formats = tmp[1]
record = np.dtype({'names':names,'formats':formats})
data = []
for ifile, fname in enumerate(filename_lst):
t1 = time.time()
data1 = []
infile = open(fname)
for row in infile:
if row[0] == '#':
continue
kic = int(row[0:8])
ra = np.float64(row[9:19])
dec = np.float64(row[19:29])
pmra = _str_to_float(row[30:38], np.NaN)
pmde = _str_to_float(row[39:47], np.NaN)
plx = _str_to_float(row[48:56], np.NaN)
umag = _str_to_float(row[57:63], np.NaN)
gmag = _str_to_float(row[63:70], np.NaN)
rmag = _str_to_float(row[70:77], np.NaN)
imag = _str_to_float(row[77:84], np.NaN)
zmag = _str_to_float(row[84:91], np.NaN)
grmag = _str_to_float(row[92:98], np.NaN)
d51mag = _str_to_float(row[99:105], np.NaN)
#magJ = _str_to_float(row[106:112], np.NaN)
#magH = _str_to_float(row[112:119], np.NaN)
#magK = _str_to_float(row[119:126], np.NaN)
kepmag = _str_to_float(row[127:133], np.NaN)
flag_g = int(row[209])
flag_v = int(row[211])
tmp = list(zip(*types))
record = np.dtype({'names':tmp[0],'formats':tmp[1]})
fill_item = np.array(
(0, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN),
dtype=record)
data = {}
infile = open(inputfile)
for row in infile:
hip = int(row[0:6])
radeg = float(row[15:28])/math.pi*180.
dedeg = float(row[29:42])/math.pi*180.
plx = _str_to_float(row[43:50], np.NaN)
e_plx = _str_to_float(row[83:89], np.NaN)
pmRA = _str_to_float(row[51:59], np.NaN)
pmDE = _str_to_float(row[60:68], np.NaN)
e_pmRA = _str_to_float(row[90:96], np.NaN)
e_pmDE = _str_to_float(row[97:103], np.NaN)
Hpmag = _str_to_float(row[129:136], np.NaN)
e_Hpmag = _str_to_float(row[137:143], np.NaN)
Hpscat = _str_to_float(row[144:149], np.NaN)
BV = _str_to_float(row[152:158], np.NaN)
e_BV = _str_to_float(row[159:164], np.NaN)
VI = _str_to_float(row[165:171], np.NaN)
if not np.isnan(pmRA):
pm_ra = pmRA*1e-3/3600. # convert pm_RA from mas/yr to degree/yr
#radeg += (2000.0-1991.25)*pm_ra/math.cos(dedeg/180.*math.pi)
def main():
path = os.path.join(os.getenv('ASTRO_DATA'), 'catalog/I/259/')
# load duplicate list
dup_tyc_lst = []
infile1 = open('duplicate.txt')
for row in infile1:
g = row.split('|')[0].split()
tyc1 = int(g[0])
tyc2 = int(g[1])
tyc3 = int(g[2])
dup_tyc_lst.append((tyc1,tyc2,tyc3))
infile1.close()
types = [
('TYC', np.int32),
('RAdeg', np.float64),
('DEdeg', np.float64),
('e_RA', np.int16),
('e_DE', np.int16),
('epoch_RA', np.float32),
('epoch_DE', np.float32),
('q_RA', np.float32),
('q_DE', np.float32),
('pmRA', np.float32),
('pmDE', np.float32),
('e_pmRA', np.float32),
('e_pmDE', np.float32),
('q_pmRA', np.float32),
('q_pmDE', np.float32),
('Num', np.int16),
('BTmag', np.float32),
('e_BTmag', np.float32),
('VTmag', np.float32),
('e_VTmag', np.float32),
('prox', np.float32),
]
tmp = list(zip(*types))
record = np.dtype({'names':tmp[0],'formats':tmp[1]})
fn_lst = ['tyc2.dat.%02d'%i for i in range(20)]
data = []
for fn in fn_lst:
print(fn)
infile = open(os.path.join(path, fn))
for row in infile:
tyc1 = int(row[0:4])
tyc2 = int(row[5:10])
tyc3 = int(row[11])
tyc = np.int32((tyc1<<18) + (tyc2<<4) + (tyc3<<1))
radeg = _str_to_float(row[15:27], np.NaN)
dedeg = _str_to_float(row[28:40], np.NaN)
pmRA = _str_to_float(row[41:48], np.NaN)
pmDE = _str_to_float(row[49:56], np.NaN)
e_ra = _str_to_int(row[57:60], -1)
e_de = _str_to_int(row[61:64], -1)
e_pmRA = _str_to_float(row[65:69], np.NaN)
e_pmDE = _str_to_float(row[70:74], np.NaN)
epoch_ra = _str_to_float(row[75:82], np.NaN)
epoch_de = _str_to_float(row[83:90], np.NaN)
num = _str_to_int(row[91:93], -1)
q_RA = _str_to_float(row[94:97], np.NaN)
q_DE = _str_to_float(row[98:101], np.NaN)
q_pmRA = _str_to_float(row[102:105], np.NaN)
q_pmDE = _str_to_float(row[106:109], np.NaN)
BTmag = _str_to_float(row[110:116], np.NaN)
e_BTmag = _str_to_float(row[117:122], np.NaN)
VTmag = _str_to_float(row[123:129], np.NaN)
e_VTmag = _str_to_float(row[130:135], np.NaN)
prox = _str_to_float(row[136:139], np.NaN)*0.1
item = (tyc, radeg, dedeg, e_ra, e_de, epoch_ra, epoch_de, q_RA, q_DE,
pmRA, pmDE, e_pmRA, e_pmDE, q_pmRA, q_pmDE, num,
BTmag, e_BTmag, VTmag, e_VTmag, prox)
data.append(item)
infile.close()
for fn in ['suppl_1.dat', 'suppl_2.dat']:
infile = open(os.path.join(path, fn))
for row in infile:
tyc1 = int(row[0:4])
tyc2 = int(row[5:10])
tyc3 = int(row[11])
if (tyc1,tyc2,tyc3) in dup_tyc_lst:
m = 1
else:
m = 0
tyc = np.int32((tyc1<<18) + (tyc2<<4) + (tyc3<<1) + m)
radeg = _str_to_float(row[15:27], np.NaN)
dedeg = _str_to_float(row[28:40], np.NaN)
pmRA = _str_to_float(row[41:48], np.NaN)
pmDE = _str_to_float(row[49:56], np.NaN)
e_ra = _str_to_int(row[57:60], -1)
e_de = _str_to_int(row[61:64], -1)
e_pmRA = _str_to_float(row[65:69], np.NaN)
e_pmDE = _str_to_float(row[70:74], np.NaN)
epoch_ra = _str_to_float(row[75:82], np.NaN)
epoch_de = _str_to_float(row[83:90], np.NaN)
num = _str_to_int(row[91:93], -1)
q_RA = _str_to_float(row[94:97], np.NaN)
q_DE = _str_to_float(row[98:101], np.NaN)
q_pmRA = _str_to_float(row[102:105], np.NaN)
q_pmDE = _str_to_float(row[106:109], np.NaN)
BTmag = _str_to_float(row[110:116], np.NaN)
