def construct_initial_album(illustris_images, psf_blur_size=None):
"""
the initial album contains 32 images of the illustris galaxy,
the images will be a little blured so that 3 Gaussians will be sufficient for the fitting process.
the album will contain a galaxy_3d_model that contains 3 Gaussians
"""
num_of_images = len(illustris_images)
# album and PSF initialisation
album = astrohack_projections.album_and_model()
psf = astrohack_projections.mixture_of_gaussians(2)
psf.add_gaussian(1., numpy.array([0., 0.]), numpy.eye(2)*1.)
# construct the galaxy using Gaussian mixture
basevar = 0.5 * numpy.eye(3)
gal_model = astrohack_projections.galaxy_model_3d()
for i in xrange(3):
v = numpy.random.uniform(0, 3, size=3)
mu = numpy.random.uniform(-3, 3, size=3)
gal_model.add_gaussian(1.0, mu, basevar + numpy.outer(v, v))
# add all images to the album
for i in xrange(num_of_images):
if psf_blur_size != None:
data = gaussian_filter(illustris_images[i], psf_blur_size)
else:
data = illustris_images[i]
# projection parameters
xi_hat, eta_hat = astrohack_projections.choose_random_projection()
alpha, beta, gamma = numpy.random.uniform(0.0, 360.0, 3)
intensity = 20 #150 #
scale = 0.5 * numpy.exp(numpy.random.uniform()) #0.18 * numpy.exp(numpy.random.uniform()) #
xshift = numpy.random.uniform(29.5, 31.)#(13., 16.)#
yshift = numpy.random.uniform(39.5, 41.)#(18., 21.)#
bg = 0.
image = astrohack_projections.image_and_model()
image.set_shape((60, 80))
image.set_psf(psf)
scale = 0.3 #0.5
kwargs = {'alpha':alpha, 'beta':beta, 'gamma':gamma, 'intensity':intensity, 'scale':scale, 'xshift': xshift, 'yshift': yshift, 'bg':0.0}
image.set_parameters(**kwargs)
image.set_galaxy(gal_model)
image.set_ivar(numpy.ones(data.shape))
image.set_data(data + numpy.random.normal(size=data.shape)/ numpy.sqrt(image.ivar))
# album
album.add_image(image)
return album
def _construct_initial_album(self):
"""
construct the initial album with which the fitting begins,
the album is constrcuted based on the same image parameters
"""
assert len(self.images_to_fit) > 0
assert self.in_gaus_num != None
# album and PSF initialisation
album = astrohack_projections.album_and_model()
psf = astrohack_projections.mixture_of_gaussians(2)
psf.add_gaussian(1., numpy.array([0., 0.]), numpy.eye(2)*1.)
# construct the galaxy using Gaussian mixture
basevar = 0.5 * numpy.eye(3)
gal_model = astrohack_projections.galaxy_model_3d()
for i in xrange(self.in_gaus_num):
v = numpy.random.uniform(0, 3, size=3)
mu = numpy.random.uniform(-3, 3, size=3)
gal_model.add_gaussian(1.0, mu, basevar + numpy.outer(v, v))
# add all images to the album
for i in xrange(self.image_parameters['num']):
data = self.images_to_fit[i]
# projection parameters
xi_hat, eta_hat = astrohack_projections.choose_random_projection()
alpha, beta, gamma = numpy.random.uniform(0.0, 360.0, 3)
intensity = self.image_parameters['intensity']
scale = self.image_parameters['scale'] * numpy.exp(numpy.random.uniform())
if scale < 0.5:
scale = 0.5
xshift = numpy.random.uniform(self.image_parameters['xshift'][0], self.image_parameters['xshift'][1])
yshift = numpy.random.uniform(self.image_parameters['yshift'][0], self.image_parameters['yshift'][1])
bg = self.image_parameters['bg']
image = astrohack_projections.image_and_model()
image.set_shape(self.image_parameters['shape'])
image.set_psf(psf)
kwargs = {'alpha':alpha, 'beta':beta, 'gamma':gamma, 'intensity':intensity, 'scale':scale, 'xshift': xshift, 'yshift': yshift, 'bg':0.0}
image.set_parameters(**kwargs)
image.set_galaxy(gal_model)
image.set_ivar(numpy.ones(data.shape))
image.set_data(data + numpy.random.normal(size=data.shape)/ numpy.sqrt(image.ivar))
# album
album.add_image(image)
album.set_galaxy(gal_model)
self.albums[len(album.galaxy.alphas)] = album
self.in_album = album
