def calibrateCluster(self, pl):
partServ = ParticleService()
x_list = numpy.array([cluster.getX() for cluster in pl.GET()])
y_list = numpy.array([cluster.getY() for cluster in pl.GET()])
r_list = numpy.array([cluster.getR() for cluster in pl.GET()])
for cluster in pl.GET():
x_square = (cluster.getX() - x_list)**2
y_square = (cluster.getY() - y_list)**2
distance_list = numpy.sqrt(x_square + y_square)
r_ol = (numpy.array(pl.GET()))[(distance_list <= cluster.getR() + r_list)]
r_ol_clear = [elm for elm in r_ol if (elm not in cluster.getContacts()) and (elm != cluster)]
for interCluster in r_ol_clear:
if interCluster.getN() > cluster.getN():
continue
else:
partServ.clusterSurfaceTouching(cluster, interCluster)
for adCluster in cluster.getContacts():
if adCluster.getN() > cluster.getN():
continue
else:
partServ.clusterSurfaceTouching(cluster, adCluster)
def getMeanValues(self, clusterList):
partServ = ParticleService()
intServ = InteractionService()
r = 0
d = 0
r_list = []
d_list = []
cluster_plist = []
for cluster in clusterList.GET():
# Radius
r += cluster.getR()
# Distance
d_part = 0
if len(cluster.getContacts()) != 0:
for adCluster in cluster.getContacts():
if d_part > partServ.getParticleDistance(cluster, adCluster):
d_part = partServ.getParticleDistance(cluster, adCluster)
else:
d_part = intServ.findClosestCluster(cluster, clusterList)
d += d_part
# Radius List
r_list.append(cluster.getR())
# Distance List
d_list.append(d_part)
# Cluster Parameter List
cluster_plist.append(self.getClusterParameter(cluster))
return r/clusterList.clusterNumber() , d/clusterList.clusterNumber() , r_list , d_list, cluster_plist
def adatomOnCluster(self, initval, adatomList, adatomWWList, clusterList, coalescenceList, smeasure):
pServ = ParticleService()
x_list = numpy.array([cluster.getX() for cluster in clusterList.GET()])
y_list = numpy.array([cluster.getY() for cluster in clusterList.GET()])
r_list = numpy.array([cluster.getR() for cluster in clusterList.GET()])
for adatom in adatomList.GET():
x_square = (adatom.getX() - x_list)**2
y_square = (adatom.getY() - y_list)**2
distance_list = numpy.array(numpy.sqrt(x_square + y_square))
cluster = (numpy.array(clusterList.GET()))[distance_list <= (adatom.getR() + r_list)]
if len(cluster)!=0:
pServ.addAdatomtoCluster(initval, adatom, cluster, adatomList, clusterList)
smeasure.adatomEvent('clusterdeposition_sputter', 1)
else:
pServ.AdatomOnSurface(adatom, adatomList, adatomWWList, clusterList, coalescenceList)
smeasure.adatomEvent('deposition_sputter', 1)
def diffusionOverlap(self, initval, pl, clusterList, coalescenceList):
pServ = ParticleService()
x_list = numpy.array([cluster.getX() for cluster in clusterList.GET()])
y_list = numpy.array([cluster.getY() for cluster in clusterList.GET()])
r_list = numpy.array([cluster.getR() for cluster in clusterList.GET()])
rev_list = numpy.array([cluster.getREv() for cluster in clusterList.GET()])
for cluster in pl.GET():
x_square = (cluster.getX() - x_list)**2
y_square = (cluster.getY() - y_list)**2
distance_list = numpy.sqrt(x_square + y_square)
r_ol = (numpy.array(clusterList.GET()))[(distance_list <= cluster.getR() + r_list)]
rev_ol = (numpy.array(clusterList.GET()))[(distance_list <= cluster.getREv() + rev_list)]
r_ol_clear = [cluster for cluster in r_ol if cluster not in pl.GET()]
