def source_morphology(in_image, ext_name, **kwargs):
fo = fits.open(in_image, "append")
hdu = fo[ext_name]
segm_obj = SegmentationImage(fo["DEBLEND"].data)
errmap = fo["WEIGHT_MAP"].data
seg_props = fo["DEBLEND_PROPS"].data
im = hdu.data
bkg_estimator = photutils.MedianBackground()
bkg = photutils.Background2D(hdu.data, (50, 50),
bkg_estimator=bkg_estimator)
im -= bkg.background
npix = im.shape[0]
center_slice = segm_obj.data[int(npix / 2) - 2:int(npix / 2) + 2,
int(npix / 2) - 2:int(npix / 2) + 2]
central_index = np.where(seg_props["id"] == center_slice[0, 0])[0][0]
fo.flush()
fo.close()
source_morph = statmorph.SourceMorphology(im,
segm_obj,
central_index,
weightmap=errmap,
**kwargs)
return source_morph
def test_catastrophic():
label = 1
image = np.full((3, 3), -1.0)
segmap = np.full((3, 3), label)
gain = 1.0
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image, segmap, label, gain=gain)
assert w[0].category == AstropyUserWarning
assert 'Total flux is nonpositive.' in str(w[0].message)
assert morph.flag_catastrophic == 1
def test_full_gini_segmap():
"""
This produces a "full" Gini segmap.
"""
label = 1
ny, nx = 11, 11
y, x = np.mgrid[0:ny, 0:nx]
image = np.exp(-((x - nx // 2)**2 + (y - ny // 2)**2) / 50)
segmap = np.int64(image > 0.5)
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image, segmap, label, gain=1.0)
assert w[-3].category == AstropyUserWarning
assert 'Full Gini segmap!' in str(w[-3].message)
assert morph.flag == 1
def test_random_noise():
np.random.seed(1)
ny, nx = 11, 11
image = 0.1 * np.random.standard_normal(size=(ny, nx))
weightmap = 0.01 * np.random.standard_normal(size=(ny, nx))
segmap = np.ones((ny, nx), dtype=np.int64)
label = 1
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image,
segmap,
label,
weightmap=weightmap)
assert w[-1].category == AstropyUserWarning
assert morph.flag == 1
def test_negative_source():
label = 1
ny, nx = 51, 51
y, x = np.mgrid[0:ny, 0:nx]
r = np.sqrt((x - nx // 2)**2 + (y - ny // 2)**2)
image = np.ones((ny, nx), dtype=np.float64)
locs = r > 0
image[locs] = 2.0 / r[locs] - 1.0
segmap = np.int64(r < 2)
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image, segmap, label, gain=1.0)
assert w[0].category == AstropyUserWarning
assert 'Total flux sum is negative.' in str(w[0].message)
assert morph.flag == 1
def test_asymmetric():
"""
Test a case in which the asymmetry center is pushed outside of
the image boundaries.
"""
label = 1
y, x = np.mgrid[0:25, 0:25]
image = x - 20
segmap = image > 0
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image, segmap, label, gain=1.0)
assert w[0].category == AstropyUserWarning
assert 'Minimizer tried to exit bounds.' in str(w[0].message)
assert morph.flag == 1
assert morph._use_centroid
def test_empty_gini_segmap():
"""
This pathological case results in an "empty" Gini segmap.
