Showing 5 open source projects for "distributions linux"

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  • 1
    GrainSizeTools script

    GrainSizeTools script

    A Python script for estimating the grain size from thin sections

    Homepage & docs: http://marcoalopez.github.io/GrainSizeTools/ GrainSizeTools is a free, open-source, cross-platform script written in Python that provides several tools for (1) estimating average grain size in polycrystalline materials, (2) characterizing the nature of the distribution of grain sizes (either from apparent distributions or approximating 3D grain size distributions via stereology), and estimating differential stress via paleopizometers. The script requires as the input the...
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  • 2

    Open Grid Analysis and Display System

    OpenGrADS provides extensions and interfaces for GrADS.

    The Grid Analysis and Display System (GrADS) is an interactive desktop tool for easy access, manipulation, and visualization of earth science data. The OpenGrADS Project seeks to develop advanced interfaces and extensions based on the main GrADS engine.
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    Downloads: 271 This Week
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  • 3

    TimescapeGlobal

    a space-time interpolation geostatistical tool

    This software is a time-aware geostatistical tool. Including time variability adds further issues to the already complicated field of geostatistical interpolation. On the other hand, most of the distributions of variables used in Earth and environmental sciences show patterns of change over time, not only in space. This tool is a free, open-source software, based on a generalization of the Inverse Distance Weighted algorithm. It outputs three-dimensional, layered discrete models from which...
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  • 4

    viewpix

    A Landsat 8 scene viewer

    ...This is the "lite" version of Viewpix as it has no cuda filters installed. Viewpix is written in C. It is tested on Ubuntu and Centos. It should work with most current Linux distributions. Viewpix runs efficiently on computers with modest CPU's such as low power mini-ITX boards. It is known to work nicely on Intel NUC, AMD A6 SOC , and NVIDIA TX2. A multiple core cpu, 8 GB ram, and a large capacity hard drive are suggested.
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  • 5
    Simulates data from a gaussian/beta/piecewise-linear species response function on an environmental gradient, with different sampling (error) distributions. See "Cline (biology)" on wikipedia.org.
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