def make_lc(evtfile, bkgevtfile, epochfile, dt):
epoch_file = np.loadtxt(epochfile)
evt_file = np.loadtxt(evtfile)
bkgevt_file = np.loadtxt(bkgevtfile)
tstart = epoch_file[:, 0]
tstop = epoch_file[:, 1]
ID = epoch_file[:, 2]
exptime = epoch_file[:, 3]
T_tot = tstop[-1] - tstart[0]
cts_rate = len(evt_file) / (2 *
np.sum(exptime)) * dt # 实际的cts-rate应为这个的2倍
num_bins = int(T_tot / dt)
sim = simulator.Simulator(N=num_bins + 1, mean=cts_rate, dt=dt)
w = np.arange(1 / T_tot, 0.5 / dt, 1 / (T_tot))
spectrum = bending_po(
w, [2.3e-3, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(
w, [4.01e-4, 4.01e-4 / 16, 200, 2])
lc = sim.simulate(spectrum)
# lc=sim.simulate(pow)
lc.time = lc.time + tstart[0]
# lc.gti=[[lc.time[0],lc.time[-1]]]
lc.counts += cts_rate
lc.counts[np.where(lc.counts < 0)] = 0
return lc
def test_compare_composite(self):
"""
Compare the PSD of a light curve simulated using a composite model
(using SmoothBrokenPowerLaw plus GeneralizedLorentz1D)
with the actual model
"""
N = 50000
dt = 0.01
m = 30000.
self.simulator = simulator.Simulator(N=N, mean=m, dt=dt)
smoothbknpo = models.SmoothBrokenPowerLaw(norm=1.,
gamma_low=1.,
gamma_high=2.,
break_freq=1.)
lorentzian = models.GeneralizedLorentz1D(x_0=10,
fwhm=1.,
value=10.,
power_coeff=2.)
myModel = smoothbknpo + lorentzian
lc = [self.simulator.simulate(myModel) for i in range(1, 50)]
simulated = self.simulator.powerspectrum(lc, lc[0].tseg)
w = np.fft.rfftfreq(N, d=dt)[1:]
actual = myModel(w)[:-1]
actual_prob = actual / float(sum(actual))
simulated_prob = simulated / float(sum(simulated))
assert np.all(
np.abs(actual_prob - simulated_prob) < 3 * np.sqrt(actual_prob))
def test_compare_smoothbknpo(self):
"""
Compare simulated smooth broken power law spectrum with original
spectrum.
"""
N, red_noise, dt = 1024, 10, 1
self.simulator = simulator.Simulator(N=N,
dt=dt,
mean=0.1,
rms=0.7,
red_noise=red_noise)
lc = [
self.simulator.simulate('smoothbknpo', [0.6, 0.2, 0.6, 0.5])
for i in range(1, 30)
]
simulated = self.simulator.powerspectrum(lc, lc[0].tseg)
w = np.fft.rfftfreq(N, d=dt)[1:]
actual = models.smoothbknpo(w, [0.6, 0.2, 0.6, 0.5])[:-1]
actual_prob = actual / float(sum(actual))
simulated_prob = simulated / float(sum(simulated))
assert np.all(
np.abs(actual_prob - simulated_prob) < 3 * np.sqrt(actual_prob))
def test_compare_lorentzian(self):
"""
Compare simulated lorentzian spectrum with original spectrum.
"""
N, red_noise, dt = 1024, 10, 1
self.simulator = simulator.Simulator(N=N,
dt=dt,
mean=0.1,
rms=0.4,
red_noise=red_noise)
lc = [
self.simulator.simulate('generalized_lorentzian',
[0.3, 0.9, 0.6, 0.5])
for i in range(1, 30)
]
simulated = self.simulator.powerspectrum(lc, lc[0].tseg)
w = np.fft.rfftfreq(N, d=dt)[1:]
actual = models.generalized_lorentzian(w, [0.3, 0.9, 0.6, 0.5])[:-1]
actual_prob = actual / float(sum(actual))
simulated_prob = simulated / float(sum(simulated))
assert np.all(
np.abs(actual_prob - simulated_prob) < 3 * np.sqrt(actual_prob))
def test_simulate_with_tstart(self):
"""
Simulate with a random seed value.
