Initial commit

scripts/print_transform.py

@@ -0,0 +1,67 @@
+import glob, sys
+from astropy.io import fits
+import statistics
+import pandas as pd
+import numpy as np
+import csv
+from uds.config import *
+
+colnames=['Match', 'Ref', 'Dup', 'RA', 'Dec', 'Incl']
+
+flist=glob.glob('../products/tm[1,5,6,7]*en0*.xfm')
+total1=0
+total2=0
+
+for f in flist:
+
+    pos = f.find("_SourceCatalog")
+    key=f[12:pos]
+    
+    hdul = fits.open(f)
+    try:
+        tab=hdul[1].data
+    except:
+        continue
+    hdul.close()
+
+    dsrc=f.replace(".xfm",".shu2019.src.fits")
+    hdul = fits.open(dsrc)
+    try:
+        hdr=hdul[0].header
+        cdelt=hdr['CDELT2']*3600
+    except:
+        continue
+    hdul.close()
+
+    a11=tab[0]['a11']
+    a12=tab[0]['a12']
+    a22=tab[0]['a22']
+    a21=tab[0]['a21']
+    x_scale=tab[0]['x_scale']
+    y_scale=tab[0]['y_scale']
+
+    t1=tab[0]['t1']*cdelt
+    t2=tab[0]['t2']*cdelt
+
+    sx1=np.sign(a11)*np.sqrt(a11**2 + a12**2)
+    sy1=np.sign(a22)*np.sqrt(a21**2 + a22**2)
+
+    sx2=np.sign(a11)*np.sqrt(a11**2 + a21**2)
+    sy2=np.sign(a22)*np.sqrt(a12**2 + a22**2)
+    
+    a1 = np.arctan2(a12/sx1,a11/sy2) * 180 / np.pi * 60
+    a2 = np.arctan2(a12/sx1,a22/sy2) * 180 / np.pi * 60
+
+    b1 = np.arctan2(a21,a11) * 180 / np.pi * 60
+    b2 = np.arctan2(a21,a22) * 180 / np.pi * 60
+
+    det=a11*a22-a12*a21
+    
+    alpha=355*np.pi/180
+    a3 = np.arctan2(np.sin(alpha),np.cos(alpha)) * 180 / np.pi 
+
+    print("{:+.8} {:+.8}".format(a11,a12))
+    print("{:+.8} {:+.8}".format(a21,a22))
+    
+    #print("{} d {:.10f} s {:.8f} {:.8f} {:.8f} {:.8f} | {:+.8f} {:+.8f} {:+.8f} {:+.8f} t {:+.2f} {:+.2f}".format(obslist[key],np.sqrt(det)*cdelt,sx1*cdelt,sx2*cdelt,sy1*cdelt,sy2*cdelt,a1,a2,b1,b2,t1,t2))
+    #print("{} d {:.10f} s {:.8f} {:.8f} {:.8f} {:.8f} | {:+.8f} {:+.8f} {:+.8f} {:+.8f} t {:+.2f} {:+.2f}".format(obslist[key],np.sqrt(det)*cdelt,sx1*cdelt,sx2*cdelt,sy1*cdelt,sy2*cdelt,a1,a2,b1,b2,t1,t2))