Metadata-Version: 1.1
Name: pysptools
Version: 0.14.1
Summary: A hyperspectral imaging tools box
Home-page: http://pysptools.sourceforge.net/
Author: Christian Therien
Author-email: ctherien@users.sourceforge.net
License: Apache License Version 2.0
Description: 
        PySptools is a hyperspectral and spectral imaging library that provides spectral algorithms for the Python programming language. Specializations of the library are the endmembers extraction, unmixing process, supervised classification, target detection, noise reduction, convex hull removal and features extraction at spectrum level.
        
        The library is designed to be easy to use and almost all functionality has a plot function to save you time with the data analysis process. The actual sources of the algorithms are the Matlab Hyperspectral Toolbox of Isaac Gerg, the pwctools of M. A. Little, the Endmember Induction Algorithms toolbox (EIA), the HySime Matlab module of José Bioucas-Dias and José Nascimento and science articles.
        
        The current version introduce a scikit-learn bridge. The bridge is partial and *alpha*.
        
        Functionalities
        ***************
        
        The functions and classes are organized by topics:
        
        * abundance maps: FCLS, NNLS, UCLS
        * classification: AbundanceClassification, NormXCorr, SAM, SID
        * detection: ACE, CEM, GLRT, MatchedFilter, OSP
        * distance: chebychev, NormXCorr, SAM, SID
        * endmembers extraction: ATGP, FIPPI, NFINDR, PPI
        * material count: HfcVd, HySime
        * noise: Savitzky Golay, MNF, whiten
        * sigproc: bilateral
        * sklearn: HyperEstimatorCrossVal, HyperSVC, HyperGradientBoostingClassifier, HyperRandomForestClassifier, HyperKNeighborsClassifier, HyperLogisticRegression and others
        * spectro: convex hull quotient, features extraction (tetracorder style), USGS06 lib interface
        * util: load_ENVI_file, load_ENVI_spec_lib, corr, cov, plot_linear_stretch, display_linear_stretch, convert2D, convert3D, normalize, InputValidation, ROIs and others
        
        The library do an extensive use of the numpy numeric library and can achieve good speed for some functions. The library is mature enough and is very usable even if the development is at a beta stage.
        
        Installation
        ************
        
        PySptools can run under Python 2.7 and 3.5. It is tested with these versions but can probably run under others Python versions.
        
        Manual installation
        ===================
        
        To install download the sources, expand it in a directory and add the path of
        the pysptools-0.xx.x directory to the PYTHONPATH system variable.
        
        Distutils installation
        ======================
        
        You can use Distutils. Expand the sources in a directory,
        go to the pysptools-0.xx.x directory and at the command prompt type 'python setup.py install'.
        To uninstall the library, you have to do it manually. Go to your python installation. In the
        Lib/site-packages folder simply removes the associated pysptools folder and files.
        
        Dependencies
        ************
        
            * Python 2.7 or 3.x
            * Numpy, required
            * Scipy, required
            * scikit-learn, required, version >= 0.18
            * SPy, required, version >= 0.17
            * Matplotlib, required, version 1.5.3 or less (not working with 2.0.x)
            * CVXOPT, optional, to run FCLS, version 1.1.8
            * IPython, optional, if you want to use the display feature
        
Keywords: python,hyperspectral imaging,signal processing,library,endmembers,unmixing,pysptools,sam,sid,atgp,N-FINDR,NFINDR,spectroscopy,target detection,georessources,geoimaging,chemical imaging,pharmaceutical,pharma,minerals,spectral,remote sensing
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
