tadd new 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 f747e43ef3abf99c7365e9eb6451f7bbd8828304
(DIR) parent 3e077e59134905ebc4b377df485aeb0f422682a9
(HTM) Author: Anders Damsgaard <anders.damsgaard@geo.au.dk>
Date: Mon, 6 Oct 2014 14:53:53 +0200
add new plot
Diffstat:
M python/shear-results-pressures.py | 4 ++--
A python/shear-results-strain.py | 148 +++++++++++++++++++++++++++++++
2 files changed, 150 insertions(+), 2 deletions(-)
---
(DIR) diff --git a/python/shear-results-pressures.py b/python/shear-results-pressures.py
t@@ -47,9 +47,8 @@ for i in numpy.arange(sim.status()):
dz = sim.L[2]/sim.num[2]
wall0_iz = int(sim.w_x[0]/dz)
for z in numpy.arange(0, wall0_iz+1):
- #(wall0_iz*dz - zpos_c[z] + 0.5*dz)*sim.rho_f*numpy.abs(sim.g[2])\
pres_static[z,i] = \
- (wall0_iz*dz - zpos_c[z])*sim.rho_f*numpy.abs(sim.g[2])\
+ (wall0_iz*dz - zpos_c[z] + 0.5*dz)*sim.rho_f*numpy.abs(sim.g[2])\
+ sim.p_f[0,0,-1]
#pres_static[z,i] = zpos_c[z]
#pres_static[z,i] = z
t@@ -77,6 +76,7 @@ ax1 = plt.subplot(311)
# cmap=cmap, norm=norm)
im1 = ax1.pcolormesh(shear_strain, zpos_c, dev_pres/1000.0, vmin=min_p,
vmax=max_p, rasterized=True)
+#im1 = ax1.pcolormesh(shear_strain, zpos_c, dev_pres/1000.0, rasterized=True)
#ax1.set_xlim([0, shear_strain[-1]])
#ax1.set_ylim([zpos_c[0], sim.w_x[0]])
ax1.set_xlabel('Shear strain $\\gamma$ [-]')
(DIR) diff --git a/python/shear-results-strain.py b/python/shear-results-strain.py
t@@ -0,0 +1,148 @@
+#!/usr/bin/env python
+import matplotlib
+matplotlib.use('Agg')
+matplotlib.rcParams.update({'font.size': 18, 'font.family': 'serif'})
+matplotlib.rc('text', usetex=True)
+matplotlib.rcParams['text.latex.preamble']=[r"\usepackage{amsmath}"]
+import shutil
+
+import os
+import numpy
+import sphere
+from permeabilitycalculator import *
+import matplotlib.pyplot as plt
+from matplotlib.ticker import MaxNLocator
+
+#cvals = ['dry', 1.0, 0.1]
+sigma0 = 20000.0
+cvals = ['dry', 1.0]
+step = 1000
+nsteps_avg = 1 # no. of steps to average over
+
+sim = sphere.sim('halfshear-sigma0=' + str(sigma0) + '-shear')
+sim.readfirst(verbose=False)
+
+
+# particle z positions
+zpos_p = numpy.zeros((len(cvals), sim.np))
+
+# cell midpoint cell positions
+zpos_c = numpy.zeros((len(cvals), sim.num[2]))
+dz = sim.L[2]/sim.num[2]
+for i in numpy.arange(sim.num[2]):
+ zpos_c[:,i] = i*dz + 0.5*dz
+
+# particle x displacements
+xdisp = numpy.zeros((len(cvals), sim.np))
+
+xdisp_mean = numpy.zeros((len(cvals), sim.num[2]))
+
+s = 0
+for c in cvals:
+
+ if c == 'dry':
+ fluid = False
+ sid = 'halfshear-sigma0=' + str(sigma0) + '-shear'
+ else:
+ fluid = True
+ sid = 'halfshear-sigma0=' + str(sigma0) + '-c=' + str(c) + '-shear'
+
+ sim = sphere.sim(sid, fluid=fluid)
+
+ if os.path.isfile('../output/' + sid + '.status.dat'):
+
+ for substep in numpy.arange(nsteps_avg):
+
+ if step + substep > sim.status():
+ raise Exception(
+ 'Simulation step %d not available (sim.status = %d).'
