/usr/lib/python3/dist-packages/photutils/isophote/tests/test_fitter.py is in python3-photutils 0.4-1.
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from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import pytest
from astropy.io import fits
from astropy.tests.helper import remote_data
from .make_test_data import make_test_image
from ..fitter import EllipseFitter, CentralEllipseFitter
from ..geometry import EllipseGeometry
from ..harmonics import fit_first_and_second_harmonics
from ..integrator import MEAN
from ..isophote import Isophote
from ..sample import EllipseSample, CentralEllipseSample
from ...datasets import get_path
try:
import scipy # noqa
HAS_SCIPY = True
except ImportError:
HAS_SCIPY = False
DATA = make_test_image(random_state=123)
DEFAULT_POS = 256
def test_gradient():
sample = EllipseSample(DATA, 40.)
sample.update()
assert sample.mean == pytest.approx(200.02, abs=0.01)
assert sample.gradient == pytest.approx(-4.222, abs=0.001)
assert sample.gradient_error == pytest.approx(0.0003, abs=0.0001)
assert sample.gradient_relative_error == pytest.approx(7.45e-05,
abs=1.e-5)
assert sample.sector_area == pytest.approx(2.00, abs=0.01)
@pytest.mark.skipif('not HAS_SCIPY')
def test_fitting_raw():
"""
This test performs a raw (no EllipseFitter), 1-step correction in
one single ellipse coefficient.
"""
# pick first guess ellipse that is off in just
# one of the parameters (eps).
sample = EllipseSample(DATA, 40., eps=2*0.2)
sample.update()
s = sample.extract()
harmonics = fit_first_and_second_harmonics(s[0], s[2])
y0, a1, b1, a2, b2 = harmonics[0]
# when eps is off, b2 is the largest (in absolute value).
assert abs(b2) > abs(a1)
assert abs(b2) > abs(b1)
assert abs(b2) > abs(a2)
correction = (b2 * 2. * (1. - sample.geometry.eps) /
sample.geometry.sma / sample.gradient)
new_eps = sample.geometry.eps - correction
# got closer to test data (eps=0.2)
assert new_eps == pytest.approx(0.21, abs=0.01)
@pytest.mark.skipif('not HAS_SCIPY')
def test_fitting_small_radii():
sample = EllipseSample(DATA, 2.)
fitter = EllipseFitter(sample)
isophote = fitter.fit()
assert isinstance(isophote, Isophote)
assert isophote.ndata == 13
@pytest.mark.skipif('not HAS_SCIPY')
def test_fitting_eps():
# initial guess is off in the eps parameter
sample = EllipseSample(DATA, 40., eps=2*0.2)
fitter = EllipseFitter(sample)
isophote = fitter.fit()
assert isinstance(isophote, Isophote)
g = isophote.sample.geometry
assert g.eps >= 0.19
assert g.eps <= 0.21
@pytest.mark.skipif('not HAS_SCIPY')
def test_fitting_pa():
data = make_test_image(pa=np.pi/4, noise=0.01, random_state=123)
# initial guess is off in the pa parameter
sample = EllipseSample(data, 40)
fitter = EllipseFitter(sample)
isophote = fitter.fit()
g = isophote.sample.geometry
assert g.pa >= (np.pi/4 - 0.05)
assert g.pa <= (np.pi/4 + 0.05)
@pytest.mark.skipif('not HAS_SCIPY')
def test_fitting_xy():
pos = DEFAULT_POS - 5
data = make_test_image(x0=pos, y0=pos, random_state=123)
# initial guess is off in the x0 and y0 parameters
sample = EllipseSample(data, 40)
fitter = EllipseFitter(sample)
isophote = fitter.fit()
g = isophote.sample.geometry
assert g.x0 >= (pos - 1)
assert g.x0 <= (pos + 1)
assert g.y0 >= (pos - 1)
assert g.y0 <= (pos + 1)
@pytest.mark.skipif('not HAS_SCIPY')
def test_fitting_all():
# build test image that is off from the defaults
# assumed by the EllipseSample constructor.
POS = DEFAULT_POS - 5
ANGLE = np.pi / 4
EPS = 2 * 0.2
data = make_test_image(x0=POS, y0=POS, eps=EPS, pa=ANGLE,
random_state=123)
sma = 60.
