def main():
xmax = 500
ymax = 700
graph.windowSize(xmax, ymax)
graph.canvasSize(xmax, ymax)
background(xmax, ymax, 300)
x0 = 500
y0 = 300
window_width = 180
window_indent = 20
while x0 >= 0:
window(x0, y0, window_width, window_indent, 5)
x0 -= (window_width + window_indent)
clew(200, 640, 50, 1)
clew(400, 600, 30, -1)
clew(300, 500, 30, -1)
clew(150, 370, 15, 1)
clew(70, 600, 15, 1)
clew(425, 400, 15, -1)
cat(350, 300, 80, 1, 'brown')
cat(150, 450, 80, -1, 'grey')
cat(100, 350, 30, -1, 'brown')
cat(450, 500, 30, -1, 'brown')
cat(100, 650, 30, -1, 'grey')
cat(400, 650, 30, 1, 'grey')
cat(350, 550, 30, 1, 'brown')
graph.run()
def main():
xmax = 500
ymax = 700
graph.windowSize(xmax, ymax)
graph.canvasSize(xmax, ymax)
background(xmax, ymax, 300)
x0 = 500
y0 = 300
window_width = 180
window_indent = 20
while x0 >= 0:
window(x0, y0, window_width, window_indent, 5)
x0 -= (window_width + window_indent)
my_pic = graph.canvas()
graph.canvasSize(xmax, ymax)
clew(200, 640, 50, 1)
cat(350, 300, 80, 1, 'brown')
my_pic.pack()
graph.run()
def P1(fo, strategy_q, buffer_q):
# t4 = threading.Thread(target=graph.run, name='graph')
# t4.daemon = True
# t4.start()
# time.sleep(5)
# plt initilization
#plt.figure()
f, axarr = plt.subplots(3, sharex=True)
li = [
axarr[i].plot([], [], 'r', [], [], 'b', [], [], 'g') for i in xrange(3)
]
li.append(axarr)
plt.setp(li[2][0], label="X-axis")
plt.setp(li[2][1], label="Y-axis")
plt.setp(li[2][2], label="Z-axis")
axarr[0].set_title("Acceleration")
axarr[1].set_title("Velocity")
axarr[2].set_title("Displacement")
box = axarr[2].get_position()
axarr[2].set_position(
[box.x0, box.y0 + box.height * 0.2, box.width, box.height * 0.8])
axarr[2].legend(loc='upper center',
bbox_to_anchor=(0.5, -0.2),
fancybox=True,
ncol=3)
# li = plt.plot([],[],'r',[],[],'b')
plt.ion()
plt.show(block=False)
t1 = threading.Thread(target=host.serv, name='server')
t1.daemon = True
t1.start()
t2 = threading.Thread(target=datahandler.handler,
name='datahandler',
args=(
buffer_q,
plt,
li,
))
t2.daemon = True
t2.start()
print "datahandler start"
t3 = threading.Thread(target=servogene.servo_gene,
name='servo_generation',
args=(strategy_q, ))
t3.daemon = True
t3.start()
print "servo_generation start"
t5 = threading.Thread(target=monitor.monitor, name='monitor')
t5.daemon = True
t5.start()
print "monitor start"
# t6 = threading.Thread(target=ml, name='ml',args=(fo,))
# t6.daemon = True
# t6.start()
graph.run()
sys.exit()
def get_size():
dict_relations = graph.run('MATCH (n:User)-[r:RETWEETED]-(m:User) \
where (n)-[:RETWEETED]->() and not ()-[:RETWEETED]->(n)\
RETURN DISTINCT n.author,r,m.author').data()
# dict_relations = graph.run('MATCH (n:User)\
# WITH n, COUNT(DISTINCT(()-[:REPLIED_TO]->(n))) as NodesCnt\
# RETURN NodesCnt').data()
size = len(dict_relations)
return size
def route():
data = ImmutableMultiDict(urlparse.parse_qs(request.data))
errors = validate(data)
if errors['errors']:
return jsonify(errors), 400
target_node_ids = data.getlist('target_node_ids')
speed = data.get('speed')
bonuses = get_bonuses(data)
return jsonify(graph.run(target_node_ids, bonuses, speed))
def P1(fo,strategy_q,buffer_q):
# t4 = threading.Thread(target=graph.run, name='graph')
# t4.daemon = True
# t4.start()
# time.sleep(5)
# plt initilization
#plt.figure()
