def check_geometry_health(self):
r"""
Perform a check to find pores with overlapping or undefined Geometries
"""
geoms = self.geometries()
Ptemp = sp.zeros((self.Np,))
Ttemp = sp.zeros((self.Nt,))
for item in geoms:
Pind = self['pore.'+item]
Tind = self['throat.'+item]
Ptemp[Pind] = Ptemp[Pind] + 1
Ttemp[Tind] = Ttemp[Tind] + 1
health = Tools.HealthDict()
health['overlapping_pores'] = sp.where(Ptemp > 1)[0].tolist()
health['undefined_pores'] = sp.where(Ptemp == 0)[0].tolist()
health['overlapping_throats'] = sp.where(Ttemp > 1)[0].tolist()
health['undefined_throats'] = sp.where(Ttemp == 0)[0].tolist()
return health
def check_physics_health(self):
r'''
Perform a check to find pores which have overlapping or undefined Physics
'''
phys = self.physics()
Ptemp = sp.zeros((self.Np, ))
Ttemp = sp.zeros((self.Nt, ))
for item in phys:
Pind = self['pore.' + item]
Tind = self['throat.' + item]
Ptemp[Pind] = Ptemp[Pind] + 1
Ttemp[Tind] = Ttemp[Tind] + 1
health = Tools.HealthDict()
health['overlapping_pores'] = sp.where(Ptemp > 1)[0].tolist()
health['undefined_pores'] = sp.where(Ptemp == 0)[0].tolist()
health['overlapping_throats'] = sp.where(Ttemp > 1)[0].tolist()
health['undefined_throats'] = sp.where(Ttemp == 0)[0].tolist()
return health
def check_network_health(self):
r"""
This method check the network topological health by checking for:
(1) Isolated pores
(2) Islands or isolated clusters of pores
(3) Duplicate throats
(4) Bidirectional throats (ie. symmetrical adjacency matrix)
(5) Headless throats
Returns
-------
A dictionary containing the offending pores or throat numbers under
each named key.
It also returns a list of which pores and throats should be trimmed
from the network to restore health. This list is a suggestion only,
and is based on keeping the largest cluster and trimming the others.
Notes
-----
- Does not yet check for duplicate pores
- Does not yet suggest which throats to remove
- This is just a 'check' method and does not 'fix' the problems it finds
"""
health = Tools.HealthDict()
health['disconnected_clusters'] = []
health['isolated_pores'] = []
health['trim_pores'] = []
health['duplicate_throats'] = []
health['bidirectional_throats'] = []
health['headless_throats'] = []
health['looped_throats'] = []
# Check for headless throats
hits = sp.where(self['throat.conns'] > self.Np - 1)[0]
if sp.size(hits) > 0:
health['headless_throats'] = sp.unique(hits)
logger.warning('Health check cannot complete due to connectivity '
'errors. Please correct existing errors & recheck.')
