tmp = (norm_I_e, norm_r_e, norm_n, norm_I_0, norm_h, args.truePsfFWHM)
plt.suptitle(r'Original model: $I_e = %.3f$, $r_e = %.3f$, $n = %.3f$, $I_0 = %.3f$, $h = %.3f$, $FWHM = %.2f$' % tmp)
gs.tight_layout(fig, rect=[0, 0, 1, 0.97])
pdf.savefig()
################################################################################
##########
########## Decomposition
##########
################################################################################
logger.info('Beginning decomposition.')
decomp = IFSDecomposer()
logger.info('Model using PSF FWHM = %.2f ".' % args.modelPsfFWHM)
decomp.setSynthPSF(FWHM=args.modelPsfFWHM, size=9)
decomp.loadData(l_ssp, full_spectra, full_noise, np.zeros_like(full_spectra, dtype='bool'))
swll, swlu = 5590.0, 5680.0
sl1 = find_nearest_index(decomp.wl, swll)
sl2 = find_nearest_index(decomp.wl, swlu)
qSignal, qNoise, qWl = decomp.getSpectraSlice(sl1, sl2)
logger.warn('Computing initial model (takes a LOT of time).')
t1 = time.time()
initial_model = bd_initial_model(qSignal, qNoise, decomp.PSF, quiet=False)
bulge_image, disk_image = create_model_images(initial_model, qSignal.shape, decomp.PSF)
logger.warn('Initial model time: %.2f\n' % (time.time() - t1))
logger.debug('Plotting guessed initial model.')
vmin = np.log10(qSignal.min())
vmax = np.log10(qSignal.max())
tmp = (norm_I_e, norm_r_e, norm_n, norm_I_0, norm_h, true_psf_FWHM)
plt.suptitle(r'Original model: $I_e = %.3f$, $r_e = %.3f$, $n = %.3f$, $I_0 = %.3f$, $h = %.3f$, $FWHM = %.2f$' % tmp)
gs.tight_layout(fig, rect=[0, 0, 1, 0.97])
pdf.savefig()
################################################################################
##########
########## Decomposition
##########
################################################################################
logger.info('Beginning decomposition.')
decomp = IFSDecomposer()
logger.info('Model using PSF FWHM = %.2f ", beta = %.2f.' % (args.modelPsfFWHM, args.modelPsfBeta))
decomp.setSynthPSF(FWHM=args.modelPsfFWHM, beta=args.modelPsfBeta, size=15)
decomp.loadData(wl, full_ifs / flux_unit, full_ifs_noise / flux_unit, np.zeros_like(full_ifs, dtype='bool'))
swll, swlu = 5590.0, 5680.0
sl1 = find_nearest_index(decomp.wl, swll)
sl2 = find_nearest_index(decomp.wl, swlu)
qSignal, qNoise, qWl = decomp.getSpectraSlice(sl1, sl2)
logger.warn('Computing initial model (takes a LOT of time).')
t1 = time.time()
initial_model = bd_initial_model(qSignal, qNoise, decomp.PSF, quiet=False, cache_model_file=args.cacheModel)
bulge_image, disk_image = create_model_images(initial_model, qSignal.shape, decomp.PSF)
logger.warn('Initial model time: %.2f\n' % (time.time() - t1))
logger.debug('Plotting guessed initial model.')
vmin = np.log10(qSignal.min())
vmax = np.log10(qSignal.max())
tmp = (norm_I_e, norm_r_e, norm_n, norm_I_0, norm_h, args.truePsfFWHM)
plt.suptitle(r"Original model: $I_e = %.3f$, $r_e = %.3f$, $n = %.3f$, $I_0 = %.3f$, $h = %.3f$, $FWHM = %.2f$" % tmp)
gs.tight_layout(fig, rect=[0, 0, 1, 0.97])
pdf.savefig()
################################################################################
##########
########## Decomposition
##########
################################################################################
logger.info("Beginning decomposition.")
decomp = IFSDecomposer()
logger.info('Model using PSF FWHM = %.2f ".' % args.modelPsfFWHM)
decomp.setSynthPSF(FWHM=args.modelPsfFWHM, size=9)
decomp.loadData(l_ssp, full_ifs, full_ifs_noise, np.zeros_like(full_ifs, dtype="bool"))
swll, swlu = 5590.0, 5680.0
sl1 = find_nearest_index(decomp.wl, swll)
sl2 = find_nearest_index(decomp.wl, swlu)
qSignal, qNoise, qWl = decomp.getSpectraSlice(sl1, sl2)
logger.warn("Computing initial model (takes a LOT of time).")
t1 = time.time()
initial_model = bd_initial_model(qSignal, qNoise, decomp.PSF, quiet=False)
bulge_image, disk_image = create_model_images(initial_model, qSignal.shape, decomp.PSF)
logger.warn("Initial model time: %.2f\n" % (time.time() - t1))
logger.debug("Plotting guessed initial model.")
vmin = np.log10(qSignal.min())
vmax = np.log10(qSignal.max())