f, axarr = plt.subplots(3, sharex=True)
li = [axarr[i].plot([],[],'r',[],[],'b',[],[],'g') for i in xrange(3)]
li.append(axarr)
plt.setp(li[2][0],label="X-axis")
plt.setp(li[2][1],label="Y-axis")
plt.setp(li[2][2],label="Z-axis")
axarr[0].set_title("Acceleration")
axarr[1].set_title("Velocity")
axarr[2].set_title("Displacement")
box = axarr[2].get_position()
axarr[2].set_position([box.x0, box.y0 + box.height * 0.2, box.width, box.height * 0.8])
axarr[2].legend(loc='upper center', bbox_to_anchor=(0.5, -0.2), fancybox=True,ncol=3)
# li = plt.plot([],[],'r',[],[],'b')
plt.ion()
plt.show(block=False)
t1 = threading.Thread(target=host.serv, name='server')
t1.daemon = True
t1.start()
t2 = threading.Thread(target=datahandler.handler, name='datahandler',args=(buffer_q,plt,li,))
t2.daemon = True
t2.start()
print "datahandler start"
t3 = threading.Thread(target=servogene.servo_gene, name='servo_generation',args=(strategy_q,))
t3.daemon = True
t3.start()
print "servo_generation start"
t5 = threading.Thread(target=monitor.monitor, name='monitor')
t5.daemon = True
t5.start()
print "monitor start"
# t6 = threading.Thread(target=ml, name='ml',args=(fo,))
# t6.daemon = True
# t6.start()
graph.run()
sys.exit()
def get_longest_path():
# dict_relations = graph.run('MATCH (n:User)-[r:RETWEETED]-(m:User) \
# RETURN n.author,r,m.author LIMIT ' + str(500)).data()
#https://stackoverflow.com/questions/41805735/cypher-query-to-find-the-longest-path-using-neo4j-3-1-0-version
#https://stackoverflow.com/questions/41789561/find-longest-path-in-graph
dict_relations = graph.run('match (n)\
where (n)-[:REPLIED_TO]->() and not ()-[:REPLIED_TO]->(n)\
match p = (n)-[:REPLIED_TO*1..]->(m)\
return p, length(p) as L\
order by L desc LIMIT 1').data()
return dict_relations
def parse_data():
# TODO currently I simply read the file and parse data, THIS IS
# UNACCEPTABLY SLOW AND UGLY!!!
# fp = open("Datafile.txt")
# content = [(lambda s: [float(x) for x in s])(line.split()) for line in fp.readlines()]
content = graph.run()
length = graph.get_length()
size = graph.get_size()
content = list(content[:length])
content = [content[i:i+size] for i in xrange(0, len(content), size)]
return content
def parse_data():
# TODO currently I simply read the file and parse data, THIS IS
# UNACCEPTABLY SLOW AND UGLY!!!
# fp = open("Datafile.txt")
# content = [(lambda s: [float(x) for x in s])(line.split()) for line in fp.readlines()]
# graph = ctypes.cdll.LoadLibrary( 'G:\igem2013_sysu_oschina\project\Python27\web\\graph.dll' )
content = graph.run()
length = graph.get_length()
size = graph.get_size()
content = list(content[:length])
content = [content[i:i+size] for i in xrange(0, len(content), size)]
return content
def print_longest_path():
dict_relations = graph.run('match (n)\
where (n)-[:RETWEETED]->() and not ()-[:RETWEETED]->(n)\
match p = (n)-[:RETWEETED*1..]->(m)\
return p, length(p) as L').data()
# order by L desc LIMIT 5
# dict_relations = graph.run('match (n)\
# match p = (n)-[:RETWEETED*..]->(m)\
# return p, length(p) as L\
# order by L desc LIMIT 5').data()
total_ = []
for item in dict_relations:
total_.append(item['L'])
average = sum(total_) * 1. / len(total_) * 1.
