def extractMesh(t,
extractionMesh,
order=2,
extrapOrder=1,
constraint=40.,
tol=1.e-6,
mode='robust',
hook=None,
graph=None):
if graph is None:
tb = Cmpi.createBBoxTree(t)
tb2 = Cmpi.createBBoxTree(extractionMesh)
graph = Cmpi.computeGraph(tb, type='bbox3', t2=tb2)
tl = Cmpi.addXZones(t, graph)
tl = Cmpi.convert2PartialTree(tl)
ext = Cmpi.convert2PartialTree(extractionMesh)
# print info
zones = Internal.getZones(tl)
print('Rank %d has %d source zones.' % (Cmpi.rank, len(zones)))
ext = P.extractMesh(tl,
ext,
order=order,
extrapOrder=extrapOrder,
constraint=constraint,
tol=tol,
mode=mode,
hook=hook)
return ext
def optimizeOverlap(t, double_wall=0, priorities=[], graph=None,
intersectionsDict=None):
if graph is None:
tb = Cmpi.createBBoxTree(t)
graph = Cmpi.computeGraph(tb, type='bbox2',
intersectionsDict=intersectionsDict)
tl = Cmpi.addXZones(t, graph)
tl = Cmpi.convert2PartialTree(tl)
# print info
zones = Internal.getZones(tl)
#print 'Rank %d has %d zones.'%(Cmpi.rank, len(zones))
tl = X.optimizeOverlap(tl, double_wall, priorities, intersectionsDict)
tl = Cmpi.rmXZones(tl)
return tl
def redispatch(t, graph=None):
if graph is None:
graph = Cmpi.computeGraph(t, type='proc')
procs = D2.getProcDict(t)
t = Cmpi.addXZones(t, graph)
# Enleve les zones envoyees
zones = Internal.getZones(t)
for z in zones:
tag = Internal.getNodesFromName1(z, 'XZone')
if len(tag) == 0:
if procs[z[0]] != Cmpi.rank:
(p, c) = Internal.getParentOfNode(t, z)
del p[2][c]
else: # enleve le noeud tag XZone
(p, c) = Internal.getParentOfNode(z, tag[0])
del p[2][c]
return t
# - addXZones (pyTree) -
import Converter.PyTree as C
import Converter.Mpi as Cmpi
import Distributor2.PyTree as Distributor2
import Generator.PyTree as G
import KCore.test as test
# Cree le fichier test
if (Cmpi.rank == 0):
a = G.cart( (0,0,0), (1,1,1), (10,10,10) )
b = G.cart( (9,0,0), (1,1,1), (10,10,10) )
t = C.newPyTree(['Base',a,b])
C.convertPyTree2File(t, 'test.cgns')
Cmpi.barrier()
# Relit des zones par procs
t = Cmpi.convertFile2SkeletonTree('test.cgns')
(t, dic) = Distributor2.distribute(t, NProc=Cmpi.size, algorithm='fast')
t = Cmpi.readZones(t, 'test.cgns', proc=Cmpi.rank)
# Cree le bbox tree
tb = Cmpi.createBBoxTree(t)
# Cree le graph
graph = Cmpi.computeGraph(tb)
# Add X Zones
t = Cmpi.addXZones(t, graph)
if (Cmpi.rank == 0): test.testT(t, 1)