e_BTmag = _str_to_float(row[117:122], np.NaN)
VTmag = _str_to_float(row[123:129], np.NaN)
e_VTmag = _str_to_float(row[130:135], np.NaN)
prox = _str_to_float(row[136:139], np.NaN)*0.1
item = (tyc, radeg, dedeg, e_ra, e_de, epoch_ra, epoch_de, q_RA, q_DE,
pmRA, pmDE, e_pmRA, e_pmDE, q_pmRA, q_pmDE, num,
BTmag, e_BTmag, VTmag, e_VTmag, prox)
data.append(item)
infile.close()
fill_item = (0, np.NaN, np.NaN, 0, 0, np.NaN, np.NaN, np.NaN, np.NaN,
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, -1,
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN)
data = np.array(data, dtype=record)
data = np.sort(data, order='TYC')
# add an empty item in the beginning
data = np.insert(data, 0, np.array(fill_item, dtype=record))
pri_hdu = fits.PrimaryHDU()
tbl_hdu = fits.BinTableHDU(data)
hdu_lst = fits.HDUList([pri_hdu,tbl_hdu])
outputfile = 'TYC2.fits'
if os.path.exists(outputfile):
os.remove(outputfile)
hdu_lst.writeto(outputfile)
data = fits.getdata(outputfile)
tyc_lst = data['TYC']
diff = np.diff(tyc_lst)
mask = diff==0
for i, m in enumerate(mask):
if m:
print(data[i]['TYC'], data[i]['Note'], data[i+1]['TYC'],data[i+1]['Note'])
def main():
path = os.path.join(os.getenv('ASTRO_DATA'), 'catalog/I/239/')
types = [
('TYC', np.int32),
('RAdeg', np.float64),
('DEdeg', np.float64),
('e_RA', np.float32),
('e_DE', np.float32),
('pmRA', np.float32),
('pmDE', np.float32),
('e_pmRA', np.float32),
('e_pmDE', np.float32),
('Plx', np.float32),
('e_Plx', np.float32),
('Nastro', np.int16),
('Vmag', np.float32),
('r_Vmag', 'S1'),
('BTmag', np.float32),
('e_BTmag', np.float32),
('VTmag', np.float32),
('e_VTmag', np.float32),
('r_BTmag', 'S1'),
('B-V', np.float32),
('e_B-V', np.float32),
('Nphoto', np.int16),
('VTscat', np.float32),
('VTmax', np.float32),
('VTmin', np.float32),
('VarFlag', 'S1'),
('MultFlag', 'S1'),
]
tmp = list(zip(*types))
record = np.dtype({'names': tmp[0], 'formats': tmp[1]})
fill_item = (
0,
np.NaN,
np.NaN,
np.NaN,
np.NaN, # ra, de, e_ra, e_de
np.NaN,
np.NaN,
np.NaN,
np.NaN, # pm
np.NaN,
np.NaN,
-1, # plx, Nastro
np.NaN,
'',
np.NaN,
np.NaN,
np.NaN,
np.NaN,
'', # vmag ~ r_BTmag
np.NaN,
np.NaN,
-1,
np.NaN,
np.NaN,
np.NaN,
'',
'')
data = []
fn = 'tyc_main.dat'
infile = open(os.path.join(path, fn))
for row in infile:
if row[0] != 'T':
print('Warning: Not Tycho star')
g = row[2:14].split()
tyc1 = int(g[0])
tyc2 = int(g[1])
tyc3 = int(g[2])
tyc = np.int32((tyc1 << 18) + (tyc2 << 4) + (tyc3 << 1))
radeg = _str_to_float(row[51:63], np.NaN)
dedeg = _str_to_float(row[64:76], np.NaN)
vmag = _str_to_float(row[41:46], np.NaN)
r_vmag = row[49].strip()
plx = _str_to_float(row[79:86], np.NaN)
pm_ra = _str_to_float(row[87:95], np.NaN)
pm_de = _str_to_float(row[96:104], np.NaN)
e_ra = _str_to_float(row[105:111], np.NaN)
e_de = _str_to_float(row[112:118], np.NaN)
e_plx = _str_to_float(row[119:125], np.NaN)
e_pmra = _str_to_float(row[126:132], np.NaN)
e_pmde = _str_to_float(row[133:139], np.NaN)
nastro = _str_to_int(row[200:203], 0)
btmag = _str_to_float(row[217:223], np.NaN)
e_btmag = _str_to_float(row[224:229], np.NaN)
vtmag = _str_to_float(row[230:236], np.NaN)
e_vtmag = _str_to_float(row[237:242], np.NaN)
r_btmag = row[243].strip()
bv = _str_to_float(row[245:251], np.NaN)
e_bv = _str_to_float(row[252:257], np.NaN)
nphoto = _str_to_int(row[269:272], 0)
vtscat = _str_to_float(row[273:278], np.NaN)
vtmax = _str_to_float(row[279:284], np.NaN)
vtmin = _str_to_float(row[285:290], np.NaN)
varflag = row[293].strip()
multflag = row[295].strip()
item = (tyc, radeg, dedeg, e_ra, e_de, pm_ra, pm_de, e_pmra, e_pmde,
plx, e_plx, nastro, vmag, r_vmag, btmag, e_btmag, vtmag,
e_vtmag, r_btmag, bv, e_bv, nphoto, vtscat, vtmax, vtmin,
varflag, multflag)
data.append(item)
infile.close()
data = np.array(data, dtype=record)
data = np.sort(data, order='TYC')
# add an empty item in the beginning
data = np.insert(data, 0, np.array(fill_item, dtype=record))
pri_hdu = fits.PrimaryHDU()
tbl_hdu = fits.BinTableHDU(data)
hdu_lst = fits.HDUList([pri_hdu, tbl_hdu])
outputfile = 'TYC.fits'
if os.path.exists(outputfile):
os.remove(outputfile)
hdu_lst.writeto(outputfile)
data = fits.getdata(outputfile)
tyc_lst = data['TYC']
diff = np.diff(tyc_lst)
mask = diff == 0
for i, m in enumerate(mask):
if m:
print(data[i]['TYC'], data[i + 1]['TYC'])
def main():
inputfile = os.path.join(os.getenv('ASTRO_DATA'), 'catalog/I/131A/sao.dat')
types = [
('SAO', np.int32),
('RAdeg', np.float64),
('DEdeg', np.float64),
('pmRA', np.float32),
('pmDE', np.float32),
('e_pmRA', np.float32),
('e_pmDE', np.float32),
('Vmag', np.float32),
('Pmag', np.float32),
('SpType', 'S3'),
('r_Vmag', np.int16),
('r_Pmag', np.int16),
('r_Num', np.int16),
('r_pm', np.int16),
('r_SpType', np.int16),
('RAdeg2000', np.float64),
('DEdeg2000', np.float64),
('pmRA2000', np.float32),
('pmDE2000', np.float32),
]
tmp = list(zip(*types))
record = np.dtype({'names': tmp[0], 'formats': tmp[1]})
data = []
infile = open(inputfile)
for row in infile:
sao = int(row[0:6])
radeg = (int(row[7:9]) + int(row[9:11])/60. + float(row[11:17])/3600.)*15.