"""
tstart = 10.0
self.simulator = simulator.Simulator(N=1024, tstart=tstart)
assert self.simulator.time[0] == tstart
def sim_bunch_lc_evt(CR, dt, period, epoch_file, outpath, num_trials=100):
lenbin = dt
# epoch_89 = '/Users/baotong/Desktop/CDFS/txt_all_obs_0.5_8_ep3/epoch_src_89.txt'
w = make_freq_range(dt=lenbin, epoch_file=epoch_file)
qpo_f = 1. / period
(TSTART, TSTOP, OBSID, exptime) = epoch_file
if type(TSTART) == type(1.2):
print('Single exposure')
TSTART = [TSTART]
TSTOP = [TSTOP]
OBSID = [OBSID]
exptime = [exptime]
with open(
outpath + 'CR_{0}_P_{1}_REJ1034_simpleway.txt'.format(
"%.0e" % CR, str(int(period))), 'a+') as f:
k_trial = 0
while k_trial < num_trials:
ev_all = EventList()
# lc = make_lc_from_psd(psd=psd_model, cts_rate=CR / 2 * lenbin, dt=lenbin, epoch_file=epoch_file)
print('trial' + ': ' + str(k_trial))
# lc_evt = Lightcurve(time=lc.time, counts=lc.counts, dt=lc.dt, gti=lc.gti)
# lc_evt.counts = np.random.poisson(lc_evt.counts)
T_tot = TSTOP[-1] - TSTART[0]
for i in range(len(exptime)):
cts_rate = 0.5 * CR * lenbin # 实际的cts-rate应为这个的2倍
num_bins = int(exptime[i] / dt)
sim = simulator.Simulator(N=num_bins, mean=cts_rate, dt=lenbin)
w = np.arange(1 / exptime[i], 0.5 / lenbin, 1 / exptime[i])
psd_model = build_psd(x=w,
p=[2.3e-3, 3.4, 0., 4.3e-4],
x_2=w,
p_2=[qpo_f, qpo_f / 16, 100, 2],
type='bendp+lorentz')
# psd_model = build_psd(x=w, p=[2.3e-3, 3.4, 0., 4.3e-4],
# type='bendp')
spectrum = psd_model
lc_cut = sim.simulate(spectrum)
lc_cut.counts += cts_rate
lc_cut.counts[np.where(lc_cut.counts < 0)] = 0
lc_cut.counts = np.random.poisson(lc_cut.counts)
# print(np.sum(lc_cut.counts))
ev = EventList()
ev.time = func.sim_evtlist(lc_cut) + TSTART[i]
ev_all = ev_all.join(ev)
lc_long = ev_all.to_lc(dt=dt,
tstart=ev_all.time[0] - 0.5 * dt,
tseg=ev_all.time[-1] - ev_all.time[0])
print('counts={0}'.format(np.sum(lc_long.counts)))
T_exp = lc_long.time[-1] - lc_long.time[0]
freq = np.arange(1 / T_exp, 0.5 / lenbin, 1 / (5 * T_exp))
freq = freq[np.where(freq > 1 / 20000.)]
# print(T_tot)
# print(T_exp)
temp = func.get_LS(lc_long.time, lc_long.counts, freq=freq)
f.writelines((str(temp[0]) + ' ' + str(temp[1]) +
' ' + str(temp[2]) + ' ' + '\n'))
k_trial += 1
f.close()
def test_io_with_unsupported_format(self):
sim = simulator.Simulator(N=1024)
with pytest.raises(KeyError):
sim.write('sim.hdf5', format_='hdf5')
with pytest.raises(KeyError):
sim.write('sim.pickle', format_='pickle')
sim.read('sim.pickle', format_='hdf5')
os.remove('sim.pickle')
def make_lc_from_psd(psd, cts_rate, dt, epoch_file, frms=1):
(TSTART, TSTOP, OBSID, exptime) = epoch_file
T_tot = TSTOP[-1] - TSTART[0]
num_bins = int(T_tot / dt)
sim = simulator.Simulator(N=num_bins + 1, mean=cts_rate, dt=dt, rms=frms)
lc = sim.simulate(psd)
lc.time = lc.time + TSTART[0]
lc.counts[np.where(lc.counts < 0)] = 0
lc.gti = [[lc.time[0], lc.time[-1]]]
return lc
def get_lc_onesource_fixpds(k,src_index,num_trials=2):
k_trial =0
FP = [];
period = [];
cts_num=[];
peakP=[];
power_P=[]
path = '/Users/baotong/Desktop/CDFS/txt_all_obs_0.5_8_ep{0}/'.format(k)
epoch_file = np.loadtxt(path + 'CDFS_epoch_ep{0}.txt'.format(k))
tstart = epoch_file[:, 0];tstop = epoch_file[:, 1]
ID=epoch_file[:,2];exptime = epoch_file[:, 3]
evt_file = np.loadtxt(path + '{0}.txt'.format(src_index))
bkgevt_file = np.loadtxt(path + '{0}_bkg.txt'.format(src_index))
for i in range(len(ID)):
index = len(np.where(evt_file[:,2] == ID[i])[0])
index_b=len(np.where(bkgevt_file[:,2] == ID[i])[0])
cts_num.append(index-index_b/12.)
dt = 100
T_exp = 11000154.981141508
freq=np.arange(1/T_exp,0.5/dt,1/(5*T_exp))
freq=freq[np.where(freq > 1 / 20000.)]
