def add_lb(cols): (ra, dec) = cols['ra'], cols['dec'] l = np.empty_like(ra) b = np.empty_like(dec) for i in xrange(len(ra)): (l[i], b[i]) = np.degrees(sla_eqgal(*np.radians((ra[i], dec[i])))) cols['l'] = l cols['b'] = b
def raDec2thetaPhi(r, d):
ra = r * 15 * math.pi / 180
dec = d * math.pi / 180
l, b = slalib.sla_eqgal(ra, dec)
l *= 180 / math.pi
b *= 180 / math.pi
j = int(b + 91.5)
j = 180 if j > 180 else j
nl = int(l - 0.5)
nl = 359 if l < 0.5 else nl
i = (nl / 4) + 1
return i, j
def import_from_sweeps_aux(file, db, tabname, all=False):
# import an SDSS run
dat = pyfits.getdata(file, 1)
table = db.table(tabname)
if not all:
F1 = F1_BRIGHT | F1_SATURATED | F1_NODEBLEND | F1_EDGE; # these must not be set for an object to qualify
F2 = F2_DEBLENDED_AS_MOVING # these must not be set for an object to qualify # Compute which objects pass flag cuts
f1 = dat.field('objc_flags')
f2 = dat.field('objc_flags2')
rs = dat.field('resolve_status')
ok = (rs & RS_SURVEY_PRIMARY != 0) & (f1 & F1 == 0) & (f2 & F2 == 0)
ok |= all
else:
ok = np.ones(len(dat.field('resolve_status')), dtype=bool)
# Import objects passing some basic quality cuts
if any(ok != 0):
# Load the data, cutting on flags
coldefs = sdss_table_def['schema']['main']['columns'] + sdss_table_def['schema']['survey']['columns']
cols = dict(( (name, dat.field(fitsname)[ok]) for (name, _, fitsname) in coldefs if fitsname != ''))
(ext, flux, ivar, calib) = [ dat.field(col)[ok].transpose() for col in ['extinction', 'modelflux', 'modelflux_ivar', 'calib_status'] ]
# Compute magnitudes and related quantities for all bands
for pos, band in enumerate('ugriz'):
(fluxB, ivarB, extB, calibB) = (flux[pos], ivar[pos], ext[pos], calib[pos])
# Compute magnitude from flux
fluxB[fluxB <= 0] = 0.001
mag = -2.5 * np.log10(fluxB) + 22.5
magErr = (1.08574 / fluxB) / np.sqrt(ivarB)
# Append these to the list of columns
for suffix, col in izip(['', 'Err', 'Ext', 'Calib'], [mag, magErr, extB, calibB]):
cols[band + suffix] = col
# Add computed columns
(ra, dec) = cols['ra'], cols['dec']
l = np.empty_like(ra)
b = np.empty_like(dec)
for i in xrange(len(ra)):
(l[i], b[i]) = np.degrees(sla_eqgal(*np.radians((ra[i], dec[i]))))
cols['l'] = l
cols['b'] = b
ids = table.append(cols)
else:
ids = []
yield (file, len(ids), len(ok))
def transform_celestial(coords, systems):
lons, lats = np.radians(coords['lon']), np.radians(coords['lat'])
out = Table()
out['lon'] = np.zeros(len(coords), dtype='float64')
out['lat'] = np.zeros(len(coords), dtype='float64')
for ii, (lon, lat) in enumerate(zip(lons, lats)):
# First convert to FK5 J2000 in all cases
if systems['in'] == 'fk4':
lon, lat = slalib.sla_fk45z(lon, lat, 2000.0012775136652)
elif systems['in'] == 'icrs':
lon, lat = slalib.sla_hfk5z(lon, lat, 2000)[:2]
elif systems['in'] == 'galactic':
lon, lat = slalib.sla_galeq(lon, lat)
elif systems['in'] == 'ecliptic':
lon, lat = slalib.sla_ecleq(lon, lat, 51544)
# Now convert from FK5 J2000 to out system
if systems['out'] == 'fk4':
# FK5 -> FK4 at BEPOCH 2000 assuming no proper motion or parallax
lon, lat = slalib.sla_fk54z(lon, lat, 2000.0012775136652)[:2]
elif systems['out'] == 'icrs':
# FK5 -> Hipparcos (i.e. ICRF, which is as close as SLALIB
# gets to ICRS) at epoch 2000 and with no proper motion
lon, lat = slalib.sla_fk5hz(lon, lat, 2000)
elif systems['out'] == 'galactic':
# FK5 -> Galactic
lon, lat = slalib.sla_eqgal(lon, lat)
elif systems['out'] == 'ecliptic':
# FK5 -> Ecliptic at TDB (MJD) 51544 (i.e. J2000)
lon, lat = slalib.sla_eqecl(lon, lat, 51544)
out[ii]['lon'] = np.degrees(lon)
out[ii]['lat'] = np.degrees(lat)
return out
def transform_celestial(coords, systems):
lons, lats = np.radians(coords['lon']), np.radians(coords['lat'])
out = Table()
out['lon'] = np.zeros(len(coords), dtype='float64')
out['lat'] = np.zeros(len(coords), dtype='float64')
for ii, (lon, lat) in enumerate(zip(lons, lats)):
# First convert to FK5 J2000 in all cases
if systems['in'] == 'fk4':
lon, lat = slalib.sla_fk45z(lon, lat, 2000.0012775136652)
elif systems['in'] == 'icrs':
lon, lat = slalib.sla_hfk5z(lon, lat, 2000)[:2]
elif systems['in'] == 'galactic':