# initial guess is off in all parameters. We find that the initial
# guesses, especially for position angle, must be kinda close to the
# actual value. 20% off max seems to work in this case of high SNR.
sample = EllipseSample(data, sma, position_angle=(1.2 * ANGLE))
fitter = EllipseFitter(sample)
isophote = fitter.fit()
assert isophote.stop_code == 0
g = isophote.sample.geometry
assert g.x0 >= (POS - 1.5) # position within 1.5 pixel
assert g.x0 <= (POS + 1.5)
assert g.y0 >= (POS - 1.5)
assert g.y0 <= (POS + 1.5)
assert g.eps >= (EPS - 0.01) # eps within 0.01
assert g.eps <= (EPS + 0.01)
assert g.pa >= (ANGLE - 0.05) # pa within 5 deg
assert g.pa <= (ANGLE + 0.05)
sample_m = EllipseSample(data, sma, position_angle=(1.2 * ANGLE),
integrmode=MEAN)
fitter_m = EllipseFitter(sample_m)
isophote_m = fitter_m.fit()
assert isophote_m.stop_code == 0
@remote_data
@pytest.mark.skipif('not HAS_SCIPY')
class TestM51(object):
def setup_class(self):
path = get_path('isophote/M51.fits', location='photutils-datasets',
cache=True)
hdu = fits.open(path)
self.data = hdu[0].data
hdu.close()
def test_m51(self):
# here we evaluate the detailed convergence behavior
# for a particular ellipse where we can see the eps
# parameter jumping back and forth.
# sample = EllipseSample(self.data, 13.31000001, eps=0.16,
# position_angle=((-37.5+90)/180.*np.pi))
# sample.update()
# fitter = EllipseFitter(sample)
# isophote = fitter.fit()
# we start the fit with initial values taken from
# previous isophote, as determined by the old code.
# sample taken in high SNR region
sample = EllipseSample(self.data, 21.44, eps=0.18,
position_angle=(36./180.*np.pi))
fitter = EllipseFitter(sample)
isophote = fitter.fit()
assert isophote.ndata == 119
assert isophote.intens == pytest.approx(685.4, abs=0.1)
# last sample taken by the original code, before turning inwards.
sample = EllipseSample(self.data, 61.16, eps=0.219,
position_angle=((77.5+90)/180*np.pi))
fitter = EllipseFitter(sample)
isophote = fitter.fit()
assert isophote.ndata == 382
assert isophote.intens == pytest.approx(155.0, abs=0.1)
def test_m51_outer(self):
# sample taken at the outskirts of the image, so many
# data points lay outside the image frame. This checks
# for the presence of gaps in the sample arrays.
sample = EllipseSample(self.data, 330., eps=0.2,
position_angle=((90)/180*np.pi),
integrmode='median')
fitter = EllipseFitter(sample)
isophote = fitter.fit()
assert not np.any(isophote.sample.values[2] == 0)
def test_m51_central(self):
# this code finds central x and y offset by about 0.1 pixel wrt the
# spp code. In here we use as input the position computed by this
# code, thus this test is checking just the extraction algorithm.
g = EllipseGeometry(257.02, 258.1, 0.0, 0.0, 0.0, 0.1, False)
sample = CentralEllipseSample(self.data, 0.0, geometry=g)
fitter = CentralEllipseFitter(sample)
isophote = fitter.fit()
# the central pixel intensity is about 3% larger than
# found by the spp code.
assert isophote.ndata == 1
assert isophote.intens <= 7560.
assert isophote.intens >= 7550.
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