diff --git a/AegeanTools/__init__.py b/AegeanTools/__init__.py
index ae8de367..a14b6d52 100755
--- a/AegeanTools/__init__.py
+++ b/AegeanTools/__init__.py
@@ -11,7 +11,7 @@
 """
 __author__ = 'Paul Hancock'
 __version__ = '2.2.2'
-__date__ = '2020-06-19'
+__date__ = '2020-07-23'
 __citation__ = """
 % If your work makes use of AegeanTools please cite the following papers as appropriate:
 
diff --git a/AegeanTools/fitting.py b/AegeanTools/fitting.py
index 4e695626..cfbb0250 100644
--- a/AegeanTools/fitting.py
+++ b/AegeanTools/fitting.py
@@ -871,16 +871,15 @@ def condon_errors(source, theta_n, psf=None):
     if psf is not None:
         beam = psf.get_beam(source.ra, source.dec)
         if beam is not None:
-            theta_n = np.hypot(beam.a, beam.b)
-            print(beam, theta_n)
+            theta_n = np.sqrt(beam.a * beam.b)
 
     if theta_n is None:
         source.err_a = source.err_b = source.err_peak_flux = source.err_pa = source.err_int_flux = 0.0
         return
 
     smoothing = major * minor / (theta_n ** 2)
-    factor1 = (1 + (major / theta_n))
-    factor2 = (1 + (minor / theta_n))
+    factor1 = (1 + (theta_n/ major)**2)
+    factor2 = (1 + (theta_n/ minor)**2)
     snr = source.peak_flux / source.local_rms
     # calculation of rho2 depends on the parameter being used so we lambda this into a function
     rho2 = lambda x: smoothing / 4 * factor1 ** alphas[x][0] * factor2 ** alphas[x][1] * snr ** 2
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 71ed8f44..ef24e642 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -3,6 +3,7 @@ v 2.2.2
 Aegean
 - Fixed a bug that could cause a crash if the psf map had nan values
 - Fixed a bug that caused island contours to just be boxes.
+- Fixed an error in the calculation of condon errors.
 
 MIMAS
 - added new functionality, `--mask2mim`, which will convert a fits file into a region file.
diff --git a/scripts/aegean b/scripts/aegean
index 6359e02a..deea8774 100755
--- a/scripts/aegean
+++ b/scripts/aegean
@@ -387,7 +387,7 @@ if __name__ == "__main__":
         # theta_N is the FWHM of the smoothing kernel (the noise correlation)
         # which in this case is the same as the synthesized beam FWHM
         if options.beam:
-            theta_n = np.hypot(options.beam[0], options.beam[1])
+            theta_n = np.sqrt(options.beam.a * options.beam.b)
             psf = None
         else:
             psf = sf.global_data.psfhelper