# Tess Licensing

Tess is released as open source software under a BSD style [license](

# Tess Installation

(for tess based on qhull)

1. Install Dependencies

a. DIY

git clone
cd diy

b. Parallel netCDF

tar -xvf parallel-netcdf-1.4.1.tar.gz
cd parallel-netcdf-1.4.1
./configure --prefix=/your/install/location --with-mpi=/your/mpi/install/location --disable-fortran
make install

c. Qhull

tar -xvf qhull-2012.1-src.tgz
cd qhull-2012.1-src

2. Install Tess

git clone
cd tess

Configure using cmake:

cmake /path/to/tess \
-Dserial=QHull \
-DDIY_INCLUDE_DIRS=/path/to/diy/include \
-DDIY_LIBRARY=/path/to/diy/lib \
-DPNetCDF_INCLUDE_DIR=/path/to/pnetcdf/include \
-DPNetCDF_LIBRARY=/path/to/pnetcdf/lib \
-DQHull_INCLUDE_DIRS=/path/to/qhull/include \


# Tess Execution

1. Test tessellation only

(from tess top level directory)
cd examples/test-tess
edit TESS_TEST: select ARCH, num_procs, dsize (number of particles)
../../tools/draw 0
mouse move to rotate, ‘z’ + mouse up, down to zoom, ‘t’ to toggle voronoi tessellation, ‘y’ to toggle delaunay tessellation, ‘f’ to toggle shaded rendering

2. Test tessellation + density estimator

(from tess top level directory)
cd examples/tess-dense
edit TESS_DENSE_TEST; select ARCH, num_procs, dsize (number of particles), gsize (number of grid points)
../../tools/ --raw=dense.raw --numpts=512
(assuming outfile was dense.raw and gsize was 512 512 512 in TESS_DENSE_TEST) is a python script using numpy and matplotlib, but you can use your favorite visualization/plotting tool (VisIt, ParaView, R, Octave, Matlab, etc.) to plot the output. It is just an array of 32-bit floating-point density values listed in C-order (x changes fastest).