def read_guide_stars_catalog(self, filename, max_sep_arcsec=2.):
log = get_logger()
log.info("reading guide stars in {}".format(filename))
# here we could do some conversion of column names
catalog = Table.read(filename)
if (not "xcentroid" in catalog.dtype.names) or (
not "ra_gaia" in catalog.dtype.names):
log.error(
"I can only deal with Aaron's catalogs with columns xcentroid,ycentroid,ra_gaia,dec_gaia, sorry"
)
raise RuntimeError(
"I can only deal with Aaron's catalogs with columns xcentroid,ycentroid,ra_gaia,dec_gaia, sorry"
)
max_sep_arcsec = 2.
log.info(
"selection stars for which we have a good match (< {} arcsec)".
format(max_sep_arcsec))
dra = (catalog["ra"] - catalog["ra_gaia"]) * cosd(
catalog["dec_gaia"]) * 3600. # arcsec
ddec = (catalog["dec"] - catalog["dec_gaia"]) * 3600. # arcsec
dr = np.hypot(dra, ddec)
selection = (dr < 2) # arcsec
if np.sum(selection) == 0:
log.error("no star is matched with sufficient precision!")
raise RuntimeError("no star is matched with sufficient precision!")
return catalog[:][selection]
def test_tancorr_fit(self):
tcorr = TanCorr()
tel_ha1 = 12.
tel_dec1 = 80.
npts = 24
x1 = 0.1 * np.random.uniform(size=npts)
y1 = 0.1 * np.random.uniform(size=npts)
ha, dec = xy2hadec(x1, y1, tel_ha1, tel_dec1)
true_dha_arcsec = 3.
true_ddec_arcsec = 1.
tel_ha2 = tel_ha1 + true_dha_arcsec / 3600.
tel_dec2 = tel_dec1 + true_ddec_arcsec / 3600.
x2, y2 = hadec2xy(ha, dec, tel_ha2, tel_dec2)
tcorr.fit(x1, y1, x2, y2)
meas_dha_arcsec = tcorr.dha / cosd(tel_dec1) * 3600.
meas_ddec_arcsec = tcorr.ddec * 3600.
assert (np.abs(true_dha_arcsec - meas_dha_arcsec) < 0.01)
assert (np.abs(true_ddec_arcsec - meas_ddec_arcsec) < 0.01)
def test_it(self):
print("Testing fiberassign_radec2xy_cs5")
nrand = 500
square_side_in_degrees = 1.5
xtan = np.pi / 180. * square_side_in_degrees * (
np.random.uniform(size=nrand) - 0.5)
ytan = np.pi / 180. * square_side_in_degrees * (
np.random.uniform(size=nrand) - 0.5)
tile_ra = 12.
tile_dec = 40.
tile_ha = 1
tile_mjd = 59344.4
tile_fieldrot = -130 / 3600. # deg
lst = tile_ra + tile_ha
ha, dec = xy2hadec(xtan, ytan, tile_ha, tile_dec)
ra = lst - ha
x, y = fiberassign_radec2xy_cs5(ra, dec, tile_ra, tile_dec, tile_mjd,
tile_ha, tile_fieldrot)
print("Testing fiberassign_cs5_xy2radec")
ra2, dec2 = fiberassign_cs5_xy2radec(x, y, tile_ra, tile_dec, tile_mjd,
tile_ha, tile_fieldrot)
drad = cosd(dec) * (ra2 - ra)
ddec = (dec2 - dec)
distdeg = np.sqrt(drad**2 + ddec**2)
rms = (np.sqrt(np.mean(distdeg**2)))
print("rms={} arcsec".format(rms * 3600.))
assert (rms * 3600. < 0.1)
print("Testing fiberassign_radec2xy_flat")
x, y = fiberassign_radec2xy_flat(ra, dec, tile_ra, tile_dec, tile_mjd,
tile_ha, tile_fieldrot)
print("Testing fiberassign_flat_xy2radec")
ra2, dec2 = fiberassign_flat_xy2radec(x, y, tile_ra, tile_dec,
tile_mjd, tile_ha, tile_fieldrot)
drad = cosd(dec) * (ra2 - ra)
ddec = (dec2 - dec)
distdeg = np.sqrt(drad**2 + ddec**2)
rms = (np.sqrt(np.mean(distdeg**2)))
print("rms={} arcsec".format(rms * 3600.))
assert (rms * 3600. < 0.1)
def qs2xy(q, s):
'''angular q,s on curved focal surface -> focal tangent plane x,y
Args:
q: angle in degrees
s: focal surface radial distance in mm
Returns (x, y) cartesian location on focal tangent plane in mm
Notes: (x,y) are in the "CS5" DESI coordinate system tangent plane to
the curved focal surface. q is the radial angle measured counter-clockwise
from the x-axis; s is the radial distance along the curved focal surface;
it is *not* sqrt(x**2 + y**2). (q,s) are the preferred coordinates for
the DESI focal plane hardware engineering team.
