56 lines
1.5 KiB
Python
56 lines
1.5 KiB
Python
import glob, sys
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from astropy.io import fits
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import statistics
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import pandas as pd
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import numpy as np
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import csv
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colnames=['Match', 'Ref', 'Dup', 'RA', 'Dec', 'Incl']
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flist=glob.glob('../products/tm[1,5,6,7]*en0*src.fits')
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total1=0
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total2=0
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for f in flist:
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hdul = fits.open(f)
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try:
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table=hdul[1].data['RADEC_ERR']
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except:
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continue
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hdul.close()
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dref=f.replace("src.fits","ref.fits")
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hdul = fits.open(dref)
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try:
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rtable=hdul[1].data['RA']
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except:
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continue
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hdul.close()
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err=[]
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err10=[]
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dfile=f.replace("shu2019.src.fits","xfm.log.dat.awk")
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with open(dfile) as csvfile:
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spamreader = csv.reader(csvfile, delimiter=' ')
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total=0
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for row in spamreader:
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if(row[5] == 'N'):
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continue
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for ii,values in np.ndenumerate(rtable):
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if(int(row[2]) == int(ii[0])):
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total=total+1
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#print(">>",row[5],rtable[ii],table[ii],ii[0])
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if(table[ii]>0.0):
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err.append(table[ii])
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if(table[ii]>10.0):
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err10.append(table[ii])
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total1=total1+total
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total2=total2+len(err)
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#print("{} MIN {:.2f} MAX {:.2f} ({}/{})".format(f[12:15],min(err),max(err),len(err10),len(err)))
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print("{} MIN {:.2f} MAX {:.2f} ({}/{})".format(f,min(err),max(err),len(err10),len(err)))
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#sys.exit()
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#print(total1,total2)
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