tmodify plotContacts to optional data output, add creep dynamics 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 bc291003152a18b8628c5c600e6ae61a1a5ddcee
(DIR) parent cd17a179736874baf8385287c4cfdf074e99d12c
(HTM) Author: Anders Damsgaard <anders.damsgaard@geo.au.dk>
Date: Fri, 15 May 2015 20:35:31 +0200
modify plotContacts to optional data output, add creep dynamics plot
Diffstat:
A python/halfshear-darcy-creep-dynam… | 482 +++++++++++++++++++++++++++++++
M python/sphere.py | 13 +++++++------
2 files changed, 489 insertions(+), 6 deletions(-)
---
(DIR) diff --git a/python/halfshear-darcy-creep-dynamics.py b/python/halfshear-darcy-creep-dynamics.py
t@@ -0,0 +1,482 @@
+#!/usr/bin/env python
+import matplotlib
+matplotlib.use('Agg')
+import shutil
+
+import os
+import sys
+import numpy
+import sphere
+import matplotlib.pyplot as plt
+import matplotlib.patches
+import matplotlib.colors
+import matplotlib.ticker
+import matplotlib.cm
+
+matplotlib.rcParams.update({'font.size': 7, 'font.family': 'sans-serif'})
+matplotlib.rc('text', usetex=True)
+matplotlib.rcParams['text.latex.preamble']=[r"\usepackage{amsmath}"]
+
+#import seaborn as sns
+#sns.set(style='ticks', palette='Set2')
+#sns.set(style='ticks', palette='colorblind')
+#sns.set(style='ticks', palette='muted')
+#sns.set(style='ticks', palette='pastel')
+#sns.set(style='ticks', palette='pastel')
+#sns.set(style='ticks')
+#sns.despine() # remove right and top spines
+
+outformat='pdf'
+
+
+sids = ['halfshear-darcy-sigma0=10000.0-k_c=2e-16-mu=2.08e-07-ss=2000.0-A=4000.0-f=0.2']
+timescalings=[1.157e-4]
+
+steps = numpy.arange(1625, 1875)
+plotsteps = numpy.array([1670,1750,1850]) # slow creep, fast creep, slip
+#plotsteps = numpy.array([1670])
+contactfigs = []
+contactidx = []
+
+datalists = [[], [], []]
+strikelists = [[], [], []]
+diplists = [[], [], []]
+forcemagnitudes = [[], [], []]
+alphas = [[], [], []]
+f_n_maxs = [[], [], []]
+taus = [[], [], []]
+ts = [[], [], []]
+Ns = [[], [], []]
+
+#f_min = 1.0
+#f_max = 1.0e16
+lower_limit = 0.3
+upper_limit = 0.5
+f_n_max = 50 # for force chain plots
+
+N = numpy.zeros_like(steps, dtype=numpy.float64)
+t = numpy.zeros_like(steps, dtype=numpy.float64)
+
+
+s=0
+for sid in sids:
+
+ sim = sphere.sim(sid, fluid=True)
+ t_DEM_to_t_real = timescalings[s]
+
+ i=0
+ i_scatter = 0
+ for step in steps:
+
+ sim.readstep(step, verbose=False)
+ if i == 0:
+ L = sim.L
+
+ N[i] = sim.currentNormalStress('defined')
+ t[i] = sim.currentTime()
+ #sim.plotContacts(outfolder='../img_out/')
+
+ if (step == plotsteps).any():
+ #contactdata.append(sim.plotContacts(return_data=True))
+ datalists[i_scatter], strikelists[i_scatter], diplists[i_scatter],\
+ forcemagnitudes[i_scatter], alphas[i_scatter], \
+ f_n_maxs[i_scatter] = sim.plotContacts(return_data=True,
+ lower_limit=lower_limit,
+ upper_limit=upper_limit)
+ #f_min=f_min,
+ #f_max=f_max)
+ #contactfigs.append(
+ #sim.plotContacts(return_fig=True,
+ #f_min=f_min,
+ #f_max=f_max))
+ #datalists.append(data)
+ #strikelists.append(strikelist)
+ #diplists.append(diplist)
+ #forcemagnitudes.append(forcemagnitude)
+ #alphas.append(alpha)
+ #f_n_maxs.append(f_n_max)
+ ts[i_scatter] = t[i]
+ Ns[i_scatter] = N[i]
+ #taus.append(sim.shearStress('defined'))
+ taus[i_scatter] = sim.shearStress('defined')
+
+ #contactidx.append(step)
+ i_scatter += 1
+
+
+ i += 1
+ s += 1
+
+
+
+ ## PLOTTING ######################################################
+
+ # Time in days
+ scalingfactor = 1./t_DEM_to_t_real / (24.*3600.)