if os.path.exists(path+'/simulation/{0}_LS_simP_fixpds.csv'.format(src_index)):
print('caution! file exists')
return None
with open(path + '/simulation/{0}_LS_simP_fixpds.csv'.format(src_index), 'a+') as csvfile:
header = freq
header = header.astype('str')
writer = csv.writer(csvfile)
for i in range(len(exptime)):
cts_rate = cts_num[i] / (2 * exptime[i]) * dt # 实际的cts-rate应为这个的2倍
num_bins = int(exptime[i] / dt)
sim = simulator.Simulator(N=num_bins, mean=cts_rate, dt=dt)
w = np.arange(1 / exptime[i], 0.5 / dt, 1 / exptime[i])
spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4])
# spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(w, [1.0518215e-3,1.0518215e-3/16,200,2])
lc = sim.simulate(spectrum)
lc.counts += cts_rate
lc.counts[np.where(lc.counts < 0)] = 0
lc.time+=tstart[i]
if i==0: lc_all=lc
else: lc_all=lc_all.join(lc)
print('run')
print(lc_all.time)
while k_trial<num_trials:
ev_all = EventList()
ev_all.time = sim_evtlist(lc_all) + tstart[0]
# ev_all = ev_all.join(ev)
lc_new = ev_all.to_lc(dt=dt, tstart=ev_all.time[0] - 0.5 * dt, tseg=ev_all.time[-1] - ev_all.time[0])
temp = get_LS(lc_new.time, lc_new.counts, freq=freq, trial=k_trial)
writer.writerows([temp[-1]])
k_trial+=1
def get_lc_byspec_1hr(k,j,num_trials=1000):
k_trial=0
FP = [];
period = [];
while k_trial <num_trials:
path = '/Users/baotong/Desktop/CDFS/txt_all_obs_0.5_8_ep{0}/'.format(k)
epoch_file=np.loadtxt(path+'CDFS_epoch_ep{0}.txt'.format(k))
# path = '/Users/baotong/Desktop/CDFS/txt_all_obs_0.5_8/'
# epoch_file = np.loadtxt(path + 'CDFS_epoch.txt')
tstart=epoch_file[:,0];tstop=epoch_file[:,1];exptime=epoch_file[:,3]
ev_all = EventList()
for i in range(len(exptime)):
dt=100
cts_rate=cr[j] *dt #实际的cts-rate应为这个的2倍
num_bins=int(exptime[i]/dt)
sim = simulator.Simulator(N=num_bins, mean=cts_rate, dt=dt)
w = np.arange(1 / exptime[i], 0.5 / dt, 1 / exptime[i])
# w = np.fft.rfftfreq(sim.N, d=sim.dt)[1:]
# spectrum = smoothbknpo(w, [0.01, 2, 1e-2, 1e-3])
# spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4]) ## 这是RE J1034+396 的参数
# spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(w, [6.68e-4 ,6.68e-4 /16,200,2])
spectrum = bending_po(w, [2.3e-3, 3.4, 0., 4.3e-4]) + generalized_lorentzian(w,[5.6e-4, 5.6e-4 / 16, 200,2])
# spectrum =powerlaw + generalized_lorentzian(w, [1 / 1000., 1 / 10000., 0.5*np.max(powerlaw), 2])
lc = sim.simulate(spectrum)
lc.counts += cts_rate
lc.counts[np.where(lc.counts<0)]=0
ps=Powerspectrum(lc,norm='abs')
ev = EventList()
# ev.simulate_times(use_spline=False,lc=lc,bin_time=dt)
# ev.time+=tstart[i]
ev.time=sim_evtlist(lc)+tstart[i]
# print(ev.time)RX J1301.9+2747
ev_all=ev_all.join(ev)
print('cts={0}'.format(len(ev_all.time)))
lc_new = ev_all.to_lc(dt=dt, tstart=ev_all.time[0]-0.5*dt, tseg=ev_all.time[-1]-ev_all.time[0])
T_exp=lc_new.time[-1]-lc_new.time[0]
freq = np.arange(1 / T_exp, 0.5 / dt, 1 / (5 * T_exp))
freq=freq[np.where(freq > 1 / 20000.)]