lon, lat = slalib.sla_galeq(lon, lat)
elif systems['in'] == 'ecliptic':
lon, lat = slalib.sla_ecleq(lon, lat, 51544)
# Now convert from FK5 J2000 to out system
if systems['out'] == 'fk4':
# FK5 -> FK4 at BEPOCH 2000 assuming no proper motion or parallax
lon, lat = slalib.sla_fk54z(lon, lat, 2000.0012775136652)[:2]
elif systems['out'] == 'icrs':
# FK5 -> Hipparcos (i.e. ICRF, which is as close as SLALIB
# gets to ICRS) at epoch 2000 and with no proper motion
lon, lat = slalib.sla_fk5hz(lon, lat, 2000)
elif systems['out'] == 'galactic':
# FK5 -> Galactic
lon, lat = slalib.sla_eqgal(lon, lat)
elif systems['out'] == 'ecliptic':
# FK5 -> Ecliptic at TDB (MJD) 51544 (i.e. J2000)
lon, lat = slalib.sla_eqecl(lon, lat, 51544)
out[ii]['lon'] = np.degrees(lon)
out[ii]['lat'] = np.degrees(lat)
return out
def convert(coords, systems):
if not set(systems.values()).issubset(SUPPORTED_SYSTEMS):
return None
lons, lats = np.radians(coords['lon']), np.radians(coords['lat'])
for ii, (lon, lat) in enumerate(zip(lons, lats)):
# First convert to FK5 J2000 in all cases
if systems['in'] == 'fk4':
lon, lat = slalib.sla_fk45z(lon, lat, 2000.0012775136652)
elif systems['in'] == 'icrs':
lon, lat = slalib.sla_hfk5z(lon, lat, 2000)[:2]
elif systems['in'] == 'galactic':
lon, lat = slalib.sla_galeq(lon, lat)
elif systems['in'] == 'ecliptic':
lon, lat = slalib.sla_ecleq(lon, lat, 51544)
# Now convert from FK5 J2000 to out system
if systems['out'] == 'fk4':
# FK5 -> FK4 at BEPOCH 2000 assuming no proper motion or parallax
lon, lat = slalib.sla_fk54z (lon, lat, 2000.0012775136652)[:2]
elif systems['out'] == 'icrs':
# FK5 -> Hipparcos (i.e. ICRF, which is as close as SLALIB
# gets to ICRS) at epoch 2000 and with no proper motion
lon, lat = slalib.sla_fk5hz(lon, lat, 2000)
elif systems['out'] == 'galactic':
# FK5 -> Galactic
lon, lat = slalib.sla_eqgal(lon, lat)
elif systems['out'] == 'ecliptic':
# FK5 -> Ecliptic at TDB (MJD) 51544 (i.e. J2000)
lon, lat = slalib.sla_eqecl(lon, lat, 51544)
lons[ii], lats[ii] = lon, lat
return dict(lon=np.degrees(lons), lat=np.degrees(lats))
def import_from_dvo_aux(file, cat):
# Load object data
dat, hdr = pyfits.getdata(file, 1, header=1)
cols = dict(( (name, dat.field(fitsname)) for (name, _, fitsname) in astromCols if fitsname != ''))
# Load magnitudes (they're stored in groups of 5 rows)
mag = pyfits.getdata(file[:-1]+'s', 1)
magRawCols = [ mag.field(fitsname) for fitsname, _, _ in magData ];
photoData = [ col[band::5] for band in xrange(5) for col in magRawCols ]
assert len(photoData) == len(photoCols)
for i, (col, _, _) in enumerate(photoCols):
cols[col] = photoData[i]
#idx = np.arange(len(cols['cat_id']))
#i = idx.argsort(
#ra = np.sort(cols['ra']); dra = np.diff(ra)
#dec = np.sort(cols['dec']); ddec = np.diff(dec)
#assert (abs(dra) + abs(ddec) > 1.e-14).all(), str(sorted(dra)[:10]) + '\n' + str(sorted(ddec)[:10])
#assert len(np.unique1d(cols['obj_id'])) == len(cols['obj_id'])
#assert len(np.unique1d(cols['ext_id'])) == len(cols['ext_id'])
#assert len(np.unique1d(cols['cat_id'])) == len(cols['cat_id'])
#print ''
#for i, col in enumerate(magRawCols):
# print magData[i][0],'=',col[10:15]
#for col, _, _ in photoCols:
# print col,'=',cols[col][2]
#exit()
# Add computed columns
(ra, dec) = cols['ra'], cols['dec']
l = np.empty_like(ra)
b = np.empty_like(dec)
for i in xrange(len(ra)):
(l[i], b[i]) = np.degrees(sla_eqgal(*np.radians((ra[i], dec[i]))))
cols['l'] = l
cols['b'] = b
# Add the ID of the file the object came from
fn = '/'.join(file.split('/')[-2:])
assert(len(fn) < 20)
cols['file_id'] = np.empty(len(l), dtype='a20')
cols['file_id'][:] = fn
# Add some blobs (this is mostly for testing)
cols['hdr'] = np.empty(len(l), dtype=np.object_)
cols['hdr'][:] = str(hdr)
# BLOB checksum (for debugging)
cols['cksum'] = np.empty(len(l), dtype='a32')
cols['cksum'][:] = hashlib.md5(str(hdr)).hexdigest()
# Add some array data
cols['imageid'] = np.empty(len(l), dtype='64i8')
cols['imageid'][:] = np.arange(len(l)*64, dtype='i8').reshape((len(l), 64))
# Add a blob array
s = np.array([ str(i) for i in np.random.random_integers(0, 100, 64) ])
cols['blobarr'] = np.empty(len(l), dtype='64O')
