def aggrAggregate(portNum, metaNum, pod_id, aggr_id, network, G,
aggrGroupEdges):
P = [0] * portNum
for i in range(portNum):
P[i] = aggr.Port(i)
M = [0] * metaNum
for i in range(metaNum):
M[i] = aggr.MetaGroup(i)
idmap = {}
groups = network.pods[pod_id].aggrs[aggr_id].groups
Gr = [0] * len(groups)
i = 0
for g_id in groups:
ports = set(G.groups[g_id].members[pod_id].keys())
Gr[i] = aggr.Group(i, g_id, ports, G.groups[g_id].rate, P)
idmap[g_id] = i
i += 1
G_unassigned = set(range(len(groups)))
M_empty = set(range(portNum, metaNum - 1))
while len(G_unassigned) > 0:
aggr.Aggregate(Gr[G_unassigned.pop()], M, Gr, P, M_empty, portNum)
for g_id in groups:
if g_id not in aggrGroupEdges.keys():
aggrGroupEdges[g_id] = {}
aggrGroupEdges[g_id][pod_id] = M[Gr[idmap[g_id]].meta].ports
switchAddr = 0
for i in range(metaNum):
if len(M[i].ports) > 0:
switchAddr += 1
return switchAddr
def edgeAggregate(portNum, metaNum, pod_id, edge_id, network, G):
P = [0] * portNum
for i in range(portNum):
P[i] = aggr.Port(i)
M = [0] * metaNum
for i in range(metaNum):
M[i] = aggr.MetaGroup(i)
groups = network.pods[pod_id].edges[edge_id].groups
Gr = [0] * len(groups)
i = 0
for g_id in groups:
ports = G.groups[g_id].members[pod_id][edge_id]
Gr[i] = aggr.Group(i, g_id, ports, G.groups[g_id].rate, P)
i += 1
G_unassigned = set(range(len(groups)))
M_empty = set(range(portNum, metaNum - 1))
while len(G_unassigned) > 0:
aggr.Aggregate(Gr[G_unassigned.pop()], M, Gr, P, M_empty, portNum)
linkRate = [0] * 2
linkRate[0] = []
linkRate[1] = []
for i in range(portNum):
linkRate[0].append(P[i].effective)
linkRate[1].append(P[i].rate)
switchAddr = [0] * 2
switchAddr[0] = len(groups)
for i in range(metaNum):
if len(M[i].ports) > 0:
switchAddr[1] += 1
return [linkRate, switchAddr]
def generate_rosette(D, min_grid_res=40e-6):
grid_res = min(D / 20, min_grid_res)
rot = rotator.UniformRotator()
cry = crystal.Rosette(D)
gen = generator.MonodisperseGenerator(cry, rot, grid_res)
agg = aggregate.Aggregate(gen)
return (agg, grid_res)
def polydisp_dendrite(N=5, grid=None, align=True):
#cry = crystal.Column(0.3e-3)
agg = []
psd = stats.expon(scale=1.0e-3)
rot = rotator.UniformRotator()
for i in xrange(N):
D = 1e3
while D > 0.3e-2 or D < 0.2e-3:
D = psd.rvs()
print "D: " + str(D)
cry = crystal.Dendrite(D,
alpha=0.705,
beta=0.5,
gamma=0.0001,
num_iter=2500,
hex_grid=grid)
gen = generator.MonodisperseGenerator(cry, rot, 0.02e-3)
agg.append(aggregate.Aggregate(gen, levels=5))
aggregate.t_i = 0
aggregate.t_o = 0
while len(agg) > 1:
r = array([((a.extent[0][1] - a.extent[0][0]) +
(a.extent[1][1] - a.extent[1][0])) / 4.0 for a in agg])
m_r = numpy.sqrt(array([a.X.shape[0] for a in agg]) / r)
r_mat = (numpy.tile(r, (len(agg), 1)).T + r)**2
mr_mat = abs(numpy.tile(m_r, (len(agg), 1)).T - m_r)
p_mat = r_mat * mr_mat
p_max = p_mat.max()
p_mat /= p_mat.max()
collision = False
while not collision:
i = random.randint(len(agg))
j = random.randint(len(agg))
rnd = random.rand()
if rnd < p_mat[i][j]:
print i, j
agg_top = agg[i] if (m_r[i] > m_r[j]) else agg[j]
agg_btm = agg[i] if (m_r[i] <= m_r[j]) else agg[j]
