def simul_css(CataSect, _CssImg, cssbands, filtnumb, npi):
# print('Process'+str(npi)
CssHei, CssWid = _CssImg.shape
OutSecStr = ''
LenCatSec = len(CataSect)
procedi = 0
if IfProgBarOn == True:
bar = Bar(max_value=LenCatSec,
empty_color=7,
filled_color=18 + npi * 6,
title='Process-' + str(npi))
bar.cursor.clear_lines(1)
bar.cursor.save()
for procedi, cataline in enumerate(CataSect, 1):
np.random.seed()
ident = str(cataline['IDENT'])
objwind = csstpkg.windcut(_CssImg, cataline)
if objwind is None:
if DebugTF == True:
print('--- Object window cutting error ---')
continue
# DataArr2Fits(objwind, ident+'_convwin.fits')
objwinshape = objwind.shape
objwind.data = objwind.data * ExpCssFrm
WinImgBands = np.zeros(
(len(cssbands), objwinshape[0],
objwinshape[1])) # 3-D array contains images of all the cssbands
if IfPlotObjWin == True:
csstpkg.PlotObjWin(objwind, cataline)
outcatrowi = [ident, cataline['Z_BEST']]
if DebugTF == True:
print(' '.join([
ident, '\nRA DEC:',
str(cataline['RA']),
str(cataline['DEC'])
]))
# Photometry for the central object on the convolved window
ObjWinPhot_DeBkg = csstpkg.CentrlPhot(objwind.data,
id=str(outcatrowi[0]) +
" ConvWdW DeBkg")
ObjWinPhot_DeBkg.Bkg(idb=str(outcatrowi[0]) + " ConvWdW DeBkg",
debug=DebugTF,
thresh=1.5,
minarea=10,
deblend_nthresh=32,
deblend_cont=0.01)
ObjWinPhot_DeBkg.Centract(idt=str(outcatrowi[0]) + " ConvWdW DeBkg",
thresh=2.5,
deblend_nthresh=32,
deblend_cont=0.1,
minarea=10,
debug=DebugTF,
sub_backgrd_bool=True)
if ObjWinPhot_DeBkg.centobj is np.nan:
if DebugTF == True:
print('--- No central object detected in convolved image ---')
continue
else:
ObjWinPhot_DeBkg.KronR(idk=str(outcatrowi[0]) + " ConvWdW",
debug=DebugTF,
mask_bool=True)
NeConv_DeBkg, ErrNeConv_DeBkg = ObjWinPhot_DeBkg.EllPhot(
ObjWinPhot_DeBkg.kronr, mask_bool=True)
if ((NeConv_DeBkg <= 0) or (NeConv_DeBkg is np.nan)):
if DebugTF == True:
print(
'NeConv_DeBkg for a winimg <= 0 or NeConv_DeBkg is np.nan')
continue
noisebkg_conv = ObjWinPhot_DeBkg.bkg.background_rms_median
if DebugTF == True:
print('self.bkg Flux & ErrFlux =',
ObjWinPhot_DeBkg.bkg.background_median,
ObjWinPhot_DeBkg.bkg.background_rms_median)
print('Class processed NeConv_DeBkg & ErrNeConv_DeBkg:',
NeConv_DeBkg, ErrNeConv_DeBkg)
# Read model SED to NDArray
# modsednum = cataline['MOD_BEST']
sedname = seddir + 'Id' + '{:0>9}'.format(ident) + '.spec'
modsed, readflag = csstpkg.readsed(sedname)
if readflag == 1:
modsed[:, 1] = csstpkg.mag2flam(
modsed[:, 1], modsed[:, 0]
) # to convert model SED from magnitude to f_lambda(/A)
else:
print('model sed not found.')