if len(r_ol_clear) != 0 and coalescenceList.findCluster(r_ol_clear[0])!=None:
fuse=False
for cluster2 in r_ol_clear:
if pServ.addContact(cluster, cluster2):
pServ.fuseParticleLists(coalescenceList.findCluster(cluster2), pl)
fuse=True
break
rev_ol_clear = [cluster for cluster in rev_ol if (cluster not in pl.GET() and cluster not in r_ol_clear)]
if len(rev_ol_clear) != 0 and coalescenceList.findCluster(r_ol_clear[0])!=None and fuse==False:
for cluster2 in rev_ol_clear:
distance = self.getParticleDistance(cluster.getX(), cluster.getY(), cluster2.getX(), cluster2.getY())
if self.checkGreatProhability(cluster.getREv(), cluster2.getREv(), cluster.getR(), cluster2.getR(), distance) >= 1:
if pServ.addContact(cluster, cluster2):
pServ.fuseParticleLists(coalescenceList.findCluster(cluster2),pl)
else:
WQS = self.getCollisionProhability(cluster2.getREv(), cluster.getREv(), cluster2.getR(), cluster.getR(), distance)
rndm = random.random
if rndm < WQS:
if pServ.addContact(cluster, cluster2):
pServ.fuseParticleLists(coalescenceList.findCluster(cluster2),pl)
def adatomWW(self, initval, adatomWWList, clusterList, coalescenceList, smeasure):
pServ = ParticleService()
x_list = numpy.array([cluster.getX() for cluster in clusterList.GET()])
y_list = numpy.array([cluster.getY() for cluster in clusterList.GET()])
r_list = numpy.array([cluster.getR() for cluster in clusterList.GET()])
rev_list = numpy.array([cluster.getREv() for cluster in clusterList.GET()])
for adatom in adatomWWList.GET():
x_square = (adatom.getX() - x_list)**2
y_square = (adatom.getY() - y_list)**2
distance_list = numpy.array(numpy.sqrt(x_square + y_square))
r_ol = (numpy.array(clusterList.GET()))[(distance_list <= adatom.getR() + r_list)]
rev_ol = (numpy.array(clusterList.GET()))[(distance_list <= adatom.getREv() + rev_list)]
''' *** R Overlap *** '''
r_ol=numpy.delete(r_ol, numpy.where(r_ol==adatom)[0][0])
if len(r_ol) != 0:
pServ.adatomClusterWW(initval, adatom, r_ol[0], adatomWWList, clusterList, coalescenceList)
if r_ol[0].getN() == 1:
smeasure.adatomEvent('nucleation',1)
else:
smeasure.adatomEvent('aggregation',1)
continue
''' *** Rev Overlap for great WQS *** '''
rev_ol=numpy.delete(rev_ol, numpy.where(rev_ol==adatom)[0][0])
interaction = False
if len(rev_ol) != 0:
for cluster in rev_ol:
distance = self.getParticleDistance(adatom.getX(), adatom.getY(), cluster.getX(), cluster.getY())
if self.checkGreatProhability(adatom.getREv(), cluster.getREv(), adatom.getR(), cluster.getR(), distance) >= 1:
pServ.adatomClusterWW(initval, adatom, cluster, adatomWWList, clusterList, coalescenceList)
if cluster.getN() == 1:
smeasure.adatomEvent('nucleation',1)
else:
smeasure.adatomEvent('aggregation',1)
interaction = True
break
''' *** Rev Overlap for small WQS *** '''
if interaction == False:
for cluster in rev_ol:
distance = self.getParticleDistance(adatom.getX(), adatom.getY(), cluster.getX(), cluster.getY())
WQS = self.getCollisionProhability(adatom.getREv(), cluster.getREv(), adatom.getR(), cluster.getR(), distance)
if random() < WQS:
pServ.adatomClusterWW(initval, adatom, cluster, adatomWWList, clusterList, coalescenceList)
if cluster.getN() == 1:
smeasure.adatomEvent('nucleation',2)
else:
smeasure.adatomEvent('aggregation',1)
interaction = True
break