collision = agg_top.add_particle(particle=agg_btm.X,
required=True)
if collision:
if align:
agg_top.align()
else:
agg_top.rotate(rot)
agg.pop(i if (m_r[i] <= m_r[j]) else j)
print aggregate.t_i, aggregate.t_o
if align:
agg[0].align()
agg[0].rotate(rotator.HorizontalRotator())
return agg[0]
def monodisp_demo(N=5):
#cry = crystal.Plate(0.3e-3)
#cry = crystal.Rosette(0.6e-3)
cry = crystal.Spheroid(0.6e-3, 0.6)
rot = rotator.UniformRotator()
gen = generator.MonodisperseGenerator(cry, rot, 0.01e-3)
agg = aggregate.Aggregate(gen)
for i in xrange(N - 1):
print i
agg.add_particle(required=True, pen_depth=0.02e-3)
agg.align()
return agg
def ar(D):
cry = crystal.Dendrite(D, hex_grid=grid)
gen = generator.MonodisperseGenerator(cry, rot, grid_res)
agg = aggregate.Aggregate(gen)
m = agg.X.mean(0)
X_c = agg.X - m
cov = np.dot(X_c.T, X_c)
(l, v) = np.linalg.eigh(cov)
size = np.sqrt(l / X_c.shape[0] + (1. /
(2 * np.sqrt(3)) * grid_res)**2)
width = np.sqrt(0.5 * (size[1]**2 + size[2]**2))
height = size[0]
print D, size, width, height
return height / width
def gen():
if psd == "monodisperse":
D = size
elif psd == "exponential":
psd_f = stats.expon(scale=size)
D = max_size + 1
while (D < min_size) or (D > max_size):
D = psd_f.rvs()
cry = make_cry(D)
gen = generator.MonodisperseGenerator(cry, rot, grid_res)
if rimed:
agg = aggregate.RimedAggregate(gen)
else:
agg = aggregate.Aggregate(gen)
return agg
def monodisp_pseudo(N=5, grid=None, sig=1.0):
cry = crystal.Dendrite(0.5e-3,
alpha=0.705,
beta=0.5,
gamma=0.0001,
num_iter=2500,
hex_grid=grid)
rot = rotator.UniformRotator()
gen = generator.MonodisperseGenerator(cry, rot, 0.02e-3)
"""
p_agg = aggregate.PseudoAggregate(gen, sig=0.1e-2)
rho_i = 916.7 #kg/m^3
N_dip = p_agg.grid().shape[0]
m = 0.02e-3**3 * N_dip * N * rho_i
sig = (m/20.3)**(1.0/2.35)
print N_dip, sig
"""
p_agg = aggregate.PseudoAggregate(gen, sig=sig)
aggs = [aggregate.Aggregate(gen, levels=5) for i in xrange(N - 1)]
for agg in aggs:
p_agg.add_particle(particle=agg.X, required=False)
return p_agg
def monodisp_demo2(N=5):
#cry = crystal.Column(0.3e-3)
cry = crystal.Dendrite(0.3e-3, 0.705, 0.5, 0.0001, num_iter=2500)
rot = rotator.UniformRotator()
gen = generator.MonodisperseGenerator(cry, rot, 0.01e-3)
agg = [aggregate.Aggregate(gen) for i in xrange(N)]
aggregate.t_i = 0
aggregate.t_o = 0
while len(agg) > 1:
r = array([((a.extent[0][1] - a.extent[0][0]) +
(a.extent[1][1] - a.extent[1][0])) / 4.0 for a in agg])
m_r = numpy.sqrt(array([a.X.shape[0] for a in agg]) / r)
r_mat = (numpy.tile(r, (len(agg), 1)).T + r)**2
mr_mat = abs(numpy.tile(m_r, (len(agg), 1)).T - m_r)
p_mat = r_mat * mr_mat
p_max = p_mat.max()
p_mat /= p_mat.max()
collision = False
while not collision:
i = random.randint(len(agg))
j = random.randint(len(agg))
rnd = random.rand()
if rnd < p_mat[i][j]:
print i, j
agg_top = agg[i] if (m_r[i] > m_r[j]) else agg[j]
agg_btm = agg[i] if (m_r[i] <= m_r[j]) else agg[j]
collision = agg_top.add_particle(particle=agg_btm.X,
required=True)
agg_top.align()
agg.pop(i if (m_r[i] <= m_r[j]) else j)
print aggregate.t_i, aggregate.t_o
return agg[0]