def gen_fake(self):
'''
make fake lightcurves
:return:
mf.myfake arguments are
wavelengths: enter the wavelengths (-1 indicates an emission line light curve modelled with a top-hat response),
snr: set the signal-to-noise relative to light curve rms
cadence:set the mean cadence
top hat centroid: set the centroid for the top-hat (I think thats what this does but the line lag
thing is still newish so Im used to just making continuum light curve)
'''
synthetic_data = mf.myfake(self.fake_wavelength,
self.fake_snr,
self.fake_cadence,
thcent=20.0)
self.dat = synthetic_data['echo light curves']
def gen_fake(self, iseed=-1):
'''
make fake lightcurves
:return:
mf.myfake arguments are
wavelengths: enter the wavelengths (-1 indicates an emission line light curve modelled with a top-hat response),
snr: set the signal-to-noise relative to light curve rms
cadence:set the mean cadence
top hat centroid: set the centroid for the top-hat (I think thats what this does but the line lag
thing is still newish so Im used to just making continuum light curve)
'''
synthetic_data = mf.myfake(self.fake_wavelength,
self.fake_snr,
self.fake_cadence,
embh=self.BHMass,
er=self.EddRat,
eta=self.BHefficiency,
thcent=self.line_lag,
degi=self.disk_inc,
thi=self.time_baseline,
iseed=iseed,
sx=self.disk_TXslope)
self.dat = synthetic_data['echo light curves']
import astropy_stark.myfake as mf
import matplotlib.pylab as plt
import numpy as np
output_directory = 'fit_synthetic_lightcurves_background_polynomial'
'''
same as test_pycecream.py but using a background polynomial light curve
'''
synthetic_data = mf.myfake(
[4000.0,5000.0,5000.0,7000.0],
[50.0,50.0,10.0,50.0],
[1.0,1.0,2.0,1.0],
thcent = 20.0
)
'''This recovers the synthetic data'''
dat = synthetic_data['echo light curves']
''' Now append a simple polynomial model'''
tlo = dat[0][:,0]
thi = dat[0][:,-1]
n = len(dat[0])
t = np.arange(n)/n*(thi - tlo) + tlo
x = 5.0 + 2.0*t + 0.1*t**2
x = (x - np.mean(x))/np.std(x)
sig = np.ones(n)*0.05
import astropy_stark.myfake as mf
import matplotlib.pylab as plt
lc1 = mf.myfake([-1.0, -1.0], [50.0, 100.], [1.0, 2.0],
sdforcein=[1.0, 1.0],
meanforcein=[0.0, 0.0],
thcent=20.0,
iseed=12345)['echo light curves']
lc2 = mf.myfake([-1.0], [50.0], [1.0],
thcent=5.0,
sdforcein=[2.0],
meanforcein=[5.0],
iseed=12345)['echo light curves']
dat = lc1 + lc2
#plot the light curves here to demonstrate
fig = plt.figure()
ax1 = fig.add_subplot(111)
for i in range(len(dat)):
ax1.errorbar(dat[i][:, 0], dat[i][:, 1], dat[i][:, 2], ls=None)
plt.show()