continue
bandi = 0
NeBands = []
magsimorigs = []
scalings = []
for cssband, numb in zip(cssbands, filtnumb):
expcss = 150. * numb # s
# cssbandpath = thrghdir+cssband+'.txt'
NeABand0 = csstpkg.NeObser(modsed, cssband, expcss,
TelArea) # *cataline['SCALE_BEST']
if NeABand0 < 1:
continue
magaband0 = csstpkg.Ne2MagAB(NeABand0, cssband, expcss, TelArea)
delmag = magaband0 - float(cataline['MOD_' + cssband + '_css'])
magsimorig_band = magaband0 - delmag
NeABand = NeABand0 / 10**(-0.4 * delmag)
# print(NeABand0, magaband0, delmag)
NeBands.append(NeABand)
if DebugTF == True:
print(' '.join(
[cssband, 'band model electrons = ',
str(NeABand), 'e-']))
print('MOD_' + cssband + '_css =',
cataline['MOD_' + cssband + '_css'])
magsimorigs.append(
csstpkg.Ne2MagAB(NeABand, cssband, expcss, TelArea))
print('Magsim_' + cssband + ' =', magsimorigs[bandi])
Scl2Sed = NeABand / NeConv_DeBkg
scalings.append(Scl2Sed)
if DebugTF == True:
print(ident, 'Scaling Factor: ', Scl2Sed)
# ZeroLevel = config.getfloat('Hst2Css', 'BZero')
SkyLevel = 0 #csstpkg.backsky[cssband] * expcss
DarkLevel = 0 #config.getfloat('Hst2Css', 'BDark') * expcss
RNCssFrm = config.getfloat('Hst2Css', 'RNCss')
# IdealImg = objwind.data * Scl2Sed + SkyLevel + DarkLevel # e-
IdealImg = ObjWinPhot_DeBkg.data_bkg * Scl2Sed # + SkyLevel + DarkLevel # e-
# IdealImg[IdealImg < 0] = 0
if DebugTF == True:
# csstpkg.DataArr2Fits(IdealImg/Gain, 'Ideal_Zero_Gain_check_'+ident+'_'+cssband+'.fits')
# Testing photometry for the scaled convolved window's central object
ObjWinPhot = csstpkg.CentrlPhot(IdealImg,
id=(ident + " SclTesting"))
try:
ObjWinPhot.Bkg(idb=ident + " SclTesting",
debug=DebugTF,
thresh=1.5,
minarea=10,
deblend_nthresh=32,
deblend_cont=0.01)
except Exception as e:
# print(NeConv_DeBkg, NeABand, IdealImg)
continue
ObjWinPhot.Centract(idt=ident + " SclTesting",
thresh=2.5,
deblend_nthresh=32,
deblend_cont=0.1,
minarea=10,
debug=DebugTF,
sub_backgrd_bool=False)
if ObjWinPhot.centobj is np.nan:
print(
'--- No central object detected in testing photometry image---'
)
continue
else:
ObjWinPhot.KronR(idk=ident + " SclTesting",
debug=DebugTF,
mask_bool=True)
NeConv, ErrNeConv = ObjWinPhot.EllPhot(ObjWinPhot.kronr,
mask_bool=True)
print(' '.join([
'Model electrons:',
str(NeABand), '\nTesting Photometry After scaling:',
str(NeConv)
]))
BkgNoiseTot = (SkyLevel + DarkLevel + RNCssFrm**2 * numb)**0.5
if BkgNoiseTot > noisebkg_conv * Scl2Sed:
Noise2Add = (BkgNoiseTot**2 -
(noisebkg_conv * Scl2Sed)**2)**0.5
else:
Noise2Add = 0
if DebugTF == True:
print('Added Noise ' + cssband + ' band: ', Noise2Add)
# ImgPoiss = np.random.poisson(lam=IdealImg, size=objwinshape)
ImgPoiss = IdealImg
NoisNormImg = csstpkg.NoiseArr(objwinshape,
loc=0,
scale=Noise2Add,
func='normal')
# DigitizeImg = np.round((ImgPoiss + NoisNorm + ZeroLevel) / Gain)
DigitizeImg = (ImgPoiss + NoisNormImg) / Gain
# DigitizeImg = IdealImg/Gain
if DebugTF == True:
csstpkg.DataArr2Fits(
DigitizeImg, 'Ideal_Zero_Gain_RN_check_' + ident + '_' +
cssband + '.fits')
WinImgBands[bandi, ::] = DigitizeImg
bandi = bandi + 1
if DebugTF == True:
print('Stack all bands and detect objects:')
WinImgStack = WinImgBands.sum(0)
# print(WinImgStack.shape)
# AduStack, ErrAduStack, ObjectStack, KronRStack, MaskStack = septract(WinImgStack, id=str(outcatrowi[0])+" Stack", debug=DebugTF, thresh=1.2, minarea=10)
StackPhot = csstpkg.CentrlPhot(WinImgStack, id=ident + " Stack")
StackPhot.Bkg(idb=ident + " Stack",
debug=DebugTF,
thresh=1.5,
minarea=10)
StackPhot.Centract(idt=ident + " Stack",
thresh=1.5,
minarea=10,
deblend_nthresh=32,
deblend_cont=0.1,
debug=DebugTF)
if StackPhot.centobj is np.nan:
if DebugTF == True:
print('No central object on STACK image.')
