def compute_simulations_mt(milp_ce, z3_ce):
vs = 20
step = 0.000001
closed1_a_matrix = np.array([[0, -21052.6316, 0, 0], [42105.2632, -40100.2506, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]],
dtype=float)
closed1_c_vector = np.array([21052.6316 * vs, 0 * vs, 1, 1], dtype=float)
open1_a_matrix = np.array([[0, -21052.6316, 0, 0], [42105.2632, -40100.2506, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]],
dtype=float)
open1_c_vector = np.array([0 * vs, 0 * vs, 1, 1], dtype=float)
milp_simulation_1 = compute_simulation(milp_ce, closed1_a_matrix, closed1_c_vector, step, 0.000022 / step)
init_state_in_open1 = milp_simulation_1[len(milp_simulation_1) - 1]
milp_simulation_2 = compute_simulation(init_state_in_open1, open1_a_matrix, open1_c_vector, step, 0.000029 / step)
z3_simulation_1 = compute_simulation(z3_ce, closed1_a_matrix, closed1_c_vector, step, 0.000022 / step)
init_state_in_open1 = z3_simulation_1[len(z3_simulation_1) - 1]
z3_simulation_2 = compute_simulation(init_state_in_open1, open1_a_matrix, open1_c_vector, step, 0.000029 / step)
with open("simulation", 'w') as f:
f.write('milp_simulation = [')
for point in milp_simulation_1:
f.write('{},{};\n'.format(str(point[0]), str(point[1])))
for point in milp_simulation_2:
f.write('{},{};\n'.format(str(point[0]), str(point[1])))
f.write('];\n')
f.write('z3_simulation = [')
for point in z3_simulation_1:
f.write('{},{};\n'.format(str(point[0]), str(point[1])))
for point in z3_simulation_2:
f.write('{},{};\n'.format(str(point[0]), str(point[1])))
f.write('];\n')
def compute_simulation_mt(longest_ce, deepest_ce):
a_matrix = np.array([[0, -1, 1, 0, 0], [0, -0.02, 0, 1, 0],
[0, 0, 0, 0, 0], [0, -2, 2, -2, 0], [0, 0, 0, 0, 0]])
c_vector = np.array([0, 0, 0, 0, 1], dtype=float)
longest_ce_simulation = compute_simulation(longest_ce, a_matrix, c_vector,
0.2, 100)
deepest_ce_simulation = compute_simulation(deepest_ce, a_matrix, c_vector,
0.2, 100)
with open("simulation", 'w') as f:
f.write('longest_simulation = [')
t = 0.0
for point in longest_ce_simulation:
f.write('{},{};\n'.format(str(point[0]), str(point[1])))
t = t + 0.2
f.write(']')
f.write('\n**************************************\n')
f.write('deepest_simulation = [')
t = 0.0
for point in deepest_ce_simulation:
f.write('{},{};\n'.format(point[0], str(point[1])))
t = t + 0.2
f.write(']')
def compute_simulation_py(longest_ce, deepest_ce):
step = 0.08
max_time = 4.0
loc3_a_matrix = np.array(
[[-2, 0, 0, 0, 0, 0], [0, -1, 0, 0, 0, 0], [5, 0, -5, 0, 0, 0],
[0, 0, 5, -5, 0, 0], [0, 0, 0, 5, -5, 0], [0, 0, 0, 0, 5, -5]],
dtype=float)
loc3_c_vector = np.array([1.4, -0.7, 0, 0, 0, 0], dtype=float)
deepest_simulation = compute_simulation(deepest_ce, loc3_a_matrix,
loc3_c_vector, step,
step * 16 / step)
longest_simulation = compute_simulation(longest_ce, loc3_a_matrix,
loc3_c_vector, step,
step * 16 / step)
sim_t = np.array(deepest_simulation).T
plt.plot(sim_t[1], sim_t[5], 'g-')
sim_t = np.array(longest_simulation).T
plt.plot(sim_t[1], sim_t[5], 'r-')
init_state_in_loc4 = deepest_simulation[len(deepest_simulation) - 1]
loc4_a_matrix = np.array(
[[-2, 0, 0, 0, 0, 0], [0, -1, 0, 0, 0, 0], [5, 0, -5, 0, 0, 0],
[0, 0, 5, -5, 0, 0], [0, 0, 0, 5, -5, 0], [0, 0, 0, 0, 5, -5]],
dtype=float)
loc4_c_vector = np.array([-1.4, 0.7, 0, 0, 0, 0], dtype=float)
deepest_simulation = compute_simulation(init_state_in_loc4, loc4_a_matrix,
loc4_c_vector, step,
step * 5 / step)
sim_t = np.array(deepest_simulation).T
plt.plot(sim_t[1], sim_t[5], 'g-')
init_state_in_loc4 = longest_simulation[len(longest_simulation) - 1]
longest_simulation = compute_simulation(init_state_in_loc4, loc4_a_matrix,
