def test_dataflow_state_is_ready_for_evaluation():
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")
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)
dfs = DataflowState(df)
assert not dfs.is_ready_for_evaluation()
dfs.set_data(pid10, 0)
assert dfs.is_ready_for_evaluation()
dfs.clear()
for i, pid in enumerate([pid11, pid21, pid33]):
dfs.set_data(pid, i)
assert not dfs.is_ready_for_evaluation()
def test_dataflow_state_reinit():
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")
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)
dfs = DataflowState(df)
dfs.set_data(pid10, 0)
for i, pid in enumerate([pid11, pid21, pid33]):
dfs.set_data(pid, i)
dfs.reinit()
assert dfs.is_ready_for_evaluation()
for pid in (pid11, pid21, pid33):
raises(KeyError, lambda: dfs.get_data(pid))
def test_dataflow_state_reinit():
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")
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)
dfs = DataflowState(df)
dfs.set_data(pid10, 0)
for i, pid in enumerate([pid11, pid21, pid33]):
dfs.set_data(pid, i)
dfs.reinit()
assert dfs.is_ready_for_evaluation()
for pid in (pid11, pid21, pid33):
assert_raises(KeyError, lambda: dfs.get_data(pid))
def test_dataflow_evaluation_eval_no_vid():
df, (pid_in, pid_out) = get_dataflow()
algo = BruteEvaluation(df)
env = 0
dfs = DataflowState(df)
dfs.set_data(pid_in, 1)
assert not dfs.is_valid()
algo.eval(env, dfs)
assert dfs.is_valid()
def test_dataflow_evaluation_no_input_two_outputs():
df = DataFlow()
vid = df.add_vertex()
pid0 = df.add_out_port(vid, "out1")
df.set_actor(vid, FuncNode({}, {}, double_fixed_function))
dfs = DataflowState(df)
env = 0
algo = BruteEvaluation(df)
algo.eval(env, dfs, vid)
assert tuple(dfs.get_data(pid0)) == (5, 5)
algo.clear()
dfs.reinit()
pid1 = df.add_out_port(vid, "out2")
algo.eval(env, dfs, vid)
assert dfs.get_data(pid0) == 5
assert dfs.get_data(pid1) == 5
algo.clear()
dfs.reinit()
pid2 = df.add_out_port(vid, "out3")
assert_raises(UserWarning, lambda: algo.eval(env, dfs, vid))
def test_dataflow_evaluation_eval_init():
df, (pid_in, pid_out) = get_dataflow()
algo = BruteEvaluation(df)
env = 0
dfs = DataflowState(df)
assert_raises(UserWarning, lambda: algo.eval(env, dfs))
def test_dataflow_evaluation_no_input_two_outputs():
df = DataFlow()
vid = df.add_vertex()
pid0 = df.add_out_port(vid, "out1")
df.set_actor(vid, FuncNode({}, {}, double_fixed_function))
dfs = DataflowState(df)
env = 0
algo = BruteEvaluation(df)
algo.eval(env, dfs, vid)
assert tuple(dfs.get_data(pid0)) == (5, 5)
algo.clear()
dfs.reinit()
pid1 = df.add_out_port(vid, "out2")
algo.eval(env, dfs, vid)
assert dfs.get_data(pid0) == 5
assert dfs.get_data(pid1) == 5
algo.clear()
dfs.reinit()
pid2 = df.add_out_port(vid, "out3")
assert_raises(UserWarning, lambda: algo.eval(env, dfs, vid))
def test_dataflow_evaluation_single_input_single_output():
df = DataFlow()
vid = df.add_vertex()
pid0 = df.add_in_port(vid, "in")
pid1 = df.add_in_port(vid, "in")
pid2 = df.add_out_port(vid, "out")
df.set_actor(vid, FuncNode({}, {}, operator.add))
dfs = DataflowState(df)
env = 0
algo = BruteEvaluation(df)
dfs.set_data(pid0, 1)
dfs.set_data(pid1, 2)
algo.eval(env, dfs, vid)
assert dfs.get_data(pid0) == 1
assert dfs.get_data(pid1) == 2
assert dfs.get_data(pid2) == 3
def test_dataflow_evaluation_eval_no_vid2():
df = DataFlow()
vid0 = df.add_vertex()
pid0 = df.add_in_port(vid0, "in")
df.add_out_port(vid0, "out")
vid1 = df.add_vertex()
pid1 = df.add_in_port(vid1, "in")
df.add_out_port(vid1, "out")
df.set_actor(vid0, FuncNode({}, {}, int))
df.set_actor(vid1, FuncNode({}, {}, int))
