def test_science_state():
assert erfa_astrom.get().__class__ is ErfaAstrom
res = 300 * u.s
with erfa_astrom.set(ErfaAstromInterpolator(res)):
assert isinstance(erfa_astrom.get(), ErfaAstromInterpolator)
erfa_astrom.get().mjd_resolution == res.to_value(u.day)
# context manager should have switched it back
assert erfa_astrom.get().__class__ is ErfaAstrom
# must be a subclass of BaseErfaAstrom
with pytest.raises(TypeError):
erfa_astrom.set('foo')
def test_interpolation_broadcasting():
from astropy.coordinates.angle_utilities import golden_spiral_grid
from astropy.coordinates import SkyCoord, EarthLocation, AltAz
from astropy.time import Time
import astropy.units as u
from astropy.coordinates.erfa_astrom import (erfa_astrom,
ErfaAstromInterpolator)
# 1000 gridded locations on the sky
rep = golden_spiral_grid(100)
coord = SkyCoord(rep)
# 30 times over the space of 1 hours
times = Time('2020-01-01T20:00') + np.linspace(-0.5, 0.5, 30) * u.hour
lst1 = EarthLocation(
lon=-17.891498 * u.deg,
lat=28.761443 * u.deg,
height=2200 * u.m,
)
# note the use of broadcasting so that 300 times are broadcast against 1000 positions
aa_frame = AltAz(obstime=times[:, np.newaxis], location=lst1)
aa_coord = coord.transform_to(aa_frame)
with erfa_astrom.set(ErfaAstromInterpolator(300 * u.s)):
aa_coord_interp = coord.transform_to(aa_frame)
assert aa_coord.shape == aa_coord_interp.shape
assert np.all(aa_coord.separation(aa_coord_interp) < 1 * u.microarcsecond)
def test_erfa_astrom():
# I was having a pretty hard time in coming
# up with a unit test only testing the astrom provider
# that would not just test its implementation with its implementation
# so we test a coordinate conversion using it
location = EarthLocation(
lon=-17.891105 * u.deg,
lat=28.761584 * u.deg,
height=2200 * u.m,
)
obstime = Time('2020-01-01T18:00') + np.linspace(0, 1, 100) * u.hour
altaz = AltAz(location=location, obstime=obstime)
coord = SkyCoord(ra=83.63308333, dec=22.0145, unit=u.deg)
# do the reference transformation, no interpolation
ref = coord.transform_to(altaz)
with erfa_astrom.set(ErfaAstromInterpolator(300 * u.s)):
interp_300s = coord.transform_to(altaz)
# make sure they are actually different
assert np.any(ref.separation(interp_300s) > 0.005 * u.microarcsecond)
# make sure the resolution is as good as we expect
assert np.all(ref.separation(interp_300s) < 1 * u.microarcsecond)
def add_icrs_position_params(data, source_pos):
"""
Updating data with ICRS position values of reconstructed positions in
RA DEC coordinates and add column on separation form true source position.
"""
reco_alt = data["reco_alt"]
reco_az = data["reco_az"]
time_utc = Time(data["dragon_time"], format="unix", scale="utc")
reco_altaz = SkyCoord(alt=reco_alt,
az=reco_az,
frame=AltAz(obstime=time_utc, location=location))
with erfa_astrom.set(ErfaAstromInterpolator(300 * u.s)):
reco_icrs = reco_altaz.transform_to(frame="icrs")
data["RA"] = reco_icrs.ra.to(u.deg)
data["Dec"] = reco_icrs.dec.to(u.deg)
data["theta"] = reco_icrs.separation(source_pos).to(u.deg)
return data
def create_event_list(
data, run_number, source_name, source_pos, effective_time, elapsed_time
):
"""
Create the event_list BinTableHDUs from the given data
Parameters
----------
Data: DL2 data file
'astropy.table.QTable'
Run: Run number
Int
Source_name: Name of the source
Str
Source_pos: Ra/Dec position of the source
'astropy.coordinates.SkyCoord'
Effective_time: Effective time of triggered events of the run
Float
Elapsed_time: Total elapsed time of triggered events of the run
Float
Returns
