def gen_to_tree(g):
n = tree.Node(cargo=g)
#==
if g.__name__ == 'broadcast' : children = g.gi_frame.f_locals['targets']
elif g.__name__ == 'sink' : children = []
else : children = [g.gi_frame.f_locals['target']]
#==
for child in children:
tree.connect(gen_to_tree(child), n)
return n
def setup_graph(nb, nb_cnx):
elements = map(gen_el, range(nb))
root = elements[0]
for idx, el in enumerate(elements):
rst = elements[:idx]
if not rst:
continue
ii = min(nb_cnx, len(rst))
els = random.sample(rst, ii)
for e in els:
if el in e.children:
continue
tree.connect(el, e)
#==
for el in elements:
if el != root:
assert el.parents
assert root.children
#==
return root, elements
def func_to_node(f):
sink = f.__dict__.get('sink')
if sink: gen = base.sink
else : gen = base.transformer
gp = base.GeneratorProto(gen, f)
tn = graph.TNode(cargo=gp)
#==
if not sink:
os = graph.OSlot()
tree.connect(os, tn)
else:
os = None
#==
if f.__code__.co_varnames: nb_arg = 1
else : nb_arg = f.__code__.co_argcount
islots = []
for i in range(nb_arg):
islot = graph.ISlot()
islots.append(islot)
tree.connect(tn, islot)
#==
return islots, tn, os
def test():
gp = base.GeneratorProto(base.value, 5)
tn = graph.TNode(cargo=gp)
os = graph.OSlot()
tree.connect(os, tn)
#==
oss = [os]
for i in range(100):
op = random.choice([add, minus, inc, decr])
iss, _, os = func_to_node(op)
for i in iss:
tree.connect(i, random.choice(oss))
oss.append(os)
#==
op = pprint
iss, _, os = func_to_node(op)
while oss:
tree.connect(random.choice(iss), oss.pop())
assert not oss
return tn