cols['blobarr'][:] = s[ np.random.random_integers(0, 63, len(l)*64) ].reshape((len(l), 64))
# sanity check
for (name, _, _) in astromCols + photoCols:
assert name in cols or name in ['id', 'cached'], name
ids = cat.append(cols)
return (file, len(ids), len(ids))
vals = {}
for system in 'FK4', 'Ecliptic', 'Galactic', 'ICRS':
vals[system] = [np.zeros_like(ra_j2000_fk5), np.zeros_like(dec_j2000_fk5)]
for ii, (raj, decj) in enumerate(zip(ra_j2000_fk5, dec_j2000_fk5)):
# FK5 -> FK4 at BEPOCH 2000.0 assuming no proper motion or parallax
r1950, d1950, dr1950, dd1950 = S.sla_fk54z(raj, decj, 2000.0)
vals['FK4'][0][ii], vals['FK4'][1][ii] = r1950, d1950
# FK5 -> Ecliptic at TDB (MJD) 51544.0 (i.e. J2000)
dl, db = S.sla_eqecl(raj, decj, 51544.0)
vals['Ecliptic'][0][ii], vals['Ecliptic'][1][ii] = dl, db
# FK5 -> Galactic
dl, db = S.sla_eqgal(raj, decj)
vals['Galactic'][0][ii], vals['Galactic'][1][ii] = dl, db
# FK5 -> Hipparcos (i.e. ICRF, which is as close as SLALIB
# gets to ICRS) at epoch 2000.0 and with no proper motion
rh, dh = S.sla_fk5hz(raj, decj, 2000.0)
vals['ICRS'][0][ii], vals['ICRS'][1][ii] = rh, dh
glon = vals['Galactic'][0]
glat = vals['Galactic'][1]
np.savetxt('coords_galactic.txt',
zip(np.degrees(glon), np.degrees(glat)),
fmt="%20.15f")
ra_fk4 = vals['FK4'][0]
dec_fk4 = vals['FK4'][1]
def import_from_catalogs_aux(file, det_table, exp_table, djm, all=False):
# read SExtractor catalog file
# print >>sys.stderr, file
try:
hdus = pyfits.open(file)
except IOError:
yield (file, 0, 1, 0)
else:
dat = hdus[1].data
hdr_det = hdus[1].header
hdr_exp = hdus[2].header
hdus.close()
# delete PV coefficients from the header
for i in np.arange(17):
del hdr_exp["PV1_" + str(i)]
del hdr_exp["PV2_" + str(i)]
# test WCS of this image
try:
wcs = pywcs.WCS(hdr_exp)
except:
yield (file, 0, 4, 0)
else:
# import header data into exposures table
try:
coldefs = (
exp_table_def["schema"]["main"]["columns"] + exp_table_def["schema"]["image_quality"]["columns"]
)
exp_cols = dict(
(name, np.array([hdr_exp.get(fitsname)]).astype(coltype))
for (name, coltype, fitsname, _) in coldefs
if fitsname != ""
)
coldefs = exp_table_def["schema"]["abs_photo"]["columns"]
exp_cols.update(
dict(
(name, np.array([0]).astype(coltype))
for (name, coltype, fitsname, _) in coldefs
if fitsname != ""
)
)
exp_cols.update(
dict(
(name, np.array([hdr_exp.get(fitsname)]).astype(coltype))
for (name, coltype, fitsname, _) in coldefs
if (fitsname != "") & (hdr_exp.has_key(fitsname))
)
)
except TypeError:
yield (file, 0, 2, 0)
else:
# find the RA and Dec for the center of this exposure
pixcrd = np.array([[1024, 2048]], np.float_)
sky = wcs.all_pix2sky(pixcrd, 1)
exp_cols["ra"] = np.array([sky[0][0]])
exp_cols["dec"] = np.array([sky[0][1]])
(l, b) = np.degrees(sla_eqgal(*np.radians((exp_cols["ra"].squeeze(), exp_cols["dec"].squeeze()))))
exp_cols["l"] = np.array([l])
exp_cols["b"] = np.array([b])
exp_cols["mjd_import"] = np.array([djm]).astype("u4")
exp_cols["mumax_med"] = np.array([-99.99]).astype("f4")
exp_cols["mumax_rms"] = np.array([-99.99]).astype("f4")
exp_cols["n_bright"] = np.array([0]).astype("i2")
# Import sources into detection table
coldefs = det_table_def["schema"]["main"]["columns"]
try:
if conversion_to_int == 1:
det_cols = dict(
(
(name, np.around(dat.field(fitsname) * factor).astype(coltype[-2:]))
for (name, _, coltype, factor, fitsname, _) in coldefs
if fitsname != "" and factor > 1
)
)
det_cols.update(
dict(
(
(name, (dat.field(fitsname) * factor).astype(coltype[-2:]))
for (name, _, coltype, factor, fitsname, _) in coldefs
if fitsname != "" and factor == 1
)
)
)
else:
det_cols = dict(
(
(name, dat.field(fitsname).astype(coltype[-2:]))
for (name, coltype, _, _, fitsname, _) in coldefs
if fitsname != ""
)
)
except TypeError:
yield (file, 0, 3, 0)
else:
det_cols["mjd"] = (np.zeros(len(det_cols["ra"])) + hdr_exp["OBSMJD"]).astype("f8")
det_cols["fid"] = (np.zeros(len(det_cols["ra"])) + hdr_exp["DBFID"]).astype("u1")
# det_cols['mjd_import'] = (np.zeros(len(det_cols['ra'])) + djm).astype('u2')
det_cols["mag_abs"] = (np.zeros(len(det_cols["ra"])) + 32000).astype("u2")