dedeg = int(row[42:44]) + int(row[44:46])/60. + float(row[46:51])/3600.
if row[41]=='-':
dedeg = -dedeg
pmra = _str_to_float(row[17:24], np.NaN)*1000.
e_pmra = _str_to_float(row[24:26], np.NaN)
pmde = _str_to_float(row[51:57], np.NaN)*1000.
e_pmde = _str_to_float(row[57:59], np.NaN)
pmag = _str_to_float(row[76:80], np.NaN)
vmag = _str_to_float(row[80:84], np.NaN)
sptype = row[84:87].strip()
r_vmag = int(row[87:89])
r_num = int(row[89:91])
r_pmag = int(row[91])
r_pm = int(row[92])
r_sptype = int(row[93])
ra2000 = (int(row[150:152]) + int(row[152:154])/60. + float(row[154:160])/3600.)*15.
pmra2000 = _str_to_float(row[160:167], np.NaN)*1000.
de2000 = int(row[168:170]) + int(row[170:172])/60. + float(row[172:177])/3600.
pmde2000 = _str_to_float(row[177:183], np.NaN)*1000.
if row[167]=='-':
de2000 = -de2000
item = (sao, radeg, dedeg, pmra, pmde, e_pmra, e_pmde,
vmag, pmag, sptype, r_vmag, r_pmag, r_num, r_pm, r_sptype,
ra2000, de2000, pmra2000, pmde2000)
data.append(item)
data = np.array(data, dtype=record)
pri_hdu = fits.PrimaryHDU()
tbl_hdu = fits.BinTableHDU(data)
hdu_lst = fits.HDUList([pri_hdu, tbl_hdu])
outname = 'SAO.fits'
if os.path.exists(outname):
os.remove(outname)
hdu_lst.writeto(outname)
data = {}
infile = open(inputfile)
for row in infile:
hip = int(row[8:14])
rah = int(row[17:19])
ram = int(row[20:22])
ras = float(row[23:28])
radeg = (rah + ram/60. + ras/3600.)*15.
ded = abs(int(row[30:32]))
dem = int(row[33:35])
des = float(row[36:40])
dedeg = ded + dem/60. + des/3600.
if row[29]=='-':
dedeg = -dedeg
vmag = _str_to_float(row[41:46], np.NaN)
plx = _str_to_float(row[79:86], np.NaN)
e_plx = _str_to_float(row[119:125], np.NaN)
pmRA = _str_to_float(row[87:95], np.NaN)
pmDE = _str_to_float(row[96:104], np.NaN)
e_pmRA = _str_to_float(row[126:132], np.NaN)
e_pmDE = _str_to_float(row[133:139], np.NaN)
BTmag = _str_to_float(row[217:223], np.NaN)
VTmag = _str_to_float(row[230:236], np.NaN)
e_BTmag = _str_to_float(row[224:229], np.NaN)
e_VTmag = _str_to_float(row[237:242], np.NaN)
BV = _str_to_float(row[245:251], np.NaN)
e_BV = _str_to_float(row[252:257], np.NaN)
r_BV = row[258].strip()
VI = _str_to_float(row[260:264], np.NaN)
e_VI = _str_to_float(row[265:269], np.NaN)
def main():
path = os.path.join(os.getenv('ASTRO_DATA'), 'catalog/I/259/')
# load duplicate list
dup_tyc_lst = []
infile1 = open('duplicate.txt')
for row in infile1:
g = row.split('|')[0].split()
tyc1 = int(g[0])
tyc2 = int(g[1])
tyc3 = int(g[2])
dup_tyc_lst.append((tyc1, tyc2, tyc3))
infile1.close()
types = [
('TYC', np.int32),
('RAdeg', np.float64),
('DEdeg', np.float64),
('e_RA', np.int16),
('e_DE', np.int16),
('epoch_RA', np.float32),
('epoch_DE', np.float32),
('q_RA', np.float32),
('q_DE', np.float32),
('pmRA', np.float32),
('pmDE', np.float32),
('e_pmRA', np.float32),
('e_pmDE', np.float32),
('q_pmRA', np.float32),
('q_pmDE', np.float32),
('Num', np.int16),
('BTmag', np.float32),
('e_BTmag', np.float32),
('VTmag', np.float32),
('e_VTmag', np.float32),
('prox', np.float32),
]
tmp = list(zip(*types))
record = np.dtype({'names': tmp[0], 'formats': tmp[1]})
fn_lst = ['tyc2.dat.%02d' % i for i in range(20)]
data = []
for fn in fn_lst:
print(fn)
infile = open(os.path.join(path, fn))
for row in infile:
tyc1 = int(row[0:4])
tyc2 = int(row[5:10])
tyc3 = int(row[11])
tyc = np.int32((tyc1 << 18) + (tyc2 << 4) + (tyc3 << 1))
radeg = _str_to_float(row[15:27], np.NaN)
dedeg = _str_to_float(row[28:40], np.NaN)
pmRA = _str_to_float(row[41:48], np.NaN)
pmDE = _str_to_float(row[49:56], np.NaN)
e_ra = _str_to_int(row[57:60], -1)
e_de = _str_to_int(row[61:64], -1)
e_pmRA = _str_to_float(row[65:69], np.NaN)
e_pmDE = _str_to_float(row[70:74], np.NaN)
epoch_ra = _str_to_float(row[75:82], np.NaN)
epoch_de = _str_to_float(row[83:90], np.NaN)
num = _str_to_int(row[91:93], -1)
q_RA = _str_to_float(row[94:97], np.NaN)
q_DE = _str_to_float(row[98:101], np.NaN)
