Showing 5 open source projects for "aspect"

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  • 1

    StochDecomp

    User Manual describing theory behind the package, installation instruc

    Stochasticity is an indispensable aspect of biochemical processes at the cellular level. Studies on how the noise enters and propagates in biochemical systems provided us with nontrivial insights into the origins of stochasticity, in total however they constitute a patchwork of different theoretical analyses. Here we present a flexible and generally applicable noise decomposition tool, that allows us to calculate contributions of individual reactions to the total variability of a system’s output. ...
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  • 2

    AspectR

    calculating aspect ratio

    Small tool for calculating the aspect ratio of a certain resolution
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  • 3

    Visual Aspect Ratio

    Aspect ratio calculator with GUI

    This small program allows you to enter two integers to return the aspect ratio. For example; HDTV uses a 16:9 aspect ratio, with common resolutions such as 1920x1080 or 1280x720. Have an obscure screen size? No problem! Enter the dimensions and hit enter to return the aspect ratio!
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  • 4
    reputron is a knowledge extraction engine platform that covers all aspect of text mining, relevance, indexing and querying on a corpus of text documents.
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  • 5
    ExoPlanet

    ExoPlanet

    GUI based toolkit for running common Machine Learning algorithms.

    ...With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. Post analysis, the toolkit further automates building the visual representations for the trained model.
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