Showing 5 open source projects for "python data analysis"

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  • 1

    Hyperspectral data analysis in R

    Handling and basic analysis of hyperspectral data in R

    The hsdar package contains classes and functions to manage, analyse and simulate hyperspectral data. These might be either spectrometer measurements or hyperspectral images through the interface of rgdal.
    Downloads: 0 This Week
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  • 2
    iGPS

    iGPS

    An interactive tool for GNSS position time series analysis

    * Please check latest update on https://github.com/igps-ftk/iGPS A tool written in Interactive Data Language (IDL), for processing and analyzing daily continuous GPS position time series. It can read time series in various formats, detect outliers, remove abnormal observation spans, find jumps, extract common-mode components(CMC), etc.
    Downloads: 0 This Week
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  • 3
    OzGIS free open-source  mapping system

    OzGIS free open-source mapping system

    Analysis and display of Census, business, government attribute data

    OzGIS is an extensive mapping system for the analysis and display of geographically referenced data. Map data are downloaded from Census bureaux and map agencies or extracted from your own databases. The system can be used to to support management decisions associated with, for example, government planning, marketing, sales, site and personnel location, advertising and research.
    Downloads: 0 This Week
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  • 4
    The aim of this project is to translate the geostatistical BMELib Matlab Toolbox (http://www.unc.edu/depts/case/BMELIB/) into Python.
    Downloads: 0 This Week
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  • 5

    geoscipy

    Python-accessible toolkit for Geoscience & Remote Sensing Applications

    GeoSciPy is a set of C and Python functions that provide an API for all aspects of Geoscience and Remote Sensing Applications. Functions include reading/writing of many data formats, images, vectors, ..., and processing of images, vectors, ... including map projections, ... The library is written C, using HDF5 as the file format for storage of all remotely-sensed data and ancillary data, as well as processed data.
    Downloads: 0 This Week
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