# if there is Eran's absolute photometry...
if exp_cols["apbsrms"] > 0:
det_cols["mag_abs"] = (
np.round(
(
dat.field("MAG_AUTO")
+ 2.5 * np.log10(hdr_exp["AEXPTIME"])
+ hdr_exp["APPAR01"]
+ hdr_exp["APPAR03"] * hdr_exp["AIRMASS"]
+ hdr_exp["APPAR05"] * (hdr_exp["OBSJD"] - hdr_exp["APMEDJD"])
+ hdr_exp["APPAR06"] * (hdr_exp["OBSJD"] - hdr_exp["APMEDJD"]) ** 2
+ hdr_exp["APPAR07"] * (dat.field("X_IMAGE") - 1024.0) / 2048.0
+ hdr_exp["APPAR08"] * (dat.field("Y_IMAGE") - 2048.0) / 4096.0
+ hdr_exp["APPAR09"] * ((dat.field("Y_IMAGE") - 2048.0) / 4096.0) ** 2
+ hdr_exp["APPAR10"] * ((dat.field("Y_IMAGE") - 2048.0) / 4096.0) ** 3
+ hdr_exp["APPAR11"]
* (dat.field("X_IMAGE") - 1024.0)
/ 2048.0
* (dat.field("Y_IMAGE") - 2048.0)
/ 4096.0
)
* 1000.0
)
.clip(min=5000, max=32000)
.astype("u2")
)
# use bright stars to correct for seeing
# import header data into exposures table
try:
coldefs = (
exp_table_def["schema"]["main"]["columns"] + exp_table_def["schema"]["image_quality"]["columns"]
)
exp_cols = dict(
(name, np.array([hdr_exp.get(fitsname)]).astype(coltype))
for (name, coltype, fitsname, _) in coldefs
if fitsname != ""
)
coldefs = exp_table_def["schema"]["abs_photo"]["columns"]
exp_cols.update(
dict(
(name, np.array([0]).astype(coltype))
for (name, coltype, fitsname, _) in coldefs
if fitsname != ""
)
)
exp_cols.update(
dict(
(name, np.array([hdr_exp.get(fitsname)]).astype(coltype))
for (name, coltype, fitsname, _) in coldefs
if (fitsname != "") & (hdr_exp.has_key(fitsname))
)
)
except TypeError:
yield (file, 0, 2, 0)
else:
# find the RA and Dec for the center of this exposure
pixcrd = np.array([[1024, 2048]], np.float_)
sky = wcs.all_pix2sky(pixcrd, 1)
exp_cols["ra"] = np.array([sky[0][0]])
exp_cols["dec"] = np.array([sky[0][1]])
(l, b) = np.degrees(sla_eqgal(*np.radians((exp_cols["ra"].squeeze(), exp_cols["dec"].squeeze()))))
exp_cols["l"] = np.array([l])
exp_cols["b"] = np.array([b])
exp_cols["mjd_import"] = np.array([djm]).astype("u4")
exp_cols["mumax_med"] = np.array([-99.99]).astype("f4")
exp_cols["mumax_rms"] = np.array([-99.99]).astype("f4")
exp_cols["n_bright"] = np.array([0]).astype("i2")
# Import sources into detection table
coldefs = det_table_def["schema"]["main"]["columns"]
try:
if conversion_to_int == 1:
det_cols = dict(
(
(name, np.around(dat.field(fitsname) * factor).astype(coltype[-2:]))
for (name, _, coltype, factor, fitsname, _) in coldefs
if fitsname != "" and factor > 1
)
)
det_cols.update(
dict(
(
(name, (dat.field(fitsname) * factor).astype(coltype[-2:]))
for (name, _, coltype, factor, fitsname, _) in coldefs
if fitsname != "" and factor == 1
)
)
)
else:
det_cols = dict(
(
(name, dat.field(fitsname).astype(coltype[-2:]))
for (name, coltype, _, _, fitsname, _) in coldefs
if fitsname != ""
)
)
except TypeError:
yield (file, 0, 3, 0)
else:
det_cols["mjd"] = (np.zeros(len(det_cols["ra"])) + hdr_exp["OBSMJD"]).astype("f8")
det_cols["fid"] = (np.zeros(len(det_cols["ra"])) + hdr_exp["DBFID"]).astype("u1")
# det_cols['mjd_import'] = (np.zeros(len(det_cols['ra'])) + djm).astype('u2')
det_cols["mag_abs"] = (np.zeros(len(det_cols["ra"])) + 32000).astype("u2")