+ t_scaled = t*scalingfactor
+
+
+ ## Normal stress plot
+ fig = plt.figure(figsize=[3.5, 3.5])
+
+ ax1 = plt.subplot(1, 1, 1)
+
+ ax1.plot(t_scaled, N/1000., '-k', label='$N$', clip_on=False)
+ ax1.plot([0,10],[taus[0]/.3/1000., taus[0]/.3/1000.], '--', color='gray')
+ ax1.set_xlabel('Time [d]')
+ ax1.set_ylabel('Effective normal stress $N$ [kPa]')
+
+ ax1.spines['right'].set_visible(False)
+ ax1.spines['top'].set_visible(False)
+ # Only show ticks on the left and bottom spines
+ ax1.yaxis.set_ticks_position('left')
+ ax1.xaxis.set_ticks_position('bottom')
+
+ ax1.set_xlim([numpy.min(t_scaled), numpy.max(t_scaled)])
+ #ax1.locator_params(axis='x', nbins=5)
+ ax1.locator_params(axis='y', nbins=4)
+
+ ## Contact scatter plots
+ dx=.23; dy=.23
+
+ # Scatter plot 1
+ sc=0
+ Lx=.17; Ly=.3;
+ #xytext=(Lx+.5*dx, Ly+.5*dy)
+ xytext=(Lx+.15*dx, Ly+dy+.07)
+ xy=(ts[0]*scalingfactor, Ns[0]/1000.)
+ #print xytext
+ #print xy
+ ax1.annotate('',
+ xytext=xytext, textcoords='axes fraction',
+ xy=xy, xycoords='data',
+ arrowprops=dict(arrowstyle='->', connectionstyle='arc3'))
+
+ axsc1 = fig.add_axes([Lx, Ly, dx, dy], polar=True)
+ cs = axsc1.scatter(strikelists[sc], 90. - diplists[sc], marker='o',
+ c=forcemagnitudes[sc],
+ s=forcemagnitudes[sc]/f_n_maxs[sc]*5.,
+ alpha=alphas[sc],
+ edgecolors='none',
+ vmin=f_n_maxs[sc]*lower_limit,
+ vmax=f_n_maxs[sc]*upper_limit,
+ cmap=matplotlib.cm.get_cmap('afmhot_r'))#,
+ #norm=matplotlib.colors.LogNorm())
+ # tick locations
+ #thetaticks = numpy.arange(0,360,90)
+ # set ticklabels location at 1.3 times the axes' radius
+ #ax.set_thetagrids(thetaticks, frac=1.3)
+ axsc1.set_xticklabels([])
+ axsc1.set_yticklabels([])
+
+ axsc1.set_title('\\textbf{Slow creep}', fontsize=7)
+ if upper_limit < 1.0:
+ cbar = plt.colorbar(cs, extend='max', fraction=0.035, pad=0.04)
+ else:
+ cbar = plt.colorbar(cs, fraction=0.045, pad=0.04)
+ #cbar.set_label('$||\\boldsymbol{f}_n||$')
+ cbar.set_label('$\\boldsymbol{f}_\\text{n}$ [N]')
+ cbar.locator = matplotlib.ticker.MaxNLocator(nbins=4)
+ cbar.update_ticks()
+
+ # plot defined max compressive stress from tau/N ratio
+ axsc1.scatter(0., numpy.degrees(numpy.arctan(taus[sc]/Ns[sc])),
+ marker='+', c='none', edgecolor='red', s=100)
+ axsc1.scatter(0., numpy.degrees(numpy.arctan(taus[sc]/Ns[sc])),
+ marker='o', c='none', edgecolor='red', s=100)
+ '''
+ ax.sc1scatter(0., # actual stress
+ numpy.degrees(numpy.arctan(
+ self.shearStress('effective')/
+ self.currentNormalStress('effective'))),
+ marker='+', color='blue', s=300)
+ '''
+
+ axsc1.set_rmax(90)
+ axsc1.set_rticks([])
+ #axsc1.grid(False)
+
+ # force chain plot
+
+ axfc1 = fig.add_axes([Lx-0.007, Ly-0.7*dy, dx, dy*0.7])
+
+ data = datalists[sc]
+
+ # find the max. value of the normal force
+ #f_n_max = numpy.amax(data[:,6])
+
+ # specify the lower limit of force chains to do statistics on
+ f_n_lim = lower_limit * f_n_max
+
+ # find the indexes of these contacts
+ I = numpy.nonzero(data[:,6] >= f_n_lim)
+