loc4_c_vector, step,
step * 5 / step)
sim_t = np.array(longest_simulation).T
plt.plot(sim_t[1], sim_t[5], 'r-')
loc2_a_matrix = np.array(
[[-2, 0, 0, 0, 0, 0], [0, -1, 0, 0, 0, 0], [5, 0, -5, 0, 0, 0],
[0, 0, 5, -5, 0, 0], [0, 0, 0, 5, -5, 0], [0, 0, 0, 0, 5, -5]],
dtype=float)
loc2_c_vector = np.array([-1.4, 0.7, 0, 0, 0, 0], dtype=float)
init_state_in_loc2 = deepest_simulation[len(deepest_simulation) - 1]
deepest_simulation = compute_simulation(init_state_in_loc2, loc2_a_matrix,
loc2_c_vector, step,
step * 16 / step)
sim_t = np.array(deepest_simulation).T
plt.plot(sim_t[1], sim_t[5], 'g-')
plt.show()
def compute_simulation_mt(milp_ce, z3_ce):
a_matrix = np.array([[-0.1, 1], [-1, -0.1]])
c_vector = np.array([0, 0], dtype=float)
milp_ce_simulation = compute_simulation(milp_ce, a_matrix, c_vector, 0.2,
100)
z3_ce_simulation = compute_simulation(z3_ce, a_matrix, c_vector, 0.2, 100)
with open("simulation", 'w') as f:
f.write('milp_simulation = [')
for point in milp_ce_simulation:
f.write('{},{};\n'.format(str(point[0]), str(point[1])))
f.write(']')
f.write('\n**************************************\n')
f.write('z3_simulation = [')
for point in z3_ce_simulation:
f.write('{},{};\n'.format(point[0], str(point[1])))
f.write(']')
def compute_simulation_py(longest_ce, deepest_ce, robust_ce):
vs = 20
step = 0.000001
closed1_a_matrix = np.array([[0, -21052.6316, 0, 0], [42105.2632, -40100.2506, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]],
dtype=float)
closed1_c_vector = np.array([21052.6316 * vs, 0 * vs, 1, 1], dtype=float)
open1_a_matrix = np.array([[0, -21052.6316, 0, 0], [42105.2632, -40100.2506, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]],
dtype=float)
open1_c_vector = np.array([0 * vs, 0 * vs, 1, 1], dtype=float)
simulation = compute_simulation(longest_ce, closed1_a_matrix, closed1_c_vector, step, 0.000022 / step)
sim_t = np.array(simulation).T
plt.plot(sim_t[1], sim_t[0], 'r-')
init_state_in_open1 = simulation[len(simulation) - 1]
simulation = compute_simulation(init_state_in_open1, open1_a_matrix, open1_c_vector, step, 0.000029 / step)
sim_t = np.array(simulation).T
plt.plot(sim_t[1], sim_t[0], 'r-')
simulation = compute_simulation(deepest_ce, closed1_a_matrix, closed1_c_vector, step, 0.000022 / step)
sim_t = np.array(simulation).T
plt.plot(sim_t[1], sim_t[0], 'g-')
init_state_in_open1 = simulation[len(simulation) - 1]
simulation = compute_simulation(init_state_in_open1, open1_a_matrix, open1_c_vector, step, 0.000029 / step)
sim_t = np.array(simulation).T
plt.plot(sim_t[1], sim_t[0], 'g-')
simulation = compute_simulation(robust_ce, closed1_a_matrix, closed1_c_vector, step, 0.000022 / step)
sim_t = np.array(simulation).T
plt.plot(sim_t[1], sim_t[0], 'b-')
init_state_in_open1 = simulation[len(simulation) - 1]
simulation = compute_simulation(init_state_in_open1, open1_a_matrix, open1_c_vector, step, 0.000029 / step)
sim_t = np.array(simulation).T
plt.plot(sim_t[1], sim_t[0], 'b-')
def compute_simulation_mt(longest_ce, deepest_ce = None):
a_matrix = np.array([[0, -1, 1, 0, 0], [0, 0, 0, 1, 0], [0, 0, 0, 0, 0], [1, -4, 3, -1.2, 0], [0, 0, 0, 0, 0]])
c_vector = np.array([0, 0, 0, -10, 1], dtype=float)
longest_ce_simulation = compute_simulation(longest_ce, a_matrix, c_vector, 0.1, 200)
deepest_ce_simulation = compute_simulation(deepest_ce, a_matrix, c_vector, 0.1, 200)
with open("simulation", 'w') as f:
f.write(' Unsafe longest_simulation = [')
t = 0.0
for point in longest_ce_simulation:
f.write('{},{};\n'.format(str(point[4]), str(point[1])))
t = t + 0.1
f.write('];')
f.write('\n**************************************\n')