# if there is Eran's absolute photometry...
if exp_cols["apbsrms"] > 0:
det_cols["mag_abs"] = (
np.round(
(
dat.field("MAG_AUTO")
+ 2.5 * np.log10(hdr_exp["AEXPTIME"])
+ hdr_exp["APPAR01"]
+ hdr_exp["APPAR03"] * hdr_exp["AIRMASS"]
+ hdr_exp["APPAR05"] * (hdr_exp["OBSJD"] - hdr_exp["APMEDJD"])
+ hdr_exp["APPAR06"] * (hdr_exp["OBSJD"] - hdr_exp["APMEDJD"]) ** 2
+ hdr_exp["APPAR07"] * (dat.field("X_IMAGE") - 1024.0) / 2048.0
+ hdr_exp["APPAR08"] * (dat.field("Y_IMAGE") - 2048.0) / 4096.0
+ hdr_exp["APPAR09"] * ((dat.field("Y_IMAGE") - 2048.0) / 4096.0) ** 2
+ hdr_exp["APPAR10"] * ((dat.field("Y_IMAGE") - 2048.0) / 4096.0) ** 3
+ hdr_exp["APPAR11"]
* (dat.field("X_IMAGE") - 1024.0)
/ 2048.0
* (dat.field("Y_IMAGE") - 2048.0)
/ 4096.0
)
* 1000.0
)
.clip(min=5000, max=32000)
.astype("u2")
)
# use bright stars to correct for seeing
bright = np.where((det_cols["mag_abs"] > 14000) & (det_cols["mag_abs"] < 17000))
if len(bright[0]) > 0:
sg = dat.field("MU_MAX") - dat.field("MAG_AUTO")
mumax_med = np.median(sg[bright])
mumax_rms = 0.741 * (np.percentile(sg[bright], 75) - np.percentile(sg[bright], 25))
exp_cols["mumax_med"] = np.array([mumax_med]).astype("f4")
exp_cols["mumax_rms"] = np.array([mumax_rms]).astype("f4")
exp_cols["n_bright"] = np.array([len(bright[0])]).astype("i2")
(exp_id,) = exp_table.append(exp_cols)
det_cols["exp_id"] = (np.zeros(len(det_cols["ra"])) + hdr_exp["DBPID"]).astype("u8")
det_cols["exp_id"][:] = exp_id
ids = det_table.append(det_cols)
yield (file, len(ids), 0, exp_id)
vals = {}
for system in 'FK4', 'Ecliptic', 'Galactic', 'ICRS':
vals[system] = [np.zeros_like(ra_j2000_fk5), np.zeros_like(dec_j2000_fk5)]
for ii, (raj, decj) in enumerate(zip(ra_j2000_fk5, dec_j2000_fk5)):
# FK5 -> FK4 at BEPOCH 2000.0 assuming no proper motion or parallax
r1950, d1950, dr1950, dd1950 = S.sla_fk54z (raj, decj, 2000.0)
vals['FK4'][0][ii],vals['FK4'][1][ii] = r1950, d1950
# FK5 -> Ecliptic at TDB (MJD) 51544.0 (i.e. J2000)
dl, db = S.sla_eqecl(raj, decj, 51544.0)
vals['Ecliptic'][0][ii],vals['Ecliptic'][1][ii] = dl, db
# FK5 -> Galactic
dl, db = S.sla_eqgal(raj, decj)
vals['Galactic'][0][ii],vals['Galactic'][1][ii] = dl, db
# FK5 -> Hipparcos (i.e. ICRF, which is as close as SLALIB
# gets to ICRS) at epoch 2000.0 and with no proper motion
rh, dh = S.sla_fk5hz(raj, decj, 2000.0)
vals['ICRS'][0][ii],vals['ICRS'][1][ii] = rh, dh
glon = vals['Galactic'][0]
glat = vals['Galactic'][1]
np.savetxt('coords_galactic.txt', zip(np.degrees(glon),
np.degrees(glat)), fmt="%20.15f")
ra_fk4 = vals['FK4'][0]
dec_fk4 = vals['FK4'][1]
def get_vobs(self, mjdtmp, xtmp, ytmp, mode, offx, offy, dcos, offmode):
mode = mode.lower()
offmode = offmode.lower()
### for 'coord == horizontal' skip
try:
mode = self.coord_dict[mode]
except:
xxtmp = xtmp
yytmp = ytmp
try:
offmode = self.coord_dict[offmode]
except:
xxtmp = xtmp
yytmp = ytmp
if mode == 1: #j2000
if offmode == 0 or offmode == 1: #same or j2000
yytmp = ytmp + offy
if dcos == 0:
xxtmp = xtmp + offx
else:
xxtmp = xtmp + offx / math.cos(yytmp)
elif offmode == 2: #b1950
ret = slalib.sla_fk54z(xtmp, ytmp, 2000)
xtmp_b = ret[0]
ytmp_b = ret[1]
ytmp_b += offy
if dcos == 0:
xtmp_b += offx
else:
xtmp_b += offx / math.cos(ytmp_b)
ret_1 = slalib.sla_fk45z(xtmp_b, ytmp_b, 1950)
xxtmp = ret_1[0]
yytmp = ret_1[1]
elif offmode == 3: #lb,galactic,gal
ret = slalib.sla_eqgal(xtmp, ytmp)
xtmp_g = ret[0]
ytmp_g = ret[1]
ytmp_g += offy
if dcos == 0:
xtmp_g += offx
else:
xtmp_g += offx / math.cos(ytmp_g)
ret_1 = slalib.sla_galeq(xtmp_g, ytmp_g)
xxtmp = ret_1[0]
yytmp = ret_1[1]
if mode == 2: #b1950
if offmode == 1: #j2000
ret = slalib.sla_fk45z(xtmp, ytmp, 1950)
xtmp_j = ret[0]
ytmp_j = ret[1]
yytmp = ytmp_j + offy
if dcos == 0:
xxtmp = xtmp_j + offx
else:
xxtmp = xtmp_j + offx / math.cos(ytmp_j)
elif offmode == 2 or offmode == 0: #b1950
ytmp += offy
if dcos == 0:
xtmp += offx
else:
xtmp += offx / math.cos(ytmp)
ret = slalib.sla_fk45z(xtmp, ytmp, 1950)
xxtmp = ret[0]
yytmp = ret[1]
elif offmode == 3: #lb,galactic,gal
ret = slalib.sla_eg50(xtmp, ytmp)
xtmp_g = ret[0]
ytmp_g = ret[1]
ytmp_g += offy
if dcos == 0:
xtmp_g += offx
else:
xtmp_g += offx / math.cos(ytmp_g)
ret = slalib.sla_galeq(xtmp_g, ytmp_g)
xxtmp = ret[0]
yytmp = ret[1]
if mode == 3: #lb,galactic,gal
if offmode == 1: #j2000