'''
r = s2r(s)
x = r * cosd(q)
y = r * sind(q)
return x, y
def fit_tancorr(self, catalog, mjd=None, hexrot_deg=None, lst=None):
log = get_logger()
x_gfa = catalog["xcentroid"]
y_gfa = catalog["ycentroid"]
ra_gaia = catalog["ra_gaia"]
dec_gaia = catalog["dec_gaia"]
# mjd,hexprot_deg,lst could have been set before
if mjd is not None:
self.mjd = mjd
log.info("Use argument MJD={}".format(self.mjd))
elif "mjd_obs" in catalog.keys():
self.mjd = np.mean(catalog["mjd_obs"])
log.info("Use 'mjd_obs' in catalog, MJD={}".format(self.mjd))
elif self.mjd is None:
log.error("mjd is None")
raise RuntimeError("mjd is None")
else:
log.info("Use MJD={}".format(self.mjd))
if hexrot_deg is not None:
self.hexrot_deg = hexrot_deg
elif self.hexrot_deg is None:
log.error("hexrot_deg is None")
raise RuntimeError("hexrot_deg is None")
if lst is not None:
self.lst = lst
elif self.lst is None:
from desimeter.time import mjd2lst
log.warning("Compute LST from MJD={}".format(self.mjd))
self.lst = mjd2lst(self.mjd)
log.info("Use LST={}".format(self.lst))
# first transfo: gfa2fp
x_fp, y_fp = self.all_gfa2fp(x_gfa,
y_gfa,
petal_loc=catalog["petal_loc"])
# keep only petal data for which we have the metrology
selection = (x_fp != 0)
x_gfa = x_gfa[selection]
y_gfa = y_gfa[selection]
x_fp = x_fp[selection]
y_fp = y_fp[selection]
ra_gaia = ra_gaia[selection]
dec_gaia = dec_gaia[selection]
# transform focal plane to tangent plane
x_tan_meas, y_tan_meas = fp2tan(x_fp, y_fp, self.adc1, self.adc2)
correction = TanCorr()
for _ in range(
3
): # loop because change of pointing induces a rotation of the field
# we transform GAIA coordinates to the tangent plane
x_tan_gaia, y_tan_gaia = radec2tan(
ra_gaia,
dec_gaia,
self.ra,
self.dec,
mjd=self.mjd,
lst_deg=self.lst,
hexrot_deg=self.hexrot_deg,
precession=self.precession,
aberration=self.aberration,
polar_misalignment=self.polar_misalignment)
# now that we have both sets of coordinates, we fit a transformation from one to the other
correction.fit(x_tan_meas, y_tan_meas, x_tan_gaia, y_tan_gaia)
# opposite sign for the telescope offset because I have converted GAIA RA Dec to tangent plane ...
self.dec -= correction.ddec
self.ra += correction.dha / cosd(self.dec) # HA = LST-RA
# save params to this
log.info("RMS coord. residual = {:3.2f} arcsec".format(
correction.rms_arcsec))
log.info("Rotation angle (field rot ZP) ={:4.3f} deg".format(
correction.rot_deg))
log.info("Pointing correction dHA={:3.2f} arcsec, dDec={:3.2f} arcsec".
format(correction.dha * 3600., correction.ddec * 3600.))
log.info("Scales sxx={:5.4f} syy={:5.4f} sxy={:5.4f}".format(
correction.sxx, correction.syy, correction.sxy))
# now I just copy the correction parameters in this class
self.sxx = correction.sxx
self.syy = correction.syy
self.sxy = correction.sxy
self.fieldrot_zp_deg = correction.rot_deg
self.nstars = correction.nstars
self.rms_arcsec = correction.rms_arcsec
# I now derive the field rotation
self.fieldrot_deg = self.compute_fieldrot()
def read_guide_stars_catalog(self, filename, max_sep_arcsec=2.):
log = get_logger()
log.info("reading guide stars in {}".format(filename))
# here we could do some conversion of column names
catalog = Table.read(filename)
if "mjd_obs" in catalog.dtype.names:
self.mjd = np.mean(catalog["mjd_obs"])
log.info("use mjd={} from catalog['mjd_obs']".format(self.mjd))
if (not "xcentroid" in catalog.dtype.names) or (
not "ra_gaia" in catalog.dtype.names):
log.error(
"I can only deal with Aaron's catalogs with columns xcentroid,ycentroid,ra_gaia,dec_gaia, sorry"
)
raise RuntimeError(
"I can only deal with Aaron's catalogs with columns xcentroid,ycentroid,ra_gaia,dec_gaia, sorry"
)
log.info(
"selection stars for which we have a good match (< {} arcsec)".
format(max_sep_arcsec))
if all([_ in catalog.columns for _ in ['pmra', 'pmdec', 'ref_epoch']]):
if self.mjd is None:
log.error(
"Cannot compute proper motion correction because mjd=None")
raise RuntimeError(
"Cannot compute proper motion correction because mjd=None")
# if proper motions and reference epochs are there
pmra = catalog['pmra']
pmdec = catalog['pmdec']
# if unknown, zero out the pms
pmra[~np.isfinite(pmra)] = 0
pmdec[~np.isfinite(pmdec)] = 0
cur_year = Time(self.mjd, format='mjd').to_value(format='jyear')
# observation time in decimal years (like 2020.3)
ref_epoch = catalog['ref_epoch']
dra = (cur_year - ref_epoch) * pmra / 3600e3 / cosd(
catalog['dec_gaia'])
ddec = (cur_year - ref_epoch) * pmdec / 3600e3
# add pm and rename columns
catalog['ra_gaia'] += dra
catalog['dec_gaia'] += ddec
catalog.rename_column('ra_gaia', 'ra_gaia_with_pm')
catalog.rename_column('dec_gaia', 'dec_gaia_with_pm')
ra_column = 'ra_gaia_with_pm'
dec_column = 'dec_gaia_with_pm'
else:
ra_column = 'ra_gaia'
dec_column = 'dec_gaia'
log.warning("No proper motion info in catalog")
match_dra = (catalog["ra"] - catalog[ra_column]) * cosd(
catalog[dec_column]) * 3600. # arcsec
match_ddec = (catalog["dec"] - catalog[dec_column]) * 3600. # arcsec
dr = np.hypot(match_dra, match_ddec)
selection = (dr < max_sep_arcsec) # arcsec
if np.sum(selection) == 0:
log.error("no star is matched with sufficient precision!")
raise RuntimeError("no star is matched with sufficient precision!")
return catalog[:][selection]