q_pmRA = _str_to_float(row[102:105], np.NaN)
q_pmDE = _str_to_float(row[106:109], np.NaN)
BTmag = _str_to_float(row[110:116], np.NaN)
e_BTmag = _str_to_float(row[117:122], np.NaN)
VTmag = _str_to_float(row[123:129], np.NaN)
e_VTmag = _str_to_float(row[130:135], np.NaN)
prox = _str_to_float(row[136:139], np.NaN) * 0.1
item = (tyc, radeg, dedeg, e_ra, e_de, epoch_ra, epoch_de, q_RA,
q_DE, pmRA, pmDE, e_pmRA, e_pmDE, q_pmRA, q_pmDE, num,
BTmag, e_BTmag, VTmag, e_VTmag, prox)
data.append(item)
infile.close()
for fn in ['suppl_1.dat', 'suppl_2.dat']:
infile = open(os.path.join(path, fn))
for row in infile:
tyc1 = int(row[0:4])
tyc2 = int(row[5:10])
tyc3 = int(row[11])
if (tyc1, tyc2, tyc3) in dup_tyc_lst:
m = 1
else:
m = 0
tyc = np.int32((tyc1 << 18) + (tyc2 << 4) + (tyc3 << 1) + m)
radeg = _str_to_float(row[15:27], np.NaN)
dedeg = _str_to_float(row[28:40], np.NaN)
pmRA = _str_to_float(row[41:48], np.NaN)
pmDE = _str_to_float(row[49:56], np.NaN)
e_ra = _str_to_int(row[57:60], -1)
e_de = _str_to_int(row[61:64], -1)
e_pmRA = _str_to_float(row[65:69], np.NaN)
e_pmDE = _str_to_float(row[70:74], np.NaN)
epoch_ra = _str_to_float(row[75:82], np.NaN)
epoch_de = _str_to_float(row[83:90], np.NaN)
num = _str_to_int(row[91:93], -1)
q_RA = _str_to_float(row[94:97], np.NaN)
q_DE = _str_to_float(row[98:101], np.NaN)
q_pmRA = _str_to_float(row[102:105], np.NaN)
q_pmDE = _str_to_float(row[106:109], np.NaN)
BTmag = _str_to_float(row[110:116], np.NaN)
e_BTmag = _str_to_float(row[117:122], np.NaN)
VTmag = _str_to_float(row[123:129], np.NaN)
e_VTmag = _str_to_float(row[130:135], np.NaN)
prox = _str_to_float(row[136:139], np.NaN) * 0.1
item = (tyc, radeg, dedeg, e_ra, e_de, epoch_ra, epoch_de, q_RA,
q_DE, pmRA, pmDE, e_pmRA, e_pmDE, q_pmRA, q_pmDE, num,
BTmag, e_BTmag, VTmag, e_VTmag, prox)
data.append(item)
infile.close()
fill_item = (0, np.NaN, np.NaN, 0, 0, np.NaN, np.NaN, np.NaN, np.NaN,
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, -1, np.NaN,
np.NaN, np.NaN, np.NaN, np.NaN)
data = np.array(data, dtype=record)
data = np.sort(data, order='TYC')
# add an empty item in the beginning
data = np.insert(data, 0, np.array(fill_item, dtype=record))
pri_hdu = fits.PrimaryHDU()
tbl_hdu = fits.BinTableHDU(data)
hdu_lst = fits.HDUList([pri_hdu, tbl_hdu])
outputfile = 'TYC2.fits'
if os.path.exists(outputfile):
os.remove(outputfile)
hdu_lst.writeto(outputfile)
data = fits.getdata(outputfile)
tyc_lst = data['TYC']
diff = np.diff(tyc_lst)
mask = diff == 0
for i, m in enumerate(mask):
if m:
print(data[i]['TYC'], data[i]['Note'], data[i + 1]['TYC'],
data[i + 1]['Note'])
formats = tmp[1]
record = np.dtype({'names': names, 'formats': formats})
data = []
for ifile, fname in enumerate(filename_lst):
t1 = time.time()
data1 = []
infile = open(fname)
for row in infile:
if row[0] == '#':
continue
kic = int(row[0:8])
ra = np.float64(row[9:19])
dec = np.float64(row[19:29])
pmra = _str_to_float(row[30:38], np.NaN)
pmde = _str_to_float(row[39:47], np.NaN)
plx = _str_to_float(row[48:56], np.NaN)
umag = _str_to_float(row[57:63], np.NaN)
gmag = _str_to_float(row[63:70], np.NaN)
rmag = _str_to_float(row[70:77], np.NaN)
imag = _str_to_float(row[77:84], np.NaN)
zmag = _str_to_float(row[84:91], np.NaN)
grmag = _str_to_float(row[92:98], np.NaN)
d51mag = _str_to_float(row[99:105], np.NaN)
#magJ = _str_to_float(row[106:112], np.NaN)
#magH = _str_to_float(row[112:119], np.NaN)
#magK = _str_to_float(row[119:126], np.NaN)
kepmag = _str_to_float(row[127:133], np.NaN)
flag_g = int(row[209])
flag_v = int(row[211])
tmp = list(zip(*types))
record = np.dtype({'names': tmp[0], 'formats': tmp[1]})
fill_item = np.array(
(0, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN),
dtype=record)
data = {}
infile = open(inputfile)
for row in infile:
hip = int(row[0:6])
radeg = float(row[15:28]) / math.pi * 180.
dedeg = float(row[29:42]) / math.pi * 180.
