def test_griddata_fits():
"""Round tripping with write_griddata_fits() and read_griddata_fits()"""
x0 = np.array([0., 1.])
x1 = np.array([0., 1., 2.])
y = np.zeros((2, 3))
f = BytesIO()
sncosmo.write_griddata_fits(x0, x1, y, f)
# Read it back
f.seek(0)
x0_in, x1_in, y_in = sncosmo.read_griddata_fits(f)
assert_allclose(x0_in, x0)
assert_allclose(x1_in, x1)
assert_allclose(y_in, y)
f.close()
# Test reading 3-d grid data. We don't have a writer for
# this, so we write a temporary FITS file by hand.
x2 = np.array([3., 5., 7., 9])
y = np.zeros((len(x0), len(x1), len(x2)))
# write a FITS file that represents x0, x1, x2, y
w = wcs.WCS(naxis=3)
w.wcs.crpix = [1, 1, 1]
w.wcs.crval = [x2[0], x1[0], x0[0]]
w.wcs.cdelt = [2., 1., 1.]
hdu = fits.PrimaryHDU(y, header=w.to_header())
f = BytesIO()
hdu.writeto(f)
# Read it back
f.seek(0)
x0_in, x1_in, x2_in, y_in = sncosmo.read_griddata_fits(f)
f.close()
assert_allclose(x0_in, x0)
assert_allclose(x1_in, x1)
assert_allclose(x2_in, x2)
assert_allclose(y_in, y)
def test_griddata_fits():
"""Round tripping with write_griddata_fits() and read_griddata_fits()"""
x0 = np.array([0., 1.])
x1 = np.array([0., 1., 2.])
y = np.zeros((2, 3))
f = six.BytesIO()
sncosmo.write_griddata_fits(x0, x1, y, f)
# Read it back
f.seek(0)
x0_in, x1_in, y_in = sncosmo.read_griddata_fits(f)
assert_allclose(x0_in, x0)
assert_allclose(x1_in, x1)
assert_allclose(y_in, y)
f.close()
# Test reading 3-d grid data. We don't have a writer for
# this, so we write a temporary FITS file by hand.
x2 = np.array([3., 5., 7., 9])
y = np.zeros((len(x0), len(x1), len(x2)))
# write a FITS file that represents x0, x1, x2, y
w = wcs.WCS(naxis=3)
w.wcs.crpix = [1, 1, 1]
w.wcs.crval = [x2[0], x1[0], x0[0]]
w.wcs.cdelt = [2., 1., 1.]
hdu = fits.PrimaryHDU(y, header=w.to_header())
f = six.BytesIO()
hdu.writeto(f)
# Read it back
f.seek(0)
x0_in, x1_in, x2_in, y_in = sncosmo.read_griddata_fits(f)
f.close()
assert_allclose(x0_in, x0)
assert_allclose(x1_in, x1)
assert_allclose(x2_in, x2)
assert_allclose(y_in, y)
def model_Ia_hsiao(self):
"""
"""
sncosmo.get_source('hsiao', version='3.0')
p, w, f = sncosmo.read_griddata_fits(
os.path.join(sncosmo.builtins.get_cache_dir(),
'sncosmo/models/hsiao/Hsiao_SED_V3.fits')
)
return sncosmo.Model(
source=sncosmo.StretchSource(p, w, f, name='hsiao-stretch'),
effects=[sncosmo.CCM89Dust()],
effect_names=['host'],
effect_frames=['rest']
)
def test_griddata_fits():
"""Round tripping with write_griddata_fits() and read_griddata_fits()"""
x0 = np.array([0., 1.])
x1 = np.array([0., 1., 2.])
y = np.zeros((2, 3))
f = six.BytesIO()
sncosmo.write_griddata_fits(x0, x1, y, f)
# Read it back
f.seek(0)
x0_in, x1_in, y_in = sncosmo.read_griddata_fits(f)
assert_allclose(x0_in, x0)
assert_allclose(x1_in, x1)
assert_allclose(y_in, y)
def test_griddata_fits():
"""Round tripping with write_griddata_fits() and read_griddata_fits()"""
x0 = np.array([0., 1.])
x1 = np.array([0., 1., 2.])
y = np.zeros((2, 3))
f = six.BytesIO()
sncosmo.write_griddata_fits(x0, x1, y, f)
# Read it back
f.seek(0)
x0_in, x1_in, y_in = sncosmo.read_griddata_fits(f)
assert_allclose(x0_in, x0)
assert_allclose(x1_in, x1)
assert_allclose(y_in, y)
phot_d.sort('time')
# Set redshift, initial t0 and MW extinction
z, lensz, it0 = 0.409, 0.216, 57651.2
# Galactic dust model, assuming that the photometry has not been
# corrected for MW extinction.
dust = sncosmo.CCM89Dust()
###########################################################################
# LIGHTCURVE MODEL
# setup Hsiao SN Ia stretch-model
p, w, f = sncosmo.read_griddata_fits(
'/usr/local/lib/python2.7/dist-packages/snpy/typeIa/Hsiao_SED_V3.fits')
mHs = sncosmo.StretchSource(p, w, f, name='hsiao-stretch')
mH = sncosmo.Model(source=mHs,
effects=[dust, dust, dust],
effect_names=['mw', 'host', 'lens'],
effect_frames=['obs', 'rest', 'free'])
ref = copy.copy(mH)
mH.set(mwr_v=3.1)
mH.set(z=z, lensz=lensz)
mH.set(t0=it0)
# Set the initial model, construct a MI_model with it
mH.set(amplitude=3.e-8, hostebv=0.1, hostr_v=3.1, lensr_v=2.0)
# Setup model based on SNoopy fit for 16geu
#geu_source = sn16geu(it0,1.e+9)
