def fan_wrapper(fold='None', n=10, dens=.2, sst=.9):
scipy.random.seed()
msl_time = None
sat_time = None
s = None
c = None
k = bfutils.dens2edgenum(dens, n=nodes)
output = {}
while True:
try:
output['gt'] = gk.ringmore(n, k)
gdens = traversal.density(output['gt'])
gu = bfutils.increment(output['gt'])
output['transition'] = lm.transitionMatrix4(output['gt'],
minstrength=.9)
if estimate_gu:
data = lm.drawsamplesLG(output['transition'],
nstd=np.double(NOISE_STD),
samples=BURNIN + NSAMPLES * URATE)
data = data[:, BURNIN:]
if np.max(data) > 1000.:
raise NameError()
gu_est, gu_time = gu_estimate(data[:, ::URATE], ALG)
else:
gu_est = None
gu_time = None
if estimate_g1:
try:
s, msl_time = msl_caller(gu_est)
except TimeoutError:
s = None
msl_time = None
try:
c, sat_time = sat_caller(gu_est, fold)
except TimeoutError:
c = None
sat_time = None
if msl_time is not None:
print "msl: {:2}: {:8} : {:4} {:10} seconds".\
format(fold, round(sst,3), len(s),
round(msl_time/1000.,3))
if sat_time is not None:
print "sat: {:2}: {:8} : {:4} {:10} seconds".\
format(fold, round(sst,3), len(c),
round(sat_time/1000.,3))
else:
s = None
c = None
msl_time = None
sat_time = None
output['gu'] = {'est': gu_est, 'truth': gu, 'ms': gu_time}
output['MSL'] = {'eq': s, 'ms': msl_time}
output['SAT'] = {'eq': c, 'ms': sat_time}
except MemoryError:
print 'memory error... retrying'
continue
break
return output
def prunepaths_1D(g2, path, conn):
c = []
g = cloneempty(g2)
for p in conn:
mask = addapath(g, path, p)
if gk.isedgesubset(bfu.increment(g), g2):
c.append(tuple(p))
delapath(g, path, p, mask)
return c
def nodesearch(g, g2, edges, s):
if edges:
e = edges.pop()
ln = [n for n in g2]
for n in ln:
if (n, e) in single_cache:
continue
mask = add2edges(g, e, n)
if gk.isedgesubset(bfu.increment(g), g2):
r = nodesearch(g, g2, edges, s)
if r and edgeset(bfu.increment(r)) == edgeset(g2):
s.add(g2num(r))
if capsize and len(s) > capsize:
raise ValueError('Too many elements in eqclass')
del2edges(g, e, n, mask)
edges.append(e)
else:
return g
def g22g1(g2, capsize=None):
'''
computes all g1 that are in the equivalence class for g2
'''
if bfu.isSclique(g2):
print 'Superclique - any SCC with GCD = 1 fits'
return set([-1])
single_cache = {}
@memo # memoize the search
def nodesearch(g, g2, edges, s):
if edges:
if bfu.increment(g) == g2:
s.add(g2num(g))
if capsize and len(s) > capsize:
raise ValueError('Too many elements')
return g
e = edges[0]
for n in g2:
if (n, e) in single_cache:
continue
if not edge_increment_ok(e[0], n, e[1], g, g2):
continue
mask = add2edges(g, e, n)
r = nodesearch(g, g2, edges[1:], s)
del2edges(g, e, n, mask)
elif bfu.increment(g) == g2:
s.add(g2num(g))
if capsize and len(s) > capsize:
raise ValueError('Too many elements in eqclass')
return g
# find all directed g1's not conflicting with g2
n = len(g2)
edges = gk.edgelist(g2)
random.shuffle(edges)
g = cloneempty(g2)
for e in edges:
for n in g2:
mask = add2edges(g, e, n)
if not gk.isedgesubset(bfu.increment(g), g2):
single_cache[(n, e)] = False
