def show(pathname):
print(pathname)
if len(pathname)==0 or pathname=="/visuals/" or len(pathname)<30 and "%20" not in pathname:
return dcc.Location(id="home",href="/404")
time.sleep(2)
return show_graph(pathname)
def compare_trajectory():
n = None
set_x = []
set_y = []
while True:
try:
n = int(input("How many trajectories? "))
if (type(n) == int) and (n > 0):
break
print("Enter a positive integer number")
except Exception as e:
print(e)
for _ in range(n):
while True:
try:
ivelo = float(input("Enter initial velocity (m/s): "))
if ivelo > 0:
break
print("Initial velocity cannot be negative")
except Exception as e:
print(e)
while True:
try:
angle = float(input("Enter angle of trajectory (deg): "))
if (angle > 0) and (angle < 180):
break
print("Enter a positive number")
except Exception as e:
print(e)
print(f"${n, ivelo, angle}")
t_x, t_y, t_ax = get_coords_trajectory(ivelo, angle)
set_x.extend(t_x)
set_x = list(set(set_x))
set_y.extend(t_y)
set_y = list(set(set_y))
t_ax = [min(set_x), max(set_x), min(set_y), max(set_y)]
graph.draw_graph(t_x, t_y, t_ax)
graph.show_graph()
def test3():
tree = MyBPlusTree()
tree.add_key(1)
tree.add_key(6)
tree.add_key(3)
tree.add_key(4)
# tree.delete_key(3)
tree.add_key(9)
tree.add_key(7)
tree.add_key(11)
tree.add_key(12)
tree.add_key(13)
tree.delete_key(7)
tree.add_key(14)
print(tree.find_key(13))
tree.add_key(15)
tree.add_key(17)
tree.add_key(19)
tree.add_key(21)
tree.add_key(23)
tree.add_key(25)
print(tree.find_key(23))
graph.show_graph(tree)
help='input output filetypes separated by space')
group.add_argument('--show', '-s', action="store_true", help='show the graph')
parser.add_argument('--dir',
'-d',
default=str(Path.cwd()) + "/out",
help='input directory for output files')
parser.add_argument('--name', '-n', help='input filename for the output file')
args = parser.parse_args()
assets = args.asset
filetypes = args.output
# TODO: if filename exists, auto-increment
try:
current_fig = graph.draw_graph(assets)
except (data.AssetError, data.RequestError, graph.StyleError):
pass
else:
if filetypes:
if not args.name:
args.name = '_'.join(assets) + datetime.date.today().strftime(
"%y%m%d")
print("Program running...Press ^C to exit.")
# generate output path with dir/filename
path = Path(args.dir) / args.name
graph.get_exports(current_fig, filetypes, path)
print("Export succeeded.")
else:
graph.show_graph()
def solve_graph_greedy(graph,
task,
depth,
runner,
x0=None,
optimizer='COBYLA',
max_iter=1000,
var_mask=None):
'''solve a problem defined by a graph.'''
num_bit = graph.vcount()
N = 2**num_bit
if task == 'max-cut':
clause_list = get_max_cut_clauses(graph)
loss_func = lambda z: max_cut_loss(z, clause_list)
valid_mask = None
elif task == 'vertex-cover':
valid_mask = [is_vertex_cover(graph, i) for i in range(N)]
loss_func = lambda z: vertex_cover_loss(z, graph, valid_mask)
if runner == 'projectq':
print(
'warning, solving vertex_cover problem using projectq can not use `walk_mask`!'
)
clause_list = get_vertex_cover_clauses(graph)
else:
raise
loss_table = np.array([loss_func(z) for z in range(N)])
if runner == 'scipy':
cc = circuit.build_qaoa_circuit(loss_table,
num_bit,
depth,
v0=None,
walk_mask=valid_mask)
elif runner == 'projectq':
cc = qcircuit.build_qaoa_circuit(clause_list, num_bit, depth)
else:
raise
# obtain and analyse results
if x0 is None: x0 = np.zeros(cc.num_param)
var_mask = np.zeros(cc.num_param, dtype='bool')
for i in range(cc.depth):
var_mask[i] = True
if i > 0:
var_mask[i + cc.depth - 1] = True
x = x0[var_mask]
print('i=%d, mask=%s' % (i, var_mask))
qaoa_loss, log = get_qaoa_loss(
cc, loss_table, var_mask,
x0) # the expectation value of loss function
if optimizer == 'CMA-ES':
import cma
es = cma.CMAEvolutionStrategy(x,
0.1 * np.pi,
inopts={
'seed':
np.random.randint(999999),
})
es.optimize(qaoa_loss, iterations=max_iter, verb_disp=1)
best_x = es.best.x
elif optimizer == 'COBYLA':
best_x = minimize(qaoa_loss,
x0=x,
method='COBYLA',
options={
'maxiter': max_iter
}).x
elif optimizer == 'BRUTE':
best_x = brute(qaoa_loss,
ranges=[(0, np.pi)] + [(0, 2 * np.pi)] * (i > 0),
Ns=10)
else:
raise
x0[var_mask] = best_x
plt.ion()
plt.plot(log['loss'])
pdb.set_trace()
ans = qaoa_result_digest(x0, cc, loss_table)
show_graph(graph, ans[2])
def generate_minimum_network():
initial_city = input('Digita a cidade inicial: ')
show_graph(graph, 'initial_graph.png')
new_graph = minimum_spanning_tree(graph, initial_city)
show_graph(new_graph, 'minimum_spanning_tree.png')
main_menu()
