def get_all_bkg_txt(catalog_file, obsIDlist, inpath, ecf):
###------read catalog file, need modification---##
(ra_list, dec_list, srcIDlist) = funcs.read_erosita_cat(
'/Users/baotong/Desktop/period_Tuc/erosita_cat_coord.xlsx')
###-------------------------------------------##
if len(ra_list) != len(srcIDlist) or len(dec_list) != len(srcIDlist):
print('ERROR!')
return None
# for j in range(len(obsIDlist)):
# bkgarea_all=[]
# (psf_bettervalue, not_include_index) = get_psfradius(srcID=srcIDlist, ra=ra, dec=dec, obsid=obsIDlist[j], inpath=path,
# outpath=path, ecf=0.9, if_SN_radius=False)
# (psf_bettervalue_src, not_include_index_2) = get_psfradius(srcID=srcIDlist, ra=ra, dec=dec, obsid=obsIDlist[j], inpath=path,
# outpath=path, ecf=0.5, if_SN_radius=False)
# outpath = inpath + 'txt/txt_psf75_{0}/'.format(obsIDlist[j])
# evtfile = inpath + 'pm00_{0}_020_EventList_c001_bary.fits'.format(obsIDlist[j])
# imgfilename =inpath+ '{0}_05_5_img.fits'.format(obsIDlist[j])
# for i in range(len(ra_list)):
# evtfile=inpath+'pm00_{0}_020_EventList_c001_bary.fits'.format(obsIDlist[j])
# bkgarea_temp=get_singlebkg_evt(evtfile=evtfile,imgname=imgfilename,obsid=obsIDlist[j],ra=ra_list[i],dec=dec_list[i],
# emin=200,emax=5000,radius_src=psf_bettervalue[i],radius_list=psf_bettervalue_src,
# ra_list=ra_list,dec_list=dec_list,outpath=outpath,outname=str(srcIDlist[i]))
# bkgarea_all.append(bkgarea_temp)
# np.savetxt(outpath+'bkg_area.txt',np.column_stack((srcIDlist,np.array(bkgarea_all))))
for i in range(len(ra_list)):
merge_txt(obsIDlist=obsIDlist,
inpath=inpath + 'txt/',
outpath=inpath + 'txt/txt_merge_psf50_0.2_5/',
outname=str(srcIDlist[i]),
epoch_file='epoch_47Tuc.txt',
ecf=ecf)
def get_all_src_txt(catalog_file, obsIDlist, inpath, ecf=0.50):
###------read catalog file, need modification---##
(ra_list, dec_list, srcIDlist) = funcs.read_erosita_cat(
'/Users/baotong/Desktop/period_Tuc/erosita_cat_coord.xlsx')
# ###-------------------------------------------##
if len(ra_list) != len(srcIDlist) or len(dec_list) != len(srcIDlist):
print('ERROR!')
return None
for j in range(len(obsIDlist)):
srcarea = []
(psf_bettervalue,
not_include_index) = get_psfradius(srcID=srcIDlist,
ra=ra,
dec=dec,
obsid=obsIDlist[j],
inpath=path,
outpath=path,
ecf=ecf,
if_SN_radius=False)
outpath = inpath + 'txt/txt_psf{0}_{1}/'.format(
int(ecf * 100), obsIDlist[j])
evtfile = inpath + 'pm00_{0}_020_EventList_c001_bary.fits'.format(
obsIDlist[j])
imgfilename = inpath + '{0}_02_5_img.fits'.format(obsIDlist[j])
for i in range(len(ra_list)):
get_singlesrc_evt(evtfile=evtfile,
imgname=imgfilename,
obsid=obsIDlist[j],
ra=ra_list[i],
dec=dec_list[i],
radius=psf_bettervalue[i],
emin=200,
emax=5000,
outpath=outpath,
outname=str(srcIDlist[i]))
srcarea.append(np.pi * psf_bettervalue[i]**2)
np.savetxt(outpath + 'src_area.txt',
np.column_stack((srcIDlist, np.array(srcarea))))
for i in range(len(ra_list)):
merge_txt(inpath=inpath + 'txt/',
outpath=inpath +
'txt/txt_merge_psf{0}_0.2_5/'.format(int(ecf * 100)),
outname=str(srcIDlist[i]),
epoch_file='epoch_47Tuc.txt',
ecf=ecf)
def write_src_info(ecf=0.75):
##返回的radi是arcsec单位,with bkgimage
path = '/Users/baotong/eSASS/data/raw_data/47_Tuc/'
srcid = np.arange(1, 889, 1)
obsIDlist = [700011, 700163, 700013, 700014, 700173, 700174, 700175]
expT = [25808.86, 25268.79, 25208.83, 25208.82, 8809.16, 8389.71, 8330.68]
for k in range(len(obsIDlist)):
obsid = obsIDlist[k]
srcarea = np.loadtxt(
path +
'txt/txt_psf{0}_{1}/src_area.txt'.format(int(100 * ecf), obsid))
srcscale = srcarea[:, 1]
radi = np.sqrt(srcscale / np.pi) / 20.
