def test_ex2d_subimage(self):
specrange = (0, self.nspec)
waverange = self.ww[0], self.ww[-1]
flux, fluxivar, R = ex2d_patch(self.image, self.ivar, self.psf, 0, self.nspec, self.ww)
border = 0
xmin, xmax, ymin, ymax = self.psf.xyrange(specrange, waverange)
xmin = max(0, xmin-border)
xmax = min(self.psf.npix_x, xmax+border)
ymin = max(0, ymin-border)
ymax = min(self.psf.npix_y, ymax+border)
xyrange = (xmin, xmax, ymin, ymax)
subimg = self.image[ymin:ymax, xmin:xmax]
subivar = self.ivar[ymin:ymax, xmin:xmax]
subflux, subfluxivar, subR = ex2d_patch(subimg, subivar, self.psf, \
0, self.nspec, self.ww, xyrange=xyrange)
#- First test for allclose as a hint in case the later
#- bitwise match test fails
self.assertTrue( np.allclose(subflux, flux) )
self.assertTrue( np.allclose(subfluxivar, fluxivar) )
self.assertTrue( np.allclose(subR, R) )
self.assertTrue( np.all(subflux == flux) )
self.assertTrue( np.all(subfluxivar == fluxivar) )
self.assertTrue( np.all(subR == R) )
def test_noiseless_ex2d_sigdecorr(self):
specrange = (0, self.nspec)
ivar = np.ones(self.ivar.shape)
d = ex2d_patch(self.image_orig,
ivar,
self.psf,
0,
self.nspec,
self.ww,
full_output=True)
R = d['R']
flux = d['flux'] #- resolution convolved extracted flux
xflux = d['xflux'] #- original extracted flux
#- Resolution convolved input photons (flux)
rphot = R.dot(self.phot.ravel()).reshape(flux.shape)
#- extracted flux projected back to image
ximg = self.psf.project(self.ww, xflux, verbose=False)
#- Compare inputs to outputs
bias = (flux - rphot) / rphot
dximg = ximg - self.image_orig
self.assertTrue(np.max(np.abs(bias)) < 1e-9)
self.assertTrue(np.max(np.abs(dximg)) < 1e-6)
def test_ex2d_patch(self):
d = ex2d_patch(self.image, self.ivar, self.psf, 0, self.nspec, self.ww, full_output=True)
self.assertEqual(d['flux'].shape, (self.nspec, len(self.ww)))
self.assertEqual(d['ivar'].shape, (self.nspec, len(self.ww)))
ntot = len(self.ww) * self.nspec
self.assertEqual(d['R'].shape, (ntot, ntot))
def test_ex2d_patch(self):
d = ex2d_patch(self.image, self.ivar, self.psf, 0, self.nspec, self.ww, full_output=True)
self.assertEqual(d['flux'].shape, (self.nspec, len(self.ww)))
self.assertEqual(d['ivar'].shape, (self.nspec, len(self.ww)))
ntot = len(self.ww) * self.nspec
self.assertEqual(d['R'].shape, (ntot, ntot))
def test_wave_off_image(self):
ww = self.psf.wmin - 5 + np.arange(10)
nspec = 2
specrange = [0,nspec]
xyrange = self.psf.xyrange(specrange, ww)
phot = np.ones([nspec,len(ww)])
img = self.psf.project(ww, phot, xyrange=xyrange)
ivar = np.ones(img.shape)
flux, fluxivar, R = ex2d_patch(img, ivar, self.psf, 0, self.nspec, ww, xyrange=xyrange)
self.assertTrue( np.all(flux == flux) )
def test_ex2d_subimage(self):
specrange = (0, self.nspec)
waverange = self.ww[0], self.ww[-1]
flux, fluxivar, R = ex2d_patch(self.image, self.ivar, self.psf, 0, self.nspec, self.ww)
border = 0
xmin, xmax, ymin, ymax = self.psf.xyrange(specrange, waverange)
xmin = max(0, xmin-border)
xmax = min(self.psf.npix_x, xmax+border)
ymin = max(0, ymin-border)
ymax = min(self.psf.npix_y, ymax+border)
xyrange = (xmin, xmax, ymin, ymax)
subimg = self.image[ymin:ymax, xmin:xmax]
subivar = self.ivar[ymin:ymax, xmin:xmax]
subflux, subfluxivar, subR = ex2d_patch(subimg, subivar, self.psf, \
0, self.nspec, self.ww, xyrange=xyrange)
#- These arrays pass np.allclose, but sometimes fail np.all on edison.
