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	timplementing forcechains2d plot in sphere.py - sphere - GPU-based 3D discrete …
	git clone git://src.adamsgaard.dk/sphere
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	---
	commit d56b993770731d00848516d7910fd41e9f9d7356
	parent df6ae0a224ab005821c2c6e95a35430975018268
	Author: Anders Damsgaard <[email protected]>
	Date: Tue, 23 Sep 2014 15:43:56 +0200

	implementing forcechains2d plot in sphere.py

	Diffstat:
	M python/permeability-results.py \| 2 ++
	M python/shear-results-forces.py \| 5 +++--
	M python/shear-results.py \| 12 ++++++++----
	M python/shear-starter.py \| 6 ++++--
	M python/sphere.py \| 54 +++++++++++++++++++++++++++++…

	5 files changed, 71 insertions(+), 8 deletions(-)
	---
	diff --git a/python/permeability-results.py b/python/permeability-results.py
	t@@ -60,6 +60,8 @@ for c_grad_p in cvals:
	sim.readlast(verbose=False)
	Re[c][i] = numpy.mean(sim.ReynoldsNumber())

	+ #sim.writeVTKall()
	+
	# find magnitude of fluid pressure force and total interaction for…
	'''
	fp_magn = numpy.empty(sim.np)
	diff --git a/python/shear-results-forces.py b/python/shear-results-forces.py
	t@@ -15,11 +15,12 @@ from matplotlib.ticker import MaxNLocator

	#steps = [5, 10, 100]
	#steps = [5, 10]
	-steps = sys.argv[2:]
	+steps = sys.argv[3:]
	nsteps_avg = 5 # no. of steps to average over

	sigma0 = float(sys.argv[1])
	-c_grad_p = 1.0
	+#c_grad_p = 1.0
	+c_grad_p = float(sys.argv[2])
	c_phi = 1.0

	sid = 'shear-sigma0=' + str(sigma0) + '-c_phi=' + \
	diff --git a/python/shear-results.py b/python/shear-results.py
	t@@ -16,8 +16,8 @@ import matplotlib.pyplot as plt
	#sigma0_list = numpy.array([1.0e3, 2.0e3, 4.0e3, 10.0e3, 20.0e3, 40.0e3])
	#sigma0 = 10.0e3
	sigma0 = float(sys.argv[1])
	-#cvals = [1.0, 0.1]
	-cvals = [1.0]
	+cvals = [1.0, 0.1]
	+#cvals = [1.0]
	c_phi = 1.0

	shear_strain = [[], [], []]
	t@@ -34,7 +34,8 @@ sid = 'shear-sigma0=' + sys.argv[1] + '-hw'
	sim = sphere.sim(sid)
	sim.readlast(verbose=False)
	sim.visualize('shear')
	-shear_strain[0] = sim.shear_strain
	+#shear_strain[0] = sim.shear_strain
	+shear_strain[0] = numpy.arange(sim.status()+1)
	friction[0] = sim.tau/sim.sigma_eff
	dilation[0] = sim.dilation

	t@@ -55,7 +56,8 @@ for c in numpy.arange(1,len(cvals)+1):

	sim.readlast(verbose=False)
	sim.visualize('shear')
	- shear_strain[c] = sim.shear_strain
	+ #shear_strain[c] = sim.shear_strain
	+ shear_strain[c] = numpy.arange(sim.status()+1)
	friction[c] = sim.tau/sim.sigma_eff
	dilation[c] = sim.dilation

	t@@ -116,6 +118,8 @@ ax1.set_ylabel('Shear friction $\\tau/\\sigma\'$ [-]')
	ax2.set_ylabel('Dilation $\\Delta h/(2r)$ [-]')
	ax3.set_ylabel('Fluid pressure $p_\\text{f}$ [kPa]')

