Showing 233 open source projects for "python structural engineering"

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  • 1

    mullpy

    Multilabel-learning library built on python

    Mullpy is a machine-learning library that mainly aim to solve multi-label problems. It is classifier independent, has many ensemble capabilities (diversity methods like bagging, random subspaces, etc.) and automated results presentation (Excel, images as ROC or class-separated info, etc.). It is fully configurable. At the moment supports Neural Networks and classifiers defined in files. It is working on python3.3.
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  • 2

    PyVision Computer Vision Toolkit

    A Python computer vision library

    PyVision is a object-oriented Computer Vision Toolkit for researchers that contains vision and machine learning algorithms and algorithm analysis and easily interfaces with scipy/numpy, PIL, opencv and other computer and machine learning libraries.
    Downloads: 2 This Week
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  • 3

    EducationalLCS

    eLCS - Educational Learning Classifier System

    Educational Learning Classifier System (eLCS) is a set of learning classifier system (LCS) educational demos designed to introduce students or researchers to the basics of a modern Michigan-style LCS algorithm. This eLCS package includes 5 different implementations of a basic LCS algorithm, as part of a 6 stage set of demos that will be paired with the first introductory LCS textbook. Each eLCS implementations (from demo 2 up to demo 6) progressively add major components of the entire...
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  • 4
    [Kro]bot
    To design a complete, wheeled robot, capable of accomplishing simple tasks, manipulate objects and have human interaction capabilities. Includes electronic board design, firmware and AI programming, computer-robot interaction software and mechanics.
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  • 5

    Virtual Botmaster

    Simulate Botnet NetFlow traffic for research analysis

    Simulate Botnet NetFlow traffic for research analysis
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  • 6
    A collection of software made by Milos Rancic.
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  • 7
    FineSplice

    FineSplice

    Enhanced splice junction detection and estimation from RNA-Seq data

    FineSplice is a Python wrapper to TopHat2 geared towards a reliable identification of expressed exon junctions from RNA-Seq data, at enhanced detection precision with small loss in sensitivity. Following alignment with TopHat2 using known transcript annotations, FineSplice takes as input the resulting BAM file and outputs a confident set of expressed splice junctions with the corresponding read counts. Potential false positives arising from spurious alignments are filtered out via a...
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  • 8

    Botnet Detectors Comparer

    Compares botnet detection methods

    Compares botnet detection methods by computing the error metrics by reading the labels on a NetFlow file. The original NetFlow should have a new column for the ground-truth label, and a new column with the prediction label for each botnet detection method. This program computes all the error metrics (TPR, TNR, FPR, FNR, Precision, Accuracy, ErrorRate, FMeasure1, FMeasure2, FMeasure0.5) and output the comparison results. It also ouputs a png plot. The program can compare in a...
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  • 9
    Python interface to ECLiPSe Constraint Logic Programming.
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  • 10

    ktree

    clustering, machine learning, algorithms

    This project has moved to github at http://lmwtree.devries.ninja.
    Downloads: 0 This Week
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  • 11
    This project develops a simple, fast and easy to use Python graph library using NumPy, Scipy and PySparse.
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  • 12

    MSTParser

    MSTParser is a non-projective dependency parser that searches for maxi

    MSTParser is a non-projective dependency parser that searches for maximum spanning trees over directed graphs. Models of dependency structure are based on large-margin discriminative training methods. Projective parsing is also supported. mstparser 0.5.1 is now available via Maven Central. If you use Maven as your build tool, then you can add it as a dependency in your pom.xml file: <dependency> <groupId>net.sourceforge.mstparser</groupId> <artifactId>mstparser</artifactId> ...
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  • 13
    A High-Order Multi-Variate Approximation Scheme for Arbitrary Data Sets, C implementation of the method described in http://web.mit.edu/qiqi/www/paper/interpolation.pdf, with Python and Fortran interfaces.
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  • 14

    PyRoboSim2D

    Python+Pygame robot simulator 2D

    2D robotic simulator in Python 2.x, tested in 2.6 and 2.7, under Win7(64) and Ubuntu 10.04 (Lucid). Needs the matching version of Pygame installed! (www.pygame.org) Download the .py file and two .bmp files: -->back2_800_600 for background -->any of the robo1.bmp through robo4.bmp for robot image (different colors). The map of the "room" can be changed by modifying the list of obstacles. Read more in ReadMe.txt and in the .py file comments.
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  • 15
    MyNook

    MyNook

    A machine learning system for supervised document classification

    An open source system for supervised document classification based on statistical machine learning techniques. On the contrary of the state of art classification techniques, MyNook just requires the title of the document, not the content itself.
    Downloads: 0 This Week
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  • 16
    pySTEP or Python Strongly Typed gEnetic Programming: A light Genetic Programming API that allows the user to easily evolve populations of trees with precise grammatical and structural constraints.
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  • 17
    Evoversum
    This project has been moved to https://bitbucket.org/pbazant/evoversum/src/master/ . Evoversum is a fast Darwinian evolution simulator. The program simulates a 2D world populated with "animals" which struggle for food, reproduce and may also eat each other. The subject of evolution is their behavior, which may become quite complex. There is an updated video tutorial at http://www.youtube.com/watch?v=nPkZvyVDWJU !
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  • 18
    The TUM personal robotics package is a collection of libraries that aims to offer methods for personal robotic assistants to operate successfully in indoor environments.
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  • 19
    minder

    minder

    Monitoring your infrastructure for free.

    This software presents a flexible and configurable proposal for monitoring and management of real and virtual HPC infrastructures, compatible with paradigm of cloud computing. We help you to answer: 1) What is the performance of my resources? 2) What equipment and resources do we have already? 3) What do we need to upgrade or repair? 4) What can we consolidate to reduce complexity or reduce energy use? 5) What resources would be better reused somewhere else? Status: PreAlpha, so...
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  • 20
    JBoost is a simple, robust system for classification. JBoost contains implementations of several boosting algorithms in an alternating decision tree framework. In addition, JBoost provides extensible software for adding more learning algorithms.
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  • 21
    Open Exchange (OpEx)

    Open Exchange (OpEx)

    The open source Algorithmic Trading System

    OpEx is an application suite that includes the main building blocks of commercial electronic trading systems. All OpEx applications run on distributed system architectures.
    Downloads: 0 This Week
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  • 22
    Redundancy due to cut-paste operations in text creates bias in machine learning for NLP. This module takes a directory and produces a subset of the files in that directory (in a list) with an upper bound on similarity between two files.
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  • 23
    The PYthon LInguistic Laboratory (pylilac) is a Python library and a set of tools to help in studying, analyzing and engineering languages.
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  • 24
    mlpy

    mlpy

    Machine Learning Python

    mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X.
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  • 25
    ViAmI-Server

    ViAmI-Server

    Pattern recognition for ADL events

    This software uses computer vision algorithms for mining sequence data from telemonitoring data with CBRs. We propose an approach which treats the detection of changes in behavior detected with a sensor/video fusion, which occur at radically different time-scales, through a CBR in two levels: low and high level. The system is always updating the database with the daily data.
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