# print(len(freq))
temp=get_LS(lc_new.time, lc_new.counts, freq=freq)
FP.append(temp[0]);period.append(temp[1])
k_trial+=1
result=np.column_stack((FP,period))
np.savetxt(path+'simulation/'+'trial_out_1hr_{0}_REJ1034+396_test_noC.txt'.format(cr_str[j]),result,fmt="%10.5f %10.5f")
return ev_all
def get_lc_byspec_single():
## stingray做simulation的时候powerspectrum的normlization的对lc似乎毫无影响；反正模拟的结果是这么显示的``````
exptime=1e6
dt = 10
cts_rate = 1e-4* dt # 实际得到的lc中的cts-rate应为这个的2倍，换言之这里应该是你要的cts-rate除以2
num_bins = int(exptime / dt)
sim = simulator.Simulator(N=num_bins, mean=cts_rate, dt=dt)
w = np.arange(1 / exptime, 0.5 / dt, 1 / exptime)
# w = np.fft.rfftfreq(sim.N, d=sim.dt)[1:]
spectrum=generalized_lorentzian(w,[1/500.,1/4000.,100,2])
# spectrum = smoothbknpo(w, [cts_rate * dt * 0.1, 3, 0, 1e-3])
# spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4]) ## 这是RE J1034+396 的参数
spectrum= bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4])+generalized_lorentzian(w,[2.7e-4,2.7e-4/16,200,2])
# spectrum = smoothbknpo(w, [cts_rate*dt*1, 2, 0, 1e-3]) + generalized_lorentzian(w, [1 / 1000., 1 / 10000., cts_rate*dt*100, 2])
print(np.mean(spectrum))
lc = sim.simulate(spectrum)
lc.counts += cts_rate
lc.counts[np.where(lc.counts < 0)] = 0
print(np.mean(lc.counts))
print(np.sum(lc.counts))
print(np.var(lc.counts))
plt.plot(lc.time,lc.counts)
plt.show()
ps = Powerspectrum(lc, norm='abs')
fig, ax1 = plt.subplots(1, 1, figsize=(9, 6), sharex=True)
ax1.plot(ps.freq, ps.power, lw=2, color='blue')
ax1.set_ylabel("Frequency (Hz)", fontproperties=font_prop)
ax1.set_ylabel("Power (raw)", fontproperties=font_prop)
# ax1.set_yscale('log')
ax1.tick_params(axis='x', labelsize=16)
ax1.tick_params(axis='y', labelsize=16)
ax1.tick_params(which='major', width=1.5, length=7)
ax1.tick_params(which='minor', width=1.5, length=4)
for axis in ['top', 'bottom', 'left', 'right']:
ax1.spines[axis].set_linewidth(1.5)
plt.loglog()
plt.show()
T_exp = exptime
freq = np.arange(1 / T_exp, 0.5 / dt, 1 / T_exp)
freq = freq[np.where(freq > 1 / 20000.)]
def test_compare_powerlaw(self):
"""
Compare simulated power spectrum with actual one.
"""
B, N, red_noise, dt = 2, 1024, 10, 1
self.simulator = simulator.Simulator(N=N,
dt=dt,
mean=5,
rms=1,
red_noise=red_noise)
lc = [self.simulator.simulate(B) for i in range(1, 30)]
simulated = self.simulator.powerspectrum(lc, lc[0].tseg)
w = np.fft.rfftfreq(N, d=dt)[1:]
actual = np.power((1 / w), B / 2)[:-1]
actual_prob = actual / float(sum(actual))
simulated_prob = simulated / float(sum(simulated))
assert np.all(
np.abs(actual_prob - simulated_prob) < 3 * np.sqrt(actual_prob))
if __name__ == '__main__':
path = '/Users/baotong/Desktop/CDFS/txt_all_obs_0.5_8_ep3/'
epoch_file = np.loadtxt(path + 'epoch_src_89.txt')
cts_rate = 1e-3
dt = 100
tstart = epoch_file[:, 0]
tstop = epoch_file[:, 1]
ID = epoch_file[:, 2]
exptime = epoch_file[:, 3]
T_tot = tstop[-1] - tstart[0]
cts_rate = cts_rate / 2 * dt ##这里cts_rate单位都是per bin
num_bins = int(T_tot / dt)
sim = simulator.Simulator(N=num_bins + 1, mean=cts_rate, dt=dt)
w = np.arange(1 / T_tot, 0.5 / dt, 1 / T_tot)
spectrum = bending_po(
w, [2.3e-4, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(
w, [4.01e-4, 4.01e-4 / 16, 200, 2])
lc = sim.simulate(spectrum)
lc.time = lc.time + tstart[0]
lc.counts += cts_rate
lc.counts[np.where(lc.counts < 0)] = 0
lc.gti = [[lc.time[0], lc.time[-1]]]
# plt.plot(w,spectrum)
k_trials = 1
for i in range(k_trials):
[time, lc_src] = make_evt_nobkg(cts_rate=1e-3,
dt=3.2,
epoch_file=epoch_file,
def test_io(self):
sim = simulator.Simulator(N=1024)
sim.write('sim.pickle')
sim = sim.read('sim.pickle')
assert sim.N == 1024
os.remove('sim.pickle')
def test_simulate_with_random_state(self):
self.simulator = simulator.Simulator(
N=1024, random_state=np.random.RandomState(12))
def test_simulate_with_seed(self):
"""
Simulate with a random seed value.
