with support of logical modeling. Advanced model is used to represent knowledge as a set of statements similar to natural language sentences. This project hosts a set of model storage library and server (vrb-ols) and clients.

Moved to Google Code, see http://code.google.com/p/pythonequations/downloads/list

RISO: distributed, heterogeneous Bayesian belief networks. Belief network: a probability model defined on an acyclic directed graph; distributed: nodes can be on different hosts; and heterogeneous: allowing different types of conditional distributions.

This is an automatic spike detection program which takes account of probe geometry and produces a .mask file to be used with the new masked version of KlustaKwik. We recommend you use Python 2.6 or 2.7, e.g. a free academic version can be obtained from Entthought Python. The input files for SpiKeDeteKt are: .dat (raw data file) .probe (probe file, described below - user constructed) parameters.py (optional - otherwise it uses defaultparameters.py) SpiKeDeteKt outputs the following files: .fet.n (feature file) .mask.n (needed for using the new (masked) KlustaKwik) .clu.n (a trivial clue file where everything is put into a single cluster) .fmask.n (trial - float masks instead of binary, we are using this for testing masked KlustaKwik) .spk.n (spike file) .upsk.n (unfiltered spike waveform) .res.n (list of spike times) .xml (an xml file with all the parameters that can subsequently be used by neuroscope or klusters) .fil (highpass filtered data) .h5 (

ExpLab is a set of tools that supports the running, documentation and evaluation of computational experiments.

Net.py is a tool for learning about neural nets. Currently, it only allows the user to experiment with a Hopfield net. I am now extending it to cover the Kohonen net. I'd be pleased to receive suggestions and criticism.

ThoughtFlow-Sys is a new computer neuropsychological test developed in Python to study the verbal expression of thought flow, using a modification of Jung´s Word-Association Test. © 2008 - UNIFESP / Rodrigo C. Vertulo / Prof. Dr. Carlos J. R. Campos

Yet Another Audio Feature Extractor is a toolbox for audio analysis. Easy to use and efficient at extracting a large number of audio features simultaneously. WAV and MP3 files supported, or embedding in C++, Python or Matlab applications.

Autoplot is an interactive browser for data on the web. Give Autoplot a URL or local file name and it creates a sensible plot of the data. Autoplot allows you to interactively browse data stored in ascii, .cdf, netcdf, and many other formats. Autoplot's source has been moved to GitHub. Thanks to SourceForge for many years of hosting!

Banyan is an enterprise class, web based, information management system that helps people work collaboratively to solve complex problems. Banyan increases project performance and reduces risk through the power of collaborative clear thinking.

This project houses software to analyze data acquired from electrophysiology experiments. Currently, we have an Octave/MATLAB program to analyze electroneurogram traces of coupled oscillators, and a Perl library for the analysis of voltage trace data

A cross-platform text analysis program written in Python and Free Pascal/Lazarus which scans a whole text file (in plain text, HTML, EPUB, or ODT formats) and ranks all used words according to frequency, performing a quantitative analysis of the text using Shannon-Weaver information statistic and Zipf power law function. It counts words, sentences, chars, spaces, and syllables. Also computes readability indexes (Gunning-Fog, Coleman-Liau, Automated Readability Index (ARI), SMOG grade, Flesch–Kincaid grade level and Flesch Reading Ease).

The Model Interaction Environment for Neuroscience provides tools for development, searching, editing, execution, and visualization of biophysical models, abstract mathematical models, and experimental protocols used in neuroscience research.

This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people.

Open Metaheuristic (oMetah) is a library aimed at the conception and the rigourous testing of metaheuristics (i.e. genetic algorithms, simulated annealing, ...). The code design is separated in components : algorithms, problems and a test report generator

PyPotrace is a Python programming language binding for Peter Selinger's Potrace raster to vector conversion algorithm. No separate Potrace library or application required!

Pyphant is a framework for scientific data analysis. It features a flexible plugin architecture allowing for the application in many different fields. For the analysis a graph of processing steps is constructed, that can be applied via the cli as well.

A Signal Acquisition, Visualization & Analysis software application: * Signals, as in analog sensor data * Acquisition, as in data sampling/capturing/recording * Visualization, as in plotting raw/processed data * Analysis, as in live/post data processing Capabilities: The software has build in support for National Instruments Daq equipment (NI-DAQ) or it can load external source scripts (python), for customizable data sources. Supports data exporting/importing to multiple file formats (H5, CSV, Matlab, txt) Raw and analyzed data can be visualized and inspected in real-time or via playback. Most traditional signal processing methods are available, such as trending (Mean, Peak, Min/Max, RMS, Variance, Kurtosis, Skew, MAD) and frequency domain analysis (FFT, FRF, Order Spectrum). For machinery/rotor dynamics impact testing, tacho, order tracking, order spectra, waterfall plots, orbit plots and bode plots are supported.

.ESA file editor (VOC71M Environnement S.A. analyzer), with comprehensive and facility improuvments.