continue
else:
StackPhot.KronR(idk=ident + " Stack",
debug=DebugTF,
mask_bool=True)
AduStack, ErrAduStack = StackPhot.EllPhot(StackPhot.kronr,
mask_bool=True)
if AduStack is np.nan:
if DebugTF == True:
print('RSS error for STACK image.')
continue
if DebugTF == True:
csstpkg.PlotKronrs(WinImgStack, StackPhot)
bandi = 0
for cssband, numb in zip(cssbands, filtnumb):
expcss = 150. * numb # s
if DebugTF == True:
plt.hist(
WinImgBands[bandi, ::].flatten(),
bins=np.arange(30) - 15,
)
plt.title(' '.join([cssband, 'simul image']))
plt.show()
SameApObj = csstpkg.CentrlPhot(WinImgBands[bandi, ::],
id=ident + ' ' + cssband +
' band CentralExtract')
SameApObj.Bkg(idb=ident + ' ' + cssband + ' band CentralExtract',
debug=DebugTF,
thresh=1.5,
minarea=10)
SameApObj.Centract(idt=ident + ' ' + cssband +
' band CentralExtract',
thresh=1.2,
minarea=10,
deblend_nthresh=32,
deblend_cont=0.1,
debug=DebugTF,
sub_backgrd_bool=False)
if SameApObj.centobj is np.nan:
if DebugTF == True:
print('No central object on simulated image.')
SNR = -99
MagObser = -99
ErrMagObs = -99
# AduObser, ErrAduObs = csstpkg.septractSameAp(WinImgBands[bandi, ::], StackPhot, ObjWinPhot_DeBkg.centobj, ObjWinPhot_DeBkg.kronr, mask_det=StackPhot.mask_other, debug=DebugTF, annot=cssband+'_cssos', thresh=1.2, minarea=10, sub_backgrd_bool=False)
# if AduObser>0:
# MagObser = -2.5 * math.log10(AduObser) + magab_zeros[bandi]
# ErrMagObs = -1
# ErrAduTot = (ErrAduObs ** 2 + (noisebkg_conv * scalings[bandi]) ** 2) ** 0.5
# SNR = AduObser / ErrAduTot
# else:
# SNR = -99
# MagObser = -99
# ErrMagObs = -99
else:
# AduObser, ErrAduObs = csstpkg.septractSameAp(WinImgBands[bandi, ::], StackPhot, ObjWinPhot_DeBkg.centobj, ObjWinPhot_DeBkg.kronr, mask_det=StackPhot.mask_other, debug=DebugTF, annot=cssband+'_cssos', thresh=1.2, minarea=10, sub_backgrd_bool=False)
AduObser, ErrAduObs = csstpkg.septractSameAp(
WinImgBands[bandi, ::],
StackPhot,
StackPhot.centobj,
StackPhot.kronr,
mask_det=StackPhot.mask_other,
debug=DebugTF,
annot=cssband + '_cssos',
thresh=1.2,
minarea=10,
sub_backgrd_bool=False)
if AduObser > 0:
ErrAduTot = (ErrAduObs**2 +
(noisebkg_conv * scalings[bandi])**2)**0.5
SNR = AduObser / ErrAduTot
# MagObser = Ne2MagAB(AduObser*Gain,cssband,expcss,TelArea)
MagObser = -2.5 * math.log10(AduObser) + magab_zeros[bandi]
ErrMagObs = 2.5 * math.log10(1 + 1 / SNR)
if DebugTF == True:
if ((cssband == 'r') &
(np.abs(MagObser -
cataline['MOD_' + cssband + '_css']) > 1)):
csstpkg.DataArr2Fits(objwind.data,
ident + '_convwin_r.fits')
csstpkg.DataArr2Fits(WinImgStack,
ident + '_stack.fits')
else:
SNR = -99
MagObser = -99
