tDo not generate diffusion/advection plots by default - sphere - GPU-based 3D discrete element method algorithm with optional fluid coupling
 (HTM) git clone git://src.adamsgaard.dk/sphere
 (DIR) Log
 (DIR) Files
 (DIR) Refs
 (DIR) LICENSE
       ---
 (DIR) commit ea99eb813e0a8f5e11d9f5878cafd4b3b6f6b709
 (DIR) parent 60f837c2139f0dd664e1e009a6dec97be806cbcf
 (HTM) Author: Anders Damsgaard <anders.damsgaard@geo.au.dk>
       Date:   Thu,  3 Apr 2014 12:29:14 +0200
       
       Do not generate diffusion/advection plots by default
       
       Diffstat:
         M tests/cfd_tests.py                  |       4 ++--
       
       1 file changed, 2 insertions(+), 2 deletions(-)
       ---
 (DIR) diff --git a/tests/cfd_tests.py b/tests/cfd_tests.py
       t@@ -181,11 +181,11 @@ orig.setFluidPressureModulation(A=1.0, f=1.0/orig.time_total[0])
        orig.plotPrescribedFluidPressures()
        orig.run(verbose=False)
        py.plotConvergence()
       -py.plotFluidDiffAdvPresZ()
       +#py.plotFluidDiffAdvPresZ()
        #py.writeVTKall()
        for it in range(1,py.status()+1): # gradient should be smooth in all output files
            py.readstep(it, verbose=False)
       -    py.plotFluidDiffAdvPresZ()
       +    #py.plotFluidDiffAdvPresZ()
            ideal_grad_p_z =\
                    numpy.linspace(py.p_f[0,0,0], py.p_f[0,0,-1], py.num[2])
            compareNumpyArraysClose(numpy.zeros((1,py.num[2])),\