"""
self.simulator = simulator.Simulator(N=1024, random_state=12)
assert len(self.simulator.simulate(2).counts), 1024
def slow_sim_fixpds_qpo_XMM(src_index, num_trials=2):
k_trial = 0
dt = 100
path = '/Users/baotong/Desktop/CDFS/xmm_CDFS/xmm_txt/'
epoch_file = np.loadtxt(path + 'epoch6_xmmobs.txt')
tstart = epoch_file[:, 0]
tstop = epoch_file[:, 1]
ID = epoch_file[:, 2]
exptime = epoch_file[:, 3]
# evt_file_origin =np.loadtxt(path + 'XID{0}_{1}_all_obs_10sec.txt'.format(source_id, det))
# bkgevt_file_origin = np.loadtxt(path + 'bkg_XID{0}_{1}_all_obs_10sec.txt'.format(source_id, det))
# (evt_file,bkgevt_file)=filter_obs(evt_file_origin,bkgevt_file_origin,ID)
T_tot = tstop[-1] - tstart[0]
# cts_rate = len(evt_file)/ (2 * np.sum(exptime)) * dt # 实际的cts-rate应为这个的2倍
cts_rate = 0.001 * 0.67 / 2 * dt ##这里cts_rate单位都是per bin
bkg_cts_rate = 0.001 * 0.33
num_bins = int(T_tot / dt)
freq = np.arange(1 / T_tot, 0.5 / dt, 1 / (5 * T_tot))
freq = freq[np.where(freq > 1 / 20000.)]
sim = simulator.Simulator(N=num_bins + 1, mean=cts_rate, dt=dt)
w = np.arange(1 / T_tot, 0.5 / dt, 1 / T_tot)
spectrum = bending_po(
w, [2.3e-3, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(
w, [4.01e-4, 4.01e-4 / 16, 200, 2])
# spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4])
lc = sim.simulate(spectrum)
lc.time = lc.time + tstart[0]
# lc.gti=[[lc.time[0],lc.time[-1]]]
lc.counts += cts_rate
lc.counts[np.where(lc.counts < 0)] = 0
with open(path + 'simulation/ep6_1e-3_SN3_LSP_qpo.txt', 'a+') as f:
while k_trial < num_trials:
ev_all = EventList()
ev_all_bkg = EventList()
for i in range(len(ID)):
lc_cut = lc.truncate(start=tstart[i],
stop=tstop[i],
method='time')
ev = EventList()
ev.time = sim_evtlist(lc_cut)
ev_all = ev_all.join(ev)
index_b = (tstop[i] - tstart[i]) * bkg_cts_rate
temp = index_b
cts_num = np.random.poisson(temp)
ev_bkg = EventList()
ev_bkg.time = np.random.uniform(tstart[i] - dt / 2,
tstop[i] + dt / 2, cts_num)
ev_all_bkg = ev_all_bkg.join(ev_bkg)
lc_src = ev_all.to_lc(dt=dt, tstart=tstart[0], tseg=T_tot)
lc_bkg = ev_all_bkg.to_lc(dt=dt, tstart=tstart[0], tseg=T_tot)
print(np.sum(lc_src))
print(np.sum(lc_bkg))
# T_exp=lc_new.time[-1]-lc_new.time[0]
# lc_new=lc_src-lc_bkg
lc_new = lc_src + lc_bkg
temp = get_LS(lc_new.time, lc_new.counts, freq=freq)
f.writelines(
(str(temp[0]) + ' ' + str(temp[1]) + ' ' +
str(temp[2]) + ' ' + str(temp[3]) + '\n'))
k_trial += 1
f.close()
def slow_sim_fixpds_qpo_chandra(src_index, num_trials=2, dt=100):
k_trial = 0
path = '/Users/baotong/Desktop/CDFS/txt_all_obs_0.5_8_ep3/'
epoch_file = np.loadtxt(path + 'epoch_src_{0}.txt'.format(src_index))
# epoch_file=epoch_file[23:]
tstart = epoch_file[:, 0]
tstop = epoch_file[:, 1]
ID = epoch_file[:, 2]
exptime = epoch_file[:, 3]
evt_file_origin = np.loadtxt(path + '{0}.txt'.format(src_index))
bkgevt_file_origin = np.loadtxt(path + '{0}_bkg.txt'.format(src_index))
# (evt_file,bkgevt_file)=filter_obs(evt_file_origin,bkgevt_file_origin,ID)
evt_file = evt_file_origin
bkgevt_file = bkgevt_file_origin
T_tot = tstop[-1] - tstart[0]
cts_rate = len(evt_file) / (2 * np.sum(exptime)) * dt # 实际的cts-rate应为这个的2倍
bkg_rate = len(bkgevt_file_origin) / (2 * np.sum(exptime)) * dt
num_bins = int(T_tot / dt)
freq = np.arange(1 / T_tot, 0.5 / dt, 1 / (5 * T_tot))
freq = freq[np.where(freq > 1 / 20000.)]