plx = _str_to_float(row[43:50], np.NaN)
e_plx = _str_to_float(row[83:89], np.NaN)
pmRA = _str_to_float(row[51:59], np.NaN)
pmDE = _str_to_float(row[60:68], np.NaN)
e_pmRA = _str_to_float(row[90:96], np.NaN)
e_pmDE = _str_to_float(row[97:103], np.NaN)
Hpmag = _str_to_float(row[129:136], np.NaN)
e_Hpmag = _str_to_float(row[137:143], np.NaN)
Hpscat = _str_to_float(row[144:149], np.NaN)
BV = _str_to_float(row[152:158], np.NaN)
e_BV = _str_to_float(row[159:164], np.NaN)
VI = _str_to_float(row[165:171], np.NaN)
if not np.isnan(pmRA):
pm_ra = pmRA * 1e-3 / 3600. # convert pm_RA from mas/yr to degree/yr
#radeg += (2000.0-1991.25)*pm_ra/math.cos(dedeg/180.*math.pi)
def main():
astrodata = os.getenv('ASTRO_DATA')
types = [
('EPIC', np.int32),
('Objtype', 'S8'),
('Kepflag', 'S3'),
('RAdeg', np.float64),
('DEdeg', np.float64),
('pmRA', np.float32),
('pmDE', np.float32),
('e_pmRA', np.float32),
('e_pmDE', np.float32),
('Plx', np.float32),
('e_Plx', np.float32),
('Bmag', np.float32),
('e_Bmag', np.float32),
('Vmag', np.float32),
('e_Vmag', np.float32),
('umag', np.float32),
('e_umag', np.float32),
('gmag', np.float32),
('e_gmag', np.float32),
('rmag', np.float32),
('e_rmag', np.float32),
('imag', np.float32),
('e_imag', np.float32),
('zmag', np.float32),
('e_zmag', np.float32),
('Jmag', np.float32),
('e_Jmag', np.float32),
('Hmag', np.float32),
('e_Hmag', np.float32),
('Kmag', np.float32),
('e_Kmag', np.float32),
('W1mag', np.float32),
('e_W1mag', np.float32),
('W2mag', np.float32),
('e_W2mag', np.float32),
('W3mag', np.float32),
('e_W3mag', np.float32),
('W4mag', np.float32),
('e_W4mag', np.float32),
('kepmag', np.float32),
('Teff', np.int16),
('ue_Teff', np.int16),
('le_Teff', np.int16),
('logg', np.float32),
('ue_logg', np.float32),
('le_logg', np.float32),
('FeH', np.float32),
('ue_FeH', np.float32),
('le_FeH', np.float32),
('Rad', np.float32),
('ue_Rad', np.float32),
('le_Rad', np.float32),
('Mass', np.float32),
('ue_Mass', np.float32),
('le_Mass', np.float32),
('rho', np.float32),
('ue_rho', np.float32),
('le_rho', np.float32),
('Lum', np.float32),
('ue_Lum', np.float32),
('le_Lum', np.float32),
('Dist', np.float32),
('ue_Dist', np.float32),
('le_Dist', np.float32),
('E(B-V)', np.float32),
('ue_E(B-V)',np.float32),
('le_E(B-V)',np.float32),
]
tmp = list(zip(*types))
record = np.dtype({'names':tmp[0],'formats':tmp[1]})
fill_item = (0, '', '',
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
#ra dec pmra pmdec e_pmra, e_pmdec plx, e_plx
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
#Bmag Vmag umag gmag
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
#rmag imag zmag
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
# Jmag Hmag Kmag
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
# w1 w2 w3 w4
np.NaN,
# kpmag
-1, -1, -1, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
# Teff logg FeH
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
# Rad Mass rho
np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
# Lum dist EBV
)
epic_ranges = {
1: (201000001, 210000000),
2: (210000001, 220000000),
3: (220000001, 230000000),
4: (230000001, 240000000),
5: (240000001, 250000000),
6: (250000001, 251809654),
}
for i in range(1,7):
count = 0
data = []
fn = 'epic_%d_19Dec2017.txt'%i
print(fn)
filename = os.path.join(astrodata, 'catalog/others/EPIC/%s'%fn)
prev_epic = 0
infile = open(filename)
infile.readline()
_epic = epic_ranges[i][0]
for row in infile:
g = row.split('|')
epic = int(g[0])
objtype = g[6].strip()
kepflag = g[7].strip()
ra = float(g[9])
dec = float(g[10])
pmra = _str_to_float(g[11], np.NaN)
e_pmra = _str_to_float(g[12], np.NaN)
pmde = _str_to_float(g[13], np.NaN)
e_pmde = _str_to_float(g[14], np.NaN)
plx = _str_to_float(g[15], np.NaN)
e_plx = _str_to_float(g[16], np.NaN)
bmag = _str_to_float(g[17], np.NaN)
ebmag = _str_to_float(g[18], np.NaN)
vmag = _str_to_float(g[19], np.NaN)
evmag = _str_to_float(g[20], np.NaN)
umag = _str_to_float(g[21], np.NaN)
eumag = _str_to_float(g[22], np.NaN)
gmag = _str_to_float(g[23], np.NaN)
egmag = _str_to_float(g[24], np.NaN)
rmag = _str_to_float(g[25], np.NaN)
ermag = _str_to_float(g[26], np.NaN)
imag = _str_to_float(g[27], np.NaN)
eimag = _str_to_float(g[28], np.NaN)
zmag = _str_to_float(g[29], np.NaN)
ezmag = _str_to_float(g[30], np.NaN)
jmag = _str_to_float(g[31], np.NaN)
ejmag = _str_to_float(g[32], np.NaN)
hmag = _str_to_float(g[33], np.NaN)
ehmag = _str_to_float(g[34], np.NaN)
kmag = _str_to_float(g[35], np.NaN)
ekmag = _str_to_float(g[36], np.NaN)
w1mag = _str_to_float(g[37], np.NaN)
ew1mag = _str_to_float(g[38], np.NaN)
w2mag = _str_to_float(g[39], np.NaN)
ew2mag = _str_to_float(g[40], np.NaN)
