diff --git a/python/lsst/sims/GalSimInterface/galSimInterpreter.py b/python/lsst/sims/GalSimInterface/galSimInterpreter.py
index 9ef431d..7b81922 100644
--- a/python/lsst/sims/GalSimInterface/galSimInterpreter.py
+++ b/python/lsst/sims/GalSimInterface/galSimInterpreter.py
@@ -434,7 +434,7 @@ def drawSersic(self, gsObject, bandpass=None):
         # Subtract pi/2 from the position angle, because GalSim sets position angle=0
         # aligned with East, rather than North
         centeredObj = centeredObj.shear(q=gsObject.minorAxisRadians/gsObject.majorAxisRadians, \
-                                        beta=(gsObject.positionAngleRadians-0.5*numpy.pi)*galsim.radians)
+                                        beta=(0.5*numpy.pi-gsObject.positionAngleRadians)*galsim.radians)
         if self.PSF is not None:
             centeredObj = self.PSF.applyPSF(xPupil=gsObject.xPupilArcsec, yPupil=gsObject.yPupilArcsec, obj=centeredObj,
                                             bandpass=bandpass)
diff --git a/tests/testHalfLightRadius.py b/tests/testHalfLightRadius.py
index 8ff4d02..bca809a 100644
--- a/tests/testHalfLightRadius.py
+++ b/tests/testHalfLightRadius.py
@@ -147,7 +147,7 @@ def testHalfLightRadiusOfImage(self):
 
             totalFlux, hlrFlux = self.get_flux_in_half_light_radius(imageName, hlr, detector, camera, obs)
             sigmaFlux = numpy.sqrt(0.5*totalFlux/cat.photParams.gain) #divide by gain because Poisson stats apply to photons
-            self.assertTrue(numpy.abs(hlrFlux-0.5*totalFlux)<3.0*sigmaFlux)
+            self.assertTrue(numpy.abs(hlrFlux-0.5*totalFlux)<4.0*sigmaFlux)
 
             if os.path.exists(catName):
                 os.unlink(catName)
diff --git a/tests/testPositionAngle.py b/tests/testPositionAngle.py
index a2b8e59..c322d7c 100644
--- a/tests/testPositionAngle.py
+++ b/tests/testPositionAngle.py
@@ -101,15 +101,15 @@ def get_position_angle(self, imageName, afwCamera, afwDetector, \
 
         # find the angle between the (1,1) vector in pixel space and the
         # north axis of the image
-        theta = numpy.arctan2(raCenterP1[0]-raCenter[0], decCenterP1[0]-decCenter[0])
+        theta = numpy.arctan2(-1.0*(raCenterP1[0]-raCenter[0]), decCenterP1[0]-decCenter[0])
 
         # rotate the (1,1) vector in pixel space so that it is pointing
         # along the north axis
         north = numpy.array([numpy.cos(theta)-numpy.sin(theta), numpy.cos(theta)+numpy.sin(theta)])
         north = north/numpy.sqrt(north[0]*north[0]+north[1]*north[1])
 
-        # find the east axis of the image
-        east = numpy.array([north[1], -1.0*north[0]])
+        # find the west axis of the image
+        west = numpy.array([north[1], -1.0*north[0]])
 
         # now find the covariance matrix of the x, y  pixel space distribution
         # of flux on the image
@@ -140,7 +140,7 @@ def get_position_angle(self, imageName, afwCamera, afwDetector, \
         # return the angle between the north axis of the image
         # and the semi-major axis of the object
         cosTheta = numpy.dot(majorAxis, north)
-        sinTheta = numpy.dot(majorAxis, east)
+        sinTheta = numpy.dot(majorAxis, west)
         theta = numpy.arctan2(sinTheta, cosTheta)
 
         return numpy.degrees(theta)
@@ -185,7 +185,7 @@ def testPositionAngle(self):
                                     numpy.random.random_sample(1)*20.0-10.0,
                                     numpy.random.random_sample(1)*20.0-10.0,
                                     pa=[pa],
-                                    mag_norm=[18.0])
+                                    mag_norm=[17.0])
 
                 db = paFileDBObj(dbFileName, runtable='test')
 
@@ -206,7 +206,6 @@ def testPositionAngle(self):
                                                   pa-360.0-paTest,
                                                   pa+360.0-paTest
                                                   ])).min()
-
                 self.assertTrue(deviation<2.0)
 
                 if os.path.exists(catName):