def run_simulation(self, simulation_input):
sim = self.init_rebound_simulation(simulation_input)
feature_classifier_model = FeatureClassifier()
deep_regressor_model = DeepRegressor()
stability_probability = feature_classifier_model.predict_stable(sim)
median, lower, upper = deep_regressor_model.predict_instability_time(sim, samples=10000)
return {"star_mass": simulation_input.star_mass,
"periods": ",".join([str(planet_period) for planet_period in simulation_input.planet_periods]),
"masses": ",".join([str(mass_value) for mass_value in simulation_input.mass_arr]),
"inclinations": ",".join([str(ecc_value) for ecc_value in simulation_input.inc_arr]),
"eccentricities": ",".join([str(ecc_value) for ecc_value in simulation_input.ecc_arr]),
"arg_periastron": ",".join([str(ecc_value) for ecc_value in simulation_input.omega_arr]),
"stability_probability": stability_probability, "median_expected_instability_time": median}
def run(self, planet_params):
sim = rebound.Simulation()
sim.integrator = "whfast"
sim.ri_whfast.safe_mode = 0
sim.dt = 1e-2
sim.add(m=1.0)
for planet_param in planet_params:
sim.add(m=self.mass_from_radius(planet_param.r) * 0.000003003 /
self.star_mass,
P=planet_param.P,
e=planet_param.e,
omega=planet_param.omega)
#sim.status()
sim.move_to_com()
model = FeatureClassifier()
print("SPOCK=" + str(model.predict_stable(sim)))
break
unstable = 'n' #### initialize assuming stability, until shown otherwise.
try:
running_period_list = np.load(projectdir+'/running_list_of_derived_TTV_periods.npy').tolist()
except:
running_period_list = []
### create a simulations instance.
sim = rebound.Simulation()
if include_J2 == 'y':
rebx = reboundx.Extras(sim)
gh = rebx.load_force('gravitational_harmonics')
rebx.add_force(gh)
stability_model = FeatureClassifier()
### put these in familiar units
sim.G = G.value
sim.units = ('s', 'm', 'kg') ### mks
#### now let's add Jupiter, Io, Europa, Ganymede, and Callisto!
### Jupiter
if make_imaginary_system == 'n':
### MAKE JUPITER!
sim.add(m=M_jup.value, hash='Jupiter')
system_dict = {}
moon_dict = {} ### make a dictionary
def setUp(self):
self.model = FeatureClassifier()
class TestClassifier(unittest.TestCase):
def setUp(self):
self.model = FeatureClassifier()
def test_list(self):
stable_target = [0, 0, 0, 0.7]
stable = self.model.predict_stable([hyperbolicsim(), escapesim(), unstablesim(), longstablesim()])
self.assertEqual(stable[0], 0)
self.assertEqual(stable[1], 0)
self.assertEqual(stable[2], 0)
self.assertGreater(stable[3], 0.7)
def test_sim_unchanged(self):
sim = rebound.Simulation()
sim.add(m=1.)
sim.add(m=1.e-5, P=1.)
sim.add(m=1.e-5, P=2.)
sim.add(m=1.e-5, P=3.)
sim.integrate(1.2)
x0 = sim.particles[1].x
p1 = self.model.predict_stable(sim)
self.assertEqual(sim.particles[1].x, x0)
def test_repeat(self):
sim = rebound.Simulation()
sim.add(m=1.)
sim.add(m=1.e-5, P=1.)
sim.add(m=1.e-5, P=2.)
sim.add(m=1.e-5, P=3.)
p1 = self.model.predict_stable(sim)
p2 = self.model.predict_stable(sim)
self.assertEqual(p1, p2)
def test_same_trajectory(self):
sim = longstablesim()
init_sim_parameters(sim)
_, _ = get_tseries(sim, (1e4, 80, [[1,2,3]]))
x1 = sim.particles[1].x
sim = longstablesim()
nbody = NbodyRegressor()
nbody.predict_stable(sim, tmax=1e4, archive_filename='temp.bin', archive_interval=1.e4)
sa = rebound.SimulationArchive('temp.bin')
sim = sa[-1]
x2 = sim.particles[1].x
self.assertAlmostEqual(x1, x2, delta=1.e-5)
# when chaotic realization matters, probs will vary more (eg t_inst=2e4)
def test_galilean_transformation(self):
sim = longstablesim()
sim.move_to_com()
p_com = self.model.predict_stable(sim)
sim = longstablesim()
for p in sim.particles:
p.vx += 1000
p_moving = self.model.predict_stable(sim)
self.assertAlmostEqual(p_com, p_moving, delta=1.e-2)
def test_rescale_distances(self):
sim = longstablesim()
p0 = self.model.predict_stable(sim)
sim = longstablesim()
sim = rescale(sim, dscale=1e10, tscale=1, mscale=1)
p1 = self.model.predict_stable(sim)
self.assertAlmostEqual(p0, p1, delta=1.e-2)
def test_rescale_times(self):
sim = longstablesim()
p0 = self.model.predict_stable(sim)
sim = longstablesim()
sim = rescale(sim, dscale=1, tscale=1e10, mscale=1)
p1 = self.model.predict_stable(sim)
self.assertAlmostEqual(p0, p1, delta=1.e-1)
def test_rescale_masses(self):
sim = longstablesim()
p0 = self.model.predict_stable(sim)
sim = longstablesim()
sim = rescale(sim, dscale=1, tscale=1, mscale=1e10)
p1 = self.model.predict_stable(sim)
self.assertAlmostEqual(p0, p1, delta=1.e-2)
def test_hyperbolic(self):
sim = hyperbolicsim()
self.assertEqual(self.model.predict_stable(sim), 0)
def test_escape(self):
sim = escapesim()
self.assertEqual(self.model.predict_stable(sim), 0)
def test_unstable_in_short_integration(self):
sim = unstablesim()
self.assertEqual(self.model.predict_stable(sim), 0)
def test_solarsystem(self):
sim = solarsystemsim()
self.assertGreater(self.model.predict_stable(sim), 0.7)
def test_stable(self):
sim = longstablesim()
self.assertGreater(self.model.predict_stable(sim), 0.7)