tfancy legends, fix consolidation plot - 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 78d454149f22e5d2eb8b39a84159b78ff5259dc0
 (DIR) parent 3a3e4b680084c869f0c33d45b9c289b47b53962b
 (HTM) Author: Anders Damsgaard <anders.damsgaard@geo.au.dk>
       Date:   Thu, 11 Sep 2014 14:24:12 +0200
       
       fancy legends, fix consolidation plot
       
       Diffstat:
         M python/consolidation-curve.py       |      13 +++++++------
         M python/permeability-results.py      |       2 +-
         M python/shear-results.py             |      33 ++++++++++++++++++++-----------
       
       3 files changed, 29 insertions(+), 19 deletions(-)
       ---
 (DIR) diff --git a/python/consolidation-curve.py b/python/consolidation-curve.py
       t@@ -34,15 +34,16 @@ for c_grad_p in c_grad_p_list:
        
            if os.path.isfile('../output/' + sid + '.status.dat'):
                sim = sphere.sim(sid, fluid=True)
       -        t[c] = numpy.ones(sim.status())
       -        H[c] = numpy.ones(sim.status())
       +        t[c] = numpy.ones(sim.status()-1)
       +        H[c] = numpy.ones(sim.status()-1)
        
                #sim.visualize('walls')
                #sim.writeVTKall()
        
                #sim.plotLoadCurve()
                #sim.readfirst(verbose=True)
       -        for i in numpy.arange(1, sim.status()+1):
       +        #for i in numpy.arange(1, sim.status()+1):
       +        for i in numpy.arange(1, sim.status()):
                    sim.readstep(i, verbose=False)
                    t[c][i-1] = sim.time_current[0]
                    H[c][i-1] = sim.w_x[0]
       t@@ -92,11 +93,11 @@ plt.ylabel('Thickness change [m]')
        #plt.ticklabel_format(style='sci', axis='y', scilimits=(0,0))
        #for c in range(len(c_grad_p_list)):
            #H[c] /= -min_H_c
       -plt.semilogx(t[0], H[1], '-', label='$c$ = %.2f' % (c_grad_p_list[c]))
       -plt.semilogx(t[1], H[0], '--', label='$c$ = %.2f' % (c_grad_p_list[c]))
       +plt.semilogx(t[0], H[0], '-k', label='$c$ = %.2f' % (c_grad_p_list[0]))
       +plt.semilogx(t[1], H[1], '--k', label='$c$ = %.2f' % (c_grad_p_list[1]))
        #plt.grid()
        
       -plt.legend(loc=0, prop={'size':18})
       +plt.legend(loc='best', prop={'size':18}, fancybox=True, framealpha=0.5)
        plt.tight_layout()
        filename = 'cons-curves.pdf'
        plt.savefig(filename)
 (DIR) diff --git a/python/permeability-results.py b/python/permeability-results.py
       t@@ -86,7 +86,7 @@ plt.grid()
        #plt.plot(dpdz, phi_bar, '+')
        #plt.grid()
        
       -plt.legend(loc='lower left', prop={'size':18})
       +plt.legend(loc='lower left', prop={'size':18}, fancybox=True, framealpha=0.5)
        plt.tight_layout()
        filename = 'permeability-dpdz-vs-K-vs-c.pdf'
        #print(os.getcwd() + '/' + filename)
 (DIR) diff --git a/python/shear-results.py b/python/shear-results.py
       t@@ -14,7 +14,8 @@ import matplotlib.pyplot as plt
        
        #sigma0_list = numpy.array([1.0e3, 2.0e3, 4.0e3, 10.0e3, 20.0e3, 40.0e3])
        sigma0 = 10.0e3
       -cvals = [1.0, 0.1]
       +#cvals = [1.0, 0.1]
       +cvals = [1.0]
        c_phi = 1.0
        
        shear_strain = [[], [], []]
       t@@ -62,9 +63,9 @@ for c in numpy.arange(1,len(cvals)+1):
                p_max[c] = numpy.zeros_like(shear_strain[c])
                for i in numpy.arange(sim.status()):
                    iz_top = int(sim.w_x[0]/(sim.L[2]/sim.num[2]))-1
       -            p_mean[c][i] = numpy.mean(sim.p_f[:,:,0:iz_top])
       -            p_min[c][i] = numpy.min(sim.p_f[:,:,0:iz_top])
       -            p_max[c][i] = numpy.max(sim.p_f[:,:,0:iz_top])
       +            p_mean[c][i] = numpy.mean(sim.p_f[:,:,0:iz_top])/1000
       +            p_min[c][i] = numpy.min(sim.p_f[:,:,0:iz_top])/1000
       +            p_max[c][i] = numpy.max(sim.p_f[:,:,0:iz_top])/1000
        
            else:
                print(sid + ' not found')
       t@@ -95,12 +96,17 @@ for c in numpy.arange(1,len(cvals)+1):
                    label='$c$ = %.2f' % (cvals[c-1]))
        
            ax2.plot(shear_strain[c][1:], dilation[c][1:], \
       -            label='$c$ = %.2f' % (cvals[c-1]))
       +            label='$c$ = %.2f' % (cvals[c-1]), linewidth=2)
        
       -    ax3.plot(shear_strain[c][1:], p_max[c][1:]/1000, '--' + color[c])
       -    ax3.plot(shear_strain[c][1:], p_mean[c][1:]/1000, '-' + color[c], \
       -            label='$c$ = %.2f' % (cvals[c-1]))
       -    ax3.plot(shear_strain[c][1:], p_min[c][1:]/1000, '--' + color[c])
       +    alpha = 0.5
       +    ax3.plot(shear_strain[c][1:], p_max[c][1:], '-' + color[c], alpha=alpha)
       +    ax3.plot(shear_strain[c][1:], p_mean[c][1:], '-' + color[c], \
       +            label='$c$ = %.2f' % (cvals[c-1]), linewidth=2)
       +    ax3.plot(shear_strain[c][1:], p_min[c][1:], '-' + color[c], alpha=alpha)
       +
       +    ax3.fill_between(shear_strain[c][1:], p_min[c][1:], p_max[c][1:], 
       +            where=p_min[c][1:]<=p_max[c][1:], facecolor=color[c],
       +            interpolate=True, alpha=alpha)
        
        ax3.set_xlabel('Shear strain $\\gamma$ [-]')
        
       t@@ -115,9 +121,12 @@ ax1.grid()
        ax2.grid()
        ax3.grid()
        
       -ax1.legend(loc='lower right', prop={'size':18})
       -ax2.legend(loc='lower right', prop={'size':18})
       -ax3.legend(loc='lower right', prop={'size':18})
       +legend_alpha=0.5
       +ax1.legend(loc='best', prop={'size':18}, fancybox=True, framealpha=legend_alpha)
       +ax2.legend(loc='lower right', prop={'size':18}, fancybox=True,
       +        framealpha=legend_alpha)
       +ax3.legend(loc='lower right', prop={'size':18}, fancybox=True,
       +        framealpha=legend_alpha)
        
        plt.tight_layout()
        filename = 'shear-10kPa-stress-dilation.pdf'