+ #color = matplotlib.cm.spectral(data[:,6]/f_n_max)
+ for i in I[0]:
+
+ x1 = data[i,0]
+ #y1 = data[i,1]
+ z1 = data[i,2]
+ x2 = data[i,3]
+ #y2 = data[i,4]
+ z2 = data[i,5]
+ f_n = data[i,6]
+
+ lw_max = 1.0
+ if f_n >= f_n_max:
+ lw = lw_max
+ else:
+ lw = (f_n - f_n_lim)/(f_n_max - f_n_lim)*lw_max
+
+ #print lw
+ axfc1.plot([x1,x2], [z1,z2], '-k', linewidth=lw)
+ #axfc1.plot([x1,x2], [z1,z2], '-', linewidth=lw, color=forcemagnitudes[sc])
+ #axfc1.plot([x1,x2], [z1,z2], '-', linewidth=lw, color=color)
+
+ axfc1.spines['right'].set_visible(False)
+ axfc1.spines['left'].set_visible(False)
+ # Only show ticks on the left and bottom spines
+ axfc1.xaxis.set_ticks_position('none')
+ axfc1.yaxis.set_ticks_position('none')
+ axfc1.set_xticklabels([])
+ axfc1.set_yticklabels([])
+ axfc1.set_xlim([numpy.min(data[I[0],0]), numpy.max(data[I[0],0])])
+ axfc1.set_ylim([numpy.min(data[I[0],2]), numpy.max(data[I[0],2])])
+ axfc1.set_aspect('equal')
+
+
+
+ # Scatter plot 2
+ sc=1
+ Lx=.37; Ly=.7;
+ #xytext=(Lx+.5*dx, Ly+.5*dy)
+ xytext=(Lx+.5*dx, Ly+.05)
+ xy=(ts[sc]*scalingfactor, Ns[sc]/1000.)
+ #print xytext
+ #print xy
+ ax1.annotate('',
+ xytext=xytext, textcoords='axes fraction',
+ xy=xy, xycoords='data',
+ arrowprops=dict(arrowstyle='->', connectionstyle='arc3'))
+
+ axsc2 = fig.add_axes([Lx, Ly, dx, dy], polar=True)
+
+ cs = axsc2.scatter(strikelists[sc], 90. - diplists[sc], marker='o',
+ c=forcemagnitudes[sc],
+ s=forcemagnitudes[sc]/f_n_max*5.,
+ alpha=alphas[sc],
+ edgecolors='none',
+ vmin=f_n_maxs[sc]*lower_limit,
+ vmax=f_n_maxs[sc]*upper_limit,
+ cmap=matplotlib.cm.get_cmap('afmhot_r'))#,
+ #norm=matplotlib.colors.LogNorm())
+ # tick locations
+ #thetaticks = numpy.arange(0,360,90)
+ # set ticklabels location at 1.3 times the axes' radius
+ #ax.set_thetagrids(thetaticks, frac=1.3)
+ axsc2.set_xticklabels([])
+ axsc2.set_yticklabels([])
+
+ axsc2.set_title('\\textbf{Fast creep}', fontsize=7)
+ if upper_limit < 1.0:
+ cbar = plt.colorbar(cs, extend='max', fraction=0.035, pad=0.04)
+ else:
+ cbar = plt.colorbar(cs, fraction=0.045, pad=0.04)
+ cbar.set_label('$\\boldsymbol{f}_\\text{n}$ [N]')
+ #cbar.set_label('Contact force [N]')
+ cbar.locator = matplotlib.ticker.MaxNLocator(nbins=4)
+ cbar.update_ticks()
+
+ # plot defined max compressive stress from tau/N ratio
+ axsc2.scatter(0., numpy.degrees(numpy.arctan(taus[sc]/Ns[sc])),
+ marker='+', c='none', edgecolor='red', s=100)
+ axsc2.scatter(0., numpy.degrees(numpy.arctan(taus[sc]/Ns[sc])),
+ marker='o', c='none', edgecolor='red', s=100)
+ '''
+ ax.sc2scatter(0., # actual stress
+ numpy.degrees(numpy.arctan(
+ self.shearStress('effective')/
+ self.currentNormalStress('effective'))),
+ marker='+', color='blue', s=300)
+ '''
+
+ axsc2.set_rmax(90)
+ axsc2.set_rticks([])
+ #axsc2.grid(False)
+
+ # force chain plot
+
+ #axfc2 = fig.add_axes([Lx+dx+0.05, Ly+0.03, dx, dy*0.7])
+ axfc2 = fig.add_axes([Lx+dx+0.10, Ly+0.03, dx, dy*0.7])
+
+ data = datalists[sc]
+
+ # find the max. value of the normal force
