def run_test(graph, k):
"""
Simply runs the new code for a given graph and a given graphlet size.
"""
lift_unordered = lt.Lift(graph, k, lift_type="unordered")
graphlet_counts = lift_unordered.get_graphlet_count(
num_steps=NUM_STEPS)
return graphlet_counts
# lift_operator.py
import lift
# lift 객체 생성
my_lift = lift.Lift()
# lift가 위치한 층 찾기
floor = my_lift.get_floor()
print("lift가 새로운 층으로 이동했습니다", floor)
# 새로운 층으로 lift 이동
my_lift.move_to_floor(5)
# 현재 lift가 위치한 층 찾기
floor = my_lift.get_floor()
print("lift가 새로운 층으로 이동했습니다", floor)
def test_graph(graph):
"""
Tests that the sampling method obtains correct counts for the path graph,
wheel graph, and ladder graph (see networkx documentation for graph
details). Large scale test that gives a basic sanity check of the whole sampling class.
"""
if graph == "path":
path_graph = nx.path_graph(5)
lift_unordered = lt.Lift(path_graph, 3, lift_type="unordered")
graphlet_counts = lift_unordered.get_graphlet_count(
num_steps=NUM_STEPS)
assert graphlet_counts["wedge"] == 3
assert graphlet_counts["triangle"] == 0
lift_unordered = lt.Lift(path_graph, 2, lift_type="unordered")
graphlet_counts = lift_unordered.get_graphlet_count(
num_steps=NUM_STEPS)
assert graphlet_counts["2-path"] == 4
print("Path graph passed.")
elif graph == "wheel":
wheel_graph = nx.wheel_graph(6) # this is a 6-cycle with a star center node
lift_unordered = lt.Lift(wheel_graph, 3, lift_type="unordered")
graphlet_counts = lift_unordered.get_graphlet_count(
num_steps=NUM_STEPS)
assert graphlet_counts["wedge"] == 10
assert graphlet_counts["triangle"] == 5
lift_unordered = lt.Lift(wheel_graph, 2, lift_type="unordered")
graphlet_counts = lift_unordered.get_graphlet_count(
num_steps=NUM_STEPS)
assert graphlet_counts["2-path"] == 10
print("Wheel graph passed.")
elif graph == "ladder":
ladder_graph = nx.ladder_graph(4) # this is two 6-paths joined one to one
lift_unordered = lt.Lift(ladder_graph, 3, lift_type="unordered")
graphlet_counts = lift_unordered.get_graphlet_count(
num_steps=NUM_STEPS)
assert graphlet_counts["wedge"] == 16
assert graphlet_counts["triangle"] == 0
lift_unordered = lt.Lift(ladder_graph, 2, lift_type="unordered")
graphlet_counts = lift_unordered.get_graphlet_count(
num_steps=NUM_STEPS)
assert graphlet_counts["2-path"] == 10
print("Ladder graph passed.")
elif graph == "bio-celegansneural":
graphlet_counts = run_test("bio-celegansneural", 3)
actual_triangle_count = 12.6 * 10**3 / 3
assert ((graphlet_counts["triangle"] - actual_triangle_count)
/ actual_triangle_count < THRESHOLD)
print(graph + " passed.")
print(graphlet_counts, "\n")
elif graph == "ia-email-univ":
graphlet_counts = run_test("ia-email-univ", 3)
actual_triangle_count = 16000 / 3
assert ((graphlet_counts["triangle"] - actual_triangle_count)
/ actual_triangle_count < THRESHOLD)
print(graph + " passed.")
print(graphlet_counts, "\n")
elif graph == "misc-fullb":
graphlet_counts = run_test("misc-fullb", 3)
actual_triangle_count = 180.6 * 10**6 / 3
assert ((graphlet_counts["triangle"] - actual_triangle_count)
/ actual_triangle_count < THRESHOLD)
print(graph + " passed.")
print(graphlet_counts, "\n")
elif graph == "misc-polblogs":
graphlet_counts = run_test("misc-polblogs", 3)
actual_triangle_count = 459.4 * 10**3 / 3
assert ((graphlet_counts["triangle"] - actual_triangle_count)
/ actual_triangle_count < THRESHOLD)
print(graph + " passed.")
print(graphlet_counts, "\n")
else:
print("Graph unknown.")
# # test_graph("misc-polblogs")
#
# # ICYMI: nx.star_graph(4) has 5 nodes.
# graphlet_counts = run_test(nx.star_graph(4), 5)
# assert graphlet_counts[0] == 1
# print("Star graph passed.")
#
# graphlet_counts = run_test(nx.complete_graph(5), 5)
# assert graphlet_counts[20] == 1
#
# graphlet_counts = run_test(nx.complete_graph(10), 5)
# assert graphlet_counts[20] == 252
# print("Complete graph passed.")
import time
lift = lt.Lift("bio-celegansneural", 4)
times = []
for i in range(100):
start = time.time()
lift.get_graphlet_count(num_steps=1)
times.append(time.time() - start)
print(
"Average time taken for a single iteration: ",
sum(times)/100
)
# # Pynauty tests.
# import networkx as nx
# import pynauty as na
#
# g = na.Graph(number_of_vertices=8, directed=False,
leftPedestals = [[1, 2],
[5, 8],
[7, 6],
[3, 0]]
rightPedestals = [[3, 6],
[1, 0],
[5, 2],
[7, 8]]
homeMarker = [0, 21, 14, 7]
c = configReader.ConfigReader(R.usbkey, d)
v = voltaged.Voltaged(R, d)
l = lift.Lift(R)
if c.getDebug():
f = function.Driver(R, m, c.getMaxSpeed(), c.getDistModifier(), c.getDistModifierBegin(), (c.getCamResX(), c.getCamResY()), d)
else:
f = function.Driver(R, m, c.getMaxSpeed(), c.getDistModifier(), c.getDistModifierBegin(), (c.getCamResX(), c.getCamResY()))
a = anticollisiond.AntiCollisiond(R)
l.daemon = True
m.daemon = True
a.daemon = True
v.daemon = True
b = c.getTokenOrder()
command = c.getCommands()
maxSpeed = c.getMaxSpeed()
armMotor = robot.getDevice('l5')
arm = arm.Arm(armMotor)
# arm.out()
grabConnector = robot.getDevice('connector')
# grab = grab.Grab(grabConnector )
liftMotors = []
liftMotorsNames = ['l1', 'l2', 'l3', 'l4']
for i in range(len(liftMotorsNames)):
liftMotors.append(robot.getDevice(liftMotorsNames[i]))
liftMotors[i].setPosition(0)
lift = lift.Lift(liftMotors)
level3 = 0.183
level3 = 0.18
lift.go(level3)
# while(not arm.isOut()):
# pass
arm.out()
while robot.step(timestep) != -1:
if (arm.isOut()):
print('out')
grabConnector.enablePresence(10)
print(grabConnector.getPresence())