w3mag = _str_to_float(g[41], np.NaN)
ew3mag = _str_to_float(g[42], np.NaN)
w4mag = _str_to_float(g[43], np.NaN)
ew4mag = _str_to_float(g[44], np.NaN)
kepmag = _str_to_float(g[45], np.NaN)
teff = _str_to_int(g[46], -1)
ue_teff = _str_to_int(g[47], -1)
le_teff = _str_to_int(g[48], -1)
logg = _str_to_float(g[49], np.NaN)
ue_logg = _str_to_float(g[50], np.NaN)
le_logg = _str_to_float(g[51], np.NaN)
feh = _str_to_float(g[52], np.NaN)
ue_feh = _str_to_float(g[53], np.NaN)
le_feh = _str_to_float(g[54], np.NaN)
rad = _str_to_float(g[55], np.NaN)
ue_rad = _str_to_float(g[56], np.NaN)
le_rad = _str_to_float(g[57], np.NaN)
mass = _str_to_float(g[58], np.NaN)
ue_mass = _str_to_float(g[59], np.NaN)
le_mass = _str_to_float(g[60], np.NaN)
rho = _str_to_float(g[61], np.NaN)
ue_rho = _str_to_float(g[62], np.NaN)
le_rho = _str_to_float(g[63], np.NaN)
lum = _str_to_float(g[64], np.NaN)
ue_lum = _str_to_float(g[65], np.NaN)
le_lum = _str_to_float(g[66], np.NaN)
dist = _str_to_float(g[67], np.NaN)
ue_dist = _str_to_float(g[68], np.NaN)
le_dist = _str_to_float(g[69], np.NaN)
ebv = _str_to_float(g[70], np.NaN)
ue_ebv = _str_to_float(g[71], np.NaN)
le_ebv = _str_to_float(g[72], np.NaN)
item = (epic, objtype, kepflag,
ra, dec, pmra, pmde, e_pmra, e_pmde, plx, e_plx,
bmag, ebmag, vmag, evmag, umag, eumag, gmag, egmag, rmag, ermag,
imag, eimag, zmag, ezmag, jmag, ejmag, hmag, ejmag, kmag, ekmag,
w1mag, ew1mag, w2mag, ew2mag, w3mag, ew3mag, w4mag, ew4mag, kepmag,
teff, ue_teff, le_teff, logg, ue_logg, le_logg,
feh, ue_feh, le_feh, rad, ue_rad, le_rad,
mass, ue_mass, le_mass, rho, ue_rho, le_rho,
lum, ue_lum, le_lum, dist, ue_dist, le_dist,
ebv, ue_ebv, le_ebv,
)
if epic > _epic:
for j in range(epic - _epic):
data.append(fill_item)
_epic += 1
data.append(item)
_epic += 1
count += 1
if count % 1000000==0: print(count)
infile.close()
print('Data reading finished')
data = np.array(data, dtype=record)
print('Begin file writing')
pri_hdu = fits.PrimaryHDU()
tbl_hdu = fits.BinTableHDU(data)
hdu_lst = fits.HDUList([pri_hdu,tbl_hdu])
outputfile = 'EPIC_%d.fits'%i
if os.path.exists(outputfile):
os.remove(outputfile)
hdu_lst.writeto(outputfile)
def main():
inputfile = os.path.join(os.getenv('ASTRO_DATA'), 'catalog/V/50/catalog')
types = [
('HR', np.int16),
('RAdeg', np.float64),
('DEdeg', np.float64),
('pmRA', np.float32),
('pmDE', np.float32),
('Plx', np.float32),
('n_Plx', 'S1'),
('Vmag', np.float32),
('n_Vmag', 'S1'),
('u_Vmag', 'S1'),
('B-V', np.float32),
('u_B-V', 'S1'),
('U-B', np.float32),
('u_U-B', 'S1'),
('R-I', np.float32),
('n_R-I', 'S1'),
('SpType', 'S20'),
('n_SpType','S1'),
('RadVel', np.float32),
('n_RadVel','S4'),
('l_RotVel','S1'),
('RotVel', np.float32),
('u_RotVel','S1'),
('Dmag', np.float32),
('Sep', np.float32),
('MultID', 'S4'),
('MultCnt', np.int16),
]
tmp = list(zip(*types))
record = np.dtype({'names': tmp[0], 'formats': tmp[1]})
data = []
infile = open(inputfile)
for row in infile:
hr = int(row[0:4])
try:
ra = (int(row[75:77]) + int(row[77:79])/60. + float(row[79:83])/3600.)*15.
except:
ra = np.NaN
try:
de = int(row[84:86]) + int(row[86:88])/60. + float(row[88:90])/3600.
except:
de = np.NaN
if row[83]=='-':
de = -de
vmag = _str_to_float(row[102:107], np.NaN)
n_vmag = row[107].strip()
u_vmag = row[108].strip()
bv = _str_to_float(row[109:114], np.NaN)
u_bv = row[114].strip()
ub = _str_to_float(row[115:120], np.NaN)
u_ub = row[120].strip()
ri = _str_to_float(row[121:126], np.NaN)
u_ri = row[126].strip()
sptype = row[127:147].strip()
n_sptype = row[147].strip()
pmra = _str_to_float(row[148:154], np.NaN)*1000
pmde = _str_to_float(row[154:160], np.NaN)*1000
n_plx = row[160].strip()
plx = _str_to_float(row[161:166], np.NaN)
radv = _str_to_float(row[166:170], np.NaN)
if len(row)>=174:
n_radv = row[170:174].strip()
else:
n_radv = ''
if len(row)>=176:
l_rotv = row[174:176].strip()
else:
l_rotv = ''
if len(row)>=179:
rotv = _str_to_float(row[176:179], np.NaN)
else:
rotv = np.NaN
if len(row)>=180:
u_rotv = row[179].strip()
else:
u_rotv = ''
if len(row)>=180:
dmag = _str_to_float(row[180:184], np.NaN)
sep = _str_to_float(row[184:190], np.NaN)
multid = row[190:194].strip()
multcnt = _str_to_int(row[194:196], -1)
else:
dmag = np.NaN
sep = np.NaN
multid = ''
multcnt = -1
item = (hr, ra, de, pmra, pmde, plx, n_plx,
vmag, n_vmag, u_vmag, bv, u_bv, ub, u_ub, ri, u_ri,
sptype, n_sptype, radv, n_radv, l_rotv, rotv, u_rotv,
dmag, sep, multid, multcnt)
data.append(item)
data = np.array(data, dtype=record)
pri_hdu = fits.PrimaryHDU()
tbl_hdu = fits.BinTableHDU(data)
hdu_lst = fits.HDUList([pri_hdu, tbl_hdu])
outname = 'BSC.fits'
if os.path.exists(outname):
os.remove(outname)