sim = simulator.Simulator(N=num_bins + 1, mean=cts_rate, dt=dt)
w = np.arange(1 / T_tot, 0.5 / dt, 1 / T_tot)
spectrum = bending_po(
w, [2.3e-3, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(
w, [4.01e-4, 4.01e-4 / 16, 200, 2])
# spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4])
lc = sim.simulate(spectrum)
# lc=sim.simulate(pow)
lc.time = lc.time + tstart[0]
lc.gti = [[lc.time[0], lc.time[-1]]]
lc.counts += cts_rate
lc.counts[np.where(lc.counts < 0)] = 0
ps = Powerspectrum(lc, norm='frac')
fig, ax1 = plt.subplots(1, 1, figsize=(9, 6), sharex=True)
ax1.loglog()
ax1.step(ps.freq, ps.power, lw=2, color='blue')
ax1.plot([1 / 950.7, 1 / 950.7], [0, np.max(ps.power)], '--', linewidth=1)
ax1.set_ylabel("Frequency (Hz)", fontproperties=font1)
ax1.set_ylabel("Power (raw)", fontproperties=font1)
ax1.set_yscale('log')
ax1.tick_params(axis='x', labelsize=16)
ax1.tick_params(axis='y', labelsize=16)
ax1.tick_params(which='major', width=1.5, length=7)
ax1.tick_params(which='minor', width=1.5, length=4)
for axis in ['top', 'bottom', 'left', 'right']:
ax1.spines[axis].set_linewidth(1.5)
plt.show()
with open(path + 'simulation/{0}_LSP_FP_qpo_nofix.txt'.format(src_index),
'a+') as f:
while k_trial < num_trials:
ev_all = EventList()
ev_all_bkg = EventList()
for i in range(len(ID)):
lc_cut = lc.truncate(start=tstart[i],
stop=tstop[i],
method='time')
ev = EventList()
ev.time = sim_evtlist(lc_cut)
ev_all = ev_all.join(ev)
index_b = len(np.where(bkgevt_file[:, 2] == ID[i])[0])
temp = index_b / 12.
cts_num = np.random.poisson(temp)
ev_bkg = EventList()
ev_bkg.time = np.random.uniform(tstart[i] - dt / 2,
tstop[i] + dt / 2, cts_num)
ev_all_bkg = ev_all_bkg.join(ev_bkg)
lc_src = ev_all.to_lc(dt=dt, tstart=tstart[0], tseg=T_tot)
lc_bkg = ev_all_bkg.to_lc(dt=dt, tstart=tstart[0], tseg=T_tot)
print(np.sum(lc_src))
print(np.sum(lc_bkg))
# T_exp=lc_new.time[-1]-lc_new.time[0]
lc_new = lc_src
lc_new.counts -= lc_bkg.counts
temp = get_LS(lc_new.time, lc_new.counts, freq=freq)
# f.writelines((str(temp[0]) + ' ' + str(temp[1]) +' '+ str(temp[2])+' '+ str(temp[3])+'\n'))
k_trial += 1
f.close()
def setup_class(self):
self.simulator = simulator.Simulator(N=1024, mean=0.5, dt=0.125)
def slow_sim_fixpds(k, src_index, num_trials=2):
k_trial = 0
dt = 100
FP = []
period = []
cts_num = []
peakP = []
power_P = []
path = '/Users/baotong/Desktop/CDFS/txt_all_obs_0.5_8_ep{0}/'.format(k)
epoch_file = np.loadtxt(path + 'CDFS_epoch_ep{0}.txt'.format(k))
tstart = epoch_file[:, 0]
tstop = epoch_file[:, 1]
ID = epoch_file[:, 2]
exptime = epoch_file[:, 3]
evt_file = np.loadtxt(path + '{0}.txt'.format(src_index))
bkgevt_file = np.loadtxt(path + '{0}_bkg.txt'.format(src_index))
T_tot = tstop[-1] - tstart[0]
cts_rate = len(evt_file) / (2 * np.sum(exptime)) * dt # 实际的cts-rate应为这个的2倍
num_bins = int(T_tot / dt)
sim = simulator.Simulator(N=num_bins + 1, mean=cts_rate, dt=dt)
w = np.arange(1 / T_tot, 0.5 / dt, 1 / T_tot)
spectrum = bending_po(
w, [2.3e-3, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(
w, [2.7e-4, 2.7e-4 / 16, 200, 2])
lc = sim.simulate(spectrum)
lc.time = lc.time + tstart[0]
# lc.gti=[[lc.time[0],lc.time[-1]]]
lc.counts += cts_rate
lc.counts[np.where(lc.counts < 0)] = 0
ps = Powerspectrum(lc, norm='leahy')
fig, ax1 = plt.subplots(1, 1, figsize=(9, 6), sharex=True)
ax1.loglog()
ax1.step(ps.freq, ps.power, lw=2, color='blue')
ax1.plot([1 / 950.7, 1 / 950.7], [0, np.max(ps.power)], '--', linewidth=1)
ax1.set_ylabel("Frequency (Hz)", fontproperties=font1)
ax1.set_ylabel("Power (raw)", fontproperties=font1)
ax1.set_yscale('log')
ax1.tick_params(axis='x', labelsize=16)
ax1.tick_params(axis='y', labelsize=16)
ax1.tick_params(which='major', width=1.5, length=7)
ax1.tick_params(which='minor', width=1.5, length=4)
for axis in ['top', 'bottom', 'left', 'right']:
ax1.spines[axis].set_linewidth(1.5)
plt.show()
T_exp = T_tot
freq = np.arange(1 / T_exp, 0.5 / dt, 1 / (5 * T_exp))
freq = freq[np.where(freq > 1 / 20000.)]