del2edges(g, e, n, mask)
s = set()
try:
nodesearch(g, g2, edges, s)
except ValueError:
s.add(0)
return s
def nodesearch(g, g2, edges, s):
if edges:
# key, checklist = edges.popitem()
key = random.choice(edges.keys())
checklist = edges.pop(key)
adder, remover = f[edge_function_idx(key)]
checks_ok = c[edge_function_idx(key)]
for n in checklist:
mask = adder(g, key, n)
if gk.isedgesubset(bfu.increment(g), g2):
r = nodesearch(g, g2, edges, s)
if r and bfu.increment(r) == g2:
s.add(g2num(r))
if capsize and len(s) > capsize:
raise ValueError('Too many elements')
remover(g, key, n, mask)
edges[key] = checklist
else:
return g
def nodesearch0(g, g2, order, inlist, s, cds):
if order:
key = order.pop(0)
tocheck = cds[len(inlist) - 1][inlist[0]]
adder, remover, masker = f[edge_function_idx(key)]
checks_ok = c[edge_function_idx(key)]
if len(tocheck) > 1:
for n in tocheck:
if not checks_ok(key, n, g, g2):
continue
mask = masker(g, key, n)
if not np.prod(mask):
mask = adder(g, key, n)
r = nodesearch0(g, g2, order, [n] + inlist, s, cds)
if r and bfu.increment(r) == g2:
s.add(g2num(r))
if capsize and len(s) > capsize:
raise ValueError('Too many elements')
remover(g, key, n, mask)
else:
r = nodesearch0(g, g2, order, [n] + inlist, s, cds)
if r and bfu.increment(r) == g2:
s.add(g2num(r))
if capsize and len(s) > capsize:
raise ValueError('Too many elements')
elif tocheck:
(n,) = tocheck
mask = adder(g, key, n)
r = nodesearch0(g, g2, order, [n] + inlist, s, cds)
if r and bfu.increment(r) == g2:
s.add(g2num(r))
if capsize and len(s) > capsize:
raise ValueError('Too many elements')
remover(g, key, n, mask)
order.insert(0, key)
else:
return g
def checker(n, ee):
g = gk.ringmore(n, ee)
g2 = bfu.increment(g)
d = checkable(g2)
t = [len(d[x]) for x in d]
r = []
n = len(g2)
ee = len(gk.edgelist(g2))
for i in range(1, len(t)):
r.append(sum(np.log10(t[:i])) - ee * np.log10(n))
return r
def nodesearch(g, g2, order, inlist, s, cds, pool, pc):
if order:
if bfu.increment(g) == g2:
s.add(g2num(g))
if capsize and len(s) > capsize:
raise ValueError('Too many elements')
s.update(supergraphs_in_eq(g, g2))
return g
key = order[0]
if pc:
tocheck = [x for x in pc if x in cds[len(inlist) - 1][inlist[0]]]
else:
tocheck = cds[len(inlist) - 1][inlist[0]]
if len(order) > 1:
kk = order[1]
pc = predictive_check(g, g2, pool[len(inlist)],
c[edge_function_idx(kk)], kk)
else:
pc = set()
adder, remover, masker = f[edge_function_idx(key)]
checks_ok = c[edge_function_idx(key)]
for n in tocheck:
if not checks_ok(key, n, g, g2):
continue
masked = np.prod(masker(g, key, n))
if masked:
nodesearch(g, g2, order[1:], [n] + inlist, s, cds, pool, pc)
else:
mask = adder(g, key, n)
nodesearch(g, g2, order[1:], [n] + inlist, s, cds, pool, pc)
remover(g, key, n, mask)
elif bfu.increment(g) == g2:
s.add(g2num(g))
if capsize and len(s) > capsize:
raise ValueError('Too many elements')
return g
def fan_wrapper(fold='None', n=10, dens=.2, sst=.9, card=2):
scipy.random.seed()
msl_time = None
sat_time = None
s = None
c = None