hdu_lst.writeto(outname)
def main():
astrodata = os.getenv('ASTRO_DATA')
types = [
('EPIC', np.int32),
('Objtype', 'S8'),
('Kepflag', 'S3'),
('RAdeg', np.float64),
('DEdeg', np.float64),
('pmRA', np.float32),
('pmDE', np.float32),
('e_pmRA', np.float32),
('e_pmDE', np.float32),
('Plx', np.float32),
('e_Plx', np.float32),
('Bmag', np.float32),
('e_Bmag', np.float32),
('Vmag', np.float32),
('e_Vmag', np.float32),
('umag', np.float32),
('e_umag', np.float32),
('gmag', np.float32),
('e_gmag', np.float32),
('rmag', np.float32),
('e_rmag', np.float32),
('imag', np.float32),
('e_imag', np.float32),
('zmag', np.float32),
('e_zmag', np.float32),
('Jmag', np.float32),
('e_Jmag', np.float32),
('Hmag', np.float32),
('e_Hmag', np.float32),
('Kmag', np.float32),
('e_Kmag', np.float32),
('W1mag', np.float32),
('e_W1mag', np.float32),
('W2mag', np.float32),
('e_W2mag', np.float32),
('W3mag', np.float32),
('e_W3mag', np.float32),
('W4mag', np.float32),
('e_W4mag', np.float32),
('kepmag', np.float32),
('Teff', np.int16),
('ue_Teff', np.int16),
('le_Teff', np.int16),
('logg', np.float32),
('ue_logg', np.float32),
('le_logg', np.float32),
('FeH', np.float32),
('ue_FeH', np.float32),
('le_FeH', np.float32),
('Rad', np.float32),
('ue_Rad', np.float32),
('le_Rad', np.float32),
('Mass', np.float32),
('ue_Mass', np.float32),
('le_Mass', np.float32),
('rho', np.float32),
('ue_rho', np.float32),
('le_rho', np.float32),
('Lum', np.float32),
('ue_Lum', np.float32),
('le_Lum', np.float32),
('Dist', np.float32),
('ue_Dist', np.float32),
('le_Dist', np.float32),
('E(B-V)', np.float32),
('ue_E(B-V)', np.float32),
('le_E(B-V)', np.float32),
]
tmp = list(zip(*types))
record = np.dtype({'names': tmp[0], 'formats': tmp[1]})
fill_item = (
0,
'',
'',
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
#ra dec pmra pmdec e_pmra, e_pmdec plx, e_plx
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
#Bmag Vmag umag gmag
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
#rmag imag zmag
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
# Jmag Hmag Kmag
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
# w1 w2 w3 w4
np.NaN,
# kpmag
-1,
-1,
-1,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
# Teff logg FeH
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
# Rad Mass rho
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
np.NaN,
# Lum dist EBV
)
epic_ranges = {
1: (201000001, 210000000),
2: (210000001, 220000000),
3: (220000001, 230000000),
4: (230000001, 240000000),
5: (240000001, 250000000),
6: (250000001, 251809654),
}
for i in range(1, 7):
count = 0
data = []
fn = 'epic_%d_19Dec2017.txt' % i
print(fn)
filename = os.path.join(astrodata, 'catalog/others/EPIC/%s' % fn)
prev_epic = 0
infile = open(filename)
infile.readline()
_epic = epic_ranges[i][0]
for row in infile:
g = row.split('|')
epic = int(g[0])
objtype = g[6].strip()
kepflag = g[7].strip()
ra = float(g[9])
dec = float(g[10])
pmra = _str_to_float(g[11], np.NaN)
e_pmra = _str_to_float(g[12], np.NaN)
pmde = _str_to_float(g[13], np.NaN)
e_pmde = _str_to_float(g[14], np.NaN)
plx = _str_to_float(g[15], np.NaN)
e_plx = _str_to_float(g[16], np.NaN)
bmag = _str_to_float(g[17], np.NaN)
ebmag = _str_to_float(g[18], np.NaN)
vmag = _str_to_float(g[19], np.NaN)
evmag = _str_to_float(g[20], np.NaN)
umag = _str_to_float(g[21], np.NaN)
eumag = _str_to_float(g[22], np.NaN)
gmag = _str_to_float(g[23], np.NaN)
egmag = _str_to_float(g[24], np.NaN)
rmag = _str_to_float(g[25], np.NaN)
ermag = _str_to_float(g[26], np.NaN)
imag = _str_to_float(g[27], np.NaN)
eimag = _str_to_float(g[28], np.NaN)
zmag = _str_to_float(g[29], np.NaN)
ezmag = _str_to_float(g[30], np.NaN)
jmag = _str_to_float(g[31], np.NaN)
ejmag = _str_to_float(g[32], np.NaN)
hmag = _str_to_float(g[33], np.NaN)
ehmag = _str_to_float(g[34], np.NaN)
kmag = _str_to_float(g[35], np.NaN)
ekmag = _str_to_float(g[36], np.NaN)
w1mag = _str_to_float(g[37], np.NaN)
ew1mag = _str_to_float(g[38], np.NaN)
w2mag = _str_to_float(g[39], np.NaN)
ew2mag = _str_to_float(g[40], np.NaN)
w3mag = _str_to_float(g[41], np.NaN)
ew3mag = _str_to_float(g[42], np.NaN)
w4mag = _str_to_float(g[43], np.NaN)
ew4mag = _str_to_float(g[44], np.NaN)
kepmag = _str_to_float(g[45], np.NaN)
teff = _str_to_int(g[46], -1)
ue_teff = _str_to_int(g[47], -1)
le_teff = _str_to_int(g[48], -1)
logg = _str_to_float(g[49], np.NaN)
ue_logg = _str_to_float(g[50], np.NaN)
le_logg = _str_to_float(g[51], np.NaN)
feh = _str_to_float(g[52], np.NaN)
ue_feh = _str_to_float(g[53], np.NaN)
le_feh = _str_to_float(g[54], np.NaN)
rad = _str_to_float(g[55], np.NaN)
ue_rad = _str_to_float(g[56], np.NaN)
le_rad = _str_to_float(g[57], np.NaN)