with open(path + '/simulation/{0}_max_LSP_fixpds.txt'.format(src_index),
'a+') as f:
res_period = []
res_power = []
while k_trial < num_trials:
ev_all = EventList()
for i in range(len(exptime)):
lc_cut = lc.truncate(start=tstart[i],
stop=tstop[i],
method='time')
ev = EventList()
ev.time = sim_evtlist(lc_cut)
ev_all = ev_all.join(ev)
lc_new = ev_all.to_lc(dt=dt,
tstart=ev_all.time[0] - 0.5 * dt,
tseg=ev_all.time[-1] - ev_all.time[0])
temp = get_LS(lc_new.time, lc_new.counts, freq=freq, trial=k_trial)
# res_period.append(temp[0]);res_power.append(temp[-1])
f.writelines((str(temp[0]) + ' ' + str(temp[1]) + '\n'))
k_trial += 1
f.close()
def make_evt_nobkg(cts_rate, dt, epoch_file, lc_bin=100, fixpds=True, lc=0):
tstart = epoch_file[:, 0]
tstop = epoch_file[:, 1]
ID = epoch_file[:, 2]
exptime = epoch_file[:, 3]
T_tot = tstop[-1] - tstart[0]
cts_rate = cts_rate / 2 * dt ##这里cts_rate单位都是per bin
num_bins = int(T_tot / dt)
freq = np.arange(1 / T_tot, 0.5 / dt, 1 / (5 * T_tot))
freq = freq[np.where(freq > 1 / 20000.)]
if fixpds:
lc = lc
else:
print('not fix!')
sim = simulator.Simulator(N=num_bins + 1, mean=cts_rate, dt=dt)
w = np.arange(1 / T_tot, 0.5 / dt, 1 / T_tot)
spectrum = bending_po(
w, [2.3e-4, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(
w, [4.01e-4, 4.01e-4 / 16, 0.1, 2])
lc = sim.simulate(spectrum)
lc.time = lc.time + tstart[0]
lc.counts += cts_rate
lc.counts[np.where(lc.counts < 0)] = 0
lc.gti = [[lc.time[0], lc.time[-1]]]
plt.plot(w, spectrum)
plt.loglog()
plt.show()
plt.plot(lc.time, lc.counts)
plt.show()
ps = Powerspectrum(lc, norm='abs')
fig, ax1 = plt.subplots(1, 1, figsize=(9, 6), sharex=True)
ax1.plot(ps.freq, ps.power, lw=2, color='blue')
ax1.set_ylabel("Frequency (Hz)", fontproperties=font1)
ax1.set_ylabel("Power (raw)", fontproperties=font1)
# ax1.set_yscale('log')
ax1.tick_params(axis='x', labelsize=16)
ax1.tick_params(axis='y', labelsize=16)
ax1.tick_params(which='major', width=1.5, length=7)
ax1.tick_params(which='minor', width=1.5, length=4)
for axis in ['top', 'bottom', 'left', 'right']:
ax1.spines[axis].set_linewidth(1.5)
plt.loglog()
plt.show()
ev_all = EventList()
ev_all_bkg = EventList()
for i in range(len(ID)):
lc_cut = lc.truncate(start=tstart[i], stop=tstop[i], method='time')
ev = EventList()
ev.time = sim_evtlist(lc_cut)
ev_all = ev_all.join(ev)
lc_src = ev_all.to_lc(dt=lc_bin, tstart=tstart[0], tseg=T_tot)
ps = Powerspectrum(lc_src, norm='abs')
fig, ax2 = plt.subplots(1, 1, figsize=(9, 6), sharex=True)
ax2.plot(ps.freq, ps.power, lw=2, color='blue')
ax2.set_ylabel("Frequency (Hz)", fontproperties=font1)
ax2.set_ylabel("Power (raw)", fontproperties=font1)
# ax1.set_yscale('log')
ax2.tick_params(axis='x', labelsize=16)
ax2.tick_params(axis='y', labelsize=16)
ax2.tick_params(which='major', width=1.5, length=7)
ax2.tick_params(which='minor', width=1.5, length=4)
for axis in ['top', 'bottom', 'left', 'right']:
ax2.spines[axis].set_linewidth(1.5)
plt.loglog()
plt.show()
return [ev_all.time, lc_src]
def get_lc_byspec(k,j,num_trials=1000):
k_trial=0
FP = [];
period = [];
while k_trial <num_trials:
path = '/Users/baotong/Desktop/CDFS/txt_all_obs_0.5_8_ep{0}/'.format(k)
epoch_file=np.loadtxt(path+'CDFS_epoch_ep{0}.txt'.format(k))
# path = '/Users/baotong/Desktop/CDFS/txt_all_obs_0.5_8/'
# epoch_file = np.loadtxt(path + 'CDFS_epoch.txt')
tstart=epoch_file[:,0];tstop=epoch_file[:,1];exptime=epoch_file[:,3]
