def disk_function(I_0=0.0, h=0.0, PA=0.0, ell=0.0):
disk = function_description('Exponential', name='disk')
disk.I_0.setValue(I_0)
disk.h.setValue(h)
disk.PA.setValue(PA)
disk.ell.setValue(ell)
return disk
def disk_function(I_0, h, PA, ell):
disk = function_description('Exponential', name='disk')
disk.I_0.setValue(I_0, vmin=1e-33, vmax=10*I_0)
disk.h.setValue(h, vmin=1e-33, vmax=10*h)
disk.PA.setValue(PA, vmin=0, vmax=180)
disk.ell.setValue(ell, vmin=0, vmax=1)
return disk
def bulge_function(I_e=0.0, r_e=0.0, n=0.0, PA=0.0, ell=0.0):
bulge = function_description('Sersic', name='bulge')
bulge.I_e.setValue(I_e)
bulge.r_e.setValue(r_e)
bulge.n.setValue(n)
bulge.PA.setValue(PA)
bulge.ell.setValue(ell)
return bulge
def bulge_function(I_e, r_e, n, PA, ell):
bulge = function_description('Sersic', name='bulge')
bulge.I_e.setValue(I_e, vmin=1e-33, vmax=10*I_e)
bulge.r_e.setValue(r_e, vmin=1e-33, vmax=10*r_e)
bulge.n.setValue(n, vmin=0.5, vmax=5.9)
bulge.PA.setValue(PA, vmin=0, vmax=180)
bulge.ell.setValue(ell, vmin=0, vmax=1)
return bulge
def create_model():
model = SimpleModelDescription()
model.x0.setValue(50, vmin=40, vmax=60)
model.y0.setValue(50, vmin=40, vmax=60)
bulge = function_description('Sersic', name='bulge')
bulge.I_e.setValue(1.0, vmin=0.5, vmax=1.5)
bulge.r_e.setValue(10, vmin=5, vmax=15)
bulge.n.setValue(4, vmin=3, vmax=5)
bulge.PA.setValue(45, vmin=30, vmax=60)
bulge.ell.setValue(0.5, vmin=0, vmax=1)
disk = function_description('Exponential', name='disk')
disk.I_0.setValue(0.7, vmin=0.4, vmax=0.9)
disk.h.setValue(15, vmin=10, vmax=20)
disk.PA.setValue(60, vmin=45, vmax=90)
disk.ell.setValue(0.2, vmin=0, vmax=0.5)
model.addFunction(bulge)
model.addFunction(disk)
return model
def example_model_description():
fs = FunctionSetDescription('example')
fs.x0.setValue(36.0, [25, 45])
fs.y0.setValue(32.0, [25, 45])
sersic = function_description('Sersic')
sersic.PA.setValue(93.0217, [0, 180])
sersic.ell.setValue(0.37666, [0, 1])
sersic.n.setValue(4, fixed=True)
sersic.I_e.setValue(1, [0, 10])
sersic.r_e.setValue(25, [0, 100])
exponential = function_description('Exponential')
exponential.PA.setValue(93.0217, [0, 180])
exponential.ell.setValue(0.37666, [0, 1])
exponential.I_0.setValue(1, [0, 10])
exponential.h.setValue(25, [0, 100])
fs.addFunction(sersic)
fs.addFunction(exponential)
return ModelDescription([fs])
def create_model():
model = SimpleModelDescription()
model.x0.setValue(50, vmin=40, vmax=60)
model.y0.setValue(50, vmin=40, vmax=60)
bulge = function_description('Sersic', name='bulge')
bulge.I_e.setValue(1.0, vmin=0.5, vmax=1.5)
bulge.r_e.setValue(10, vmin=5, vmax=15)
bulge.n.setValue(4, vmin=3, vmax=5)
bulge.PA.setValue(45, vmin=30, vmax=60)