return health
# Check for throats that loop back onto the same pore
P12 = self['throat.conns']
hits = sp.where(P12[:, 0] == P12[:, 1])[0]
if sp.size(hits) > 0:
health['looped_throats'] = hits
# Check for individual isolated pores
Ps = self.num_neighbors(self.pores())
if sp.sum(Ps == 0) > 0:
logger.warning(str(sp.sum(Ps == 0)) + ' pores have no neighbors')
health['isolated_pores'] = sp.where(Ps == 0)[0]
# Check for separated clusters of pores
temp = []
Cs = self.find_clusters(self.tomask(throats=self.throats('all')))
if sp.shape(sp.unique(Cs))[0] > 1:
logger.warning('Isolated clusters exist in the network')
for i in sp.unique(Cs):
temp.append(sp.where(Cs == i)[0])
b = sp.array([len(item) for item in temp])
c = sp.argsort(b)[::-1]
for i in range(0, len(c)):
health['disconnected_clusters'].append(temp[c[i]])
if i > 0:
health['trim_pores'].extend(temp[c[i]])
# Check for duplicate throats
am = self.create_adjacency_matrix(sprsfmt='lil')
mergeTs = []
for i in range(0, self.Np):
for j in sp.where(sp.array(am.data[i]) > 1)[0]:
k = am.rows[i][j]
mergeTs.extend(self.find_connecting_throat(i, k))
# Remove duplicates
mergeTs = [list(i) for i in set(tuple(i) for i in mergeTs)]
health['duplicate_throats'] = mergeTs
# Check for bidirectional throats
adjmat = self.create_adjacency_matrix(sprsfmt='coo')
num_full = adjmat.sum()
temp = sprs.triu(adjmat, k=1)
num_upper = temp.sum()
if num_full > num_upper:
biTs = sp.where(self['throat.conns'][:, 0] >
self['throat.conns'][:, 1])[0]
health['bidirectional_throats'] = biTs.tolist()
return health
def check_network_health(self):
r'''
This method check the network topological health by checking for:
(1) Isolated pores
(2) Islands or isolated clusters of pores
(3) Duplicate throats
(4) Bidirectional throats (ie. symmetrical adjacency matrix)
Returns
-------
A dictionary containing the offending pores or throat numbers under
each named key.
It also returns a list of which pores and throats should be trimmed
from the network to restore health. This list is a suggestion only,
and is based on keeping the largest cluster and trimming the others.
Notes
-----
- Does not yet check for duplicate pores
- Does not yet suggest which throats to remove
- This is just a 'check' method and does not 'fix' the problems it finds
'''
health = Tools.HealthDict()
health['disconnected_clusters'] = []
health['isolated_pores'] = []
health['trim_pores'] = []
health['duplicate_throats'] = []
health['bidirectional_throats'] = []
#Check for individual isolated pores
Ps = self.num_neighbors(self.pores())
if sp.sum(Ps==0) > 0:
logger.warning(str(sp.sum(Ps==0))+' pores have no neighbors')
health['isolated_pores'] = sp.where(Ps==0)[0]
#Check for separated clusters of pores
temp = []
Cs = self.find_clusters(self.tomask(throats=self.throats('all')))
if sp.shape(sp.unique(Cs))[0] > 1:
logger.warning('Isolated clusters exist in the network')
for i in sp.unique(Cs):
temp.append(sp.where(Cs==i)[0])
b = sp.array([len(item) for item in temp])
c = sp.argsort(b)[::-1]
for i in range(0,len(c)):
health['disconnected_clusters'].append(temp[c[i]])
if i > 0:
health['trim_pores'].extend(temp[c[i]])
#Check for duplicate throats
i = self['throat.conns'][:,0]
j = self['throat.conns'][:,1]
v = sp.array(self['throat.all'],dtype=int)
Np = self.num_pores()
adjmat = sprs.coo_matrix((v,(i,j)),[Np,Np])
temp = adjmat.tocsr() # Convert to CSR to combine duplicates
temp = adjmat.tocoo() # And back to COO
mergedTs = sp.where(temp.data>1)
Ps12 = sp.vstack((temp.row[mergedTs], temp.col[mergedTs])).T
dupTs = []
for i in range(0,sp.shape(Ps12)[0]):
dupTs.append(self.find_connecting_throat(Ps12[i,0],Ps12[i,1]).tolist)
health['duplicate_throats'] = dupTs
#Check for bidirectional throats
num_full = adjmat.sum()
temp = sprs.triu(adjmat,k=1)
num_upper = temp.sum()
if num_full > num_upper:
health['bidirectional_throats'] = str(num_full-num_upper)+' detected!'
#Check for coincident pores
# temp = misc.dist(self['pore.coords'],self['pore.coords'])
# temp = sp.triu(temp,k=1) # Remove lower triangular of matrix
# temp = sp.where(temp==0) # Find 0 values in distance matrix
# dupPs = sp.where(temp[1]>temp[0])[0] # Find 0 values above diagonal
# health['duplicate_pores'] = dupPs
return health