+ % (step, sim.status()))
+
+ sim.readstep(step + substep, verbose=False)
+
+ zpos_p[s,:] += sim.x[:,2]/nsteps_avg
+
+ xdisp[s,:] += sim.xyzsum[:,0]/nsteps_avg
+
+ #shear_strain[s] += sim.shearStrain()/nsteps_avg
+
+ # calculate mean values of xdisp and f_pf
+ for iz in numpy.arange(sim.num[2]):
+ z_bot = iz*dz
+ z_top = (iz+1)*dz
+ I = numpy.nonzero((zpos_p[s,:] >= z_bot) & (zpos_p[s,:] < z_top))
+ if len(I) > 0:
+ xdisp_mean[s,iz] = numpy.mean(xdisp[s,I])
+
+ else:
+ print(sid + ' not found')
+ s += 1
+
+
+#fig = plt.figure(figsize=(8,4*(len(steps))+1))
+#fig = plt.figure(figsize=(8,5*(len(steps))+1))
+fig = plt.figure(figsize=(8,6))
+
+ax = []
+linetype = ['-', '--', '-.']
+for s in numpy.arange(len(cvals)):
+
+ ax.append(plt.subplot(111))
+ #ax.append(plt.subplot(len(steps)*100 + 31 + s*3))
+ #ax.append(plt.subplot(len(steps)*100 + 32 + s*3, sharey=ax[s*4+0]))
+ #ax.append(plt.subplot(len(steps)*100 + 33 + s*3, sharey=ax[s*4+0]))
+ #ax.append(ax[s*4+2].twiny())
+
+ if cvals[s] == 'dry':
+ legend = 'dry'
+ else:
+ legend = 'c = ' + str(cvals[s])
+
+ ax[0].plot(xdisp[s], zpos_p[s], ',', color = '#888888')
+ ax[0].plot(xdisp_mean[s], zpos_c[s], linetype[s], color='k', label = legend,
+ linewidth=2)
+
+ ax[0].set_ylabel('Vertical position $z$ [m]')
+ ax[0].set_xlabel('$\\boldsymbol{x}^x_\\text{p}$ [m]')
+
+ #ax[s*4+0].get_xaxis().set_major_locator(MaxNLocator(nbins=5))
+ #ax[s*4+1].get_xaxis().set_major_locator(MaxNLocator(nbins=5))
+ #ax[s*4+2].get_xaxis().set_major_locator(MaxNLocator(nbins=5))
+
+ #plt.setp(ax[s*4+0].xaxis.get_majorticklabels(), rotation=90)
+ #plt.setp(ax[s*4+1].xaxis.get_majorticklabels(), rotation=90)
+ #plt.setp(ax[s*4+2].xaxis.get_majorticklabels(), rotation=90)
+ #plt.setp(ax[s*4+3].xaxis.get_majorticklabels(), rotation=90)
+
+ #if s == 0:
+ #y = 0.95
+ #if s == 1:
+ #y = 0.55
+
+ #strain_str = 'Shear strain $\\gamma = %.3f$' % (shear_strain[s])
+ #fig.text(0.1, y, strain_str, horizontalalignment='left', fontsize=22)
+ #ax[s*4+0].annotate(strain_str, xytext=(0,1.1), textcoords='figure fraction',
+ #horizontalalignment='left', fontsize=22)
+ #plt.text(0.05, 1.06, strain_str, horizontalalignment='left', fontsize=22,
+ #transform=ax[s*4+0].transAxes)
+ #ax[s*4+0].set_title(strain_str)
+
+ #ax[s*4+0].grid()
+ #ax[s*4+1].grid()
+ #ax[s*4+2].grid()
+ #ax1.legend(loc='lower right', prop={'size':18})
+ #ax2.legend(loc='lower right', prop={'size':18})
+
+legend_alpha=0.5
+ax[0].legend(loc='best', prop={'size':18}, fancybox=True, framealpha=legend_alpha)
+ax[0].grid()
+plt.tight_layout()
+plt.subplots_adjust(wspace = .05)
+plt.MaxNLocator(nbins=4)
+
+filename = 'shear-' + str(int(sigma0/1000.0)) + 'kPa-strain.pdf'
+plt.savefig(filename)
+shutil.copyfile(filename, '/home/adc/articles/own/2-org/' + filename)
+print(filename)
+
+