def test_subtract_dark():
cal_dict = sort_ibsen_by_int(DIR)
REFERENCE = copy.deepcopy(cal_dict[5.0]['reference']['tdata'])
DARK = copy.deepcopy(cal_dict[5.0]['darkcurrent']['tdata'])
SINGLE_SPECTRA = copy.deepcopy(cal_dict[5.0]['reference']['tdata'][0])
REFERENCE_MEAN = np.mean(REFERENCE, axis=0)
DARK_MEAN = np.mean(DARK, axis=0)
REFERENCE_CORRECTED = REFERENCE_MEAN - DARK_MEAN
SINGLE_SPECTRA_CORRECTED = SINGLE_SPECTRA - DARK_MEAN
cal_dict = subtract_dark(cal_dict)
assert cal_dict[5.0]['reference']['darkcurrent_corrected'] == True
assert_array_equal(cal_dict[5.0]['reference']['mean'], REFERENCE_CORRECTED)
assert_array_equal(cal_dict[5.0]['reference']['tdata'][0], SINGLE_SPECTRA_CORRECTED)
assert_array_equal(cal_dict[5.0]['reference']['data'][:,0], SINGLE_SPECTRA_CORRECTED)
def prepare_data():
corrected_calc = subtract_dark(sort_ibsen_by_int(DIR))
return corrected_calc