f.write('deepest_simulation = [')
t = 0.0
for point in deepest_ce_simulation:
f.write('{},{};\n'.format(point[4], str(point[1])))
t = t + 0.1
f.write('];')
def compute_simulation_mt(smt_ce, milp_ce=None):
a_matrix = np.array([[-0.1, -1, 0], [1, -0.1, 0], [0, 0, -0.15]])
c_vector = np.array([0, 0, 0], dtype=float)
smt_ce_simulation = compute_simulation(smt_ce, a_matrix, c_vector, 0.1,
200)
milp_ce_simulation = compute_simulation(milp_ce, a_matrix, c_vector, 0.1,
200)
with open("simulation", 'w') as f:
f.write(' SMT_simulation = [')
t = 0.0
for point in smt_ce_simulation:
f.write('{},{};\n'.format(str(point[0]), str(point[2])))
t = t + 0.1
f.write('];')
f.write('\n**************************************\n')
f.write('MILP_simulation = [')
t = 0.0
for point in milp_ce_simulation:
f.write('{},{};\n'.format(str(point[0]), str(point[2])))
t = t + 0.1
f.write('];')
def compute_simulation_mt(counter_exs):
a_matrix = np.array([[-0.1, 1], [-1, -0.1]])
c_vector = np.array([1, 0], dtype=float)
with open("simulation", 'w') as f:
for idx in range(len(counter_exs)):
counter_ex = counter_exs[idx]
# each counter_ex can have different ce's for different paths
ce = np.array(counter_ex[0]) # Take the one for the first path
print(ce)
ce_simulation = compute_simulation(ce, [a_matrix], [c_vector],
[15], 0.2)
ce_name = 'simulation' + str(idx) + "["
f.write(ce_name)
for point in ce_simulation:
f.write('{},{};\n'.format(str(point[0]), str(point[1])))
f.write(']')
f.write('\n**************************************\n')
b_matrices = []
c_vectors = []
max_steps = []
step_inputs = []
for idx in range(n_locations):
step_input = ast.literal_eval(lines[l_idx])
step_inputs.append(step_input)
l_idx += 1
a_matrices.append(a_matrix)
b_matrices.append(b_matrix)
c_vector = np.matmul(b_matrix, step_input)
c_vector[dim - 1] = step_size
# print(c_vector)
c_vectors.append(c_vector)
max_steps.append(1)
init_rect = ast.literal_eval(lines[l_idx])
last_pair = (0.0, 0.0)
init_rect.append(last_pair)
print(init_rect)
l_idx += 1
ref_simulation = np.array(compute_simulation(ref_state, a_matrices, c_vectors, max_steps, 1, disc_dyn=True))
print(ref_simulation)
# sim_t = np.array(ref_simulation).T
# plt.plot(sim_t[0], sim_t[1], 'b', linestyle='--')
# plt.show()
init_r = HyperRectangle(init_rect)
pv_object = run_hylaa(settings, init_r, None, ref_simulation, step_inputs, k_matrix, a_matrices, b_matrices)
def compute_simulation_py(robust_ce, longest_ce):
cap_d = 0.4
cap_t = 0.000025
L = 0.00008 # L = 80*10e-6
one_by_L = 12500
one_by_L_by_3 = 4166.67
R = 30
one_by_C = 1000000 # C = 1e-6
one_by_RC = 33333.33
v_in = 100 # u
step = 0.000001
loc1_a_matrix = np.array(
[[0, 0, 0, 0, 0], [0, 0, -one_by_L, 0, 0],
[0, one_by_C, -one_by_RC, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]],
dtype=float)
loc1_c_vector = np.array([one_by_L * v_in, L * v_in, 0, 0, 1], dtype=float)
robust_simulation = compute_simulation(robust_ce, loc1_a_matrix,
loc1_c_vector, step,
step * 11 / step)
sim_t = np.array(robust_simulation).T
plt.plot(sim_t[1], sim_t[2], 'r--', linewidth='2')
init_state_in_loc2 = robust_simulation[len(robust_simulation) - 1]
loc2_a_matrix = np.array(
[[0, 0, 0, 0, 0], [0, 0, -one_by_L, 0, 0],
[0, one_by_C, -one_by_RC, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]],
dtype=float)
loc2_c_vector = np.array([-one_by_L_by_3, 0, 0, 0, 1], dtype=float)
robust_simulation = compute_simulation(init_state_in_loc2, loc2_a_matrix,
loc2_c_vector, step,
step * 5 / step)
sim_t = np.array(robust_simulation).T
plt.plot(sim_t[1], sim_t[2], 'r--', linewidth='2')
init_state_in_loc5 = robust_simulation[len(robust_simulation) - 1]