mass = _str_to_float(g[58], np.NaN)
ue_mass = _str_to_float(g[59], np.NaN)
le_mass = _str_to_float(g[60], np.NaN)
rho = _str_to_float(g[61], np.NaN)
ue_rho = _str_to_float(g[62], np.NaN)
le_rho = _str_to_float(g[63], np.NaN)
lum = _str_to_float(g[64], np.NaN)
ue_lum = _str_to_float(g[65], np.NaN)
le_lum = _str_to_float(g[66], np.NaN)
dist = _str_to_float(g[67], np.NaN)
ue_dist = _str_to_float(g[68], np.NaN)
le_dist = _str_to_float(g[69], np.NaN)
ebv = _str_to_float(g[70], np.NaN)
ue_ebv = _str_to_float(g[71], np.NaN)
le_ebv = _str_to_float(g[72], np.NaN)
item = (
epic,
objtype,
kepflag,
ra,
dec,
pmra,
pmde,
e_pmra,
e_pmde,
plx,
e_plx,
bmag,
ebmag,
vmag,
evmag,
umag,
eumag,
gmag,
egmag,
rmag,
ermag,
imag,
eimag,
zmag,
ezmag,
jmag,
ejmag,
hmag,
ejmag,
kmag,
ekmag,
w1mag,
ew1mag,
w2mag,
ew2mag,
w3mag,
ew3mag,
w4mag,
ew4mag,
kepmag,
teff,
ue_teff,
le_teff,
logg,
ue_logg,
le_logg,
feh,
ue_feh,
le_feh,
rad,
ue_rad,
le_rad,
mass,
ue_mass,
le_mass,
rho,
ue_rho,
le_rho,
lum,
ue_lum,
le_lum,
dist,
ue_dist,
le_dist,
ebv,
ue_ebv,
le_ebv,
)
if epic > _epic:
for j in range(epic - _epic):
data.append(fill_item)
_epic += 1
data.append(item)
_epic += 1
count += 1
if count % 1000000 == 0: print(count)
infile.close()
print('Data reading finished')
data = np.array(data, dtype=record)
print('Begin file writing')
pri_hdu = fits.PrimaryHDU()
tbl_hdu = fits.BinTableHDU(data)
hdu_lst = fits.HDUList([pri_hdu, tbl_hdu])
outputfile = 'EPIC_%d.fits' % i
if os.path.exists(outputfile):
os.remove(outputfile)
hdu_lst.writeto(outputfile)
def main():
path = os.path.join(os.getenv('ASTRO_DATA'), 'catalog/I/239/')
types = [
('TYC', np.int32),
('RAdeg', np.float64),
('DEdeg', np.float64),
('e_RA', np.float32),
('e_DE', np.float32),
('pmRA', np.float32),
('pmDE', np.float32),
('e_pmRA', np.float32),
('e_pmDE', np.float32),
('Plx', np.float32),
('e_Plx', np.float32),
('Nastro', np.int16),
('Vmag', np.float32),
('r_Vmag', 'S1'),
('BTmag', np.float32),
('e_BTmag', np.float32),
('VTmag', np.float32),
('e_VTmag', np.float32),
('r_BTmag', 'S1'),
('B-V', np.float32),
('e_B-V', np.float32),
('Nphoto', np.int16),
('VTscat', np.float32),
('VTmax', np.float32),
('VTmin', np.float32),
('VarFlag', 'S1'),
('MultFlag', 'S1'),
]
tmp = list(zip(*types))
record = np.dtype({'names':tmp[0],'formats':tmp[1]})
fill_item = (0, np.NaN, np.NaN, np.NaN, np.NaN, # ra, de, e_ra, e_de
np.NaN, np.NaN, np.NaN, np.NaN, # pm
np.NaN, np.NaN, -1, # plx, Nastro
np.NaN, '', np.NaN, np.NaN, np.NaN, np.NaN, '', # vmag ~ r_BTmag
np.NaN, np.NaN, -1, np.NaN, np.NaN, np.NaN, '', ''
)
data = []
fn = 'tyc_main.dat'
infile = open(os.path.join(path, fn))
for row in infile:
if row[0]!='T':
print('Warning: Not Tycho star')
g = row[2:14].split()
tyc1 = int(g[0])
tyc2 = int(g[1])
tyc3 = int(g[2])
tyc = np.int32((tyc1<<18) + (tyc2<<4) + (tyc3<<1))
radeg = _str_to_float(row[51:63], np.NaN)
dedeg = _str_to_float(row[64:76], np.NaN)
vmag = _str_to_float(row[41:46], np.NaN)
r_vmag = row[49].strip()
plx = _str_to_float(row[79:86], np.NaN)
pm_ra = _str_to_float(row[87:95], np.NaN)
pm_de = _str_to_float(row[96:104], np.NaN)
e_ra = _str_to_float(row[105:111], np.NaN)
e_de = _str_to_float(row[112:118], np.NaN)
e_plx = _str_to_float(row[119:125], np.NaN)
e_pmra = _str_to_float(row[126:132], np.NaN)
e_pmde = _str_to_float(row[133:139], np.NaN)
nastro = _str_to_int(row[200:203], 0)
btmag = _str_to_float(row[217:223], np.NaN)
e_btmag = _str_to_float(row[224:229], np.NaN)
vtmag = _str_to_float(row[230:236], np.NaN)
e_vtmag = _str_to_float(row[237:242], np.NaN)
r_btmag = row[243].strip()
bv = _str_to_float(row[245:251], np.NaN)
e_bv = _str_to_float(row[252:257], np.NaN)
nphoto = _str_to_int(row[269:272], 0)
vtscat = _str_to_float(row[273:278], np.NaN)
vtmax = _str_to_float(row[279:284], np.NaN)
vtmin = _str_to_float(row[285:290], np.NaN)
varflag = row[293].strip()
multflag = row[295].strip()
item = (tyc, radeg, dedeg, e_ra, e_de, pm_ra, pm_de, e_pmra, e_pmde,
plx, e_plx, nastro,
vmag, r_vmag, btmag, e_btmag, vtmag, e_vtmag, r_btmag,
bv, e_bv, nphoto, vtscat, vtmax, vtmin, varflag, multflag)
data.append(item)
infile.close()
data = np.array(data, dtype=record)
data = np.sort(data, order='TYC')
# add an empty item in the beginning
data = np.insert(data, 0, np.array(fill_item, dtype=record))
pri_hdu = fits.PrimaryHDU()
tbl_hdu = fits.BinTableHDU(data)
hdu_lst = fits.HDUList([pri_hdu,tbl_hdu])
outputfile = 'TYC.fits'
if os.path.exists(outputfile):
os.remove(outputfile)
hdu_lst.writeto(outputfile)
data = fits.getdata(outputfile)
tyc_lst = data['TYC']
diff = np.diff(tyc_lst)
mask = diff==0
for i, m in enumerate(mask):
if m:
print(data[i]['TYC'], data[i+1]['TYC'])