bulge.ell.setValue(0.5, vmin=0, vmax=1)
disk = function_description('Exponential', name='disk')
disk.I_0.setValue(0.7, vmin=0.4, vmax=0.9)
disk.h.setValue(15, vmin=10, vmax=20)
disk.PA.setValue(60, vmin=45, vmax=90)
disk.ell.setValue(0.2, vmin=0, vmax=0.5)
model.addFunction(bulge)
model.addFunction(disk)
return model
flux = []
for cube in cubes:
f = pyfits.open(cube)
shape = f[0].data.shape
_mask = f[0].data <= 0
_flux = np.ma.array(f[0].data, mask=_mask)
y0, x0 = np.where(_flux == _flux.max())
r = distance(shape, x0, y0)
_flux[r > fitradius] = np.ma.masked
y0 = shape[0] / 2
_flux /= _flux.max()
flux.append(_flux)
f.close()
psf_func = function_description(func, name='psf')
psf_func.PA.setValue(60, vmin=-190, vmax=190)
psf_func.ell.setValue(0.2, vmin=-1.0, vmax=1.0)
psf_func.I_0.setValue(1.0, vmin=1e-20, vmax=10.0)
if func == 'Gaussian':
psf_func.sigma.setValue(1.0, vmin=0.1, vmax=20.0)
else:
psf_func.fwhm.setValue(2.5, vmin=0.1, vmax=20.0)
if func == 'Moffat':
if beta4:
psf_func.beta.setValue(4, fixed=True)
else:
psf_func.beta.setValue(1.9, vmin=1e-20, vmax=20.0)
model = SimpleModelDescription()
model.x0.setValue(flux[0].shape[1] / 2)
model.x0.setLimitsRel(5, 5)
label = {0.5: r'$n=0.5$',
1: r'$n=1\ (\mathrm{exponencial})$',
4: r'$n=4\ (\mathrm{de\ Vaucouleurs})$',
10: r'$n=10$',
}
line = {0.5: 'k:',
1: 'b-',
4: 'r-',
10: 'k-.',
}
bins = np.arange(100)
bins_c = bins[1:] - 0.5
sersic = function_description('Sersic')
model = SimpleModelDescription()
model.addFunction(sersic)
model.x0.setValue(x0 + 1)
model.y0.setValue(x0 + 1)
model.Sersic.I_e.setValue(1.0)
model.Sersic.r_e.setValue(r_e)
model.Sersic.PA.setValue(0.0)
model.Sersic.ell.setValue(0.0)
model.Sersic.n.setValue(4)
plot_setup()
width_pt = 448.07378
width_in = width_pt / 72.0 * 0.95
fig = plt.figure(figsize=(width_in, width_in * 0.5))
bins_c = bins[:-1] + 0.5
y0 = psfradius
x0 = psfradius
pa = 90.0
ba = 1.0
flux_r = radialProfile(psfflux[i_plot], bins, x0, y0, pa, ba)
bg_r = radialProfile(psfbg[i_plot], bins, x0, y0, pa, ba)
flux_bg_r = radialProfile(psfflux[i_plot] - psfbg[i_plot], bins, x0, y0, pa, ba)
plt.clf()
plt.plot(bins_c, flux_r)
plt.plot(bins_c, flux_bg_r)
plt.plot(bins_c, bg_r)
plt.show()
psf_func = function_description(func, 'psf')
psf_func.PA.setValue(0.0, vmin=-190, vmax=190)
psf_func.ell.setValue(0.2, vmin=-1.0, vmax=1.0)
psf_func.I_0.setValue(1.0, vmin=1e-20, vmax=10.0)
if func == 'Gaussian':
psf_func.sigma.setValue(1.0, vmin=1e-20, vmax=20.0)
else:
psf_func.fwhm.setValue(3.0, vmin=1e-20, vmax=20.0)
if func == 'Moffat':
if beta4:
psf_func.beta.setValue(4.0, fixed=True)
else:
psf_func.beta.setValue(2.0, vmin=1.0, vmax=20.0)
model = SimpleModelDescription()
model.x0.setValue(psfradius)
