def test_dataflow_state_get_data():
df = DataFlow()
vid1 = df.add_vertex()
pid10 = df.add_in_port(vid1, "in")
pid11 = df.add_out_port(vid1, "out")
vid2 = df.add_vertex()
pid21 = df.add_out_port(vid2, "out")
vid5 = df.add_vertex()
pid51 = df.add_out_port(vid5, "out")
vid3 = df.add_vertex()
pid31 = df.add_in_port(vid3, "in1")
pid32 = df.add_in_port(vid3, "in2")
pid33 = df.add_out_port(vid3, "res")
vid4 = df.add_vertex()
pid41 = df.add_in_port(vid4, "in")
df.connect(pid11, pid31)
df.connect(pid21, pid32)
df.connect(pid33, pid41)
df.connect(pid51, pid32)
dfs = DataflowState(df)
for pid in df.ports():
raises(KeyError, lambda: dfs.get_data(pid))
for i, pid in enumerate([pid11, pid21, pid33, pid51]):
dfs.set_data(pid, i)
raises(KeyError, lambda: dfs.get_data(pid10))
dfs.set_data(pid10, 'a')
assert dfs.get_data(pid10) == 'a'
for i, pid in enumerate([pid11, pid21, pid33, pid51]):
assert dfs.get_data(pid) == i
assert dfs.get_data(pid31) == 0
assert tuple(dfs.get_data(pid32)) == (1, 3)
assert dfs.get_data(pid41) == 2
n2 = Node()
df.set_actor(vid2, n2)
assert tuple(dfs.get_data(pid32)) == (1, 3)
n5 = Node()
df.set_actor(vid5, n5)
assert tuple(dfs.get_data(pid32)) == (1, 3)
n2.get_ad_hoc_dict().set_metadata('position', [10, 0])
n5.get_ad_hoc_dict().set_metadata('position', [0, 0])
assert tuple(dfs.get_data(pid32)) == (3, 1)
def create_fake_node(self, vid):
""" Return an empty node with the correct number of inputs
and output """
# Count in and out needed
ins = 0
outs = 0
for eid, link in self.connections.iteritems():
(source_vid, source_port, target_vid, target_port) = link
if(source_vid == vid):
outs = max(outs, source_port)
elif(target_vid == vid):
ins = max(ins, target_port)
node = Node()
attributes = copy.deepcopy(self.elt_data[vid])
ad_hoc = copy.deepcopy(self.elt_ad_hoc.get(vid, None))
self.load_ad_hoc_data(node, attributes, ad_hoc)
# copy node input data if any
values = copy.deepcopy(self.elt_value.get(vid, ()))
for p in range(ins+1):
port = node.add_input(name="In"+str(p))
for p in range(outs+1):
port = node.add_output(name="Out"+str(p))
for vs in values:
try:
#the two first elements are the historical
#values : port Id and port value
#beyond that are extensions added by gengraph:
#the ad_hoc_dict representation is third.
port, v = vs[:2]
node.set_input(port, eval(v))
if(len(vs)>2):
d = MetaDataDict(vs[2])
node.input_desc[port].get_ad_hoc_dict().update(d)
except:
continue
return node