+ #f_n_max = numpy.amax(data[:,6])
+
+ # specify the lower limit of force chains to do statistics on
+ f_n_lim = lower_limit * f_n_max
+
+ # find the indexes of these contacts
+ I = numpy.nonzero(data[:,6] >= f_n_lim)
+
+ #color = matplotlib.cm.spectral(data[:,6]/f_n_max)
+ for i in I[0]:
+
+ x1 = data[i,0]
+ #y1 = data[i,1]
+ z1 = data[i,2]
+ x2 = data[i,3]
+ #y2 = data[i,4]
+ z2 = data[i,5]
+ f_n = data[i,6]
+
+ lw_max = 1.0
+ if f_n >= f_n_max:
+ lw = lw_max
+ else:
+ lw = (f_n - f_n_lim)/(f_n_max - f_n_lim)*lw_max
+
+ #print lw
+ axfc2.plot([x1,x2], [z1,z2], '-k', linewidth=lw)
+ #axfc2.plot([x1,x2], [z1,z2], '-', linewidth=lw, color=forcemagnitudes[sc])
+ #axfc2.plot([x1,x2], [z1,z2], '-', linewidth=lw, color=color)
+
+ axfc2.spines['right'].set_visible(False)
+ axfc2.spines['left'].set_visible(False)
+ # Only show ticks on the left and bottom spines
+ axfc2.xaxis.set_ticks_position('none')
+ axfc2.yaxis.set_ticks_position('none')
+ axfc2.set_xticklabels([])
+ axfc2.set_yticklabels([])
+ axfc2.set_xlim([numpy.min(data[I[0],0]), numpy.max(data[I[0],0])])
+ axfc2.set_ylim([numpy.min(data[I[0],2]), numpy.max(data[I[0],2])])
+ axfc2.set_aspect('equal')
+
+
+
+
+ # Scatter plot 3
+ sc=2
+ #Lx=.50; Ly=.40;
+ Lx=.65; Ly=.40;
+ #xytext=(Lx+.5*dx, Ly+.5*dy)
+ #xytext=(Lx+1.75*dx, Ly+0.01)
+ xytext=(Lx+1.15*dx, 0.2)
+ xy=(ts[sc]*scalingfactor, Ns[sc]/1000.)
+ #print xytext
+ #print xy
+ ax1.annotate('',
+ xytext=xytext, textcoords='axes fraction',
+ xy=xy, xycoords='data',
+ arrowprops=dict(arrowstyle='->', connectionstyle='arc3'))
+
+ axsc2 = fig.add_axes([Lx, Ly, dx, dy], polar=True)
+
+ cs = axsc2.scatter(strikelists[sc], 90. - diplists[sc], marker='o',
+ c=forcemagnitudes[sc],
+ s=forcemagnitudes[sc]/f_n_max*5.,
+ alpha=alphas[sc],
+ edgecolors='none',
+ vmin=f_n_maxs[sc]*lower_limit,
+ vmax=f_n_maxs[sc]*upper_limit,
+ cmap=matplotlib.cm.get_cmap('afmhot_r'))#,
+ #norm=matplotlib.colors.LogNorm())
+ # tick locations
+ #thetaticks = numpy.arange(0,360,90)
+ # set ticklabels location at 1.3 times the axes' radius
+ #ax.set_thetagrids(thetaticks, frac=1.3)
+ axsc2.set_xticklabels([])
+ axsc2.set_yticklabels([])
+
+ axsc2.set_title('\\textbf{Slip}', fontsize=7)
+ if upper_limit < 1.0:
+ cbar = plt.colorbar(cs, extend='max', fraction=0.035, pad=0.04)
+ else:
+ cbar = plt.colorbar(cs, fraction=0.045, pad=0.04)
+ cbar.set_label('$\\boldsymbol{f}_\\text{n}$ [N]')
+ #cbar.set_label('Contact force [N]')
+ cbar.locator = matplotlib.ticker.MaxNLocator(nbins=4)
+ cbar.update_ticks()
+
+ # plot defined max compressive stress from tau/N ratio
+ axsc2.scatter(0., numpy.degrees(numpy.arctan(taus[sc]/Ns[sc])),
+ marker='+', c='none', edgecolor='red', s=100)
+ axsc2.scatter(0., numpy.degrees(numpy.arctan(taus[sc]/Ns[sc])),
+ marker='o', c='none', edgecolor='red', s=100)
+ '''
+ ax.sc2scatter(0., # actual stress
+ numpy.degrees(numpy.arctan(
+ self.shearStress('effective')/
+ self.currentNormalStress('effective'))),
+ marker='+', color='blue', s=300)
+ '''
+
