Showing 5 open source projects for "plug"

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  • 1
    Autoplot

    Autoplot

    Autoplot is an interactive browser for data on the web

    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!
    Downloads: 1 This Week
    Last Update:
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  • 2

    sequoia-dap

    SEQUOIA ocean data assimilation platform (a SIROCCO suite tool)

    ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** Within the SIROCCO suite of numerical tools, the purpose of SDAP is to provide a flexible platform to carry out multivariate assimilation of geophysical data in a numerical model. The program is multi-grid (finite differences or finite elements), multi-algebra (plug-in analysis kernels), multi-model (simple standardized interface). The program supports reduced-order data assimilation methods, as well as Ensemble assimilation approaches such as the Ensemble Kalman Filter. Recent additions include extensions towards simultaneous assimilation and downscaling (AMICO project), and a toolbox for ensemble assessment (SCRUM project).
    Downloads: 0 This Week
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  • 3
    gsdview
    Geo-Spatial Data Viewer (GSDView) is a lightweight viewer for geo-spatial data and products. It is written in python and Qt4 and uses the GDAL library. GSDView is modular and has a simple plug-in architecture.
    Downloads: 0 This Week
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  • 4
    ESML is an interchange technology that utilizes external metadata to allow applications to plug and play seamlessly with Earth Science specific datasets in heterogeneous formats.
    Downloads: 2 This Week
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  • 5
    The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
    Downloads: 0 This Week
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