return sum(total_), len(total_), average
def get_breadth():
# dict_relations = graph.run('MATCH (n:User)-[:REPLIED_TO]->(m)\
# WITH m, SIZE((n)-[:REPLIED_TO]->()) as mostNodesCnt\
# where (n)-[:REPLIED_TO]->() and not ()-[:REPLIED_TO]->(n)\
# RETURN mostNodesCnt\
# ORDER BY mostNodesCnt DESC LIMIT 1').data()
# dict_relations = graph.run('MATCH p = (n:User)-[:REPLIED_TO]->()\
# WITH n, COLLECT(p) AS paths\
# where (n)-[:REPLIED_TO]->() and not ()-[:REPLIED_TO]->(n)\
# RETURN n, REDUCE(s = paths[0], x IN paths[1..] | CASE WHEN LENGTH(x) < LENGTH(s) THEN x ELSE s END) AS path\
# limit 10').data()
dict_relations = graph.run('match (n)\
WITH SIZE((n)-[:RETWEETED]->()) as mostNodesCnt\
where (n)-[:RETWEETED]->() and not ()-[:RETWEETED]->(n)\
match p = (n)-[:RETWEETED*1..]->(m)\
return mostNodesCnt, length(p) as L ORDER BY mostNodesCnt desc LIMIT 3'
).data()
return dict_relations
sail_top_mount_x = mast_base_x
sail_top_mount_y = mast_base_y - mast_hight
sail_bottom_mount_x = mast_base_x
sail_bottom_mount_y = mast_base_y
sail_left_edge_x = ship_bow_x - ship_size * 134
sail_left_edge_y = (sail_top_mount_y + sail_bottom_mount_y) / 2
sail_right_edge_x = ship_bow_x - ship_size * 96
sail_right_edge_y = sail_left_edge_y
g.penSize(pen_width_1)
g.penColor('black')
sail_color = '#c9c094'
g.brushColor(sail_color)
g.polygon([(sail_top_mount_x, sail_top_mount_y),
(sail_left_edge_x, sail_left_edge_y),
(sail_right_edge_x, sail_right_edge_y)])
g.polygon([(sail_bottom_mount_x, sail_bottom_mount_y),
(sail_left_edge_x, sail_left_edge_y),
(sail_right_edge_x, sail_right_edge_y)])
ship_1_bow_x = 581
ship_1_size = 1
draw_a_ship(ship_1_bow_x, ship_1_size)
ship_2_bow_x = 296
ship_2_size = 0.43
draw_a_ship(ship_2_bow_x, ship_2_size)
g.run()
(xf5[9], yf5[9]), (650, 435), (675, 450), (xf6[0], yf6[0]),
(xf6[1], yf6[1]), (xf6[2], yf6[2]), (xf6[3], yf6[3]),
(xf6[4], yf6[4]), (xf6[5], yf6[5]), (xf6[6], yf6[6]),
(xf6[7], yf6[7]), (xf6[8], yf6[8]), (xf6[9], yf6[9]),
(xf6[10], yf6[10]), (xf6[11], yf6[11]), (xf6[12], yf6[12]),
(xf6[13], yf6[13])])
# рисует третью линию гор, используя для рисования кривых массивы xf5, yf5 и xf6, yf6
canvasSize(1000, 500)
windowSize(1000, 500)
points_filling()
backstage()
mtn_line1()
mtn_line2()
mtn_line3()
sun(475, 95, 50)
penColor(51, 0, 29)
brushColor(51, 0, 29)
bird(750, 400, 1)
bird(650, 330, 0.8)
bird(775, 340, 0.5)
bird(675, 350, 0.5)
bird(475, 207, 0.5)
bird(475, 170, 0.5)
bird(425, 225, 0.5)
bird(415, 160, 0.5)
run()
import graph
import math
def dragon(n, x0, y0, x1, y1, q):
if n == 0:
graph.line(x0, y0, x1, y1)
else:
alf1 = alf * q
