tadd results from c=0.01 - sphere - GPU-based 3D discrete element method algorithm with optional fluid coupling
HTML git clone git://src.adamsgaard.dk/sphere
DIR Log
DIR Files
DIR Refs
DIR LICENSE
---
DIR commit f0b61ebf969f44f406fc957a85a252cd3cd7cc0a
DIR parent efb694257466958625ede9c375b0595eaa12c06d
HTML Author: Anders Damsgaard <anders.damsgaard@geo.au.dk>
Date: Mon, 13 Oct 2014 10:42:22 +0200
add results from c=0.01
Diffstat:
M python/shear-results-pressures.py | 9 ++++++---
M python/shear-results.py | 4 ++--
2 files changed, 8 insertions(+), 5 deletions(-)
---
DIR diff --git a/python/shear-results-pressures.py b/python/shear-results-pressures.py
t@@ -17,7 +17,8 @@ matplotlib.rcParams['image.cmap'] = 'bwr'
sigma0 = float(sys.argv[1])
#c_grad_p = 1.0
-c_grad_p = [1.0, 0.1]
+#c_grad_p = [1.0, 0.1]
+c_grad_p = [1.0, 0.1, 0.01]
c_phi = 1.0
t@@ -64,7 +65,7 @@ for c in numpy.arange(len(c_grad_p)):
#fig = plt.figure(figsize=(8,6))
#fig = plt.figure(figsize=(8,12))
-fig = plt.figure(figsize=(8,15))
+fig = plt.figure(figsize=(8,5*len(c_grad_p)+2))
#cmap = matplotlib.colors.ListedColormap(['b', 'w', 'r'])
t@@ -84,7 +85,9 @@ for c in numpy.arange(len(c_grad_p)):
#im1 = ax[c].pcolormesh(shear_strain[c], zpos_c[c], dev_pres[c]/1000.0,
#vmin=min_p, vmax=max_p, rasterized=True)
- im1 = ax[c].pcolormesh(shear_strain[c], zpos_c[c], dev_pres[c]/1000.0,
+ #im1 = ax[c].pcolormesh(shear_strain[c], zpos_c[c], dev_pres[c]/1000.0,
+ #rasterized=True)
+ im1 = ax[c].pcolormesh(shear_strain[c], zpos_c[c], pres[c]/1000.0,
rasterized=True)
if c == 0:
ax[c].set_xlim([0, numpy.max(shear_strain[c])])
DIR diff --git a/python/shear-results.py b/python/shear-results.py
t@@ -205,7 +205,7 @@ if smoothed_results:
alpha=0.5)
else:
ax1.plot(shear_strain[0], friction[0], label='dry', linewidth=1, alpha=0.5)
-ax2.plot(shear_strain[0], dilation[0], label='dry', linewidth=2)
+ax2.plot(shear_strain[0], dilation[0], label='dry', linewidth=1)
#ax4.plot(shear_strain[0], f_n_mean[0], '-', label='dry', color='blue')
#ax4.plot(shear_strain[0], f_n_max[0], '--', color='blue')
t@@ -220,7 +220,7 @@ for c in numpy.arange(1,len(cvals)+1):
label='$c$ = %.2f' % (cvals[c-1]), linewidth=1, alpha=0.5)
ax2.plot(shear_strain[c][1:], dilation[c][1:], \
- label='$c$ = %.2f' % (cvals[c-1]), linewidth=2)
+ label='$c$ = %.2f' % (cvals[c-1]), linewidth=1)
'''
alpha = 0.5