dfs = DataflowState(df)
env = 0
algo = BruteEvaluation(df)
dfs.set_data(pid0, 0)
dfs.set_data(pid1, 1)
assert not dfs.is_valid()
algo.eval(env, dfs)
assert dfs.is_valid()
def test_dataflow_state_init():
df = DataFlow()
vid1 = df.add_vertex()
df.add_in_port(vid1, "in")
pid11 = df.add_out_port(vid1, "out")
vid2 = df.add_vertex()
pid21 = df.add_out_port(vid2, "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)
dfs = DataflowState(df)
dfs.clear()
assert len(dfs._state) == 0
def test_dataflow_state_init():
df = DataFlow()
vid1 = df.add_vertex()
df.add_in_port(vid1, "in")
pid11 = df.add_out_port(vid1, "out")
vid2 = df.add_vertex()
pid21 = df.add_out_port(vid2, "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)
dfs = DataflowState(df)
dfs.clear()
assert len(dfs._state) == 0
def test_dataflow_evaluation_eval_no_vid():
df, (pid_in, pid_out) = get_dataflow()
algo = BruteEvaluation(df)
env = 0
dfs = DataflowState(df)
dfs.set_data(pid_in, 1)
assert not dfs.is_valid()
algo.eval(env, dfs)
assert dfs.is_valid()
def test_dataflow_evaluation_single_input_no_output():
df = DataFlow()
vid = df.add_vertex()
pid0 = df.add_in_port(vid, "in")
df.set_actor(vid, FuncNode({}, {}, print))
dfs = DataflowState(df)
env = 0
algo = BruteEvaluation(df)
dfs.set_data(pid0, 1)
algo.eval(env, dfs, vid)
assert dfs.get_data(pid0) == 1
df.set_actor(vid, FuncNode({}, {}, int))
dfs.reinit()
algo.clear()
assert_raises(UserWarning, lambda: algo.eval(env, dfs, vid))
def test_dataflow_evaluation_single_input_single_output():
df = DataFlow()
vid = df.add_vertex()
pid0 = df.add_in_port(vid, "in")
pid1 = df.add_in_port(vid, "in")
pid2 = df.add_out_port(vid, "out")
df.set_actor(vid, FuncNode({}, {}, operator.add))
dfs = DataflowState(df)
env = 0
algo = BruteEvaluation(df)
dfs.set_data(pid0, 1)
dfs.set_data(pid1, 2)
algo.eval(env, dfs, vid)
assert dfs.get_data(pid0) == 1
assert dfs.get_data(pid1) == 2
assert dfs.get_data(pid2) == 3
def test_dataflow_evaluation_single_input_no_output():
df = DataFlow()
vid = df.add_vertex()
pid0 = df.add_in_port(vid, "in")
df.set_actor(vid, FuncNode({}, {}, print_func))
dfs = DataflowState(df)
env = 0
algo = BruteEvaluation(df)
dfs.set_data(pid0, 1)
algo.eval(env, dfs, vid)
assert dfs.get_data(pid0) == 1
df.set_actor(vid, FuncNode({}, {}, int))
dfs.reinit()
algo.clear()
assert_raises(UserWarning, lambda: algo.eval(env, dfs, vid))
def test_dataflow_evaluation_eval_no_vid2():
df = DataFlow()
vid0 = df.add_vertex()
pid0 = df.add_in_port(vid0, "in")
df.add_out_port(vid0, "out")
vid1 = df.add_vertex()
pid1 = df.add_in_port(vid1, "in")
df.add_out_port(vid1, "out")
df.set_actor(vid0, FuncNode({}, {}, int))
df.set_actor(vid1, FuncNode({}, {}, int))
dfs = DataflowState(df)
env = 0
algo = BruteEvaluation(df)
dfs.set_data(pid0, 0)
dfs.set_data(pid1, 1)
assert not dfs.is_valid()
algo.eval(env, dfs)
assert dfs.is_valid()
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():
assert_raises(KeyError, lambda: dfs.get_data(pid))
for i, pid in enumerate([pid11, pid21, pid33, pid51]):
dfs.set_data(pid, i)
assert_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 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 test_dataflow_state_is_ready_for_evaluation():
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")
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)
dfs = DataflowState(df)
assert not dfs.is_ready_for_evaluation()
dfs.set_data(pid10, 0)
assert dfs.is_ready_for_evaluation()
dfs.clear()
for i, pid in enumerate([pid11, pid21, pid33]):
dfs.set_data(pid, i)
assert not dfs.is_ready_for_evaluation()
