Getting started


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


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


Automatic Installation from PyPI:

pip uninstall pysesa (removes previous installation)
pip install pysesa

Automatic Installation from github:

git clone
cd pysesa
python install

or a local installation:

python install --user

or with admin privileges, e.g.:

sudo python install

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”

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


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+''

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)


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: Thanks for stopping by!