def spinning_period_sim():
samples = 200
fine_res = 150
fineT = 2.5 / 12.
maxT = 18. / 12.
data_out = open('./%d.txt' % time.time(), 'w')
start = time.time()
energies = []
for frac in range(1, samples):
if frac <= fine_res:
T_0 = (fineT / fine_res) * frac
else:
T_0 = fineT + (frac - fine_res) * (maxT - fineT) / (samples -
fine_res)
energies.append(T_0)
# T_0 = .5
print(T_0)
Pd = (T_0 / 10.)**.5
init = numpy.array([0.0, 0.0, 0.0, 0.0, Pd, 0., 0.0])
sim_path = utils.RK4_adapt(reduced_double_dipole,
init,
.05,
max_steps=10**6,
precision=10**-10)
S_0 = sim_path[-1]
S_0[0] = 0.0
# S_0 = init
# print(S_0)
return_times = utils.return_times_finder(reduced_double_dipole,
S_0,
max_steps=10**6,
precision=10**-10,
max_time=75)
# print(return_times)
# print([val[0]/return_times[0][0] for val in return_times])
period = utils.fit_slope_and_chisqr(return_times)
print(period)
S_0 = list(S_0)
S_0.append(period[0])
S_0.append(period[1])
data_out.write(('%f ' * 8) % tuple(S_0[1:]))
data_out.write('\n')
print(' ')
data_out.close()
# periods = utils.read_column(S_0, -2)
# matplotlib.plot(energies, periods)
# pyplot.show()
print('took %d seconds' %
(time.time() - start)) # print(len(sim_path), T_0)
def random_point_period():
state0p, state0m = utils.reduced_state_gen()
state0p = [
0.0, 0.0, 0.5166312725363087, 0.33848195776981216, 0.0,
0.10794186242929231, 0.10008255831561577
]
states = [state0p, state0m]
for state0_ind in range(1):
start = numpy.array(states[state0_ind])
print(start[-2:])
return_times = utils.return_times_finder(reduced_double_dipole,
start,
max_steps=10**6,
precision=10**-7,
max_time=2 * 2.8)
print(return_times)
print([val / return_times[0] for val in return_times])
def test_return_times_finder(self):
x0 = random.random()
p0 = (1. - x0**2)**.5
stateI = numpy.array([0., x0, p0])
return_times = utils.return_times_finder(base_SHO,
stateI,
precision=10**-10,
max_time=100.0,
max_steps=10**6)
print(return_times)
print([val[0] / (2 * numpy.pi) for val in return_times])
print(len(return_times))
for i in range(len(return_times)):
self.assertAlmostEqual((i + 1) * 2 * numpy.pi,
return_times[i][0],
delta=return_times[i][1])
self.assertTrue(len(return_times) > 10.0 / 2.1 * numpy.pi)
def orbital_period_sim():
samples = 100
# coarse_res = 50
# coarseT = 0./12.
maxT = 1. / 3.
data_out = open('./%d.txt' % time.time(), 'w')
start = time.time()
for frac in range(1, samples):
# if frac <=coarse_res:
# T_0 = (coarseT/coarse_res)*frac
# else:
# T_0 = coarseT + (frac-coarse_res)*(maxT-coarseT)/(samples-coarse_res)
T_0 = (maxT / samples) * frac
# T_0 = .5
print(T_0)
P_tht = (2. * T_0 / 7.)**.5
init = numpy.array([0.0, 0.0, 0.0, 0.0, 0.0, -P_tht / 2., P_tht])
sim_path = utils.RK4_adapt(reduced_double_dipole,
init,
.01,
max_steps=10**6,
precision=10**-10)
S_0 = sim_path[-1]
S_0[0] = 0.0
# S_0 = init
# print(S_0)
return_times = utils.return_times_finder(reduced_double_dipole,
S_0,
max_steps=10**6,
precision=10**-9,
max_time=75)
# print(return_times)
# print([val[0]/return_times[0][0] for val in return_times])
period = utils.fit_slope_and_chisqr(return_times)
print(period)
S_0 = list(S_0)
S_0.append(period[0])
S_0.append(period[1])
data_out.write(('%f ' * 8) % tuple(S_0[1:]))
data_out.write('\n')
print(' ')
data_out.close()
print('took %d seconds' %
(time.time() - start)) # print(len(sim_path), T_0)
def spinning_period_sim():
samples = 150
maxT = 2. / 12.
data_out = open('./%d.txt' % time.time(), 'w')
start = time.time()
for frac in range(1, samples):
T_0 = (maxT / samples) * frac
# T_0 = .5
print(T_0)
Pd = (T_0 / 10.)**.5
init = numpy.array([0.0, 0.0, 0.0, 0.0, Pd, 0., 0.0])
sim_path = utils.RK4_adapt(reduced_double_dipole,
init,
.05,
max_steps=10**6,
precision=10**-10)
S_0 = sim_path[-1]
S_0[0] = 0.0
# S_0 = init
# print(S_0)
return_times = utils.return_times_finder(reduced_double_dipole,
S_0,
max_steps=10**6,
precision=10**-10,
max_time=75)
# print(return_times)
# print([val[0]/return_times[0][0] for val in return_times])
period = utils.fit_slope_and_chisqr(return_times)
print(period)
S_0 = list(S_0)
S_0.append(period[0])
S_0.append(period[1])
data_out.write(('%f ' * 8) % tuple(S_0[1:]))
data_out.write('\n')
print(' ')
data_out.close()
print('took %d seconds' %
(time.time() - start)) # print(len(sim_path), T_0)