def test_invalid_method(self):
n = 10
d = np.ones((10, 10))
l = [FrameData(d, unit='adu') for i in range(n)]
comb = ImCombiner()
with pytest.raises(ValueError,
match='hulk-smash is not a valid '
'combining method.'):
comb.combine(l, method='hulk-smash')
def test_mergeheaders_no_merge(self):
images = self.create_images()
comb = ImCombiner(merge_header='no_merge')
res = comb.combine(images, method='sum')
assert_equal(res.meta, {
'astropop imcombine nimages': 30,
'astropop imcombine method': 'sum'
})
# explicit setting
comb = ImCombiner()
comb.set_merge_header('no_merge')
res = comb.combine(images, method='sum')
assert_equal(res.meta, {
'astropop imcombine nimages': 30,
'astropop imcombine method': 'sum'
})
def test_mergeheaders_first(self):
images = self.create_images()
expect = images[0].meta
expect.update({
'astropop imcombine nimages': 30,
'astropop imcombine method': 'sum'
})
comb = ImCombiner(merge_header='first')
res = comb.combine(images, method='sum')
assert_equal(res.meta, expect)
# explicit setting
comb = ImCombiner()
comb.set_merge_header('first')
res = comb.combine(images, method='sum')
assert_equal(res.meta, expect)
def test_mergeheaders_default(self):
# default is 'no_merge'
images = self.create_images()
comb = ImCombiner()
res = comb.combine(images, method='sum')
assert_equal(res.meta, {
'astropop imcombine nimages': 30,
'astropop imcombine method': 'sum'
})
def test_mergeheaders_only_equal(self):
images = self.create_images()
expect = {
'astropop imcombine nimages': 30,
'astropop imcombine method': 'sum',
'first_equal': 1,
'second_equal': 2
}
comb = ImCombiner(merge_header='only_equal')
res = comb.combine(images, method='sum')
assert_equal(res.meta, expect)
# explicit setting
comb = ImCombiner()
comb.set_merge_header('only_equal')
res = comb.combine(images, method='sum')
assert_equal(res.meta, expect)
def test_mergeheaders_selected_keys(self):
images = self.create_images()
keys = ['first_equal', 'third_differ', 'first_differ']
expect = {
'astropop imcombine nimages': 30,
'astropop imcombine method': 'sum',
'first_equal': 1,
'third_differ': 0,
'first_differ': 0
}
comb = ImCombiner(merge_header='selected_keys', merge_header_keys=keys)
res = comb.combine(images, method='sum')
assert_equal(res.meta, expect)
# explicit setting
comb = ImCombiner()
comb.set_merge_header('selected_keys', keys=keys)
res = comb.combine(images, method='sum')
assert_equal(res.meta, expect)
def test_combine_median_simple(self):
arr, base = self.create_framedata_array([0.8, 1.0, 1.2, 1.0, 1.2],
size=[1024, 1024],
unct=0.1)
comb = ImCombiner()
# the unclipped median of [0.8, 1.0, 1.2, 1.0, 1.2] is 1.0
# std([0.8, 1.0, 1.2, 1.0, 1.2])/sqrt(5) = 0.06693280212272602
res = comb.combine(arr, method='median')
assert_equal(res.data, base)
assert_almost_equal(res.uncertainty, 0.06693280212272602 * base)
assert_equal(res.meta['astropop imcombine nimages'], 5)
assert_equal(res.meta['astropop imcombine method'], 'median')
# same for 3 sigma clipping
comb.set_sigma_clip(3, 'median', 'mad_std')
res = comb.combine(arr, method='median')
assert_equal(res.data, base)
assert_almost_equal(res.uncertainty, 0.06693280212272602 * base)
assert_equal(res.meta['astropop imcombine nimages'], 5)
assert_equal(res.meta['astropop imcombine method'], 'median')
def test_combine_mask_mean(self):
comb = ImCombiner()
images = [None] * 10
shape = (10, 10)
for i in range(10):
mask = np.zeros(shape)
# all (2, 5) elements are masked, so the result must be
mask[2, 5] = 1
images[i] = FrameData(np.ones(shape), unit='adu', mask=mask)
# these points in result must no be masked
images[5].mask[7, 7] = 1
images[2].mask[7, 7] = 1
images[8].mask[8, 8] = 1
expect = np.zeros(shape)
expect[2, 5] = 1
res = comb.combine(images, 'mean')
assert_equal(res.mask, expect)