primhdu_ = plate_[0]
PLATEIDs.append(primhdu_.header['PLATEID'])
ORMASK.append(plate_[3].data)
ANDMASK.append(plate_[2].data)
INVAR.append(plate_[1].data)
log_wavst.append(primhdu_.header['COEFF0'])
MJDs.append(primhdu_.header['MJD'])
BinInfos.append(Bin_info_)
Flux.append(Flux_)
list = fits.open('Superset_DR12Q.fits', memmap=True) #opening file
supers = list[1].data # storing BINTABLE extension data
print("Restoring Data")
Full_Data = storing(PLATEIDs, supers)
X, Y, Train_z, Train_mag, And, In, wavst, ID = MLAData(Full_Data, BinInfos,
Flux, log_wavst,
ANDMASK, INVAR)
i = 0
print("Saving Files")
while i < len(PLATEIDs):
C_Plate = PLATEIDs[i]
a1 = X[i]
a2 = np.array(Y[i])
if len(a1) == 0 & len(a2) == 0:
i = i + 1
else:
a3 = And[i]
a4 = In[i]
a5 = Train_z[i]
a6 = ID[i]
Flux_ = plate_[0].data
primhdu_ = plate_[0]
PLATEIDs.append(primhdu_.header['PLATEID'])
ORMASK.append(plate_[3].data)
ANDMASK.append(plate_[2].data)
INVAR.append(plate_[1].data)
log_wavst.append(primhdu_.header['COEFF0'])
MJDs.append(primhdu_.header['MJD'])
BinInfos.append(Bin_info_)
Flux.append(Flux_)
list = fits.open('Superset_DR12Q.fits', memmap=True) #opening file
supers = list[1].data # storing BINTABLE extension data
print("Restoring Data")
Full_Data = storing(PLATEIDs, supers)
X, Y, Train_z, Train_mag, And, In, wavst, ID, MJ, MatchedPlates = MLAData(
Full_Data, BinInfos, Flux, log_wavst, ANDMASK, INVAR, MJDs, PLATEIDs)
i = 0
i = 0
print("Counting")
RejNoPlate = []
while i < len(MatchedPlates):
no = 0
a7 = And[i]
RejNo = 0
while no < len(a7):
obj_and = a7[no]
pixel_count = 0
RejNo = 0
while pixel_count < len(obj_and):
primhdu_ = plate_[0]
PLATEIDs.append(primhdu_.header['PLATEID'])
ORMASK.append(plate_[3].data)
ANDMASK.append(plate_[2].data)
INVAR.append(plate_[1].data)
log_wavst.append(primhdu_.header['COEFF0'])
MJDs.append(primhdu_.header['MJD'])
BinInfos.append(Bin_info_)
Flux.append(Flux_)
list = fits.open('Superset_DR12Q.fits', memmap=True) #opening file
supers = list[1].data # storing BINTABLE extension data
print("Restoring Data")
Full_Data = storing(PLATEIDs, supers)
X, Y, Train_z, Train_mag, And, In, wavst, ID = MLAData(Full_Data, BinInfos,
Flux, log_wavst,
ANDMASK, INVAR)
wav_ratio = 10**0.0001
plate_no = 0
all_wav = []
while plate_no < len(wavst):
append_count = 0
cent_wav = 10**wavst[plate_no]
wavelengths = []
wavelengths.append(cent_wav)
current_wav = cent_wav
while append_count < (4600 - 1):
current_wav = current_wav * wav_ratio
wavelengths.append(current_wav)
append_count = append_count + 1
Flux_ = plate_[0].data
primhdu_ = plate_[0]
PLATEIDs.append(primhdu_.header['PLATEID'])
ORMASK.append(plate_[3].data)
ANDMASK.append(plate_[2].data)
INVAR.append(plate_[1].data)
log_wavst.append(primhdu_.header['COEFF0'])
MJDs.append(primhdu_.header['MJD'])
BinInfos.append(Bin_info_)
Flux.append(Flux_)
list = fits.open('Superset_DR12Q.fits', memmap=True) #opening file
supers = list[1].data # storing BINTABLE extension data
print("Restoring Data")
Full_Data = storing(PLATEIDs, supers)
X, Y, Train_z, Train_mag, And, In, wavst, ID, MJ, MatchedPlates = MLAData(
Full_Data, BinInfos, Flux, log_wavst, ANDMASK, INVAR, MJDs, PLATEIDs)
plate_no = 0
all_Testwav = []
wav_ratio = 10**0.0001
while plate_no < len(X):
append_count = 0
cent_wav = 10**wavst[plate_no]
wavelengths = []
wavelengths.append(cent_wav)
current_wav = cent_wav
while append_count < (4600 - 1):
current_wav = current_wav * wav_ratio
wavelengths.append(current_wav)
append_count = append_count + 1
plate_no = plate_no + 1