def plot(self, index=None):
from tests import plot_whiskers
from pylab import cm
cmap = lambda i: cm.spectral(i / float(len(self._paths)))
if index is None:
for i, p in enumerate(self._paths):
plot_whiskers([e for e in p if e], color=cmap(i))
else:
p = list(self._paths)[index]
plot_whiskers([e for e in p if e], color=cmap(index))
def plot(self, index = None):
from tests import plot_whiskers
from pylab import cm
cmap = lambda i: cm.spectral( i/float(len(self._paths)) )
if index is None:
for i,p in enumerate(self._paths):
plot_whiskers( [e for e in p if e], color = cmap(i) )
else:
p = list(self._paths)[index]
plot_whiskers( [e for e in p if e], color = cmap(index) )
def update( self, newpaths, owner, stubs ):
if 0:
from pylab import plot, cla, show
from tests import plot_whiskers
cla()
plot(owner.x,owner.y,'k',linewidth=3)
plot_whiskers([e for e in p if e],marker='x')
show()
issame = lambda a,b: (a is not None) and (a==b) # true implies (b is not None)
br = stubs[owner]
if br:
didmerge = False
l,m,r = br # Filter paths to make sure only new paths
for p in newpaths:
if (not (l or r)) or issame(l,p[0]) or issame(r,p[-1]): # corresponding to `owner` are substituted
self._merge( owner, p )
didmerge = True
if not didmerge: # There was a break
self._merge( owner, None ) # But there was no parent path found that sourced the break...
def update(self, newpaths, owner, stubs):
if 0:
from pylab import plot, cla, show
from tests import plot_whiskers
cla()
plot(owner.x, owner.y, 'k', linewidth=3)
plot_whiskers([e for e in p if e], marker='x')
show()
issame = lambda a, b: (a is not None) and (
a == b) # true implies (b is not None)
br = stubs[owner]
if br:
didmerge = False
l, m, r = br # Filter paths to make sure only new paths
for p in newpaths:
if (not (l or r)) or issame(l, p[0]) or issame(
r,
p[-1]): # corresponding to `owner` are substituted
self._merge(owner, p)
didmerge = True
if not didmerge: # There was a break
self._merge(
owner, None
) # But there was no parent path found that sourced the break...
def compute_pairwise_conflict_paths(a, b, prune):
"""
a and b are each tuples of (whisker, hitindex), as returned from CollisionTable.next()
Returns a set of tuples.
"""
bnda, bndb = trace_overlap(a, b)
la, ma, ra = breakout(a[0], bnda)
lb, mb, rb = breakout(b[0], bndb)
ownership = {a[0]: (la, ma, ra), b[0]: (lb, mb, rb)}
if not ma or not mb or prune(ma) or prune(mb):
ownership = {a[0]: None, b[0]: None}
pset = set()
return pset, ownership
pset = [[la, ma, ra], [la, ma, mb, rb], [lb, mb, ma, ra], [lb, mb, rb]]
#prune
for p in pset:
for i, w in enumerate(p):
if w and prune(w):
p[i] = None
#transform to set of tuples
pset = set([tuple(e) for e in pset])
#0. Path's must have legititmate middle nodes.
for p in list(pset):
if len(p) == 3 and p[1] is None:
pset.remove(p)
elif len(p) == 4 and (p[1] is None or p[2] is None):
pset.remove(p)
#reduction
hasfullpath = False
# 1. Remove if can't get from left to right
for p in list(pset):
if p[0] is None and p[-1] is None:
pset.discard(p)
if p[0] is not None and p[-1] is not None:
hasfullpath = True
# 2. if only overlap, return composite of overlap
if len(pset
) == 0: #no endpoints - this happens for middle-only overlaps
m = max((ma, mb), key=lambda w: w.scores.mean())
ownership = {a[0]: (None, m, None), b[0]: (None, m, None)}
#ownership = {a[0]:None, b[0]:None}
pset = set(((None, m, None), )) #return best scoring
return pset, ownership
# 3. if there is at least one path from left to right, remove paths that
# don't
if hasfullpath:
for p in list(pset):
if p[0] is None or p[-1] is None:
pset.discard(p)
else:
# 4. if not, path's should not begin or end on merged middles
for p in list(pset):
if len(p) == 4 and (p[0] is None or p[-1] is None):
pset.discard(p)
if 0:
from tests import plot_whiskers
from pylab import cm, clf, show
cmap = lambda i: cm.spectral(i / float(len(pset)))
for i, p in enumerate(pset):
plot_whiskers([e for e in p if e], color=cmap(i))
show()
return pset, ownership
def compute_pairwise_conflict_paths( a, b, prune ):
"""
a and b are each tuples of (whisker, hitindex), as returned from CollisionTable.next()
Returns a set of tuples.
"""
bnda,bndb = trace_overlap(a,b)
la,ma,ra = breakout(a[0],bnda)
lb,mb,rb = breakout(b[0],bndb)
ownership = {a[0]:(la,ma,ra), b[0]:(lb,mb,rb)}
if not ma or not mb or prune(ma) or prune(mb):
ownership = {a[0]:None, b[0]:None}
pset = set()
return pset, ownership
pset = [ [ la, ma, ra ],
[ la, ma, mb, rb ],
[ lb, mb, ma, ra ],
[ lb, mb, rb ] ]
#prune
for p in pset:
for i,w in enumerate(p):
if w and prune(w):
p[i] = None
#transform to set of tuples
pset = set( [tuple(e) for e in pset] )
#0. Path's must have legititmate middle nodes.
for p in list(pset):
if len(p)==3 and p[1] is None:
pset.remove(p)
elif len(p)==4 and ( p[1] is None or p[2] is None ):
pset.remove(p)
#reduction
hasfullpath = False
# 1. Remove if can't get from left to right
for p in list(pset):
if p[0] is None and p[-1] is None:
pset.discard(p)
if p[0] is not None and p[-1] is not None:
hasfullpath = True
# 2. if only overlap, return composite of overlap
if len(pset)==0: #no endpoints - this happens for middle-only overlaps
m = max( (ma,mb), key = lambda w: w.scores.mean() )
ownership = {a[0]:(None,m,None), b[0]:(None,m,None)}
#ownership = {a[0]:None, b[0]:None}
pset = set( ((None,m,None),) ) #return best scoring
return pset, ownership
# 3. if there is at least one path from left to right, remove paths that
# don't
if hasfullpath:
for p in list(pset):
if p[0] is None or p[-1] is None:
pset.discard(p)
else:
# 4. if not, path's should not begin or end on merged middles
for p in list(pset):
if len(p)==4 and ( p[0] is None or p[-1] is None ):
pset.discard(p)
if 0:
from tests import plot_whiskers
from pylab import cm, clf, show
cmap = lambda i: cm.spectral( i/float(len(pset)) )
for i,p in enumerate(pset):
plot_whiskers([e for e in p if e], color = cmap(i))
show()
return pset,ownership
