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Numerical routines for working with spherical harmonic coefficients

Project description


SpherePy is a package for working with scalar and vector spherical harmonics. It provides:

  • scalar and vector spherical harmonic decompositions

  • objects for algebraically manipulating coefficients

  • the ability to plot coefficients and patterns



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Better Documentation

I’m working on a more complete set of documentation [HERE](


Ubuntu: Before installing SpherePy you must install build-essential, python-dev, and NumPy

` $ sudo apt-get install build-essential python-dev `

For NumPy you need to decide if you want to build it yourself with

` $ sudo pip install numpy `

or download the package with

` $ sudo apt-get install python-numpy `

I have been building NumPy using the pip method, but it takes a long time.

Then you can

` $ sudo pip install spherepy `

Windows: Make sure you have Numpy on your machine, then

` $ pip install spherepy `


If you would like to use the plotting routines within SpherePy, install matplotlib:

` $ sudo pip install matplotlib `

Quick Example

`python import spherepy as sp c = sp.random_coefs(4, 4) # generate some random coefficients sp.pretty_coefs(c) p = sp.ispht(c, 50, 50) # inverse spherical transform to pattern sp.plot_sphere_mag(p) # plot the magnitude of the pattern `


Reporting bugs, suggesting features, helping with documentation, and adding to the code is very welcome. See [Contributing](


Copyright (C) 2015 Randy Direen <>. SpherePy is licensed under GNU General Public License, version 3, a copy of this license has been provided within the COPYING file in this directory, and can also be found at <>.

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