grainsB.append(gB)
for rC, pC in zip(RsC, phiC):
freq = SDC.frequency(pC, hC) * target_area
freq = int(freq / (np.pi * rC**2.))
for f in range(freq):
gC = pss.Grain(rC)
grainsC.append(gC)
for rD, pD in zip(RsD, phiD):
freq = SDD.frequency(pD, hD) * target_area
freq = int(freq / (np.pi * rD**2.))
for f in range(freq):
gD = pss.Grain(rD)
grainsD.append(gD)
# library of grains has been generated, now place them into the mesh!
groupA = pss.Ensemble(meshA, name='normaldistA_mu=3.6_sg=2.4')
groupB = pss.Ensemble(meshB, name='normaldistB_mu=3.6_sg=4.8')
groupC = pss.Ensemble(meshC, name='normaldistC_mu=3.6_sg=1.2')
groupD = pss.Ensemble(meshD, name='normaldistD_mu=4.6_sg=2.4')
# place them in, but don't worry if not possible to fit all.
# allow for keyboard interrupt if there's a problem.
try:
i = 0
for gA in grainsA:
gA.insertRandomly(meshA, m=1)
groupA.add(gA, gA.x, gA.y)
for gB in grainsB:
gB.insertRandomly(meshB, m=1)
groupB.add(gB, gB.x, gB.y)
for gC in grainsC:
# matrix porosity = 0.5
#vf_G = 5.*vf_V
# matrix porosity = 0.6
vf_G = 2. * vf_V / 3. + 1. / 6.
# matrix porosity = 0.7
#vf_G = (2. + 3.*vf_V)/7.
# matrix porosity = 0.8
#vf_G = (.25*vf_V+3./8.)
print vf_V, vf_G
first = True
for v_void, v_grain in zip(vf_V, vf_G):
if first:
v_grain0 = v_grain
v_void0 = v_void
groupAG = pss.Ensemble(
meshA,
name='voidvariation_vfG-{:2.2f}_vfV-{:2.2f}_GRAINS_A'.format(
v_grain0, v_void0))
groupBG = pss.Ensemble(
meshB,
name='voidvariation_vfG-{:2.2f}_vfV-{:2.2f}_GRAINS_B'.format(
v_grain0, v_void0))
groupAV = pss.Ensemble(
meshA,
name='voidvariation_vfG-{:2.2f}_vfV-{:2.2f}_VOIDS_A'.format(
v_grain0, v_void0))
groupBV = pss.Ensemble(
meshB,
name='voidvariation_vfG-{:2.2f}_vfV-{:2.2f}_VOIDS_B'.format(
v_grain0, v_void0))
else:
groupAG = pss.Ensemble(
target_area = float(meshA.x * meshA.y * vfrac)
for r, p in zip(Rs, phi):
# generate grain object with radius r
g = pss.Grain(eqr=int(r))
# calculate the target number of grains from CDF (see above)
prob = abs(CDF(p + h) - CDF(p - h))
g.targetFreq = int(round(prob * (target_area / float(g.area))))
grains.append(g)
# library of grains has been generated, now place them into the mesh!
# Just meshA for now
# order grains from largest to smallest
grains = [g for _, g in sorted(zip(phi, grains))]
groupA = pss.Ensemble(meshA, name='shapevariationENS_A')
groupB = pss.Ensemble(meshB, name='shapevariationENS_B')
try:
i = 0
for g in grains:
for f in range(g.targetFreq):
g.insertRandomly(meshA, m=1)
groupA.add(g, g.x, g.y)
g.insertRandomly(meshB, m=1)
groupB.add(g, g.x, g.y)
except KeyboardInterrupt:
pass
#print groupA.fabricTensor_discs()
groupA.calcPSD()
test = diff/(np.pi*r**2.)
if (1.-test)<=0.2:
Rextra = r
break
ctr += 1
for r,freq in zip(RsA,freqs):
if r == Rextra: freq+=1
for f in range(freq):
g = pss.Grain(r)
grainsA.append(g)
grainsB.append(g)
# library of grains has been generated, now place them into the mesh!
groupA = pss.Ensemble(meshA,name='normaldistA')
groupB = pss.Ensemble(meshB,name='normaldistB')
# place them in, but don't worry if not possible to fit all.
# allow for keyboard interrupt if there's a problem.
try:
i = 0
for gA in grainsA:
gA.insertRandomly(meshA, m=1)
groupA.add(gA,gA.x,gA.y)
for gB in grainsB:
gB.insertRandomly(meshB, m=1)
groupB.add(gB,gB.x,gB.y)
except KeyboardInterrupt:
pass
freq2 = freq1 / (np.pi * r**2.)
freq = int(freq2)
diff += (freq2 - freq) * np.pi * r**2.
freqs.append(freq)
#print diff*np.pi*r**2.
ctr = 0
for r in RsA:
test = diff / (np.pi * r**2.)
if (1. - test) <= 0.2:
Rextra = r
break
ctr += 1
# library of grains has been generated, now place them into the mesh!
groupA = pss.Ensemble(meshA, name='normaldistA')
Rs = copy.deepcopy(RsA)
Fr = copy.deepcopy(freqs)
# place them in, but don't worry if not possible to fit all.
# allow for keyboard interrupt if there's a problem.
fig = plt.figure(figsize=(8, 4))
fig1 = plt.figure(figsize=(6, 4))
ax1a = fig1.add_subplot(131, aspect='equal')
ax2a = fig1.add_subplot(132, aspect='equal')
ax3a = fig1.add_subplot(133, aspect='equal')
ax1a.axis('off')
ax2a.axis('off')
ax3a.axis('off')
ax11 = fig.add_subplot(241)
ax22 = fig.add_subplot(242)
meshA = pss.Mesh(X=500,Y=1200,cellsize=2.5e-6)
meshB = pss.Mesh(X=500,Y=1200,cellsize=2.5e-6)
# target volume (area) fraction
vfrac = 0.5
# Store grain objects in list, 'grains'
grainsA = []
grainsB = []
gLarge = pss.Grain(25.)
gSmall = pss.Grain(5.)
groupA = pss.Ensemble(meshA,name='bimodaldistA')
groupB = pss.Ensemble(meshB,name='bimodaldistB')
vfracA = 0.
vfracB = 0.
try:
while vfracA < 0.3:
gLarge.insertRandomly(meshA,m=1)
groupA.add(gLarge,gLarge.x,gLarge.y)
vfracA = meshA.vfrac()
while vfracB < 0.3:
gLarge.insertRandomly(meshB,m=1)
groupB.add(gLarge,gLarge.x,gLarge.y)
vfracB = meshB.vfrac()
except KeyboardInterrupt:
target_area = float(meshA.x * meshA.y * vfrac)
for r, p in zip(Rs, phi):
# generate grain object with radius r
g = pss.Grain(eqr=int(r))
# calculate the target number of grains from CDF (see above)
prob = abs(CDF(p + h) - CDF(p - h))
g.targetFreq = int(round(prob * (target_area / float(g.area))))
grains.append(g)
# library of grains has been generated, now place them into the mesh!
# Just meshA for now
# order grains from largest to smallest
grains = [g for _, g in sorted(zip(phi, grains))]
groupA = pss.Ensemble(meshA, name='mirror_test_ens')
try:
i = 0
for g in grains:
for f in range(g.targetFreq):
g.insertRandomly(meshA, m=1)
groupA.add(g, g.x, g.y)
except KeyboardInterrupt:
pass
groupA.optimise_materials(np.array([1, 2, 3, 4, 5, 6, 7, 8]))
groupA.save()
meshA.fillAll(-1)