Showing 32 open source projects for "spatial"

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  • 1
    RasCtrl is an ActiveX control for visualizing proteins and motifs. It provides not only functions to visualize proteins but also functions to visualize and manipulate motifs, which have conserved spatial arrangements across a group of proteins.
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  • 2
    Space Time Analysis of Regional Systems: Combines a suite of geocomputational and dynamic visualization modules for the exploratory analysis of data measured for spatial and temporal units.
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  • 3
    NrdbView is GIS (Geographic Information System) for displaying and editing of spatial data stored in .shp shapefiles( M, Z and Multipatch). NRDB View Use FreeImage lib to display georeferenced images. Actually MFC c++ but working on WxWidget migrating.
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  • 4
    TacitPixel is a scalable C++ framework for building application prototypes for interactive collaborative VR/AR applications. It provides a number of features that make prototyping fast and portable. TacitPixel is the successor of the TAP and Twisted Pair engines.
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  • 5
    This project produces an Extension and VBA module that allows ESRIs ArcMap (v8.x) product to access Open Source Postgresql/PostGIS spatial data tables. Includes importing tables and exporting/updating back to the database. Currently using Postgresql OD
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  • 6
    A simple, cross-browser, OGC WMS client that may be included into any HTML page that might be enhanced by dynamic rendering of geo-spatial data.
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  • 7
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface. ...
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