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_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_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_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_init():
df, (pid_in, pid_out) = get_dataflow()
algo = AbstractEvaluation(df)
assert_raises(NotImplementedError, lambda: algo.eval(0, None))
algo = BruteEvaluation(df)
algo.clear()
assert len(algo._evaluated) == 0
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_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_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_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_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_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))