k = bfutils.dens2edgenum(dens, n=nodes)
output = {}
while True:
try:
output['gt'] = gk.ringmore(n, k)
gdens = traversal.density(output['gt'])
gu = bfutils.increment(output['gt'])
if estimate_gu:
data = dg.ConstructDynBN(output['gt'], [card] * n, sst,
BURNIN + NSAMPLES * URATE)
data = data[:, BURNIN:]
gu_est, gu_time = gu_estimate(data[:, ::URATE], ALG)
else:
gu_est = None
gu_time = None
if estimate_g1:
try:
s, msl_time = msl_caller(gu_est)
except TimeoutError:
s = None
msl_time = None
try:
c, sat_time = sat_caller(gu_est, fold)
except TimeoutError:
c = None
sat_time = None
if msl_time is not None:
print "msl: {:2}: {:8} : {:4} {:10} seconds".\
format(fold, round(sst,3), len(s),
round(msl_time/1000.,3))
if sat_time is not None:
print "sat: {:2}: {:8} : {:4} {:10} seconds".\
format(fold, round(sst,3), len(c),
round(sat_time/1000.,3))
else:
s = None
c = None
msl_time = None
sat_time = None
output['gu'] = {'est': gu_est, 'truth': gu, 'ms': gu_time}
output['MSL'] = {'eq': s, 'ms': msl_time}
output['SAT'] = {'eq': c, 'ms': sat_time}
except MemoryError:
print 'memory error... retrying'
continue
break
return output
def checkerDS(n, ee):
g = gk.ringmore(n, ee)
g2 = bfu.increment(g)
gg = checkable(g2)
d, p, idx = conformanceDS(g2, gg, gg.keys())
t = [len(x) for x in p]
r = []
n = len(g2)
ee = len(gk.edgelist(g2))
for i in range(1, len(t)):
r.append(sum(np.log10(t[:i])) - ee * np.log10(n))
return r
def edge_backtrack2g1_directed(g2, capsize=None):
'''
computes all g1 that are in the equivalence class for g2
'''
if bfu.isSclique(g2):
print 'Superclique - any SCC with GCD = 1 fits'
return set([-1])
single_cache = {}
def edgeset(g):
return set(gk.edgelist(g))
@memo # memoize the search
def nodesearch(g, g2, edges, s):
if edges:
e = edges.pop()
ln = [n for n in g2]
for n in ln:
if (n, e) in single_cache:
continue
mask = add2edges(g, e, n)
if gk.isedgesubset(bfu.increment(g), g2):
r = nodesearch(g, g2, edges, s)
if r and edgeset(bfu.increment(r)) == edgeset(g2):
s.add(g2num(r))
if capsize and len(s) > capsize:
raise ValueError('Too many elements in eqclass')
del2edges(g, e, n, mask)
edges.append(e)
else:
return g
# find all directed g1's not conflicting with g2
n = len(g2)
edges = gk.edgelist(g2)
random.shuffle(edges)
g = cloneempty(g2)
for e in edges:
for n in g2:
mask = add2edges(g, e, n)
if not gk.isedgesubset(bfu.increment(g), g2):
single_cache[(n, e)] = False
del2edges(g, e, n, mask)
s = set()
try:
nodesearch(g, g2, edges, s)
except ValueError:
s.add(0)
return s
def nodesearch(g, g2, edges, s):
if edges:
if bfu.increment(g) == g2:
s.add(g2num(g))
if capsize and len(s) > capsize:
raise ValueError('Too many elements')
return g
e = edges[0]
for n in g2:
if (n, e) in single_cache:
continue
if not edge_increment_ok(e[0], n, e[1], g, g2):
continue
mask = add2edges(g, e, n)
r = nodesearch(g, g2, edges[1:], s)
del2edges(g, e, n, mask)
elif bfu.increment(g) == g2:
s.add(g2num(g))
if capsize and len(s) > capsize:
raise ValueError('Too many elements in eqclass')
return g