ret_2 = slalib.sla_galeq(xtmp, ytmp)
xtmp_j = ret_2[0]
ytmp_j = ret_2[1]
yytmp = ytmp_j + offy
if dcos == 0:
xxtmp = xtmp_j + offx
else:
xxtmp = xtmp_j + offx / math.cos(ytmp_j)
elif offmode == 2: #b1950
ret = slalib.sla_ge50(xtmp, ytmp)
xtmp_b = ret[0]
ytmp_b = ret[1]
ytmp_b += offy
if dcos == 0:
xtmp_b += offx
else:
xtmp_b += offx / math.cos(ytmp_b)
ret = slalib.sla_fk45z(xtmp_b, ytmp_b, 1950)
xxtmp = ret[0]
yytmp = ret[1]
elif offmode == 0 or offmode == 3: #gal,lb,galactic
ytmp += offy
if dcos == 0:
xtmp += offx
else:
xtmp += offx / math.cos(ytmp)
ret = slalib.sla_galeq(xtmp, ytmp)
xxtmp = ret[0]
yytmp = ret[1]
vobs = self.calc_vobs(mjdtmp + 2400000.5, xxtmp, yytmp)
#print('vobs',vobs,type(vobs))
return vobs
def import_from_catalogs_aux(file, det_table, exp_table, djm, all=False):
# read SExtractor catalog file
# print >>sys.stderr, file
try:
hdus = pyfits.open(file)
except IOError:
yield (file, 0, 1, 0)
else:
dat = hdus[1].data
hdr_det = hdus[1].header
hdr_exp = hdus[2].header
hdus.close()
# delete PV coefficients from the header
for i in np.arange(17):
del hdr_exp['PV1_'+str(i)]
del hdr_exp['PV2_'+str(i)]
# test WCS of this image
try:
wcs = pywcs.WCS(hdr_exp)
# find the RA and Dec for the center of this exposure
pixcrd = np.array([[1024,2048]], np.float_)
sky = wcs.all_pix2sky(pixcrd, 1)
except:
yield (file, 0, 4, 0)
else:
# test if astrometry is good
pixcrd = [[i,0] for i in np.arange(2048)]+[[i,4095] for i in np.arange(2048)]+[[0,i] for i in np.arange(4096)]+[[2047,i] for i in np.arange(4096)]
n_pixel = len(pixcrd)
hdr_exp['CRVAL1']=20
hdr_exp['CRVAL2']=0
hdr_exp['CRPIX1']=1024
hdr_exp['CRPIX2']=2048
wcs = pywcs.WCS(hdr_exp)
test_sky = wcs.all_pix2sky(pixcrd, 0)
# bad = np.where((test_sky[:,0] < 19.7) + (test_sky[:,0] > 20.3) + (test_sky[:,1] < -0.58) + (test_sky[:,1] > 0.58)) # 5sigma cut
bad = np.where((test_sky[:,0] < 19.7095) + (test_sky[:,0] > 20.2902) + (test_sky[:,1] < -0.5783) + (test_sky[:,1] > 0.5782)) # 3sigma cut
bad_pixels = len(bad[0])
ratio = 1.0*bad_pixels/n_pixel
# print file, ratio, min(sky[:,0]), max(sky[:,0]), min(sky[:,1]), max(sky[:,1])
# import header data into exposures table
try:
coldefs = exp_table_def['schema']['main']['columns'] + exp_table_def['schema']['image_quality']['columns']
exp_cols = dict( (name, np.array([hdr_exp.get(fitsname)]).astype(coltype)) for (name, coltype, fitsname, _) in coldefs if fitsname != '')
coldefs = exp_table_def['schema']['abs_photo']['columns']
exp_cols.update(dict( (name, np.array([0]).astype(coltype)) for (name, coltype, fitsname, _) in coldefs if fitsname != ''))
exp_cols.update(dict( (name, np.array([hdr_exp.get(fitsname)]).astype(coltype)) for (name, coltype, fitsname, _) in coldefs if (fitsname != '') & (hdr_exp.has_key(fitsname))))
except TypeError:
yield (file, 0, 2, 0)
else:
exp_cols['ra'] = np.array([sky[0][0]])
exp_cols['dec'] = np.array([sky[0][1]])
(l, b) = np.degrees(sla_eqgal(*np.radians((exp_cols['ra'].squeeze(), exp_cols['dec'].squeeze()))))
exp_cols['l'] = np.array([l])
exp_cols['b'] = np.array([b])
exp_cols['bad_astro'] = np.array([ratio]).astype('f4')
exp_cols['mjd_import'] = np.array([djm]).astype('u4')
exp_cols['mumax_med'] = np.array([-99.99]).astype('f4')
exp_cols['mumax_rms'] = np.array([-99.99]).astype('f4')
exp_cols['n_bright'] = np.array([0]).astype('i2')
# Import sources into detection table
coldefs = det_table_def['schema']['main']['columns']
try:
if (conversion_to_int == 1):
det_cols = dict(( (name, np.around(dat.field(fitsname)*factor).astype(coltype[-2:])) for (name, _, coltype, factor, fitsname, _) in coldefs if fitsname != '' and factor > 1))
det_cols.update(dict(( (name, dat.field(fitsname).astype(coltype[-2:])) for (name, _, coltype, factor, fitsname, _) in coldefs if fitsname != '' and factor == 1)))
else:
det_cols = dict(( (name, dat.field(fitsname).astype(coltype[-2:])) for (name, coltype, _, _, fitsname, _) in coldefs if fitsname != ''))
except TypeError:
yield (file, 0, 3, 0)
else:
det_cols['mjd'] = (np.zeros(len(det_cols['ra'])) + hdr_exp['OBSMJD']).astype('f8')
det_cols['fid'] = (np.zeros(len(det_cols['ra'])) + hdr_exp['DBFID']).astype('u1')
# det_cols['mjd_import'] = (np.zeros(len(det_cols['ra'])) + djm).astype('u2')
det_cols['mag_abs'] = (np.zeros(len(det_cols['ra'])) + 32000).astype('u2')