-------
Events HDU: `astropy.io.fits.BinTableHDU`
GTI HDU: `astropy.io.fits.BinTableHDU`
Pointing HDU: `astropy.io.fits.BinTableHDU`
"""
tel_list = np.unique(data["tel_id"])
# Timing parameters
t_start = data["dragon_time"].value[0]
t_stop = data["dragon_time"].value[-1]
time_utc = Time(data["dragon_time"], format="unix", scale="utc")
t_start_iso = time_utc[0].to_value("iso", "date_hms")
t_stop_iso = time_utc[-1].to_value("iso", "date_hms")
date_obs = t_start_iso[:10]
time_obs = t_start_iso[11:]
date_end = t_stop_iso[:10]
time_end = t_stop_iso[11:]
MJDREF = Time("1970-01-01T00:00", scale="utc")
# Position parameters
reco_alt = data["reco_alt"]
reco_az = data["reco_az"]
pointing_alt = data["pointing_alt"]
pointing_az = data["pointing_az"]
reco_altaz = SkyCoord(
alt=reco_alt, az=reco_az, frame=AltAz(obstime=time_utc, location=location)
)
pnt_icrs = SkyCoord(
alt=pointing_alt[0],
az=pointing_az[0],
frame=AltAz(obstime=time_utc[0], location=location),
).transform_to(frame="icrs")
with erfa_astrom.set(ErfaAstromInterpolator(30 * u.s)):
reco_icrs = reco_altaz.transform_to(frame="icrs")
# Observation modes
source_pointing_diff = source_pos.separation(pnt_icrs)
if np.around(source_pointing_diff, 1) == wobble_offset:
mode = "WOBBLE"
elif np.around(source_pointing_diff, 1) > 1 * u.deg:
mode = "OFF"
elif np.around(source_pointing_diff, 1) == 0.0 * u.deg:
mode = "ON"
else:
# Nomenclature is to be worked out or have a separate way to mark mispointings
mode = "UNDETERMINED"
log.info(
"Source pointing difference with camera pointing"
f" is {source_pointing_diff:.3f}"
)
event_table = QTable(
{
"EVENT_ID": data["event_id"],
"TIME": data["dragon_time"],
"RA": reco_icrs.ra.to(u.deg),
"DEC": reco_icrs.dec.to(u.deg),
"ENERGY": data["reco_energy"],
# Optional columns
"GAMMANESS": data["gh_score"],
"MULTIP": u.Quantity(np.repeat(len(tel_list), len(data)), dtype=int),
"GLON": reco_icrs.galactic.l.to(u.deg),
"GLAT": reco_icrs.galactic.b.to(u.deg),
"ALT": reco_alt.to(u.deg),
"AZ": reco_az.to(u.deg),
}
)
gti_table = QTable(
{
"START": u.Quantity(t_start, unit=u.s, ndmin=1),
"STOP": u.Quantity(t_stop, unit=u.s, ndmin=1),
}
)
pnt_table = QTable(
{
"TIME": u.Quantity(t_start, unit=u.s, ndmin=1),
"RA_PNT": u.Quantity(pnt_icrs.ra.to(u.deg), ndmin=1),
"DEC_PNT": u.Quantity(pnt_icrs.dec.to(u.deg), ndmin=1),
"ALT_PNT": u.Quantity(pointing_alt[0].to(u.deg), ndmin=1),
"AZ_PNT": u.Quantity(pointing_az[0].to(u.deg), ndmin=1),
}
)
# Adding the meta data
# Comments can be added later for relevant metadata
# Event table metadata
ev_header = DEFAULT_HEADER.copy()
ev_header["CREATED"] = Time.now().utc.iso
ev_header["HDUCLAS1"] = "EVENTS"
ev_header["OBS_ID"] = run_number
ev_header["DATE-OBS"] = date_obs
ev_header["TIME-OBS"] = time_obs
ev_header["DATE-END"] = date_end
ev_header["TIME-END"] = time_end
ev_header["TSTART"] = t_start
ev_header["TSTOP"] = t_stop
ev_header["MJDREFI"] = int(MJDREF.mjd)
ev_header["MJDREFF"] = MJDREF.mjd - int(MJDREF.mjd)
ev_header["TIMEUNIT"] = "s"
ev_header["TIMESYS"] = "UTC"
ev_header["TIMEREF"] = "TOPOCENTER"
ev_header["ONTIME"] = elapsed_time
ev_header["TELAPSE"] = t_stop - t_start
ev_header["DEADC"] = effective_time / elapsed_time
ev_header["LIVETIME"] = effective_time
ev_header["OBJECT"] = source_name
ev_header["OBS_MODE"] = mode
ev_header["N_TELS"] = len(tel_list)
ev_header["TELLIST"] = "LST-" + " ".join(map(str, tel_list))
ev_header["INSTRUME"] = f"{ev_header['TELLIST']}"
ev_header["RA_PNT"] = pnt_icrs.ra.to_value()
ev_header["DEC_PNT"] = pnt_icrs.dec.to_value()
