def test_correct_model(setup_cube, instr, det):
'''Test all corrections for full frame data for all detectors.'''
ngroups = 2
nrows = 2048
ncols = 2048
# Set correction parameters
odd_even_columns = True
use_side_ref_pixels = True
side_smoothing_length = 11
side_gain = 1.0
odd_even_rows = False
rpix = 7
dataval = 150
input_model = setup_cube(instr, det, ngroups, nrows, ncols)
input_model.data[0, 0, :, :] = rpix
input_model.data[0, 0, 4:-4, 4:-4] = dataval
correct_model(input_model, odd_even_columns, use_side_ref_pixels,
side_smoothing_length, side_gain, odd_even_rows)
np.testing.assert_almost_equal(np.mean(input_model.data[0, 0, :4, 4:-4]),
0,
decimal=0)
np.testing.assert_almost_equal(np.mean(input_model.data[0, 0, 4:-4, 4:-4]),
dataval - rpix,
decimal=0)
def test_do_corrections_all_detectors(setup_cube, instr, det_list, ngroups, nrows, ncols):
'''Test all corrections for full frame data for all detectors.'''
# Set correction parameters
odd_even_columns = True
use_side_ref_pixels = True
side_smoothing_length = 11
side_gain = 1.0
odd_even_rows = False
rpix = 7
dataval = 150
for det in det_list:
input_model = setup_cube(instr, det, ngroups, nrows, ncols)
input_model.data[0, 0, :, :] = rpix
input_model.data[0, 0, 4:-4, 4:-4] = dataval
correct_model(input_model,
odd_even_columns,
use_side_ref_pixels,
side_smoothing_length,
side_gain,
odd_even_rows)
np.testing.assert_almost_equal(np.mean(input_model.data[0, 0, :4, 4:-4]), rpix - rpix, decimal=0)
np.testing.assert_almost_equal(np.mean(input_model.data[0, 0, 4:-4, 4:-4]), dataval - rpix, decimal=0)
def test_zero_frame(setup_cube):
"""
Tests ZEROFRAME refpix processing.
"""
ngroups = 2
nrows = 2048
ncols = 2048
# Set correction parameters
odd_even_columns = True
use_side_ref_pixels = True
side_smoothing_length = 11
side_gain = 1.0
odd_even_rows = False
rpix = 7
dataval = 150
instr = "NIRCAM"
det = "NRCA1"
# Setup RampModel
input_model = setup_cube(instr, det, ngroups, nrows, ncols)
nints = input_model.shape[0]
input_model.data[0, 0, :, :] = rpix
input_model.data[0, 0, 4:-4, 4:-4] = dataval
# Setup ZEROFRAME
input_model.zeroframe = np.zeros((1, nrows, ncols), dtype=float)
input_model.zeroframe[0, :, :] = rpix / 2.
input_model.zeroframe[0, 4:-4, 4:-4] = dataval / 2.
input_model.zeroframe[0, 5, 5] = 0. # Test a bad pixel.
input_model.meta.exposure.zero_frame = True
correct_model(input_model, odd_even_columns, use_side_ref_pixels,
side_smoothing_length, side_gain, odd_even_rows)
# Make sure the SCI data is as expected.
data = np.zeros(input_model.data.shape, dtype=input_model.data.dtype)
data[0, 0, 4:-4, 4:-4] = dataval - rpix
np.testing.assert_almost_equal(input_model.data, data, decimal=5)
# Check the ZEROFRAME
zeroframe = np.zeros((nints, nrows, ncols), dtype=float)
zeroframe[0, 4:-4, 4:-4] = dataval / 2. - rpix / 2.
zeroframe[0, 5, 5] = 0. # Make sure this pixel is zero.
np.testing.assert_almost_equal(input_model.zeroframe, zeroframe, decimal=5)