def test_apply_sigmaclip(self):
data = np.ma.MaskedArray([1, -1, 1, -1, 65000], mask=np.zeros(5))
comb = ImCombiner()
# if threshold=1, only 65000 must be masked.
comb._buffer = data.copy()
comb.set_sigma_clip(1)
expect = [0, 0, 0, 0, 1]
comb._apply_rejection()
assert_equal(comb._buffer.mask, expect)
# if threshold=3, 65000 must be masked too using mad_std.
comb._buffer = data.copy()
comb.set_sigma_clip(3)
expect = [0, 0, 0, 0, 1]
comb._apply_rejection()
assert_equal(comb._buffer.mask, expect)
# if threshold=3 and a mask, the mask must be preserved.
comb._buffer = data.copy()
comb._buffer.mask[1] = 1
comb.set_sigma_clip(3)
expect = [0, 1, 0, 0, 1]
comb._apply_rejection()
assert_equal(comb._buffer.mask, expect)
def test_apply_minmax_clip(self):
_min, _max = (0, 20)
outliers = ((1, 2), (6, 2), (2, 9), (5, 2))
outvalues = [1e6, -2e3, 5e3, -7e2]
expect = np.zeros((10, 10))
with NumpyRNGContext(123):
data = np.ma.MaskedArray(np.random.normal(loc=10,
scale=1,
size=[10, 10]),
mask=np.zeros((10, 10)))
for p, v in zip(outliers, outvalues):
data[p] = v
expect[p] = 1
data[0:2, 0:3].mask = 1
expect[0:2, 0:3] = 1
# force assign the buffer
comb = ImCombiner()
comb._buffer = data
# with these limits, only the outliers must be masked
comb.set_minmax_clip(_min, _max)
comb._apply_rejection()
# original mask must be kept
assert_equal(comb._buffer.mask, expect)
def test_apply_sigmaclip_only_higher(self):
data = np.ma.MaskedArray([1, -1, 1, -1, -65000], mask=np.zeros(5))
comb = ImCombiner()
# -65000 must not be masked
comb._buffer = data.copy()
comb.set_sigma_clip((None, 1))
expect = [0, 0, 0, 0, 0]
comb._apply_rejection()
assert_equal(comb._buffer.mask, expect)
def test_apply_minmax_clip_only_higher(self):
_min, _max = (None, 20)
outliers = ((1, 2), (6, 2), (2, 9), (5, 2))
outvalues = [-1e6, 2e3, 5e3, -7e2]
expect = np.zeros((10, 10))
with NumpyRNGContext(123):
data = np.ma.MaskedArray(np.random.normal(loc=10,
scale=1,
size=[10, 10]),
mask=np.zeros((10, 10)))
for p, v in zip(outliers, outvalues):
data[p] = v
if v > _max:
expect[p] = 1
data[0:2, 0:3].mask = 1
expect[0:2, 0:3] = 1
comb = ImCombiner()
comb._buffer = data
comb.set_minmax_clip(_min, _max)
comb._apply_rejection()
assert_equal(comb._buffer.mask, expect)