def test_load_invalid_spice_root(monkeypatch):
monkeypatch.delenv('ALESPICEROOT', raising=False)
reload(ale)
label_file = get_image_label('EN1072174528M')
with pytest.raises(Exception):
ale.load(label_file)
def test_viking1_load(test_kernels, label_type, formatter, image):
label_file = get_image_label(image, label_type)
isis_isd = ale.load(label_file,
props={'kernels': test_kernels[image]},
formatter=formatter)
print(isis_isd)
assert compare_dicts(isis_isd, image_dict[image][formatter]) == []
def test_mex_load(test_kernels, formatter, usgscsm_compare_dict, label):
label_file = get_image_label('h5270_0000_ir2', label)
with patch('ale.drivers.mex_drivers.MexHrscPds3NaifSpiceDriver.binary_ephemeris_times', \
new_callable=PropertyMock) as binary_ephemeris_times, \
patch('ale.drivers.mex_drivers.MexHrscPds3NaifSpiceDriver.binary_exposure_durations', \
new_callable=PropertyMock) as binary_exposure_durations, \
patch('ale.drivers.mex_drivers.MexHrscPds3NaifSpiceDriver.binary_lines', \
new_callable=PropertyMock) as binary_lines, \
patch('ale.drivers.mex_drivers.MexHrscIsisLabelNaifSpiceDriver.ephemeris_time', \
new_callable=PropertyMock) as ephemeris_time, \
patch('ale.drivers.mex_drivers.read_table_data', return_value=12345) as read_table_data, \
patch('ale.drivers.mex_drivers.parse_table', return_value={'EphemerisTime': [255744599.02748165, 255744684.33197814, 255744684.34504557], \
'ExposureTime': [0.012800790786743165, 0.012907449722290038, 0.013227428436279297], \
'LineStart': [1, 6665, 6666]}) as parse_table:
ephemeris_time.return_value = [
255744599.02748, 255744623.61901, 255744635.91477
]
binary_ephemeris_times.return_value = [
255744599.02748165, 255744599.04028246, 255744795.73322123
]
binary_exposure_durations.return_value = [
0.012800790786743165, 0.012800790786743165, 0.013227428436279297
]
binary_lines.return_value = [0.5, 1.5, 15086.5]
usgscsm_isd = ale.load(label_file,
props={'kernels': test_kernels},
formatter=formatter,
verbose='true')
assert compare_dicts(
usgscsm_isd,
usgscsm_compare_dict['h5270_0000_ir2'][formatter]) == []
def test_cassini_load(test_kernels, usgscsm_compare_dict):
label_file = get_image_label("N1702360370_1")
usgscsm_isd = ale.load(label_file,
props={'kernels': test_kernels},
formatter='usgscsm')
print(usgscsm_isd)
assert compare_dicts(usgscsm_isd, usgscsm_compare_dict) == []
def test_load(test_kernels, usgscsm_comparison_isd):
label_file = get_image_label('M103595705LE')
usgscsm_isd = ale.load(label_file,
props={'kernels': test_kernels},
formatter='usgscsm')
print(usgscsm_isd)
assert compare_dicts(usgscsm_isd, usgscsm_comparison_isd) == []
def test_cassis_load(test_kernels, isis_compare_dict):
label_file = get_image_label(
"CAS-MCO-2016-11-26T22.32.14.582-RED-01000-B1", "isis")
isis_isd = ale.load(label_file,
props={'kernels': test_kernels},
formatter="isis")
assert compare_dicts(isis_isd, isis_compare_dict) == []
def test_load_mes_with_no_metakernels(tmpdir, monkeypatch, mess_kernels):
monkeypatch.setenv('ALESPICEROOT', str(tmpdir))
# reload module to repopulate ale.spice_root
reload(ale)
updated_kernels = mess_kernels
label_file = get_image_label('EN1072174528M')
tmpdir.mkdir('mes')
# intentially make an mk file with wrong year
with open(tmpdir.join('mes', 'mes_2016_v1.tm'), 'w+') as mk_file:
mk_str = util.write_metakernel_from_kernel_list(updated_kernels)
print(mk_str)
mk_file.write(mk_str)
with pytest.raises(Exception):
