def read_gaia_file(filename, header=False):
"""Read in a Gaia healpix file in the appropriate format for desitarget.
Parameters
----------
filename : :class:`str`
File name of a single Gaia "chunks" file.
header : :class:`bool`, optional, defaults to ``False``
If ``True`` then return (data, header) instead of just data.
Returns
-------
:class:`~numpy.ndarray`
Gaia data translated to targeting format (upper-case etc.) with the
columns corresponding to `desitarget.gaiamatch.gaiadatamodel`
Notes
-----
- A better location for this might be in `desitarget.io`?
"""
# ADM check we aren't going to have an epic fail on the the version of fitsio
check_fitsio_version()
# ADM prepare to read in the Gaia data by reading in columns
fx = fitsio.FITS(filename, upper=True)
fxcolnames = fx[1].get_colnames()
hdr = fx[1].read_header()
# ADM the default list of columns
readcolumns = list(ingaiadatamodel.dtype.names)
# ADM read 'em in
outdata = fx[1].read(columns=readcolumns)
# ADM change the data model to what we want for each column
outdata.dtype = gaiadatamodel.dtype
# ADM the proper motion ERRORS need to be converted to IVARs
# ADM remember to leave 0 entries as 0
for col in ['PMRA_IVAR', 'PMDEC_IVAR', 'PARALLAX_IVAR']:
w = np.where(outdata[col] != 0)[0]
outdata[col][w] = 1. / (outdata[col][w]**2.)
# ADM return data read in from the Gaia file, with the header if requested
if header:
fx.close()
return outdata, hdr
else:
fx.close()
return outdata
def read_gaia_file(filename, header=False, addobjid=False):
"""Read in a Gaia healpix file in the appropriate format for desitarget.
Parameters
----------
filename : :class:`str`
File name of a single Gaia "healpix-" file.
header : :class:`bool`, optional, defaults to ``False``
If ``True`` then return (data, header) instead of just data.
addobjid : :class:`bool`, optional, defaults to ``False``
Include, in the output, two additional columns. A column
"GAIA_OBJID" that is the integer number of each row read from
file and a column "GAIA_BRICKID" that is the integer number of
the file itself.
Returns
-------
:class:`~numpy.ndarray`
Gaia data translated to targeting format (upper-case etc.) with the
columns corresponding to `desitarget.gaiamatch.gaiadatamodel`
Notes
-----
- A better location for this might be in `desitarget.io`?
"""
# ADM check for an epic fail on the the version of fitsio.
check_fitsio_version()
# ADM prepare to read in the Gaia data by reading in columns.
fx = fitsio.FITS(filename, upper=True)
fxcolnames = fx[1].get_colnames()
hdr = fx[1].read_header()
# ADM the default list of columns.
readcolumns = list(ingaiadatamodel.dtype.names)
# ADM read 'em in.
outdata = fx[1].read(columns=readcolumns)
# ADM change the data model to what we want for each column.
outdata.dtype.names = gaiadatamodel.dtype.names
# ADM the proper motion ERRORS need to be converted to IVARs.
# ADM remember to leave 0 entries as 0.
for col in ['PMRA_IVAR', 'PMDEC_IVAR', 'PARALLAX_IVAR']:
w = np.where(outdata[col] != 0)[0]
outdata[col][w] = 1. / (outdata[col][w]**2.)
# ADM if requested, add an object identifier for each file row.
if addobjid:
newdt = outdata.dtype.descr
for tup in ('GAIA_BRICKID', '>i4'), ('GAIA_OBJID', '>i4'):
newdt.append(tup)
nobjs = len(outdata)
newoutdata = np.zeros(nobjs, dtype=newdt)
for col in outdata.dtype.names:
newoutdata[col] = outdata[col]
newoutdata['GAIA_OBJID'] = np.arange(nobjs)
nside = _get_gaia_nside()
hpnum = radec2pix(nside, outdata["GAIA_RA"], outdata["GAIA_DEC"])
# ADM int should fail if HEALPix in the file aren't unique.
newoutdata['GAIA_BRICKID'] = int(np.unique(hpnum))
outdata = newoutdata
# ADM return data from the Gaia file, with the header if requested.
if header:
fx.close()
return outdata, hdr
else:
fx.close()
return outdata