def main():
props = []
props.append((3111, 'WD_Kilic'))
props.append((3116, 'WD_Redfield'))
props.append((3096, 'EXO_Heller'))
props.append((3095, 'EXO_vanGrootel'))
props.append((3086, 'EB_Southworth'))
props.append((3067, 'EB_Peters'))
props.append((3049, 'EB_Prsa'))
props.append((3005, 'EB_Shporer'))
#
combined = []
qm = QueryK2ByTgtId()
for p in props:
print "Getting %s" % (p[1])
text = qm.queryProposal(p[0])
data = qm.parseResults(text)
data = appendCol(data[1:, :], 'Proposal')
data[:, 'Proposal'] = p[1]
combined.append(data)
cat = np.concatenate(combined)
idx = np.unique(cat[:, 0], return_index=True)[1]
cat = cat[idx]
cat = nca.Nca(cat)
cat.setLookup(1, data.lookup[1])
return cat
def regularSpaceKeplerDataByCadence(data, missingValue=0,
cCol=FluxColDef['CADENCENO']):
"""Take Kepler multi quarter data and insert zeros where no data is present.
This results in regularly spaced data.
Inputs:
data Numpy array as returned by kplrfits.loadMultiQuarter()
Optional Inputs:
missingValue (float) What value to enter for cadences where there is
no data
"""
nR,nCol = data.shape
cin = data[:, cCol].astype(np.int32)
nCadence = cin[-1]
reg = np.zeros( (nCadence+1, nCol) ) + missingValue
for i in range(nCol):
reg[cin, i] = data[:,i]
#Insert all the cadence values, even where data was missing
reg[:, cCol] = np.arange(cin[0], cin[0]+nCadence+1)
#Fix the infinities
idx = np.isfinite(reg)
reg[~idx] = missingValue
reg = nca.Nca(reg, data.lookup)
return reg
def appendCol(data, name):
nr, nc = data.shape
nc += 1
newCol = np.atleast_2d(data[:, 0].asarray()).transpose()
newData = np.hstack((data.asarray(), newCol))
lookup = data.lookup
lookup[1].append(name)
return nca.Nca(newData, lookup)
dataList.append(data)
if len(dataList) == 0:
raise IOError("Failed to find data in any listed quarter for %i" %(int(kepid)))
out = np.concatenate( tuple(dataList))
lookup = """ TIME TIMECORR CADENCENO
SAP_FLUX SAP_FLUX_ERR SAP_BKG SAP_BKG_ERR
PDCSAP_FLUX PDCSAP_FLUX_ERR SAP_QUALITY
PSF_CENTR1 PSF_CENTR1_ERR PSF_CENTR2 PSF_CENTR2_ERR
MOM_CENTR1 MOM_CENTR1_ERR MOM_CENTR2 MOM_CENTR2_ERR
POS_CORR1 POS_CORR2""".split()
out = nca.Nca(out)
out.setLookup(1, lookup)
return out
def getNumpyArrayFromFitsRec(rec, cols=None):
#If not defined, try to get all columns
if cols is None:
cols = range(len(rec.names))
nRow = len(rec)
nCol = len(cols)
data = np.empty( (nRow, nCol) )