Open Source Python Information Analysis Software - Page 5

Diversity assessments and comparisons of large compound databases require calculating similarities of millions of compounds in an affordable time. ParaSim addresses this challenge by parallelizing the calculations according to the number of computing cores available on a single machine. It is optimized for the throughput of very large numbers of query structures against very large numbers of reference structures. As as special feature, ParaSim allows to store and and to access frequently queried datasets as persistant objects in memory for short response times. ParaSim calculates chemical similarities based on binary structural fingerprints. It does not compute fingerprints by itself but relies on third party software to do so. Basically, all types of structural fingerprints which can be stored in an array of bits (a bitset) can be used by ParaSim. See the Wiki (https://sourceforge.net/p/parasim/wiki/Documentation/) for detailed documentation. FEEDBACK HIGHLY APPRECIATED!

Retrieve statistics from SNMP-aware devices, store them in a database and graphically display them for monitoring and notification purposes.

Concurrent vision processing system; Toolkit for easy implementation of software concurrent vision processing sub-system. Aimed at robotic applications w/best effort realtime. System includes: capture,processing and displaying.

Como técnico en informática en un Instituto de Física con el tiempo surgió la necesidad de tener que crear distintas piezas de software para ir resolviendo situaciones diarias. En este proyecto iré agregando pequeños programas en Python 2.7 que voy escribiendo para dar soluciones a algunos de los problemas que surgen día a día en el laboratorio, como ser comunicación con algunos dispositivos o rutinas para ordenar o modificar datos de forma recursiva algunos cálculos matemáticos, creación de gráficas etc. La finalidad principal del proyecto es poder poner a disposición de aquel que lo necesite mi trabajo tanto dentro del Instituto donde trabajo como fuera del mismo. Asi como tambien recibir la mayor cantidad de criticas, consejos e ideas posibles para poder mejorar mi trabajo. Podrán ver que parte de los programas están mas documentados que otros tratare de ir poniéndome al día comentando el código y escribiendo la documentación de los distintos scripts.

Pink is an image processing library developed at ESIEE Engineering for research and teaching purposes. It contains implementations of over 200 algorithms for image segmentation and filtering.

Plotmeister is a data exploration tool. It parses your ASCII data and generates a simple (text-based) table format. You can modify this table and eventually create nice looking figures.

Poor Man's HPC is a framework that allows distributing and running code on a server farm. pmHPC is a scaled down and simplified version of distributed computing projects such as SETI, so is a perfect fit for enthusiasts and universities.

Network grep, on steroids

A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.

PyEsp - Enhanced/Evolving/Extensible Semantic Profiling. This Python program will sort and filter search results by applying semantic profiling on web pages. The program will learn the user preferences and profiling will be done on the client computer.

PyPedal is a Python module that provides tools for the manipulation of pedigrees, simple visualization of pedigrees, and the calculation of measures of genetic diversity from pedigrees.

PyPedal is a Python module that provides tools for the manipulation of pedigrees, simple visualization of pedigrees, and the calculation of measures of genetic diversity from pedigrees.

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.

This is a Python package for general Bayesian inference.

A lightweight, browsing-based, 100% Python, federated data integration framework. Users may create custom schemas for disparate sources, query and expand results across sources to find related data; for use in fields such as bioinformatics and datamining

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

py-rrdtool is a Python module provides an interface to RRDTool, the well known graphing/logging tool.

The Serial Data Acquisition is a lightweight data acquisition system able to parse a vast majority of mostly unidirectional streams. Results are saved in a SQLite DB and accessible over XML-RPC or plain HTTP. Its design is modular and easily extendable.

Python course (in Spanish) for Proteomics analysis using basically Jupyter NoteBooks. For more information, you can have a look at the readme.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/p4p/code/ci/default/tree/readme.md

Graph-based Extraction and Summarization - a generic graph-based summarization framework. Basic functionality is provided - third-party modules can be plugged in.

RDRPOSTagger is a robust, easy-to-use and language-independent rule-based toolkit for Part-of-Speech (POS) and morphological tagging. RDRPOSTagger obtains fast performance in both learning and tagging process. RDRPOSTagger also achieves a very competitive accuracy in comparison to the state-of-the-art results. RDRPOSTagger now supports pre-trained POS and morphological tagging models for Bulgarian, Czech, Dutch, English, French, German, Hindi, Italian, Portuguese, Spanish, Swedish, Thai and Vietnamese. Additionally, RDRPOSTagger supports the pre-trained Universal POS tagging models for 40 languages. See the full usage of RDRPOSTagger at: http://rdrpostagger.sourceforge.net/

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.

Rocksnake takes localities from geological mapping projects and plots them in 2D, over an optional basemap. Each locality has all the standard geology notebook contents and photos attached to it which can then be viewed from Rocksnake.

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.