.. _getting_started: *************** Getting started *************** .. _about: About ====== PySESA - a Python framework for Spatially Explicit Spectral Analysis PySESA is an open-source project dedicated to provide a generic Python framework for spatially explicit statistical analyses of point clouds and other geospatial data, in the spatial and frequency domains, for use in the geosciences The program is detailed in: Buscombe, D. "Spatially explicit spectral analysis of point clouds and geospatial data", forthcoming. For the source code visit `the project github site `_ .. _license: License ======== This software is in the public domain because it contains materials that originally came from the United States Geological Survey, an agency of the United States Department of Interior. For more information, see `the official USGS copyright policy `_ Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. government. This software is issued under the `GNU Lesser General Public License, Version 3 `_ .. _setup: Setup ======== Automatic Installation from PyPI:: pip uninstall pysesa (removes previous installation) pip install pysesa Automatic Installation from github:: git clone git@github.com:dbuscombe-usgs/pysesa.git cd pysesa python setup.py install or a local installation:: python setup.py install --user or with admin privileges, e.g.:: sudo python setup.py install .. _virtualenv: Virtual environment ==================== You could try before you install, using a virtual environment:: virtualenv venv source venv/bin/activate pip install numpy pip install cython pip install scipy pip install joblib pip install statsmodels pip install matplotlib pip install ift_nifty pip install pysesa python -c "import pysesa; pysesa.test()" deactivate #(or source venv/bin/deactivate) The results will live in "venv/lib/python2.7/site-packages/pysesa" .. _manualinstall: Manual installation ==================== Python libraries you need to have installed to use pysesa: 1. `Nifty `_ 2. `SciPy `_ 3. `Numpy `_ 4. `Matplotlib `_ 5. `cython `_ 6. `statsmodels `_ 7. `joblib `_ All of the above are available through `pip `_ and `easy_install `_ Installation on Amazon Linux EC-2 instance ============================================ It's best to install numpy, scipy, cython and matplotlib through the OS package manager:: sudo yum install gcc gcc-c++ sudo yum install python27-numpy python27-Cython python27-scipy python27-matplotlib Then pysesa using pip (which will install nifty, joblib and statsmodels):: sudo pip install pysesa .. _test: Test ====== A test can be carried out by running the supplied script:: python -c "import pysesa; pysesa.test()" which carries out the following operations:: # general settings infile = os.path.expanduser("~")+os.sep+'pysesa_test'+os.sep+'example_100000pts.xyz' out = 1 #m output grid detrend = 4 #ODR plane proctype = 1 #Processing spectral parameters (no smoothing) mxpts = 1024 # max pts per window res = 0.05 #cm internal grid resolution nbin = 20 #number of bins for spectral binning lentype = 1 #l less than 0.5 taper = 1 #Hann taper prc_overlap = 0 #no overlap between successive windows minpts = 64 #min pts per window pysesa.process(infile, out, detrend, proctype, mxpts, res, nbin, lentype, minpts, taper, prc_overlap) .. _support: Support ========= This is a new project written and maintained by Daniel Buscombe. Bugs are expected - please report them, I will fix them quickly. Feedback and suggestions for improvements are *very* welcome Please download, try, report bugs, fork, modify, evaluate, discuss, collaborate. Please address all suggestions, comments and queries to: dbuscombe@usgs.gov. Thanks for stopping by! .. image:: _static/pysesa_colour.jpg