bkgimgfile = 'bkg_map_02_5_{0}.fits'.format(obsid)
bkgimg = fits.open(path + bkgimgfile)[0].data.T
catalog_file = '/Users/baotong/Desktop/period_Tuc/erosita_cat_coord.xlsx'
(ra, dec, srcIDlist) = funcs.read_erosita_cat(catalog_file)
(phy_x, phy_y) = funcs.trans_radec2xy(path + bkgimgfile, ra, dec)
img_x = (phy_x + 41000) / 80
img_y = (phy_y + 41000) / 80
img_x = img_x.astype('int')
img_y = img_y.astype('int')
img_x[np.where(img_x > 1024 - 1)] = 0
img_y[np.where(img_y > 1024 - 1)] = 0
median_bkgvalue = bkgimg[img_x, img_y]
bkg_cts_est = median_bkgvalue * srcscale / 6400
src_cts = []
for i in range(len(srcid)):
srctxtfile = path + 'txt/txt_psf{0}_{1}/{2}_{1}.txt'.format(
int(100 * ecf), obsid, srcid[i])
time = np.loadtxt(srctxtfile)
src_cts.append(len(time))
src_cts = np.array(src_cts)
SNR = (src_cts - bkg_cts_est) / np.sqrt(src_cts)
SNR[np.where(radi < 0.1)] = 0 ##出界的源，SNR自然应该是0，0.1是随便取的值，筛出出界的源即可
info = np.column_stack((srcid, src_cts, bkg_cts_est, radi, SNR))
np.savetxt(
path +
'txt/txt_psf{0}_{1}/src_info.txt'.format(int(100 * ecf), obsid),
info,
fmt='%10d %10d %10.2f %10.5f %10.5f')
def get_all_src_txt_SNRpsf(catalog_file, obsIDlist, inpath):
(ra_list, dec_list, srcIDlist) = funcs.read_erosita_cat(catalog_file)
if len(ra_list) != len(srcIDlist) or len(dec_list) != len(srcIDlist):
print('ERROR!')
return None
for j in range(len(obsIDlist)):
print(obsIDlist[j])
evtfile = inpath + 'pm00_{0}_020_EventList_c001_bary.fits'.format(
obsIDlist[j])
imgfilename = inpath + '{0}_02_5_img.fits'.format(obsIDlist[j])
src_info = np.loadtxt(inpath +
'region/reg_{0}/region_SNRpsf/src_info_{0}.txt'.
format(obsIDlist[j]))
radius_list = src_info[:, 3]
not_include_index = src_info[:, 6]
radius_list *= 20.
