GRpy
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############################################################################### File: README.txt Author: Sergei Last modified: August 30, 2009 This file is part of GRPy, a small GR-centered package. ############################################################################### INSTALLATION ------------------------------------------------------------------------------- GRPy has very few prerequisites. All you need are: - Python 2.6.2 or later - Sympy, the latest stable or better an SVN trunk build To install GRPy, simply untar the source tarball and make sure the directory is in you PYTHONPATH. See testtensor.py for example usage. NOTES ------------------------------------------------------------------------------- Note that all covariant indices are negative! (except 0 of course). Also, note that the answers given by the predefined routines are NOT simplified fully. This has to do with the fact that currently sympy can only perform very trivial simnplifications and fails to simplify complicated expressions or simply hangs. For this reason, the user is well-advised to apply the simplification separetly, see commands like trim, together, ratsimp, radsimp at: http://docs.sympy.org/genindex.html Also, note that this may be obsoleted if tensor objects are finally natively implemented in sympy ############################################################################ ############################################################################ The new version has been developed by Nataly Ibarra and Guillermo Rubilar: The code works for n-dimentional spaces and can compute many interesting geometrical quantities as is shown in the test (jupyter) notebook for the sphere. Problems with the computation of the determinant of the metric have been reported. For any comment please contact Nataly Ibarra at [email protected] An extensive manual will be ready soon!! ;) Last modification: November 4, 2015. Original version download from https://pypi.python.org/pypi/GRPy. ############################################################################ ############################################################################