def read_targets_in_box(hpdirname, radecbox=[0., 360., -90., 90.],
columns=None):
"""Read in targets in an RA/Dec box.
Parameters
----------
hpdirname : :class:`str`
Full path to either a directory containing targets that
have been partitioned by HEALPixel (i.e. as made by
`select_targets` with the `bundle_files` option). Or the
name of a single file of targets.
radecbox : :class:`list`, defaults to the entire sky
4-entry list of coordinates [ramin, ramax, decmin, decmax]
forming the edges of a box in RA/Dec (degrees).
columns : :class:`list`, optional
Only read in these target columns.
Returns
-------
:class:`~numpy.ndarray`
An array of targets in the passed RA/Dec box.
"""
# ADM we'll need RA/Dec for final cuts, so ensure they're read.
addedcols = []
columnscopy = None
if columns is not None:
# ADM make a copy of columns, as it's a kwarg we'll modify.
columnscopy = columns.copy()
for radec in ["RA", "DEC"]:
if radec not in columnscopy:
columnscopy.append(radec)
addedcols.append(radec)
# ADM if a directory was passed, do fancy HEALPixel parsing...
if os.path.isdir(hpdirname):
# ADM approximate nside for area of passed box.
nside = pixarea2nside(box_area(radecbox))
# ADM HEALPixels that touch the box for that nside.
pixlist = hp_in_box(nside, radecbox)
# ADM read in targets in these HEALPixels.
targets = read_targets_in_hp(hpdirname, nside, pixlist,
columns=columnscopy)
# ADM ...otherwise just read in the targets.
else:
targets = fitsio.read(hpdirname, columns=columnscopy)
# ADM restrict only to targets in the requested RA/Dec box...
ii = is_in_box(targets, radecbox)
# ADM ...and remove RA/Dec columns if we added them.
targets = rfn.drop_fields(targets[ii], addedcols)
return targets
def resolve(targets):
"""Resolve which targets are primary in imaging overlap regions.
Parameters
----------
targets : :class:`~numpy.ndarray`
Rec array of targets. Must have columns "RA" and "DEC" and
either "RELEASE" or "PHOTSYS".
Returns
-------
:class:`~numpy.ndarray`
The original target list trimmed to only objects from the "northern"
photometry in the northern imaging area and objects from "southern"
photometry in the southern imaging area.
"""
# ADM retrieve the photometric system from the RELEASE.
from desitarget.io import release_to_photsys, desitarget_resolve_dec
if 'PHOTSYS' in targets.dtype.names:
photsys = targets["PHOTSYS"]
else:
photsys = release_to_photsys(targets["RELEASE"])
# ADM a flag of which targets are from the 'N' photometry.
from desitarget.cuts import _isonnorthphotsys
photn = _isonnorthphotsys(photsys)
# ADM grab the declination used to resolve targets.
split = desitarget_resolve_dec()
# ADM determine which targets are north of the Galactic plane. As
# ADM a speed-up, bin in ~1 sq.deg. HEALPixels and determine
# ADM which of those pixels are north of the Galactic plane.
# ADM We should never be as close as ~1o to the plane.
from desitarget.geomask import is_in_gal_box, pixarea2nside
nside = pixarea2nside(1)
theta, phi = np.radians(90 - targets["DEC"]), np.radians(targets["RA"])
pixnum = hp.ang2pix(nside, theta, phi, nest=True)
# ADM find the pixels north of the Galactic plane...
allpix = np.arange(hp.nside2npix(nside))
theta, phi = hp.pix2ang(nside, allpix, nest=True)
ra, dec = np.degrees(phi), 90 - np.degrees(theta)
pixn = is_in_gal_box([ra, dec], [0., 360., 0., 90.], radec=True)
# ADM which targets are in pixels north of the Galactic plane.
galn = pixn[pixnum]
# ADM which targets are in the northern imaging area.
arean = (targets["DEC"] >= split) & galn
# ADM retain 'N' targets in 'N' area and 'S' in 'S' area.
keep = (photn & arean) | (~photn & ~arean)
return targets[keep]
def test_targets_spatial(self):
"""Test applying RA/Dec/HEALpixel inputs to sweeps recovers same targets
"""
# ADM only test some of the galaxy cuts for speed. There's a
# ADM full run through all classes in test_cuts_basic.
tc = ["LRG", "ELG", "BGS"]
infiles = self.sweepfiles[2]
targets = cuts.select_targets(infiles, numproc=1, tcnames=tc)
# ADM test the RA/Dec box input.
radecbox = [
np.min(targets["RA"]) - 0.01,
np.max(targets["RA"]) + 0.01,
np.min(targets["DEC"]) - 0.01,
np.max(targets["DEC"] + 0.01)
]
t1 = cuts.select_targets(infiles,
numproc=1,
tcnames=tc,
radecbox=radecbox)
# ADM test the RA/Dec/radius cap input.
centra, centdec = 0.5 * (radecbox[0] + radecbox[1]), 0.5 * (
radecbox[2] + radecbox[3])
# ADM 20 degrees should be a large enough radius for the sweeps.
maxrad = 20.
radecrad = centra, centdec, maxrad
t2 = cuts.select_targets(infiles,
numproc=1,
tcnames=tc,
radecrad=radecrad)
# ADM test the pixel input.
nside = pixarea2nside(box_area(radecbox))
pixlist = hp_in_box(nside, radecbox)
t3 = cuts.select_targets(infiles,
numproc=1,
tcnames=tc,
nside=nside,
pixlist=pixlist)
# ADM sort each set of targets on TARGETID to compare them.
targets = targets[np.argsort(targets["TARGETID"])]
t1 = t1[np.argsort(t1["TARGETID"])]
t2 = t2[np.argsort(t2["TARGETID"])]
t3 = t3[np.argsort(t3["TARGETID"])]
# ADM test the same targets were recovered and that
# ADM each recovered target has the same bits set.
for targs in t1, t2, t3:
for col in "TARGETID", "DESI_TARGET", "BGS_TARGET", "MWS_TARGET":
self.assertTrue(np.all(targs[col] == targets[col]))
def get_gaia_nside_brick(bricksize=0.25):
"""Grab the HEALPixel nside that corresponds to a brick.
Parameters
----------
bricksize : :class:`float`, optional, defaults to 0.25
Size of the brick, default is the Legacy Surveys standard.
Returns
-------
:class:`int`
The HEALPixel nside number that corresponds to a brick.
"""
return pixarea2nside(bricksize * bricksize)