/usr/lib/python3/dist-packages/photutils/psf/tests/test_prf_adapter.py is in python3-photutils 0.4-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import division
import numpy as np
from numpy.testing import assert_allclose
from .. import PRFAdapter
import pytest
from astropy.modeling.models import Moffat2D
try:
HAS_SCIPY = True # noqa
except ImportError:
HAS_SCIPY = False
def normalize_moffat(mof):
# this is the analytic value needed to get a total flux of 1
mof = mof.copy()
mof.amplitude = (mof.alpha-1)/(np.pi*mof.gamma**2)
return mof
@pytest.mark.parametrize("adapterkwargs", [
dict(xname='x_0', yname='y_0', fluxname=None, renormalize_psf=False),
dict(xname=None, yname=None, fluxname=None, renormalize_psf=False),
dict(xname='x_0', yname='y_0', fluxname='amplitude',
renormalize_psf=False)])
@pytest.mark.skipif('not HAS_SCIPY')
def test_create_eval_prfadapter(adapterkwargs):
mof = Moffat2D(gamma=1, alpha=4.8)
prf = PRFAdapter(mof, **adapterkwargs)
# make sure these can be set without anything freaking out
prf.x_0 = 0.5
prf.y_0 = -0.5
prf.flux = 1.2
prf(0, 0) # just make sure it runs at all
@pytest.mark.parametrize("adapterkwargs", [
dict(xname='x_0', yname='y_0', fluxname=None, renormalize_psf=True),
dict(xname='x_0', yname='y_0', fluxname=None, renormalize_psf=False),
dict(xname=None, yname=None, fluxname=None, renormalize_psf=False)
])
@pytest.mark.skipif('not HAS_SCIPY')
def test_prfadapter_integrates(adapterkwargs):
from scipy.integrate import dblquad
mof = Moffat2D(gamma=1.5, alpha=4.8)
if not adapterkwargs['renormalize_psf']:
mof = normalize_moffat(mof)
prf1 = PRFAdapter(mof, **adapterkwargs)
# first check that the PRF over a central grid ends up summing to the
# integrand over the whole PSF
xg, yg = np.meshgrid(*([(-1, 0, 1)]*2))
evalmod = prf1(xg, yg)
if adapterkwargs['renormalize_psf']:
mof = normalize_moffat(mof)
integrando, itol = dblquad(mof, -1.5, 1.5, lambda x: -1.5, lambda x: 1.5)
assert_allclose(np.sum(evalmod), integrando, atol=itol * 10)
@pytest.mark.parametrize("adapterkwargs", [
dict(xname='x_0', yname='y_0', fluxname=None, renormalize_psf=False),
dict(xname=None, yname=None, fluxname=None, renormalize_psf=False)])
@pytest.mark.skipif('not HAS_SCIPY')
def test_prfadapter_sizematch(adapterkwargs):
from scipy.integrate import dblquad
mof1 = normalize_moffat(Moffat2D(gamma=1, alpha=4.8))
prf1 = PRFAdapter(mof1, **adapterkwargs)
# now try integrating over differently-sampled PRFs
# and check that they match
mof2 = normalize_moffat(Moffat2D(gamma=2, alpha=4.8))
prf2 = PRFAdapter(mof2, **adapterkwargs)
xg1, yg1 = np.meshgrid(*([(-0.5, 0.5)]*2))
xg2, yg2 = np.meshgrid(*([(-1.5, -0.5, 0.5, 1.5)]*2))
eval11 = prf1(xg1, yg1)
eval22 = prf2(xg2, yg2)
integrand, itol = dblquad(mof1, -2, 2, lambda x: -2, lambda x: 2)
# it's a bit of a guess that the above itol is appropriate, but it should
# be a similar ballpark
assert_allclose(np.sum(eval11), np.sum(eval22), atol=itol*100)
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