Initial commit

scripts/print_radec_err.py

@@ -0,0 +1,55 @@
+import glob, sys
+from astropy.io import fits
+import statistics
+import pandas as pd
+import numpy as np
+import csv
+colnames=['Match', 'Ref', 'Dup', 'RA', 'Dec', 'Incl']
+
+flist=glob.glob('../products/tm[1,5,6,7]*en0*src.fits')
+total1=0
+total2=0
+
+for f in flist:
+
+    hdul = fits.open(f)
+    try:
+        table=hdul[1].data['RADEC_ERR']
+    except:
+        continue
+    hdul.close()
+    
+    dref=f.replace("src.fits","ref.fits")
+    hdul = fits.open(dref)
+    try:
+        rtable=hdul[1].data['RA']
+    except:
+        continue
+    hdul.close()
+
+    err=[]
+    err10=[]
+    dfile=f.replace("shu2019.src.fits","xfm.log.dat.awk")
+    with open(dfile) as csvfile:
+        spamreader = csv.reader(csvfile,  delimiter=' ')    
+        total=0
+        for row in spamreader:
+            if(row[5] == 'N'):
+                continue
+            for ii,values in np.ndenumerate(rtable):
+                if(int(row[2]) == int(ii[0])):
+                    total=total+1
+                    #print(">>",row[5],rtable[ii],table[ii],ii[0])
+                    if(table[ii]>0.0):
+                        err.append(table[ii])
+                    if(table[ii]>10.0):
+                        err10.append(table[ii])
+                        
+    total1=total1+total
+    total2=total2+len(err)
+    #print("{} MIN {:.2f} MAX {:.2f} ({}/{})".format(f[12:15],min(err),max(err),len(err10),len(err)))
+    print("{} MIN {:.2f} MAX {:.2f} ({}/{})".format(f,min(err),max(err),len(err10),len(err)))
+    #sys.exit()
+
+
+    #print(total1,total2)