# if there is Eran's absolute photometry...
if exp_cols['apbsrms'] > 0:
det_cols['mag_abs'] = np.round((dat.field('MAG_AUTO') + 2.5*np.log10(hdr_exp['AEXPTIME'])+ hdr_exp['APPAR01'] + hdr_exp['APPAR03']*hdr_exp['AIRMASS'] + hdr_exp['APPAR05']*(hdr_exp['OBSJD'] - hdr_exp['APMEDJD']) + hdr_exp['APPAR06']*(hdr_exp['OBSJD'] - hdr_exp['APMEDJD'])**2 + hdr_exp['APPAR07']*(dat.field('X_IMAGE') - 1024.)/2048. + hdr_exp['APPAR08']*(dat.field('Y_IMAGE') - 2048.)/4096. + hdr_exp['APPAR09']*((dat.field('Y_IMAGE') - 2048.)/4096.)**2 + hdr_exp['APPAR10']*((dat.field('Y_IMAGE') - 2048.)/4096.)**3 + hdr_exp['APPAR11']*(dat.field('X_IMAGE') - 1024.)/2048. * (dat.field('Y_IMAGE') - 2048.)/4096.)*1000.).clip(min=5000, max=32000).astype('u2')
# use bright stars to correct for seeing
bright = np.where( (det_cols['mag_abs'] > 14000) & (det_cols['mag_abs'] < 17000) )
if len(bright[0]) > 0:
sg = dat.field('MU_MAX') - dat.field('MAG_AUTO')
mumax_med = np.median(sg[bright])
mumax_rms = 0.741*(np.percentile(sg[bright],75) - np.percentile(sg[bright],25))
exp_cols['mumax_med'] = np.array([mumax_med]).astype('f4')
exp_cols['mumax_rms'] = np.array([mumax_rms]).astype('f4')
exp_cols['n_bright'] = np.array([len(bright[0])]).astype('i2')
(exp_id,) = exp_table.append(exp_cols)
det_cols['exp_id'] = (np.zeros(len(det_cols['ra'])) + hdr_exp['DBPID']).astype('u8')
det_cols['exp_id'][:] = exp_id
ids = det_table.append(det_cols)
yield (file, len(ids), 0, exp_id)
def read(self, parfilenm):
self.FILE = parfilenm
pf = open(parfilenm)
for line in pf.readlines():
# Convert any 'D-' or 'D+' to 'E-' or 'E+'
line = line.replace("D-", "E-")
line = line.replace("D+", "E+")
try:
splitline = line.split()
key = splitline[0]
if key in str_keys:
setattr(self, key, splitline[1])
elif key in float_keys:
try:
setattr(self, key, float(splitline[1]))
except ValueError:
pass
if len(
splitline
) == 3: # Some parfiles don't have flags, but do have errors
if splitline[2] not in ['0', '1']:
setattr(self, key + '_ERR', float(splitline[2]))
if len(splitline) == 4:
setattr(self, key + '_ERR', float(splitline[3]))
except:
print ''
# Read PSR name
if hasattr(self, 'PSR'):
setattr(self, 'PSR', self.PSR)
if hasattr(self, 'PSRJ'):
setattr(self, 'PSRJ', self.PSRJ)
# Deal with Ecliptic coords
if (hasattr(self, 'BETA') and hasattr(self, 'LAMBDA')):
self.use_eclip = True
setattr(self, 'ELAT', self.BETA)
setattr(self, 'ELONG', self.LAMBDA)
if (slalib and hasattr(self, 'ELAT') and hasattr(self, 'ELONG')):
self.use_eclip = True
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
ra_rad, dec_rad = sla_ecleq(self.ELONG * pu.DEGTORAD,
self.ELAT * pu.DEGTORAD, epoch)
rstr = pu.coord_to_string(*pu.rad_to_hms(ra_rad))
dstr = pu.coord_to_string(*pu.rad_to_dms(dec_rad))
setattr(self, 'RAJ', rstr)
setattr(self, 'DECJ', dstr)
if hasattr(self, 'RAJ'):
setattr(self, 'RA_RAD', pu.ra_to_rad(self.RAJ))
if hasattr(self, 'DECJ'):
setattr(self, 'DEC_RAD', pu.dec_to_rad(self.DECJ))
# Compute the Galactic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
l, b = sla_eqgal(self.RA_RAD, self.DEC_RAD)
setattr(self, 'GLONG', l * pu.RADTODEG)
setattr(self, 'GLAT', b * pu.RADTODEG)
# Compute the Ecliptic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
elon, elat = sla_eqecl(self.RA_RAD, self.DEC_RAD, epoch)
setattr(self, 'ELONG', elon * pu.RADTODEG)
setattr(self, 'ELAT', elat * pu.RADTODEG)
if hasattr(self, 'P'):
setattr(self, 'P0', self.P)
if hasattr(self, 'P0'):
setattr(self, 'F0', 1.0 / self.P0)
if hasattr(self, 'F0'):
setattr(self, 'P0', 1.0 / self.F0)
if hasattr(self, 'F1'):
