def _get_model(self):
im, psf_im, coords, dims, sing_im, sing_coord = Simulation.__call__(
self)
bg_rms = self['Image']['Bgrms']
mode = self['Mode']
if mode == 'scarlet':
#constraints = {"S": None, "m": {'use_nearest': False}, "+": None}
#constraints['l1'] = bg_rms
#psf_dims = np.shape(psf_im)
#psf_im3d = psf_im.reshape( (1, psf_dims[0], psf_dims[1]) )
#target_psf = scarlet.psf_match.fit_target_psf(psf_im3d, scarlet.psf_match.gaussian)
#diff_kernels, psf_blend = scarlet.psf_match.build_diff_kernels(psf_im3d, target_psf)
sources = [
scarlet.ExtendedSource(coord, im, [bg_rms]) for coord in coords
] #,psf=diff_kernels) for coord in coords]
#config = scarlet.Config(edge_flux_thresh=0.05)
config = scarlet.Config(source_sizes=[25
]) #,edge_flux_thresh=0.05)
#scarlet.ExtendedSource.shift_center=0.0
blend = scarlet.Blend(sources, im, bg_rms=[bg_rms], config=config)
blend.fit(10000, e_rel=1e-3)
model = blend.get_model()
mod1 = blend.get_model(m=0)
#mod2 = blend.get_model(m=1)
cen_mod = sources[0].get_model()
#neigh_mod = sources[1].get_model()
#steps_used = blend.it
#return im,psf_im,model,mod1,mod2,cen_mod,neigh_mod,coords,sing_im,sing_coord
return im, psf_im, model, mod1, cen_mod, coords, sing_im, sing_coord
def get_scar_model(self):
import scarlet
import scarlet.constraint as sc
im, psf_im, coords, dims, dx1, dy1, noise = self.sim()
bg_rms = self.sim['Image']['Bgrms']
bg_rms = bg_rms / np.sqrt(len(im))
mode = self.sim['Mode']
#create multiband background im
bg = np.zeros((len(im)))
bg += bg_rms
#choose constraints for PSF and sources (optional)
#psf_constraints = ()#sc.SimpleConstraint())
#source_constraints = ()#sc.SimpleConstraint(),sc.DirectSymmetryConstraint()) #sc.DirectMonotonicityConstraint(use_nearest=False)
config = scarlet.Config(source_sizes=[25])
#create multiband PSF image
#psf_dims = np.shape(psf_im)
#psf_im3d = psf_im.reshape( (1, psf_dims[0], psf_dims[1]) )
#psfs = np.zeros((len(im), psf_dims[0],psf_dims[1]))
#psfs += psf_im3d
#PSF Matching
#target_psf = scarlet.psf_match.fit_target_psf(psfs,
# scarlet.psf_match.gaussian)
#diff_kernels, psf_blend = scarlet.psf_match.build_diff_kernels(psfs,
# target_psf)
#if use PSF matching, set psf = diff_kernels below
sources = [
scarlet.ExtendedSource(coord,
im,
bg_rms=bg,
psf=None,
config=config) for coord in coords
]
#config = scarlet.Config(edge_flux_thresh=0.05)
blend = scarlet.Blend(sources)
blend.set_data(im, bg_rms=bg, config=config)
blend.fit(10000, e_rel=1e-3)
#get full sized scarlet models
model = blend.get_model()
mod1 = blend.get_model(0)
mod2 = blend.get_model(1)
#get postage stamp models
cen_mod = sources[0].get_model()
neigh_mod = sources[1].get_model()
#get scarlet coordinates
cen_cen_pos = blend[0][0].center
neigh_cen_pos = blend[1][0].center
return im, psf_im, model, mod1, mod2, cen_mod, neigh_mod, coords, dx1, dy1, noise, cen_cen_pos, neigh_cen_pos
def _get_model(self):
im, psf_im, coords, dims, sing_im, sing_coord = Simulation.__call__(
self)
bg_rms = self['Image']['Bgrms']
mode = self['Mode']
#constraints = {"S": None, "m": {'use_nearest': False}, "+": None}
constraint = (sc.SimpleConstraint())
#constraint = PSFConstraint()
config = (scarlet.Config(source_sizes=[25]))
#psf_dims = np.shape(psf_im)
#psf_im3d = psf_im.reshape( (1, psf_dims[0], psf_dims[1]) )
#target_psf = scarlet.psf_match.fit_target_psf(psf_im3d, scarlet.psf_match.gaussian)
#diff_kernels, psf_blend = scarlet.psf_match.build_diff_kernels(psf_im3d, target_psf,constraints=constraint)
#constraint = (sc.L0Constraint(.5*bg_rms))
#& sc.DirectSymmetryConstraint(sigma=0.25))
#& sc.MonotonicityConstraint(use_nearest=True))
#constraints['l1'] = bg_rms
sources = [
scarlet.ExtendedSource(coord,
im, [bg_rms],
psf=None,
config=config,
shift_center=0.0) for coord in coords