+ axsc2.set_rmax(90)
+ axsc2.set_rticks([])
+ #axsc2.grid(False)
+
+ # force chain plot
+
+ axfc2 = fig.add_axes([Lx-0.007, Ly-0.7*dy, dx, dy*0.7])
+ #axfc2 = fig.add_axes([Lx+dx+0.05, Ly+0.03, dx, dy*0.7])
+
+ data = datalists[sc]
+
+ # find the max. value of the normal force
+ #f_n_max = numpy.amax(data[:,6])
+
+ # specify the lower limit of force chains to do statistics on
+ f_n_lim = lower_limit * f_n_max
+
+ # find the indexes of these contacts
+ I = numpy.nonzero(data[:,6] >= f_n_lim)
+
+ #color = matplotlib.cm.spectral(data[:,6]/f_n_max)
+ for i in I[0]:
+
+ x1 = data[i,0]
+ #y1 = data[i,1]
+ z1 = data[i,2]
+ x2 = data[i,3]
+ #y2 = data[i,4]
+ z2 = data[i,5]
+ f_n = data[i,6]
+
+ lw_max = 1.0
+ if f_n >= f_n_max:
+ lw = lw_max
+ else:
+ lw = (f_n - f_n_lim)/(f_n_max - f_n_lim)*lw_max
+
+ #print lw
+ axfc2.plot([x1,x2], [z1,z2], '-k', linewidth=lw)
+ #axfc2.plot([x1,x2], [z1,z2], '-', linewidth=lw, color=forcemagnitudes[sc])
+ #axfc2.plot([x1,x2], [z1,z2], '-', linewidth=lw, color=color)
+
+ axfc2.spines['right'].set_visible(False)
+ axfc2.spines['left'].set_visible(False)
+ # Only show ticks on the left and bottom spines
+ axfc2.xaxis.set_ticks_position('none')
+ axfc2.yaxis.set_ticks_position('none')
+ axfc2.set_xticklabels([])
+ axfc2.set_yticklabels([])
+ axfc2.set_xlim([numpy.min(data[:,0]), numpy.max(data[:,0])])
+ axfc2.set_ylim([numpy.min(data[:,2]), numpy.max(data[:,2])])
+ axfc2.set_aspect('equal')
+
+
+
+
+
+
+
+ #fig.tight_layout()
+ #plt.subplots_adjust(hspace=0.05)
+ plt.subplots_adjust(right=0.82)
+
+ filename = sid + '-creep-dynamics.' + outformat
+ plt.savefig(filename)
+ plt.close()
+ shutil.copyfile(filename, '/home/adc/articles/own/3/graphics/' + filename)
+ print(filename)
(DIR) diff --git a/python/sphere.py b/python/sphere.py
t@@ -5248,9 +5248,9 @@ class sim:
fig.clf()
def plotContacts(self, graphics_format = 'png', figsize=[6,6], title=None,
- lower_limit = 0.0, upper_limit = 1.0, alpha=1.0, return_data=False,
- outfolder='.',
- f_min = None, f_max = None):
+ lower_limit = 0.0, upper_limit = 1.0, alpha=1.0,
+ return_data=False, outfolder='.',
+ f_min = None, f_max = None):
'''
Plot current contact orientations on polar plot
t@@ -5329,7 +5329,7 @@ class sim:
fig = plt.figure(figsize=figsize)
ax = plt.subplot(111, polar=True, axisbg='white')
- cs = ax.scatter(strikelist, 90. - diplist, marker='o',
+ cs = ax.scatter(strikelist, 90. - diplist, marker='o',
c=forcemagnitude,
s=forcemagnitude/f_n_max*40.,
alpha=alpha,
t@@ -5360,7 +5360,8 @@ class sim:
plt.title('t = {:.2f} s'.format(self.currentTime()))
#plt.tight_layout()
- plt.savefig(outfolder + '/' + self.sid + '-contacts.' + \
+ plt.savefig(outfolder + '/' + self.sid + '-' + \
+ str(self.time_step_count[0]) + '-contacts.' + \
graphics_format,\
transparent=False)
t@@ -5370,7 +5371,7 @@ class sim:
plt.close()
if return_data:
- return data
+ return data, strikelist, diplist, forcemagnitude, alpha, f_n_max
def plotFluidPressuresY(self, y = -1, graphics_format = 'png'):
'''