setattr(self, 'P1', -self.F1 / (self.F0 * self.F0))
if hasattr(self, 'FB0'):
setattr(self, 'PB', (1.0 / self.FB0) / 86400.0)
if hasattr(self, 'P0_ERR'):
if hasattr(self, 'P1_ERR'):
f, ferr, fd, fderr = pu.pferrs(self.P0, self.P0_ERR, self.P1,
self.P1_ERR)
setattr(self, 'F0_ERR', ferr)
setattr(self, 'F1', fd)
setattr(self, 'F1_ERR', fderr)
else:
f, fd, = pu.p_to_f(self.P0, self.P1)
setattr(self, 'F0_ERR', self.P0_ERR / (self.P0 * self.P0))
setattr(self, 'F1', fd)
if hasattr(self, 'F0_ERR'):
if hasattr(self, 'F1_ERR'):
p, perr, pd, pderr = pu.pferrs(self.F0, self.F0_ERR, self.F1,
self.F1_ERR)
setattr(self, 'P0_ERR', perr)
setattr(self, 'P1', pd)
setattr(self, 'P1_ERR', pderr)
else:
p, pd, = pu.p_to_f(self.F0, self.F1)
setattr(self, 'P0_ERR', self.F0_ERR / (self.F0 * self.F0))
setattr(self, 'P1', pd)
if hasattr(self, 'DM'):
setattr(self, 'DM', self.DM)
if hasattr(self, 'EPS1') and hasattr(self, 'EPS2'):
self.use_ell = True
ecc = math.sqrt(self.EPS1 * self.EPS1 + self.EPS2 * self.EPS2)
omega = math.atan2(self.EPS1, self.EPS2)
setattr(self, 'ECC', ecc)
setattr(self, 'OM', omega)
if hasattr(self, 'PB') and hasattr(self,
'A1') and not hasattr(self, 'ECC'):
setattr(self, 'ECC', 0.0)
pf.close()
def get_vobs(self, mjdtmp, xtmp, ytmp, mode, offx, offy, dcos, offmode):
mode = mode.lower()
offmode = offmode.lower()
### for 'coord == horizontal' skip
try :
mode = self.coord_dict[mode]
except:
xxtmp = xtmp
yytmp = ytmp
try:
offmode = self.coord_dict[offmode]
except:
xxtmp = xtmp
yytmp = ytmp
if mode == 1:#j2000
if offmode == 0 or offmode == 1:#same or j2000
yytmp = ytmp+offy
if dcos == 0 :
xxtmp = xtmp+offx
else :
xxtmp = xtmp+offx/math.cos(yytmp)
elif offmode == 2:#b1950
ret = slalib.sla_fk54z(xtmp, ytmp, 2000)
xtmp_b = ret[0]
ytmp_b = ret[1]
ytmp_b += offy
if dcos == 0 :
xtmp_b += offx
else :
xtmp_b += offx/math.cos(ytmp_b)
ret_1 = slalib.sla_fk45z(xtmp_b, ytmp_b,1950)
xxtmp = ret_1[0]
yytmp = ret_1[1]
elif offmode == 3:#lb,galactic,gal
ret = slalib.sla_eqgal(xtmp,ytmp)
xtmp_g = ret[0]
ytmp_g = ret[1]
ytmp_g += offy
if dcos == 0 :
xtmp_g += offx
else :
xtmp_g += offx/math.cos(ytmp_g)
ret_1 = slalib.sla_galeq(xtmp_g, ytmp_g)
xxtmp = ret_1[0]
yytmp = ret_1[1]
if mode == 2:#b1950
if offmode == 1:#j2000
ret = slalib.sla_fk45z(xtmp, ytmp, 1950)
xtmp_j = ret[0]
ytmp_j = ret[1]
yytmp = ytmp_j+offy
if dcos == 0 :
xxtmp = xtmp_j+offx
else :
xxtmp = xtmp_j+offx/math.cos(ytmp_j)
elif offmode == 2 or offmode ==0:#b1950
ytmp += offy
if dcos == 0 :
xtmp += offx
else:
xtmp += offx/math.cos(ytmp)
ret = slalib.sla_fk45z(xtmp, ytmp, 1950)
xxtmp = ret[0]
yytmp = ret[1]
elif offmode == 3:#lb,galactic,gal
ret = slalib.sla_eg50(xtmp,ytmp)
xtmp_g = ret[0]
ytmp_g = ret[1]
ytmp_g += offy
if dcos == 0 :
xtmp_g += offx
else :
xtmp_g += offx/math.cos(ytmp_g)
ret = slalib.sla_galeq(xtmp_g, ytmp_g)
xxtmp = ret[0]
yytmp = ret[1]
if mode == 3:#lb,galactic,gal
if offmode == 1:#j2000
ret_2 = slalib.sla_galeq(xtmp, ytmp)
xtmp_j = ret_2[0]
ytmp_j = ret_2[1]
yytmp = ytmp_j+offy
if dcos == 0 :
xxtmp = xtmp_j+offx
else :
xxtmp = xtmp_j+offx/math.cos(ytmp_j)
elif offmode == 2:#b1950
ret = slalib.sla_ge50(xtmp,ytmp)
xtmp_b = ret[0]
ytmp_b = ret[1]
ytmp_b += offy
if dcos == 0 :
xtmp_b += offx
else :
xtmp_b += offx/math.cos(ytmp_b)
ret = slalib.sla_fk45z(xtmp_b, ytmp_b, 1950)
xxtmp = ret[0]
yytmp = ret[1]
elif offmode == 0 or offmode == 3:#gal,lb,galactic
ytmp += offy
if dcos == 0 :
xtmp += offx
else :
xtmp += offx/math.cos(ytmp)
ret = slalib.sla_galeq(xtmp, ytmp)
xxtmp = ret[0]
yytmp = ret[1]
vobs = self.calc_vobs(mjdtmp+2400000.5, xxtmp, yytmp)
#print('vobs',vobs,type(vobs))
return vobs
