ttake a single step, define as input arg - sphere - GPU-based 3D discrete element method algorithm with optional fluid coupling
 (HTM) git clone git://src.adamsgaard.dk/sphere
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       ---
 (DIR) commit 52f9b3e785283482c5fd012b95599580ac14e2fb
 (DIR) parent ce6e548cf6900e585d97dbe8b5482a428c96600e
 (HTM) Author: Anders Damsgaard <anders.damsgaard@geo.au.dk>
       Date:   Wed, 10 Sep 2014 09:30:24 +0200
       
       ttake a single step, define as input arg
       
       Diffstat:
         M python/shear-results-forces.py      |      11 ++++++-----
       
       1 file changed, 6 insertions(+), 5 deletions(-)
       ---
 (DIR) diff --git a/python/shear-results-forces.py b/python/shear-results-forces.py
       t@@ -14,7 +14,8 @@ import matplotlib.pyplot as plt
        from matplotlib.ticker import MaxNLocator
        
        #steps = [5, 10, 100]
       -steps = [3]
       +#steps = [5, 10]
       +steps = [sys.argv[1]]
        nsteps_avg = 1 # no. of steps to average over
        
        sigma0 = 10.0e3
       t@@ -101,7 +102,7 @@ for step in steps:
                print(sid + ' not found')
            s += 1
        
       -fig = plt.figure(figsize=(8,4*(len(steps))))
       +fig = plt.figure(figsize=(8,4*(len(steps))+1))
        
        for s in numpy.arange(len(steps)):
            ax1 = plt.subplot((s+1)*100 + 31)
       t@@ -109,15 +110,15 @@ for s in numpy.arange(len(steps)):
            ax3 = plt.subplot((s+1)*100 + 33, sharey=ax1)
            ax4 = ax3.twiny()
        
       -    ax1.plot(xdisp[s], zpos_p[s], '+', color = '#888888')
       +    ax1.plot(xdisp[s], zpos_p[s], ',', color = '#888888')
            ax1.plot(xdisp_mean[s], zpos_c[s], color = 'k')
        
       -    ax2.plot(f_pf[s],  zpos_p[s], '+', color = '#888888')
       +    ax2.plot(f_pf[s],  zpos_p[s], ',', color = '#888888')
            ax2.plot(f_pf_mean[s], zpos_c[s], color = 'k')
        
            ax3.plot(dev_p[s]/1000.0, zpos_c[s], 'k')
        
       -    phicolor = '#666666'
       +    phicolor = '#888888'
            ax4.plot(phi_bar[s], zpos_c[s], '--', color = phicolor)
            for tl in ax4.get_xticklabels():
                tl.set_color(phicolor)