def read(cls, fname, sid, **kwargs):
cache = namedtuple(
'K2Cache',
'fname objno nobj nexp time cadence quality fluxes errors x y header'
)
if not cls._cache or cls._cache.fname != fname:
with pf.open(fname) as fin:
data = fin[1].data
nobj = fin[1].header['naxis2']
nexp = fin[2].header['naxis2']
fluxes = (1. + data['f'].reshape(
[nobj, nexp, -1])) * data['f_med'][:, np.newaxis, :]
fluxes = np.swapaxes(fluxes, 1,
2) # Fluxes as [nobj,napt,nexp] ndarray
cls._nstars = nobj
cls._cache = cache(fname, fin[1].data['objno'], nobj, nexp,
fin[2].data['mjd_obs'],
fin[2].data['cadence'],
np.zeros(nexp, np.int), fluxes,
np.zeros_like(fluxes), data['x'], data['y'],
fin[0].header)
return K2Data(cls._cache.objno[sid],
time=cls._cache.time[:-1],
cadence=cls._cache.cadence[:-1],
quality=cls._cache.quality[:-1],
fluxes=cls._cache.fluxes[sid, :, :-1],
errors=cls._cache.errors[sid, :, :-1],
x=cls._cache.x[sid, :-1],
y=cls._cache.y[sid, :-1],
sap_header=cls._cache.header)
def read(cls, fname, sid, **kwargs):
ftype = kwargs.get('type', 'pdc').lower()
assert ftype in cls.allowed_types, 'Flux type must be either `sap` or `pdc`'
fkey = cls.fkeys[ftype]
try:
epic = int(re.findall('ktwo([0-9]+)-c', basename(fname))[0])
except:
epic = int(re.findall('C([0-9]+)_smear',
basename(fname))[0][2:]) # for smear
data = pf.getdata(fname, 1)
phead = pf.getheader(fname, 0)
dhead = pf.getheader(fname, 1)
[h.remove('CHECKSUM') for h in (phead, dhead)]
[phead.remove(k) for k in 'CREATOR PROCVER FILEVER TIMVERSN'.split()]
return K2Data(epic,
time=data['time'],
cadence=data['cadenceno'],
quality=data['sap_quality'],
fluxes=data[fkey],
errors=data[fkey + '_err'],
x=data['pos_corr1'],
y=data['pos_corr2'],
primary_header=phead,
data_header=dhead,
campaign=phead['campaign'])
def read(cls, fname, **kwargs):
epic = int(re.findall('EPIC_([0-9]+)_', basename(fname))[0])
data = np.loadtxt(fname, skiprows=1)
return K2Data(epic,
time=data[:, 0],
cadence=data[:, 1],
quality=data[:, -1],
fluxes=data[:, 2:-3:2].T,
errors=data[:, 3:-3:2].T,
x=data[:, -3],
y=data[:, -2])
def read(cls, fname, sid, **kwargs):
# ftype = 'sap_flux' if kwargs.get('type','sap').lower() == 'sap' else 'pdcsap_flux'
# try:
# epic = int(re.findall('ktwo([0-9]+)-c', basename(fname))[0])
# except:
# epic = int(re.findall('C([0-9]+)_smear', basename(fname))[0][2:]) # for smear
# data = pf.getdata(fname, 1)
# head = pf.getheader(fname, 0)
lcfn = 'test.fits'
transfn = '/Users/petigura//Research/K2//k2photfiles/pixeltrans_C3_ch04.h5'
tlimits = [0, 9999]
pipe = k2phot.pipeline_core.Pipeline(fname,
lcfn,
transfn,
tlimits=tlimits,
tex=None)
pipe.set_lc0('region', 200)
print "using the following aperture"
print pipe.im.ap
hduL = fits.open(pipe.pixfn)
quality = hduL[1].data['QUALITY']
fluxes = pipe.lc0['fsap']
time = pipe.lc0['t'] - bjd0
cadence = pipe.lc0['cad']
# Stand in for true photometric errors
errors = fluxes * (60 * 30 * pipe.lc0['fsap'].median())**-0.5
pos = pipe.lc0['xpr ypr'.split()]
pos -= pos.mean()
head = pf.getheader(fname, 0)
epic = head['KEPLERID']
x = pos['xpr']
y = pos['ypr']
time = np.array(time)
cadence = np.array(cadence)
quality = np.array(quality)
fluxes = np.array(fluxes)
errors = np.array(errors)
x = np.array(x)
y = np.array(y)
return K2Data(epic,
time=time,
cadence=cadence,
quality=quality,
fluxes=fluxes,
errors=errors,
x=x,
y=y,
sap_header=head)
def read(cls, fname, sid, **kwargs):
ftype = 'sap_flux' if kwargs.get(
'type', 'sap').lower() == 'sap' else 'pdcsap_flux'
try:
epic = int(re.findall('ktwo([0-9]+)-c', basename(fname))[0])
except:
epic = int(re.findall('C([0-9]+)_smear',
basename(fname))[0][2:]) # for smear
data = pf.getdata(fname, 1)
head = pf.getheader(fname, 0)
return K2Data(epic,
time=data['time'],
cadence=data['cadenceno'],
quality=data['sap_quality'],
fluxes=data[ftype],
errors=data[ftype + '_err'],
x=data['pos_corr1'],
y=data['pos_corr2'],
sap_header=head)