def test_lstchain_merge_dl1_hdf5_observed_files(temp_dir_observed_files,
observed_dl1_files):
merged_dl1_observed_file = temp_dir_observed_files / "dl1_LST-1.Run02008_merged.h5"
run_program(
"lstchain_merge_hdf5_files",
"-d",
temp_dir_observed_files,
"-o",
merged_dl1_observed_file,
"--no-image",
"False",
"--smart",
"False",
"--run-number",
"2008",
"--pattern",
"dl1_*.h5",
)
dl1a_df = pd.read_hdf(observed_dl1_files["dl1_file1"],
key=dl1_params_lstcam_key)
dl1b_df = pd.read_hdf(observed_dl1_files["dl1_file1"],
key=dl1_params_lstcam_key)
merged_dl1_df = pd.read_hdf(merged_dl1_observed_file,
key=dl1_params_lstcam_key)
assert merged_dl1_observed_file.is_file()
assert len(dl1a_df) + len(dl1b_df) == len(merged_dl1_df)
assert "dl1/event/telescope/image/LST_LSTCam" in get_dataset_keys(
merged_dl1_observed_file)
assert "dl1/event/telescope/parameters/LST_LSTCam" in get_dataset_keys(
merged_dl1_observed_file)
def test_observed_dl1_validity(observed_dl1_files):
dl1_df = pd.read_hdf(observed_dl1_files["dl1_file1"],
key=dl1_params_lstcam_key)
# The first valid timestamp in the test run corresponds
# to its third event (see night summary)
first_timestamp_nightsummary = 1582059789516351903 # ns
first_event_timestamp = dl1_df["dragon_time"].iloc[2] # third event
dl1_tables = get_dataset_keys(observed_dl1_files["dl1_file1"])
assert 'dl1/event/telescope/monitoring/calibration' in dl1_tables
assert 'dl1/event/telescope/monitoring/flatfield' in dl1_tables
assert 'dl1/event/telescope/monitoring/pedestal' in dl1_tables
assert 'dl1/event/telescope/image/LST_LSTCam' in dl1_tables
assert "alt_tel" in dl1_df.columns
assert "az_tel" in dl1_df.columns
assert "trigger_type" in dl1_df.columns
assert "ucts_trigger_type" in dl1_df.columns
assert "trigger_time" in dl1_df.columns
assert "dragon_time" in dl1_df.columns
assert "tib_time" in dl1_df.columns
assert "ucts_time" in dl1_df.columns
assert np.isclose(
(Time(first_event_timestamp, format='unix') -
Time(first_timestamp_nightsummary / 1e9, format='unix_tai')).to_value(
u.s), 0)
np.testing.assert_allclose(dl1_df["dragon_time"], dl1_df["trigger_time"])
def test_observed_dl1_validity(observed_dl1_files):
dl1_df = pd.read_hdf(observed_dl1_files["dl1_file1"],
key=dl1_params_lstcam_key)
# The first valid timestamp in the test run corresponds
# to its third event (see night summary)
first_timestamp_nightsummary = 1582059789516351903 # ns
first_event_timestamp = dl1_df["dragon_time"].iloc[2] # third event
dl1_tables = get_dataset_keys(observed_dl1_files["dl1_file1"])
assert dl1_params_lstcam_key in dl1_tables
assert dl1_images_lstcam_key in dl1_tables
assert dl1_params_tel_mon_cal_key in dl1_tables
assert dl1_params_tel_mon_ped_key in dl1_tables
assert dl1_params_tel_mon_flat_key in dl1_tables
subarray = SubarrayDescription.from_hdf(observed_dl1_files['dl1_file1'])
assert 1 in subarray.tel
assert subarray.tel[1].name == "LST"
assert "alt_tel" in dl1_df.columns
assert "az_tel" in dl1_df.columns
assert "trigger_type" in dl1_df.columns
assert "ucts_trigger_type" in dl1_df.columns
assert "trigger_time" in dl1_df.columns
assert "dragon_time" in dl1_df.columns
assert "tib_time" in dl1_df.columns
assert "ucts_time" in dl1_df.columns
assert np.isclose(
(Time(first_event_timestamp, format="unix") -
Time(first_timestamp_nightsummary / 1e9, format="unix_tai")).to_value(
u.s),
0,
)
np.testing.assert_allclose(dl1_df["dragon_time"], dl1_df["trigger_time"])