logger.info('Time coverage: {0:g} days'.format(num_samples/fs/(3600.*24.)))
# generate the screen (this takes a while)
logger.info('generating screen...')
tic = time.time()
b.generatePhases()
logger.info('took {0:g}s'.format(time.time()-tic))
# generate time series (this takes a while)
logger.info('generating time series...')
fluxes = []
frames = []
tic = time.time()
for i in range(num_samples):
# update source image to include a sinusoidal flux modulation
b.setModel(I*(1. - 0.4*np.sin(2*np.pi*i/(2*num_samples))), dx) # comment out to speedup
b.scatter(move_pix=i*b.ips)
fluxes.append(b.iss.sum())
frames.append(b.iss)
logger.info('took {0:g}s'.format(time.time()-tic))
# 1962.92s
# make figures
fig_file = '../_static/time_variability/'
extent=b.dx*b.nx//2*np.array([1,-1,-1,1])
plt.figure()
plt.subplot(121)
isrc_smooth = utilities.smoothImage(b.isrc,b.dx,2.*b.dx)
plt.imshow(isrc_smooth,extent=extent,cmap=cmap)
plt.xlabel('$\Delta\\alpha$ [$\mu$as]'); plt.ylabel('$\Delta\delta$ [$\mu$as]')
