def test_dt_backtracking():
"""
test a bit more of the decision tree.
tries all possible children, at least for strategies,
then goes with the "best" one.
"""
if 0:
plt.figure(1).clf()
fig, ax = plt.subplots(num=1)
af = test_basic_setup()
af.log.setLevel(logging.INFO)
af.cdt.post_check = False
af.root = front.DTChooseSite(af)
af.current = af.root
if 0:
def cb():
print("tried...")
af.plot_summary()
fig.canvas.draw()
else:
def cb():
pass
af.current.best_child()
af.current.best_child(cb=cb)
af.current.best_child()
# This is leaving things in a weird place
# maybe fixed now?
af.current.best_child(cb=cb)
def test_no_lookahead():
af = test_basic_setup(front.AdvancingTriangles)
af.log.setLevel(logging.INFO)
af.cdt.post_check = False
af.current = af.root = front.DTChooseSite(af)
def cb():
af.plot_summary(label_nodes=False)
try:
af.current.site.plot()
except: # AttributeError:
pass
while 1:
if not af.current.children:
break # we're done?
for child_i in range(len(af.current.children)):
if af.current.try_child(child_i):
# Accept the first child which returns true
break
else:
assert False # none of the children worked out
return af
def test_singlestep_lookahead():
af = test_basic_setup()
af.log.setLevel(logging.INFO)
af.cdt.post_check = False
af.current = af.root = front.DTChooseSite(af)
while 1:
if not af.current.children:
break # we're done?
if not af.current.best_child(): # cb=cb
assert False
return af
plt.plot(P[:, 0], P[:, 1], 'go')
plt.axis('equal')
##
# This often has scale issues at the end
# af.loop(1000)
##
# try invoking the search tree approach
import logging
af.log.setLevel(logging.INFO)
af.current = af.root = front.DTChooseSite(af)
##
# can this be rewritten so that af.current holds enough state to always
# know the next thing to do?
def advance_greedy(af):
"""
based on the state of af.current, take the next step.
returns True indicating more work to do, or False to
indicate completion or stuck
"""
# active_child refers to the last child of this node which was
# attempted. it is None/-1 if no children have been attempted.
# it is len(children) if all children have been attempted and