ev_header["ALT_PNT"] = data["pointing_alt"].mean().to_value(u.deg)
ev_header["AZ_PNT"] = data["pointing_az"].mean().to_value(u.deg)
ev_header["RA_OBJ"] = source_pos.ra.to_value()
ev_header["DEC_OBJ"] = source_pos.dec.to_value()
ev_header["FOVALIGN"] = "RADEC"
# GTI table metadata
gti_header = DEFAULT_HEADER.copy()
gti_header["CREATED"] = Time.now().utc.iso
gti_header["HDUCLAS1"] = "GTI"
gti_header["OBS_ID"] = run_number
gti_header["MJDREFI"] = ev_header["MJDREFI"]
gti_header["MJDREFF"] = ev_header["MJDREFF"]
gti_header["TIMESYS"] = ev_header["TIMESYS"]
gti_header["TIMEUNIT"] = ev_header["TIMEUNIT"]
gti_header["TIMEREF"] = ev_header["TIMEREF"]
# Pointing table metadata
pnt_header = DEFAULT_HEADER.copy()
pnt_header["CREATED"] = Time.now().utc.iso
pnt_header["HDUCLAS1"] = "POINTING"
pnt_header["OBS_ID"] = run_number
pnt_header["MJDREFI"] = ev_header["MJDREFI"]
pnt_header["MJDREFF"] = ev_header["MJDREFF"]
pnt_header["TIMEUNIT"] = ev_header["TIMEUNIT"]
pnt_header["TIMESYS"] = ev_header["TIMESYS"]
pnt_header["OBSGEO-L"] = (
location.lon.to_value(u.deg),
"Geographic longitude of telescope (deg)",
)
pnt_header["OBSGEO-B"] = (
location.lat.to_value(u.deg),
"Geographic latitude of telescope (deg)",
)
pnt_header["OBSGEO-H"] = (
round(location.height.to_value(u.m), 2),
"Geographic latitude of telescope (m)",
)
pnt_header["TIMEREF"] = ev_header["TIMEREF"]
# Create HDUs
event = fits.BinTableHDU(event_table, header=ev_header, name="EVENTS")
gti = fits.BinTableHDU(gti_table, header=gti_header, name="GTI")
pointing = fits.BinTableHDU(pnt_table, header=pnt_header, name="POINTING")
return event, gti, pointing
from ..apply import predict_energy, predict_disp, predict_separator
from ..parallel import parallelize_array_computation
from ..io import (
read_telescope_data_chunked,
copy_group,
set_sample_fraction,
load_model,
)
from ..configuration import AICTConfig
from ..feature_generation import feature_generation
from ..preprocessing import calc_true_disp
from ..logging import setup_logging
# use interpolation for all coordinate transforms
# 100x speed increase with no precision lost (~uas)
erfa_astrom.set(ErfaAstromInterpolator(5 * u.min))
dl3_columns = [
"run_id",
"event_num",
"gamma_energy_prediction",
"gamma_prediction",
"disp_prediction",
"theta_deg",
"theta_deg_off_1",
"theta_deg_off_2",
"theta_deg_off_3",
"theta_deg_off_4",
"theta_deg_off_5",
"pointing_position_az",
"pointing_position_zd",
from time import perf_counter
import numpy as np
import astropy.units as u
# array with 10000 obstimes
obstime = Time('2010-01-01T20:00') + np.linspace(0, 6, 10000) * u.hour
location = location = EarthLocation(lon=-17.89 * u.deg, lat=28.76 * u.deg, height=2200 * u.m)
frame = AltAz(obstime=obstime, location=location)
crab = SkyCoord(ra='05h34m31.94s', dec='22d00m52.2s')
# transform with default transformation and print duration
t0 = perf_counter()
crab_altaz = crab.transform_to(frame)
print(f'Transformation took {perf_counter() - t0:.2f} s')
# transform with interpolating astrometric values
t0 = perf_counter()
with erfa_astrom.set(ErfaAstromInterpolator(300 * u.s)):
crab_altaz_interpolated = crab.transform_to(frame)
print(f'Transformation took {perf_counter() - t0:.2f} s')
err = crab_altaz.separation(crab_altaz_interpolated)
print(f'Mean error of interpolation: {err.to(u.microarcsecond).mean():.4f}')
# To set erfa_astrom for a whole session, use it without context manager:
erfa_astrom.set(ErfaAstromInterpolator(300 * u.s))
def test_warnings():
with pytest.warns(AstropyWarning):
with erfa_astrom.set(ErfaAstromInterpolator(9 * u.us)):
pass
