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())