ErrMagObs = -99
if DebugTF == True:
npixel = math.pi * (
ObjWinPhot_DeBkg.centobj['a'] * csstpkg.kphotpar *
ObjWinPhot_DeBkg.kronr) * (
ObjWinPhot_DeBkg.centobj['b'] * csstpkg.kphotpar *
ObjWinPhot_DeBkg.kronr)
print(' '.join([
cssband, 'band model e- =',
str(NeBands[bandi]), 'e-'
]))
print(' '.join([
cssband, 'band simul e- =',
str(AduObser * Gain), 'e-', ' ErrNe=',
str(ErrAduTot * Gain)
]))
# print(AduObser, Gain, NeBands[bandi], -2.5*math.log10(AduObser*Gain/NeBands[bandi]))
print('SNR =', AduObser / ErrAduTot)
print('Npixel =', npixel)
print(' '.join([
cssband, 'band mag_model = ',
str(cataline['MOD_' + cssband + '_css']), '(AB mag)'
]))
print(' '.join([
cssband, 'band Magsim_orig = ',
str(magsimorigs[bandi]), '(AB mag)'
]))
print(' '.join([
cssband, 'band Mag_simul = ',
str(MagObser), '(AB mag)'
]))
print(' '.join([
cssband, 'band magerr_simul = ',
str(ErrMagObs), '(AB mag)'
]))
print(' '.join([
'Magsim - Magsimorig =',
str(MagObser - magsimorigs[bandi])
]))
outcatrowi = outcatrowi + [
cataline['MOD_' + cssband + '_css'], MagObser, ErrMagObs, SNR
]
bandi = bandi + 1
del WinImgBands
colnumb = len(outcatrowi)
OutRowStr = ('{} ' +
(colnumb - 1) * '{:8.3f}').format(*outcatrowi) + '\n'
OutSecStr = OutSecStr + OutRowStr
if IfProgBarOn == True:
bar.cursor.restore() # Return cursor to start
bar.draw(value=procedi)
if IfProgBarOn == True:
bar.cursor.restore() # Return cursor to start
bar.draw(value=bar.max_value) # Draw the bar!
# OutCatSecQueue.put(OutSecStr)
# _FinishQueue.put(1)
# write_lock.acquire()
with write_lock:
OutCssCat.write(OutSecStr)
OutCssCat.flush()
# write_lock.release()
print('\n')
ConvKernelNormal = csstpkg.ImgConvKnl(config.getfloat(
'Hst2Css', 'FwhmHst'),
FwhmCssz,
HstPS / nzoomin,
widthinfwhm=4)
ConvHst2Css = csstpkg.ImgConv(HstImgArr,
ConvKernelNormal.image,
NDivide=ndivide,
NZoomIn=nzoomin,
NZoomOut=nzoomout)
CssHdr = csstpkg.CRValTrans(HstHdr, HstPS, CssPS)
ConvHst2Css32 = np.array(ConvHst2Css, dtype='float32')
del ConvHst2Css, ConvKernelNormal
csstpkg.DataArr2Fits(ConvHst2Css32, HstAsCssFile, headerobj=CssHdr)
# csstpkg.DataArr2Fits(ConvHst2Css32[0:int(CssHei/8),0:int(CssWid/8)], HstAsCssFileTest, headerobj=CssHdr)
del ConvHst2Css32, CssHdr
CssHdu = fits.open(HstAsCssFile)
CssCat = ascii.read(config['Hst2Css']['CssCatIn'])
CssImg = CssHdu[0].data
CssHdr = CssHdu[0].header
CssHei, CssWid = CssImg.shape
w = wcs.WCS(CssHdr)
pixcorner = np.array([[0, 0], [CssHei, 0], [CssHei, CssWid], [0, CssWid]])
worldcorner = w.wcs_pix2world(pixcorner, 1)
RaMin = min(worldcorner[:, 0])
RaMax = max(worldcorner[:, 0])
DecMin = min(worldcorner[:, 1])