]
#config = scarlet.Config(edge_flux_thresh=1.25)
#scarlet.ExtendedSource.shift_center=0.0
blend = scarlet.Blend(sources)
blend.set_data(im, bg_rms=[bg_rms], config=config)
blend.fit(10000, e_rel=1e-3)
model = blend.get_model()
mod1 = blend.get_model(0)
#mod2 = blend.get_model(1)
cen_mod = sources[0].get_model()
#cen_pos = sources[0].center
#neigh_mod = sources[1].get_model()
#print(cen_pos[0]-coords[0][0],cen_pos[1]-coords[0][1])
#psf_model = psf_blend.get_model()
"""
masked_mod = np.ma.masked_equal(diff_kernels,0.0)
f,ax = plt.subplots(1,2,figsize=(8,4))
f1 = ax[0].imshow(psf_im3d[0,:,:])
ax[0].set_title("Orig PSF")
plt.colorbar(f1,ax=ax[0])
f2 = ax[1].imshow(masked_mod[0,:,:])
plt.colorbar(f2,ax=ax[1])
ax[1].set_title("Diff Kernels")
plt.tight_layout()
f.savefig('test.png')
plt.close()
steps_used = blend.it
print(steps_used)
"""
#return im,psf_im,model,mod1,mod2,cen_mod,neigh_mod,coords,sing_im,sing_coord
return im, psf_im, model, mod1, cen_mod, coords, sing_im, sing_coord
def get_scar_model(self):
import scarlet
import scarlet.constraint as sc
im, psf_im, coords, dims, dx1, dy1, noise = self.sim()
bg_rms = self.sim['Image']['Bgrms']
mode = self.sim['Mode']
bg = np.zeros((len(im)))
bg += bg_rms
#psf_constraints = (sc.SimpleConstraint())
#source_constraints = ()#sc.SimpleConstraint(),sc.DirectSymmetryConstraint()) #sc.DirectMonotonicityConstraint(use_nearest=False)
config = scarlet.Config(source_sizes=[25])
psf_dims = np.shape(psf_im)
psf_im3d = psf_im.reshape((1, psf_dims[0], psf_dims[1]))
psfs = np.zeros((len(im), psf_dims[0], psf_dims[1]))
psfs += psf_im3d
#target_psf = scarlet.psf_match.fit_target_psf(psfs,
# scarlet.psf_match.gaussian)
#diff_kernels, psf_blend = scarlet.psf_match.build_diff_kernels(psfs,
# target_psf, constraints = None)
sources = [
scarlet.ExtendedSource(coord,
im,
bg_rms=bg,
psf=None,
config=config) for coord in coords
]
#config = scarlet.Config(edge_flux_thresh=0.05)
blend = scarlet.Blend(sources)
blend.set_data(im, bg_rms=bg, config=config)
blend.fit(10000, e_rel=1e-3)
model = blend.get_model()
mod1 = blend.get_model(0)
#mod2 = blend.get_model(1)
cen_mod = sources[0].get_model()
#neigh_mod = sources[1].get_model()
#psf_model = psf_blend.get_model()
#steps_used = blend.it
cen_cen_pos = blend[0][0].center
#return im,psf_im,model,mod1,mod2,cen_mod,neigh_mod,coords,dx1,dy1,noise
return im, psf_im, model, mod1, cen_mod, coords, dx1, dy1, noise, cen_cen_pos, psfs
def get_scar_model(self):
import scarlet
im, psf_im, coords, dims, dx1, dy1, noise, sep_coords = self.sim()
bg_rms = self.sim['Image']['Bgrms']
mode = self.sim['Mode']
#constraints = {"S": None, "m": {'use_nearest': False}, "+": None}
#constraints['l0'] = bg_rms
constraint = (sc.SimpleConstraint())
# & sc.MonotonicityConstraint(use_nearest=True))
config = scarlet.Config(source_sizes=[25])
psf_dims = np.shape(psf_im)
psf_im3d = psf_im.reshape((1, psf_dims[0], psf_dims[1]))
target_psf = scarlet.psf_match.fit_target_psf(
psf_im3d, scarlet.psf_match.gaussian)
diff_kernels, psf_blend = scarlet.psf_match.build_diff_kernels(
psf_im3d, target_psf, constraints=constraint.copy())
sources = [
scarlet.ExtendedSource(coord,
im, [bg_rms],
psf=diff_kernels,
config=config) for coord in coords
]
#sources = [scarlet.ExtendedSource(coord, im, [bg_rms]) for coord in coords]
#scarlet.ExtendedSource.shift_center=0.0
#config = scarlet.Config(edge_flux_thresh=0.05)
blend = scarlet.Blend(sources, im, bg_rms=[bg_rms], config=config)
blend.fit(10000, e_rel=1e-3)
model = blend.get_model()
mod1 = blend.get_model(m=0)
mod2 = blend.get_model(m=1)
cen_mod = sources[0].get_model()
neigh_mod = sources[1].get_model()
#steps_used = blend.it
return im, psf_im, model, mod1, mod2, cen_mod, neigh_mod, coords, dx1, dy1, noise, sep_coords