usgscsm_isd_obj = ale.load(label_file, verbose=True)
def test_load_mes_from_metakernels(tmpdir, monkeypatch, mess_kernels):
monkeypatch.setenv('ALESPICEROOT', str(tmpdir))
# reload module to repopulate ale.spice_root
reload(ale)
updated_kernels = mess_kernels
label_file = get_image_label('EN1072174528M')
tmpdir.mkdir('mess')
with open(tmpdir.join('mess', 'mess_2015_v1.tm'), 'w+') as mk_file:
mk_str = util.write_metakernel_from_kernel_list(updated_kernels)
print(mk_str)
mk_file.write(mk_str)
usgscsm_isd_obj = ale.load(label_file, verbose=True)
assert usgscsm_isd_obj['name_platform'] == 'MESSENGER'
assert usgscsm_isd_obj['name_sensor'] == 'MERCURY DUAL IMAGING SYSTEM NARROW ANGLE CAMERA'
assert usgscsm_isd_obj['name_model'] == 'USGS_ASTRO_FRAME_SENSOR_MODEL'
def test_load_invalid_label():
with pytest.raises(Exception):
ale.load('Not a label path')
def test_load(test_kernels):
isd = {
'radii': {
'semimajor': 1737.4,
'semiminor': 1737.4,
'unit': 'km'
},
'sensor_position': {
'positions':
np.array([[195490.61933009, 211972.79163854, -1766965.21759375],
[194934.34274256, 211332.14192709, -1767099.36601459],
[194378.02078141, 210691.44358962, -1767233.10640484],
[193821.65246371, 210050.69819792, -1767366.43865632],
[193265.23762617, 209409.90567475, -1767499.36279925],
[192708.77531467, 208769.0676026, -1767631.87872367]]),
'velocities':
np.array([[-1069.71186948, -1231.97377674, -258.3672068],
[-1069.80166655, -1232.06495814, -257.58238805],
[-1069.89121909, -1232.15585752, -256.7975062],
[-1069.98052705, -1232.24647484, -256.01256158],
[-1070.06959044, -1232.3368101, -255.2275542],
[-1070.15840923, -1232.42686325, -254.44248439]]),
'unit':
'm'
},
'sun_position': {
'positions':
np.array([[9.50465237e+10, 1.15903815e+11, 3.78729685e+09]]),
'velocities':
np.array([[285707.13474515, -232731.15884149, 592.91742112]]),
'unit':
'm'
},
'sensor_orientation': {
'quaternions':
np.array([[-0.19095485, -0.08452708, 0.88748467, -0.41080698],
[-0.19073945, -0.08442789, 0.88753312, -0.41082276],
[-0.19052404, -0.08432871, 0.88758153, -0.41083852],
[-0.19030862, -0.08422952, 0.88762988, -0.41085426],
[-0.19009352, -0.08412972, 0.88767854, -0.41086914],
[-0.18987892, -0.08402899, 0.88772773, -0.41088271]])
},
'detector_sample_summing': 1,
'detector_line_summing': 1,
'focal_length_model': {
'focal_length': 72.45
},
'detector_center': {
'line': 0.5,
'sample': 2048.0
},
'starting_detector_line': 0,
'starting_detector_sample': 1,
'focal2pixel_lines': [0, -142.85714285714286, 0],
'focal2pixel_samples': [0, 0, -142.85714285714286],
'optical_distortion': {
'kaguyatc': {
'x':
[-0.0009649900000000001, 0.00098441, 8.5773e-06, -3.7438e-06],
'y':
[-0.0013796, 1.3502e-05, 2.7251e-06, -6.193800000000001e-06]
}
},
'image_lines': 400,
'image_samples': 3208,
'name_platform': 'SELENE-M',
'name_sensor': 'Terrain Camera 1',
'reference_height': {
'maxheight': 1000,
'minheight': -1000,
'unit': 'm'
},
'name_model': 'USGS_ASTRO_LINE_SCANNER_SENSOR_MODEL',
'interpolation_method': 'lagrange',
'line_scan_rate': [[0.5, -1.300000011920929, 0.006500000000000001]],
'starting_ephemeris_time': 292234259.82293594,
'center_ephemeris_time': 292234261.12293595,
't0_ephemeris': -1.300000011920929,
'dt_ephemeris': 0.5200000047683716,
't0_quaternion': -1.300000011920929,
'dt_quaternion': 0.5200000047683716
}
label_file = get_image_label('TC1S2B0_01_06691S820E0465')
