def test_cosmicray_lacosmic_does_not_change_input():
ccd_data = ccd_data_func()
original = ccd_data.copy()
error = np.zeros_like(ccd_data)
ccd = cosmicray_lacosmic(ccd_data)
np.testing.assert_array_equal(original.data, ccd_data.data)
assert original.unit == ccd_data.unit
def test_cosmicray_lacosmic_ccddata():
ccd_data = ccd_data_func(data_scale=DATA_SCALE)
threshold = 5
add_cosmicrays(ccd_data, DATA_SCALE, threshold, ncrays=NCRAYS)
noise = DATA_SCALE * np.ones_like(ccd_data.data)
ccd_data.uncertainty = noise
nccd_data = cosmicray_lacosmic(ccd_data, sigclip=5)
def test_cosmicray_lacosmic_detects_inconsistent_units():
# This is intended to detect cases like a ccd with units
# of adu, a readnoise in electrons and a gain in adu / electron.
# That is not internally inconsistent.
ccd_data = ccd_data_func(data_scale=DATA_SCALE)
ccd_data.unit = 'adu'
threshold = 5
add_cosmicrays(ccd_data, DATA_SCALE, threshold, ncrays=NCRAYS)
noise = DATA_SCALE * np.ones_like(ccd_data.data)
ccd_data.uncertainty = noise
readnoise = 6.5 * u.electron
# The units below are deliberately incorrect.
gain = 2.0 * u.adu / u.electron
with pytest.raises(ValueError) as e:
cosmicray_lacosmic(ccd_data,
gain=gain,
gain_apply=True,
readnoise=readnoise)
assert 'Inconsistent units' in str(e.value)
def test_cosmicray_lacosmic_accepts_quantity_gain():
ccd_data = ccd_data_func(data_scale=DATA_SCALE)
threshold = 5
add_cosmicrays(ccd_data, DATA_SCALE, threshold, ncrays=NCRAYS)
noise = DATA_SCALE * np.ones_like(ccd_data.data)
ccd_data.uncertainty = noise
# The units below are the point of the test
gain = 2.0 * u.electron / u.adu
# Since gain and ccd_data have units, the readnoise should too.
readnoise = 6.5 * u.electron
new_ccd = cosmicray_lacosmic(ccd_data, gain=gain, gain_apply=True)
def test_cosmicray_gain_correct(array_input, gain_correct_data):
# Add regression check for #705 and for the new gain_correct
# argument.
# The issue is that cosmicray_lacosmic gain-corrects the
# data and returns that gain corrected data. That is not the
# intent...
ccd_data = ccd_data_func(data_scale=DATA_SCALE)
threshold = 5
add_cosmicrays(ccd_data, DATA_SCALE, threshold, ncrays=NCRAYS)
noise = DATA_SCALE * np.ones_like(ccd_data.data)
ccd_data.uncertainty = noise
# No units here on purpose.
gain = 2.0
# Don't really need to set this (6.5 is the default value) but want to
# make lack of units explicit.
readnoise = 6.5
if array_input:
new_data, cr_mask = cosmicray_lacosmic(ccd_data.data,
gain=gain,
gain_apply=gain_correct_data)
else:
new_ccd = cosmicray_lacosmic(ccd_data,
gain=gain,
gain_apply=gain_correct_data)
new_data = new_ccd.data
cr_mask = new_ccd.mask
# Fill masked locations with 0 since there is no simple relationship
# between the original value and the corrected value.
orig_data = np.ma.array(ccd_data.data, mask=cr_mask).filled(0)
new_data = np.ma.array(new_data.data, mask=cr_mask).filled(0)
if gain_correct_data:
gain_for_test = gain
else:
gain_for_test = 1.0
np.testing.assert_allclose(gain_for_test * orig_data, new_data)
def test_cosmicray_lacosmic_warns_on_ccd_in_electrons(recwarn):
# Check that an input ccd in electrons raises a warning.
ccd_data = ccd_data_func(data_scale=DATA_SCALE)
# The unit below is important for the test; this unit on
# input is supposed to raise an error.
ccd_data.unit = u.electron
threshold = 5
add_cosmicrays(ccd_data, DATA_SCALE, threshold, ncrays=NCRAYS)
noise = DATA_SCALE * np.ones_like(ccd_data.data)
ccd_data.uncertainty = noise
# No units here on purpose.
gain = 2.0
# Don't really need to set this (6.5 is the default value) but want to
# make lack of units explicit.
readnoise = 6.5
new_ccd = cosmicray_lacosmic(ccd_data,
gain=gain,
gain_apply=True,
readnoise=readnoise)
assert len(recwarn) == 1
assert "Image unit is electron" in str(recwarn.pop())
def test_cosmicray_lacosmic_check_data():
ccd_data = ccd_data_func(data_scale=DATA_SCALE)
with pytest.raises(TypeError):
noise = DATA_SCALE * np.ones_like(ccd_data.data)
cosmicray_lacosmic(10, noise)
def test_cosmicray_lacosmic():
ccd_data = ccd_data_func(data_scale=DATA_SCALE)
threshold = 5
add_cosmicrays(ccd_data, DATA_SCALE, threshold, ncrays=NCRAYS)
noise = DATA_SCALE * np.ones_like(ccd_data.data)
data, crarr = cosmicray_lacosmic(ccd_data.data, sigclip=5)