ev_all = EventList()
for i in range(len(exptime)):
dt=100
cts_rate=cr[j] *dt #实际的cts-rate应为这个的2倍
num_bins=int(exptime[i]/dt)
sim = simulator.Simulator(N=num_bins, mean=cts_rate, dt=dt)
w = np.arange(1 / exptime[i], 0.5 / dt, 1 / exptime[i])
# w = np.fft.rfftfreq(sim.N, d=sim.dt)[1:]
# spectrum = smoothbknpo(w, [0.01, 2, 1e-2, 1e-3])
spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4]) ## 这是RE J1034+396 的参数
# spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(w, [6.68e-4 ,6.68e-4 /16,200,2])
# spectrum = bending_po(w, [2.3e-3, 3.4, 0.40, 4.3e-4]) + generalized_lorentzian(w,[2.7e-4, 2.7e-4 / 16, 200,2])
# spectrum =powerlaw + generalized_lorentzian(w, [1 / 1000., 1 / 10000., 0.5*np.max(powerlaw), 2])
lc = sim.simulate(spectrum)
lc.counts += cts_rate
lc.counts[np.where(lc.counts<0)]=0
# plt.plot(w,spectrum)
# plt.loglog()
# plt.xlabel("Frequency (Hz)", fontproperties=font_prop)
# plt.ylabel("Power (abs)", fontproperties=font_prop)
# plt.show()
ps=Powerspectrum(lc,norm='abs')
# fig, ax1 = plt.subplots(1, 1, figsize=(9, 6), sharex=True)
# ax1.plot(ps.freq, ps.power, lw=2, color='blue')
# ax1.set_ylabel("Frequency (Hz)", fontproperties=font_prop)
# ax1.set_ylabel("Power (raw)", fontproperties=font_prop)
# # ax1.set_yscale('log')
# ax1.tick_params(axis='x', labelsize=16)
# ax1.tick_params(axis='y', labelsize=16)
# ax1.tick_params(which='major', width=1.5, length=7)
# ax1.tick_params(which='minor', width=1.5, length=4)
# for axis in ['top', 'bottom', 'left', 'right']:
# ax1.spines[axis].set_linewidth(1.5)
# plt.loglog()
# plt.show()
ev = EventList()
# ev.simulate_times(use_spline=False,lc=lc,bin_time=dt)
# ev.time+=tstart[i]
ev.time=sim_evtlist(lc)+tstart[i]
# print(ev.time)RX J1301.9+2747
ev_all=ev_all.join(ev)
# lc_temp = ev.to_lc(dt=dt, tstart=ev.time[0]-0.5*dt, tseg=ev.time[-1]-ev.time[0])
# ps_temp=Powerspectrum(lc_temp,norm='abs')
# fig2, ax2 = plt.subplots(1, 1, figsize=(9, 6), sharex=True)
# ax2.plot(ps_temp.freq, ps_temp.power, lw=2, color='blue')
# ax2.set_ylabel("Frequency (Hz)", fontproperties=font_prop)
# ax2.set_ylabel("Power (raw)", fontproperties=font_prop)
# # ax1.set_yscale('log')
# ax2.tick_params(axis='x', labelsize=16)
# ax2.tick_params(axis='y', labelsize=16)
# ax2.tick_params(which='major', width=1.5, length=7)
# ax2.tick_params(which='minor', width=1.5, length=4)
# for axis in ['top', 'bottom', 'left', 'right']:
# ax2.spines[axis].set_linewidth(1.5)
# plt.loglog()
# plt.show()
#
# plt.figure(2)
# plt.plot(lc.time,lc.counts,c='green')
# plt.plot(lc_temp.time,lc_temp.counts,c='r')
# plt.show()
# plt.figure(3)
# get_LS(lc.time,lc.counts,w)
# print('cts={0}'.format(len(ev_all.time)))
lc_new = ev_all.to_lc(dt=dt, tstart=ev_all.time[0]-0.5*dt, tseg=ev_all.time[-1]-ev_all.time[0])
# plt.figure(2)
# plt.plot(lc_new.time,lc_new.counts,c='r')
# plt.show()
# plt.figure(3)
T_exp=lc_new.time[-1]-lc_new.time[0]
freq=np.arange(1/T_exp,0.5/dt,1/(5*T_exp))
freq=freq[np.where(freq > 1 / 10000.)]
# print(len(freq))
temp=get_LS(lc_new.time, lc_new.counts, freq=freq)
FP.append(temp[0]);period.append(temp[1])
k_trial+=1
result=np.column_stack((FP,period))
np.savetxt(path+'simulation/'+'trial_out_{0}_REJ1034+396_noQPO.txt'.format(cr_str[j]),result,fmt="%10.5f %10.5f")
return ev_all
