def dpc(data, pval=0.05):
n = data.shape[0]
# stack the data: first n rows is t-1 slice, the next n are slice t
data = np.asarray(np.r_[data[:,:-1],data[:,1:]])
def tetrad_cind_(y,x,condset=[], alpha=0.01, shift=0):
y = data[n+int(y)-1,:]
x = data[shift+int(x)-1,:]
if condset:
X = data[condset,:]
ry, rx = residuals_(y,x,X)
else:
ry, rx = [y,x]
return independent_(ry, rx, alpha = alpha)
def cind_(y,x, condset=[], pval=pval, shift=0):
yd = data[n+int(y)-1,:].T
X = data[[shift+int(x)-1]+condset,:].T
return independent(yd, X, pval=pval)
def cindependent(y, x, counter, parents=[], pval=pval):
for S in [j for j in iter.combinations(parents,counter)]:
if cind_(y, x, condset=list(S), pval=pval): return True
#if tetrad_cind_(x, y, condset=list(S), alpha=pval): return True
return False
def bindependent(y, x, parents=[], pval=pval):
return cind_(y, x, condset=parents, pval=pval, shift=n)
#return tetrad_cind_(y, x, condset=parents, alpha=pval, shift=n)
def prune(elist, mask, g):
for e in mask:
g[e[0]][e[1]].remove((0,1))
elist.remove(e)
gk.clean_leaf_nodes(g)
g = gk.superclique(n)
gtr= bfu.gtranspose(g)
el = gk.edgelist(g)
for counter in range(n):
to_remove = []
for e in el:
ppp = [int(k)-1 for k in gtr[e[1]] if k != e[0]]
if counter <= len(ppp):
if cindependent(e[1], e[0], counter, parents=ppp, pval=pval):
to_remove.append(e)
gtr[e[1]].pop(e[0],None)
prune(el, to_remove, g)
bel = [map(lambda k: str(k+1), x) for x in iter.combinations(range(n),2)]
for e in bel:
ppp = list(set(gtr[e[0]].keys()) | set(gtr[e[1]].keys()))
ppp = map(lambda x: int(x)-1, ppp)
if bindependent(e[0], e[1], parents=ppp, pval=pval):
g[e[0]][e[1]].remove((2,0))
g[e[1]][e[0]].remove((2,0))
gk.clean_leaf_nodes(g)
return g
def reverse(H, verbose=True, capsize=1000):
n = len(H)
s = set()
g = gk.superclique(n)
sloops = set(allsloops(n))
ds = {bfu.g2num(g): sloops}
if verbose: print '%3s'%'i'+'%10s'%' graphs'
i=0
while ds:
ds, ss = del_loop(ds, H, iter=i,
verbose=verbose,
capsize=capsize)
s = s | ss
i += 1
if capsize <= len(s): break
return s
def dpc(data, pval=0.05):
n = data.shape[0]
# stack the data: first n rows is t-1 slice, the next n are slice t
data = np.asarray(np.r_[data[:, :-1], data[:, 1:]])
def tetrad_cind_(y, x, condset=[], alpha=0.01, shift=0):
y = data[n + int(y) - 1, :]
x = data[shift + int(x) - 1, :]
if condset:
X = data[condset, :]
ry, rx = residuals_(y, x, X)
else:
ry, rx = [y, x]
return independent_(ry, rx, alpha=alpha)
def cind_(y, x, condset=[], pval=pval, shift=0):
yd = data[n + int(y) - 1, :].T
X = data[[shift + int(x) - 1] + condset, :].T
return independent(yd, X, pval=pval)
def cindependent(y, x, counter, parents=[], pval=pval):
for S in [j for j in iter.combinations(parents, counter)]:
if cind_(y, x, condset=list(S), pval=pval): return True
#if tetrad_cind_(x, y, condset=list(S), alpha=pval): return True
return False
def bindependent(y, x, parents=[], pval=pval):
return cind_(y, x, condset=parents, pval=pval, shift=n)
#return tetrad_cind_(y, x, condset=parents, alpha=pval, shift=n)
def prune(elist, mask, g):
for e in mask:
g[e[0]][e[1]].remove((0, 1))
elist.remove(e)
gk.clean_leaf_nodes(g)
g = gk.superclique(n)
gtr = bfu.gtranspose(g)
el = gk.edgelist(g)
for counter in range(n):
to_remove = []
for e in el:
ppp = [int(k) - 1 for k in gtr[e[1]] if k != e[0]]
if counter <= len(ppp):
if cindependent(e[1], e[0], counter, parents=ppp, pval=pval):
to_remove.append(e)
gtr[e[1]].pop(e[0], None)
prune(el, to_remove, g)
bel = [
map(lambda k: str(k + 1), x) for x in iter.combinations(range(n), 2)
]
for e in bel:
ppp = list(set(gtr[e[0]].keys()) | set(gtr[e[1]].keys()))
ppp = map(lambda x: int(x) - 1, ppp)
if bindependent(e[0], e[1], parents=ppp, pval=pval):
g[e[0]][e[1]].remove((2, 0))
g[e[1]][e[0]].remove((2, 0))
gk.clean_leaf_nodes(g)
return g