loc5_a_matrix = np.array(
[[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, -one_by_RC, 0, 0],
[0, 0, 0, 0, 0], [0, 0, 0, 0, 0]],
dtype=float)
loc5_c_vector = np.array([-one_by_L_by_3, 0, 0, 0, 1], dtype=float)
robust_simulation = compute_simulation(init_state_in_loc5, loc5_a_matrix,
loc5_c_vector, step,
step * 2 / step)
sim_t = np.array(robust_simulation).T
plt.plot(sim_t[1], sim_t[2], 'r--', linewidth='2')
longest_simulation = compute_simulation(longest_ce, loc1_a_matrix,
loc1_c_vector, step,
step * 11 / step)
sim_t = np.array(longest_simulation).T
plt.plot(sim_t[1], sim_t[2], 'b--', linewidth='2')
init_state_in_loc2 = longest_simulation[len(longest_simulation) - 1]
longest_simulation = compute_simulation(init_state_in_loc2, loc2_a_matrix,
loc2_c_vector, step,
step * 5 / step)
sim_t = np.array(longest_simulation).T
plt.plot(sim_t[1], sim_t[2], 'b--', linewidth='2')
init_state_in_loc5 = longest_simulation[len(longest_simulation) - 1]
longest_simulation = compute_simulation(init_state_in_loc5, loc5_a_matrix,
loc5_c_vector, step,
step * 2 / step)
sim_t = np.array(longest_simulation).T
plt.plot(sim_t[1], sim_t[2], 'b--', linewidth='2')
plt.show()
def compute_simulation_py(longest_ce, deepest_ce, robust_ce):
step = 0.02
a_matrix = np.array([[0.0, 1.0], [-100.0, -4.0]], dtype=float)
c_vector = np.array([0.0, -9.81], dtype=float)
deepest_simulation = compute_simulation(deepest_ce, a_matrix, c_vector,
step, 0.2 / step)
longest_simulation = compute_simulation(longest_ce, a_matrix, c_vector,
step, 0.2 / step)
robust_simulation = compute_simulation(robust_ce, a_matrix, c_vector, step,
0.2 / step)
sim_t = np.array(deepest_simulation).T
deepest_ce_handle = plt.plot(sim_t[0],
sim_t[1],
'g',
label='Deepest Counterexample=[-0.99, 0.15]',
linestyle='--',
linewidth='2')
sim_t = np.array(longest_simulation).T
longest_ce_handle = plt.plot(sim_t[0],
sim_t[1],
'r',
label='Longest Counterexample=[-1.05, -0.15]',
linestyle='-.',
linewidth='2')
sim_t = np.array(robust_simulation).T
robust_ce_handle = plt.plot(sim_t[0],
sim_t[1],
'b',
label='Robust Counterexample=[-1.026, 0.0]',
linestyle='--',
linewidth='2')
init_state_in_freefall = deepest_simulation[len(deepest_simulation) - 1]
a_matrix = np.array([[0.0, 1.0], [0.0, 0.0]], dtype=float)
c_vector = np.array([0.0, -9.81], dtype=float)
deepest_simulation = compute_simulation(init_state_in_freefall, a_matrix,
c_vector, step, 0.2 / step)
sim_t = np.array(deepest_simulation).T
plt.plot(sim_t[0], sim_t[1], 'g', linestyle='--')
init_state_in_freefall = longest_simulation[len(longest_simulation) - 1]
a_matrix = np.array([[0.0, 1.0], [0.0, 0.0]], dtype=float)
c_vector = np.array([0.0, -9.81], dtype=float)
longest_simulation = compute_simulation(init_state_in_freefall, a_matrix,
c_vector, step, 0.2 / step)
sim_t = np.array(longest_simulation).T
plt.plot(sim_t[0], sim_t[1], 'r', linestyle='-.')
init_state_in_freefall = robust_simulation[len(robust_simulation) - 1]
a_matrix = np.array([[0.0, 1.0], [0.0, 0.0]], dtype=float)
c_vector = np.array([0.0, -9.81], dtype=float)
robust_simulation = compute_simulation(init_state_in_freefall, a_matrix,
c_vector, step, 0.2 / step)
sim_t = np.array(robust_simulation).T
plt.plot(sim_t[0], sim_t[1], 'b', linestyle='--')
usafe_vertices = np.array([[-0.5, 5], [0.5, 5], [0.5, 6.2], [-0.5, 6.2],
[-0.5, 5]])
usafe_region_handle = plt.plot(
usafe_vertices.T[0],
usafe_vertices.T[1],
label='Unsafe Region=([-0.5,0.5],[5.0,6.2])',
linestyle='--',
linewidth='3',
color='crimson')
plt.legend(handles=[
longest_ce_handle[0], deepest_ce_handle[0], robust_ce_handle[0],
usafe_region_handle[0]
])
plt.show()