"""
label = 1
np.random.seed(0)
ny, nx = 11, 11
y, x = np.mgrid[0:ny, 0:nx]
image = x - 9.0
segmap = image > 0
image += 0.1 * np.random.standard_normal(size=(ny, nx))
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image, segmap, label, gain=1.0)
assert w[-1].category == AstropyUserWarning
assert 'Segmaps are empty!' in str(w[-1].message)
assert morph.flag == 1
def test_full_segmap():
ny, nx = 11, 11
y, x = np.mgrid[0:ny, 0:nx]
image = np.exp(-(x - 5)**2 - (y - 5)**2)
segmap = np.ones((ny, nx), dtype=np.int64)
label = 1
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image,
segmap,
label,
gain=1.0,
verbose=True)
assert w[-1].category == AstropyUserWarning
assert 'Image is not background-subtracted.' in str(w[-1].message)
assert morph.flag == 1
assert morph._slice_skybox == (slice(0, 0), slice(0, 0))
def test_masked_centroid():
label = 1
ny, nx = 11, 11
y, x = np.mgrid[0:ny, 0:nx]
image = np.exp(-(x - 5)**2 - (y - 5)**2)
segmap = np.int64(image > 1e-3)
mask = np.zeros((ny, nx), dtype=np.bool8)
mask[5, 5] = True
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image,
segmap,
label,
gain=1.0,
mask=mask)
assert w[0].category == AstropyUserWarning
assert 'Centroid is masked.' in str(w[0].message)
assert morph.flag == 1
def test_merger():
"""
Test a "merger" scenario. This manages to produce different Gini
and MID segmaps, as well as a failed Sersic fit.
"""
label = 1
ny, nx = 25, 25
y, x = np.mgrid[0:ny, 0:nx]
image = np.exp(-(x - 8)**2 / 4 - (y - 12)**2)
image += np.exp(-(x - 16)**2 / 4 - (y - 12)**2)
segmap = np.int64(np.abs(image) > 1e-3)
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image, segmap, label, gain=1.0)
assert w[-1].category == AstropyUserWarning
assert 'Gini and MID segmaps are quite different.' in str(
w[-1].message)
assert morph.flag == 1
def test_insufficient_data():
"""
Test insufficient data for Sersic fit (< 7 pixels).
Note that we do not remove outliers.
"""
label = 1
image = np.zeros((2, 3), dtype=np.float64)
image[:, 1] = 1.0
segmap = np.int64(image)
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image,
segmap,
label,
gain=1.0,
n_sigma_outlier=-1)
assert w[-2].category == AstropyUserWarning
assert '[sersic] Not enough data for fit.' in str(w[-2].message)
assert morph.flag == 1
def test_tiny_source():
"""
Test tiny source (actually consisting of a single bright pixel).
Note that we do not remove outliers.
"""
label = 1
image = np.zeros((5, 5), dtype=np.float64)
image[2, 2] = 1.0
segmap = np.int64(image)
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image,
segmap,
label,
gain=1.0,
n_sigma_outlier=-1)
assert w[0].category == AstropyUserWarning
assert 'Nonpositive second moment.' in str(w[0].message)
assert morph.flag == 1
def test_small_source():
np.random.seed(1)
ny, nx = 11, 11
y, x = np.mgrid[0:ny, 0:nx]
image = np.exp(-(x - 5)**2 - (y - 5)**2)
image += 0.001 * np.random.standard_normal(size=(ny, nx))
segmap = np.int64(image > 0.1)
label = 1
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image,
segmap,
label,
gain=1.0,
verbose=True)
assert w[-1].category == AstropyUserWarning
assert 'Single clump!' in str(w[-1].message)
assert morph.flag == 0
assert morph.multimode == 0
assert morph.intensity == 0
def test_bright_pixel():
"""
Test bright pixel outside of main segment. Note that
we do not remove outliers.
"""
label = 1
ny, nx = 11, 11
y, x = np.mgrid[0:ny, 0:nx]
image = np.exp(-(x - 5)**2 - (y - 5)**2)
image[7, 7] = 1.0
segmap = np.int64(image > 1e-3)
segmap[5, 5] = 0
with catch_warnings(AstropyUserWarning) as w:
morph = statmorph.SourceMorphology(image,
segmap,
label,
gain=1.0,
n_sigma_outlier=-1)
assert w[0].category == AstropyUserWarning
assert 'Adding brightest pixel to segmap.' in str(w[0].message)
assert morph.flag == 1
def test_missing_arguments():
label = 1
image = np.ones((3, 3), dtype=np.float64)
segmap = np.ones((3, 3), dtype=np.int64)
with pytest.raises(AssertionError):
_ = statmorph.SourceMorphology(image, segmap, label)