_x = math.cos(alf1) * ((x1 - x0) * math.cos(alf1) - (y1 - y0) * math.sin(alf1)) + x0
_y = math.cos(alf1) * ((x1 - x0) * math.sin(alf1) + (y1 - y0) * math.cos(alf1)) + y0
dragon(n - 1, x0, y0, _x, _y, 1)
dragon(n - 1, _x, _y, x1, y1, -1)
if __name__ == '__main__':
alf = 45 * math.pi / 180
dragon(16, 100, 100, 400, 400, 1)
graph.run()
# time.sleep(0.8) # globalvar.s1=105 # globalvar.s2=105 # globalvar.s4=74 # globalvar.s3=74 # time.sleep(0.8) globalvar.s1=48 time.sleep(0.1) globalvar.s4=44 time.sleep(0.5) globalvar.s1=84 globalvar.s2=120 globalvar.s3=127 globalvar.s4=82 time.sleep(0.5) globalvar.s2=140 globalvar.s3=147 time.sleep(0.1) print (globalvar.s1,globalvar.s2,globalvar.s3,globalvar.s4) if __name__=='__main__': t1 = threading.Thread(target=host.serv, name='server') t1.daemon = True t1.start() t2 = threading.Thread(target=servogene, name='servogene') t2.daemon = True t2.start() graph.run() sys.exit()
def get_totals():
dict_relations = graph.run('match (n) return length(n) as T').data()
return dict_relations
x0 = width - width / 2 * 0.4
y0 = height - height / 2 * 0.4
xk = 0.4
yk = 0.4
def shrinkPoint(v, x0, y0, xk, yk):
return [(v[0] - x0) * xk + x0, (v[1] - y0) * yk + y0]
def shrinkPolygon(polygon, x0, y0, xk, yk):
return {
'color': polygon['color'],
'points':
[shrinkPoint(v, x0, y0, xk, yk) for v in polygon['points']]
}
polygons = []
for i in range(0, 3):
shrink = SIZE**(-(-tickId % SPEED + (i - 1) * SPEED) / SPEED)
polygons += [
shrinkPolygon(polygon, width / 2, height / 3, shrink, shrink)
for polygon in scene[0]['polygons']
]
updatePolygons()
gr.onTimer(drawLoop, 1000 // 30)
gr.run()
super(MoNet, self).__init__()
self.conv1 = torch_geometric.nn.GMMConv(dataset.num_features,
args.hidden,
dim=2,
kernel_size=args.kernel_size)
self.conv2 = torch_geometric.nn.GMMConv(args.hidden,
dataset.num_classes,
dim=2,
kernel_size=args.kernel_size)
def reset_parameters(self):
self.conv1.reset_parameters()
self.conv2.reset_parameters()
def forward(self, data):
x, edge_index, edge_attr = data.x, data.edge_index, data.edge_attr
x = F.dropout(x, p=args.dropout, training=self.training)
x = F.elu(self.conv1(x, edge_index, edge_attr))
x = F.dropout(x, p=args.dropout, training=self.training)
x = self.conv2(x, edge_index, edge_attr)
return F.log_softmax(x, dim=1)
device = torch.device('cuda', args.device_idx)
args.data_fp = osp.join(osp.dirname(osp.realpath(__file__)), '..', 'data',
args.dataset)
dataset = Planetoid(args.data_fp, args.dataset)
dataset.transform = transform
run(dataset, MoNet(dataset), args.runs, args.epochs, args.lr,
args.weight_decay, args.early_stopping, device)