with patch('ale.drivers.selene_drivers.KaguyaTcPds3NaifSpiceDriver.reference_frame', \
new_callable=PropertyMock) as mock_reference_frame:
mock_reference_frame.return_value = 'IAU_MOON'
usgscsm_isd = ale.load(label_file,
props={'kernels': test_kernels},
formatter='usgscsm')
print(usgscsm_isd)
assert compare_dicts(usgscsm_isd, isd) == []
def test_load(test_kernels):
isd = {
'radii': {
'semimajor': 1737.4,
'semiminor': 1737.4,
'unit': 'km'
},
'sensor_position': {
'positions':
np.array([[195493.28614388, 211984.05137213, -1766966.32185819],
[194937.01104181, 211343.39987087, -1767100.47633473],
[194380.68920347, 210702.70097122, -1767234.22276254],
[193824.32093681, 210061.95495794, -1767367.56104995],
[193267.90484827, 209421.16305764, -1767500.49120063],
[192711.44397634, 208780.32318594, -1767633.01318365]]),
'velocities':
np.array([[-1069.71225785, -1231.97438089, -258.37880523],
[-1069.80205939, -1232.06556741, -257.5939851],
[-1069.89161639, -1232.15647191, -256.80910187],
[-1069.98092881, -1232.24709434, -256.02415587],
[-1070.06999666, -1232.33743471, -255.2391471],
[-1070.15881991, -1232.42749298, -254.4540759]]),
'unit':
'm'
},
'sun_position': {
'positions':
np.array([[9.50465237e+10, 1.15903815e+11, 3.78729685e+09]]),
'velocities':
np.array([[285707.13474515, -232731.15884149, 592.91742112]]),
'unit':
'm'
},
'sensor_orientation': {
'quaternions':
np.array([[-0.19095485, -0.08452708, 0.88748467, -0.41080698],
[-0.19073945, -0.08442789, 0.88753312, -0.41082276],
[-0.19052404, -0.08432871, 0.88758153, -0.41083852],
[-0.19030862, -0.08422952, 0.88762988, -0.41085426],
[-0.19009352, -0.08412972, 0.88767854, -0.41086914],
[-0.18987892, -0.08402899, 0.88772773, -0.41088271]])
},
'detector_sample_summing': 1,
'detector_line_summing': 1,
'focal_length_model': {
'focal_length': 72.45
},
'detector_center': {
'line': 0.5,
'sample': 2048.0
},
'starting_detector_line': 0,
'starting_detector_sample': 1,
'focal2pixel_lines': [0, -142.85714285714286, 0],
'focal2pixel_samples': [0, 0, -142.85714285714286],
'optical_distortion': {
'kaguyatc': {
'x':
[-0.0009649900000000001, 0.00098441, 8.5773e-06, -3.7438e-06],
'y':
[-0.0013796, 1.3502e-05, 2.7251e-06, -6.193800000000001e-06]
}
},
'image_lines': 400,
'image_samples': 3208,
'name_platform': 'SELENE-M',
'name_sensor': 'Terrain Camera 1',
'reference_height': {
'maxheight': 1000,
'minheight': -1000,
'unit': 'm'
},
'name_model': 'USGS_ASTRO_LINE_SCANNER_SENSOR_MODEL',
'interpolation_method': 'lagrange',
'line_scan_rate': [[0.5, -1.300000011920929, 0.006500000000000001]],
'starting_ephemeris_time': 292234259.82293594,
'center_ephemeris_time': 292234261.12293595,
't0_ephemeris': -1.300000011920929,
'dt_ephemeris': 0.5200000047683716,
't0_quaternion': -1.300000011920929,
'dt_quaternion': 0.5200000047683716
}
label_file = get_image_label('TC1S2B0_01_06691S820E0465')
with patch('ale.drivers.selene_drivers.KaguyaTcPds3NaifSpiceDriver.reference_frame', \
new_callable=PropertyMock) as mock_reference_frame:
mock_reference_frame.return_value = 'IAU_MOON'
usgscsm_isd = ale.load(label_file,
props={'kernels': test_kernels},
formatter='usgscsm')
print(usgscsm_isd)
assert compare_dicts(usgscsm_isd, isd) == []
def test_dawn_load(test_kernels, usgscsm_compare_dict):
label_file = get_image_label('FC21A0038582_15170161546F6F')
usgscsm_isd = ale.load(label_file,
props={'kernels': test_kernels},
formatter='usgscsm')
assert compare_dicts(usgscsm_isd, usgscsm_compare_dict) == []