def test_1(filename, rnd=False): # first solution for a given scenario
drone, targets = pmu.load_scenario(filename)
if rnd:
_p = rng.permutation(len(targets))
targets = np.array(targets)[_p]
pm.intercept_sequence(drone, targets)
plot(plt.gca(), drone, targets)
def test1(filename='../../data/scenario_60_6.yaml'):
scen = pmu.Scenario(filename=filename)
s = pm_cpp_ext.Solver()
s.init(scen.drone, scen.targets)
seq = [scen.targets[17]]
#nb_t = len(scen.targets)
#seq = np.random.permutation(scen.targets).tolist()
_seq = [_s.name for _s in seq]
print(_seq)
s.run_sequence(_seq)
c_psis = s.debug()
#print(psis)
# if 0:
# psi, dt = pm.intercept_1(scen.drone, scen.targets[0])
# print(f'intercept seq py {psi}, {dt}')
# scen.drone.add_leg(dt, psi)
# psi, dt = pm.intercept_1(scen.drone, scen.targets[1])
# print(f'intercept seq py {psi}, {dt}')
# scen.drone.add_leg(dt, psi)
# else:
pm.intercept_sequence(scen.drone, scen.targets[:nb_t])
#print(f'dur: {scen.drone.flight_duration()}')
#print(f'{scen.drone.psis}')
#passed = np.allclose(psis, scen.drone.psis, rtol=1e-05, atol=1e-08)
passed = np.allclose(c_psis, scen.drone.psis, rtol=1e-05, atol=1e-06)
if not passed:
print(f'{s.debug()} \n{scen.drone.psis}')
#pdb.set_trace()
print(f'Test passed: {passed}')
def plot_all_sols(drone, targets, _nc=3):
perms = set(permutations(targets))
fig = plt.figure(tight_layout=True, figsize=[12.8, 9.6])
fig.canvas.set_window_title('Interceptions')
_nc = min(_nc, len(perms))
_nr, _r = np.divmod(len(perms), _nc)
if _r > 0: _nr += 1
axes = fig.subplots(_nr, _nc, sharex=True) #, sharey=True)
print(f'{len(perms)} permutation')
for targets, ax in zip(perms, axes.flatten()):
pm.intercept_sequence(drone, targets)
plot(ax, drone, targets)
drone.clear_traj()
def main():
drone, targets = pm.load_scenario('./scenario_6.yaml')
pm.intercept_sequence(drone, targets) #[::-1])
print(
f'duration: {drone.ts[-1]:.2f}s heading: {np.rad2deg(drone.psis[-1]):.1f} deg'
)
anim = animate(plt.gcf(),
plt.gca(),
drone,
targets,
t0=0.,
t1=drone.ts[-1],
dt=0.1,
xlim=(-100, 200),
ylim=(-150, 150))
#save_animation(anim, '/tmp/anim.mp4', dt=0.1)
# ffmpeg -i /tmp/anim.mp4 -r 15 ../docs/images/animation_1.gif
plt.show()
def test_6(): # plot exhaustive search time vs number of targets
ntargs, dts = [2, 3, 4, 5, 6, 7, 8], []
for ntarg in ntargs:
drone, targets = pm.make_scenario(ntarg=ntarg, dp0=(0, 0), dv=15)
perms = set(permutations(targets))
_start = time.perf_counter()
for targets in perms:
pm.intercept_sequence(deepcopy(drone), targets)
_end = time.perf_counter()
dts.append(_end - _start)
print(f'{ntarg} targets -> {dts[-1]:.1f} s')
plt.plot(ntargs, dts, '--o')
_decorate(plt.gca(),
_l=[''],
_t='Search time vs number of targets',
_yl='time in s',
_xl='number of targets')
plt.savefig('ex_search_time_vs_size.png')
def test3(filename='../../data/scen_120/9.yaml',
ntest=1000): # scen_7820/9.yaml
scen = pmu.Scenario(filename=filename)
s = pm_cpp_ext.Solver(scen.drone, scen.targets)
seq = [_s.name - 1 for _s in scen.targets]
#pdb.set_trace()
_start1 = time.perf_counter()
for i in range(ntest):
s.run_sequence(seq)
_end1 = time.perf_counter()
_dt1 = _end1 - _start1
print(f'{ntest} evaluations in C took {_dt1:.3f} s')
_start2 = time.perf_counter()
for i in range(ntest):
pm.intercept_sequence(scen.drone, scen.targets)
scen.drone.clear_traj()
_end2 = time.perf_counter()
_dt2 = _end2 - _start2
print(f'{ntest} evaluations in Python took {_dt2:.3f} s')
print(f'improvement {_dt2/_dt1:.1f}')
def test_5(filename): # compute all solutions, keeps worst and best
#drone, targets = pmu.load_scenario(filename)
drone, targets = pmu.make_random_scenario(ntarg=8, dp0=(0, 0), dv=15)
perms = set(permutations(targets))
durations = []
best_dur, best_targets, best_drone = float('inf'), None, None
worst_dur, worst_targets, worst_drone = 0., None, None
for targets in perms:
_drone = deepcopy(drone)
dur = pm.intercept_sequence(_drone, targets)
durations.append(dur)
if dur < best_dur:
best_dur, best_targets, best_drone = dur, targets, _drone
if dur > worst_dur:
worst_dur, worst_targets, worst_drone = dur, targets, _drone
#best_id = np.argmin(durations)
#print(best_id, durations[best_id])
plot(plt.gca(), best_drone, best_targets)
plt.figure()
plot(plt.gca(), worst_drone, worst_targets)
#plt.hist(durations)
plt.show()
def intercept_sequences_copy(drones, sequences):
_drones = [copy.deepcopy(_d) for _d in drones]
_durs = [pm.intercept_sequence(_d,_s) for _d,_s in zip(_drones, sequences)]
return _drones, _durs