outpath = inpath + 'txt/txt_SNR_{0}/'.format(obsIDlist[j])
for i in range(len(ra_list)):
if not_include_index[i] == 1:
get_singlesrc_evt(evtfile=evtfile,
imgname=imgfilename,
obsid=obsIDlist[j],
ra=ra_list[i],
dec=dec_list[i],
radius=radius_list[i],
emin=200,
emax=5000,
outpath=outpath,
outname=str(srcIDlist[i]))
for i in range(len(ra_list)):
merge_txt(obsIDlist=obsIDlist[0:4],
inpath=inpath + 'txt/',
outpath=inpath + 'txt/txt_merge_psf75_0.2_5/',
outname=str(srcIDlist[i]),
epoch_file='epoch_47Tuc.txt')
if __name__ == '__main__':
# path = '/Users/baotong/eSASS/data/47_Tuc/'
path = '/Users/baotong/eSASS/data/raw_data/47_Tuc/'
ID = [700011, 700013, 700014, 700163, 700173, 700174, 700175]
catalog_file = '/Users/baotong/Desktop/period_Tuc/erosita_cat_coord.xlsx'
# make_epochfile(path=path,ID=ID,outpath=path+'txt/')
# for obsid in ID:
# get_singlesrc_evt(path+'pm00_{0}_020_EventList_c001_bary.fits'.format(obsid),obsid=obsid,
# ra=6.04485,dec=-72.07383,radius=20./3600,outpath='/Users/baotong/eSASS/data/47_Tuc/txt/',
# outname='182')
#
# merge_txt(ID,outpath='/Users/baotong/eSASS/data/47_Tuc/txt/',outname='182')
# get_psfradius(ra=np.array([6.0178,6.1078]),dec=np.array([-72.08281,-72.18281]),obsid=700011,inpath=path,outpath=path)
(ra, dec, srcIDlist) = funcs.read_erosita_cat(catalog_file)
# get_all_src_txt(catalog_file, obsIDlist=ID, inpath=path,ecf=0.90)
# get_all_bkg_txt(catalog_file, obsIDlist=ID, inpath=path)
# get_all_src_txt_SNRpsf(catalog_file, obsIDlist=ID, inpath=path)
# merge_4reg_txt(srcIDlist,ecf=0.90)
# for obsID in ID[0:]:
# (psf_bestSNR_no_overlap,ECF_allsrc,SNR_allsrc,not_include_index)=get_psfradius(srcID=srcIDlist[0:],ra=ra[0:], dec=dec[0:], obsid=obsID, inpath=path,
# outpath=path, ecf=0.9,if_SN_radius=True)
# write_cat_psfinfo(srcID=srcIDlist[0:],ra=ra[0:],dec=dec[0:],radius=psf_bestSNR_no_overlap,
# ecf=ECF_allsrc,SNR=SNR_allsrc,not_include_index=not_include_index,obsIDlist=[obsID],outpath=path)
# make_region(srcID=srcIDlist[0:],ra=ra[0:],dec=dec[0:],ecf='SNR',radius=psf_bestSNR_no_overlap,obsIDlist=[obsID],outpath=path)
expmap = fits.open(path + expmap_file)[0].data.T
path_txt = path + 'txt/txt_psf{0}_{1}/'.format(ecf, obsid)
src_info = np.loadtxt(path_txt + 'src_info.txt')
src_cts = src_info[:, 0]
bkg_cts = src_info[:, 1]
net_cts = src_cts - bkg_cts
expvalue = expmap[src_x, src_y]
return (net_cts, expvalue)
if __name__ == '__main__':
path = '/Users/baotong/eSASS/data/raw_data/47_Tuc/'
(ra, dec, srcIDlist) = funcs.read_erosita_cat(
filename='/Users/baotong/Desktop/period_Tuc/erosita_cat_coord.xlsx')
obsIDlist = [700011, 700163, 700013, 700014, 700173, 700174, 700175]
for i in range(len(obsIDlist)):
(net_cts, expvalue) = get_net_info(obsIDlist[i], ra, dec, srcIDlist)
net_CR = net_cts / expvalue / 1500
net_CR = net_CR[np.where(net_CR > 0)]
net_CR = net_CR * 1e4
plt.hist(net_CR, bins=np.logspace(-2, 2, 30), histtype='step')
plt.loglog()
plt.title('obsID: {0}'.format(obsIDlist[i]))
plt.xlabel('Net count rate')
plt.ylabel('Number')
plt.show()
# net_cts_err = poisson_conf_interval(net_cts, interval='frequentist-confidence').T
# print(net_cts_err)