	+ax1.set_xlim([200,300])
	+
	plt.setp(ax1.get_xticklabels(), visible=False)
	plt.setp(ax2.get_xticklabels(), visible=False)

	diff --git a/python/shear-starter.py b/python/shear-starter.py
	t@@ -27,7 +27,7 @@ sim.readlast()

	if fluid:
	sim.sid = 'shear-sigma0=' + str(sigma0) + '-c_phi=' + str(c_phi) + \
	- '-c_grad_p=' + str(c_grad_p) + '-hi_mu-lo_visc-hw'
	+ '-c_grad_p=' + str(c_grad_p) + '-hi_mu-lo_visc-hw-noshear'
	else:
	sim.sid = 'shear-sigma0=' + str(sigma0) + '-hw'

	t@@ -39,7 +39,8 @@ sim.cleanup()
	sim.adjustUpperWall()
	sim.zeroKinematics()

	-sim.shear(1.0/20.0)
	+#sim.shear(1.0/20.0)
	+sim.shear(0.0)

	if fluid:
	#sim.num[2] *= 2
	t@@ -51,6 +52,7 @@ sim.setFluidTopFixedPressure()
	sim.setDEMstepsPerCFDstep(10)
	sim.setMaxIterations(2e5)
	sim.initTemporal(total = 20.0, file_dt = 0.01, epsilon=0.07)
	+#sim.initTemporal(total = 20.0, file_dt = 0.01, epsilon=0.05)
	sim.c_phi[0] = c_phi
	sim.c_grad_p[0] = c_grad_p
	sim.w_devs[0] = sigma0
	diff --git a/python/sphere.py b/python/sphere.py
	t@@ -3604,6 +3604,60 @@ class sim:
	return self.shearStrainRate() * numpy.mean(self.radius) \
	* numpy.sqrt(self.rho[0]/self.w_devs[0])

	+ def findOverlaps(self):
	+ '''
	+ Find all particle-particle overlaps by a n^2 contact search. The
	+ particle pair indexes and the distance of the overlaps is saved in the
	+ object itself as the ``.pairs`` and ``.overlaps`` members.
	+ '''
	+
	+ # Allocate big arrays instead of dynamically allocating during the
	+ # iterative process. Blank positions will be erased afterwards
	+ max_avg_contacts_per_particle = 16
	+ self.pairs = numpy.empty(self.np*max_avg_contacts_per_particle, 2)
	+ self.overlaps = numpy.empty_like(self.pairs)
	+
	+ p = 0
	+ for i in numpy.arange(self.np):
	+ for j in numpy.arange(self.np):
	+
	+ if i < j:
	+ x_ij = self.x[i,:] - self.x[j,:]
	+ x_ij_length = numpy.sqrt(x_ij.dot(x_ij))
	+
	+ delta_n = x_ij_length - (self.radius[i] + self.radius[j])
	+
	+ if delta_n < 0.0:
	+ self.pairs[p,:] = [i,j]
	+ self.overlaps[p] = delta_n
	+ p += 1
	+ self.pairs = self.pairs[:p+1,:]
	+ self.overlaps = self.overlaps[:p+1]
	+
	+
	+ def forcechains2d(self, lc=200.0, uc=650.0, outformat='png', axes=[0,2]):
	+ '''
	+ Visualizes the force chains in the system from the magnitude of the
	+ normal contact forces, and produces an image of them. The force chains
	+ are orthogonally projected into a 2d plane specified by the axes
	+ parameter.
	+
	+ :param lc: Lower cutoff of contact forces. Contacts below are not
	+ visualized
	+ :type lc: float
	+ :param uc: Upper cutoff of contact forces. Contacts above are
	+ visualized with this value
	+ :type uc: float
	+ :param outformat: Format of output image. Possible values are
	+ 'interactive', 'png', 'epslatex', 'epslatex-color'
	+ :type outformat: str
	+ :param axes: The coordinate system axes in the projection plane (0:x,
	+ 1:y, 2:z), default 0,2.
	+ :type axes: tuple
	+ '''
	+
	+
	+
	def forcechains(self, lc=200.0, uc=650.0, outformat='png', disp='2d'):
	'''
	Visualizes the force chains in the system from the magnitude of the