#- They should be absolutely identical. Leaving this as failing.
self.assertTrue( np.all(subflux == flux) )
self.assertTrue( np.all(subfluxivar == fluxivar) )
self.assertTrue( np.all(subR == R) )
def test_wave_off_image(self):
ww = self.psf.wmin - 5 + np.arange(10)
nspec = 2
specrange = [0,nspec]
xyrange = self.psf.xyrange(specrange, ww)
phot = np.ones([nspec,len(ww)])
img = self.psf.project(ww, phot, xyrange=xyrange)
ivar = np.ones(img.shape)
flux, fluxivar, R = ex2d_patch(img, ivar, self.psf, 0, self.nspec, ww, xyrange=xyrange)
self.assertTrue( np.all(flux == flux) )
def test_ex2d_chi2(self):
from time import time
specrange = (0, self.nspec)
waverange = (self.ww[0], self.ww[-1])
imgvar = 1/self.ivar
xmin, xmax, ymin, ymax = xyrange = self.psf.xyrange(specrange, waverange)
for i in range(3):
pix = self.image_orig + np.random.normal(scale=np.sqrt(imgvar))
d = ex2d_patch(pix, self.ivar, self.psf, 0, self.nspec, self.ww, full_output=True)
flux, ivar, R = d['flux'], d['ivar'], d['R']
rflux = R.dot(self.phot.ravel()).reshape(flux.shape)
chi = (flux - rflux) * np.sqrt(ivar)
#- loose test, just checking for catastrophic failures
self.assertLess(abs(1-np.std(chi)), 0.10)
def test_ex2d_subimage(self):
specrange = (0, self.nspec)
waverange = self.ww[0], self.ww[-1]
flux, fluxivar, R = ex2d_patch(self.image, self.ivar, self.psf, 0,
self.nspec, self.ww)
border = 0
xmin, xmax, ymin, ymax = self.psf.xyrange(specrange, waverange)
xmin = max(0, xmin - border)
xmax = min(self.psf.npix_x, xmax + border)
ymin = max(0, ymin - border)
ymax = min(self.psf.npix_y, ymax + border)
xyrange = (xmin, xmax, ymin, ymax)
subimg = self.image[ymin:ymax, xmin:xmax]
subivar = self.ivar[ymin:ymax, xmin:xmax]
subflux, subfluxivar, subR = ex2d_patch(subimg, subivar, self.psf, \
0, self.nspec, self.ww, xyrange=xyrange)
#- These arrays pass np.allclose, but sometimes fail np.all on edison.
#- They should be absolutely identical. Leaving this as failing.
self.assertTrue(np.all(subflux == flux))
self.assertTrue(np.all(subfluxivar == fluxivar))
self.assertTrue(np.all(subR == R))
def test_ex2d_chi2(self):
from time import time
specrange = (0, self.nspec)
waverange = (self.ww[0], self.ww[-1])
imgvar = 1/self.ivar
xmin, xmax, ymin, ymax = xyrange = self.psf.xyrange(specrange, waverange)
for i in range(3):
pix = self.image_orig + np.random.normal(scale=np.sqrt(imgvar))
d = ex2d_patch(pix, self.ivar, self.psf, 0, self.nspec, self.ww, full_output=True)
flux, ivar, R = d['flux'], d['ivar'], d['R']
rflux = R.dot(self.phot.ravel()).reshape(flux.shape)
chi = (flux - rflux) * np.sqrt(ivar)
#- loose test, just checking for catastrophic failures
self.assertLess(abs(1-np.std(chi)), 0.10)
def test_noiseless_ex2d_sigdecorr(self):
specrange = (0, self.nspec)
ivar = np.ones(self.ivar.shape)
d = ex2d_patch(self.image_orig, ivar, self.psf, 0, self.nspec, self.ww, full_output=True)
R = d['R']
flux = d['flux'] #- resolution convolved extracted flux
xflux = d['xflux'] #- original extracted flux
#- Resolution convolved input photons (flux)
rphot = R.dot(self.phot.ravel()).reshape(flux.shape)
#- extracted flux projected back to image
ximg = self.psf.project(self.ww, xflux, verbose=False)
#- Compare inputs to outputs
bias = (flux - rphot)/rphot
dximg = ximg - self.image_orig
self.assertTrue( np.max(np.abs(bias)) < 1e-9 )
self.assertTrue( np.max(np.abs(dximg)) < 1e-6 )
