Merge pull request #103 from lsst/tickets/DM-36928

DM-36928: Avoid deprecated Psf methods
lsst · Nov 22, 2022 · 7748303 · 7748303
2 parents 9f262a3 + 50249a6
commit 7748303
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Showing 3 changed files with 15 additions and 10 deletions.
diff --git a/tests/test_cModel.py b/tests/test_cModel.py
@@ -105,9 +105,10 @@ def testNoNoise(self):
         self.exposure.getMaskedImage().getVariance().getArray()[:, :] = var
         psfImage = self.exposure.getPsf().computeKernelImage(self.xyPosition).getArray()
         expectedFluxErr = var**0.5 * (psfImage**2).sum()**(-0.5)
+        pos = self.exposure.getPsf().getAveragePosition()
         result = algorithm.apply(
             self.exposure, makeMultiShapeletCircularGaussian(self.psfSigma),
-            self.xyPosition, self.exposure.getPsf().computeShape()
+            self.xyPosition, self.exposure.getPsf().computeShape(pos)
         )
         self.assertFalse(result.initial.flags[result.FAILED])
         self.assertFloatsAlmostEqual(result.initial.instFlux, self.trueFlux, rtol=0.01)
@@ -137,9 +138,10 @@ def testVsPsfFlux(self):
                 noiseSigma*numpy.random.randn(exposure.getHeight(), exposure.getWidth())
             ctrl = lsst.meas.modelfit.CModelControl()
             algorithm = lsst.meas.modelfit.CModelAlgorithm(ctrl)
+            pos = self.exposure.getPsf().getAveragePosition()
             cmodel = algorithm.apply(
                 exposure, makeMultiShapeletCircularGaussian(self.psfSigma),
-                self.xyPosition, self.exposure.getPsf().computeShape()
+                self.xyPosition, self.exposure.getPsf().computeShape(pos)
             )
             psfFlux, psfFluxErr = computePsfFlux(self.xyPosition, exposure)
             self.assertFloatsAlmostEqual(psfFlux, cmodel.instFlux, rtol=0.1/fluxFactor**0.5)

diff --git a/tests/test_doubleShapeletPsfApprox.py b/tests/test_doubleShapeletPsfApprox.py
@@ -87,6 +87,7 @@ def checkBounds(self, msf):
 
         These requirements must be true after a call to any fit method or measure().
         """
+        pos = self.psf.getAveragePosition()
         self.assertEqual(len(msf.getComponents()), 2)
         self.assertEqual(
             lsst.shapelet.computeSize(self.ctrl.innerOrder),
@@ -97,11 +98,11 @@ def checkBounds(self, msf):
             len(msf.getComponents()[1].getCoefficients())
         )
         self.assertGreater(
-            self.ctrl.maxRadiusBoxFraction * (self.psf.computeKernelImage().getBBox().getArea())**0.5,
+            self.ctrl.maxRadiusBoxFraction * (self.psf.computeKernelImage(pos).getBBox().getArea())**0.5,
             lsst.afw.geom.ellipses.Axes(msf.getComponents()[0].getEllipse().getCore()).getA()
         )
         self.assertGreater(
-            self.ctrl.maxRadiusBoxFraction * (self.psf.computeKernelImage().getBBox().getArea())**0.5,
+            self.ctrl.maxRadiusBoxFraction * (self.psf.computeKernelImage(pos).getBBox().getArea())**0.5,
             lsst.afw.geom.ellipses.Axes(msf.getComponents()[1].getEllipse().getCore()).getA()
         )
         self.assertLess(
@@ -139,7 +140,8 @@ def checkRatios(self, msf):
     def makeImages(self, msf):
         """Return an Image of the data and an Image of the model for comparison.
         """
-        dataImage = self.exposure.getPsf().computeKernelImage()
+        pos = self.exposure.getPsf().getAveragePosition()
+        dataImage = self.exposure.getPsf().computeKernelImage(pos)
         modelImage = dataImage.Factory(dataImage.getBBox())
         msf.evaluate().addToImage(modelImage)
         return dataImage, modelImage
@@ -218,7 +220,7 @@ def testFitMoments(self):
         correctly.
         """
         MOMENTS_RTOL = 1E-13
-        image = self.psf.computeKernelImage()
+        image = self.psf.computeKernelImage(self.psf.getAveragePosition())
         array = image.getArray()
         bbox = image.getBBox()
         x, y = numpy.meshgrid(
@@ -245,7 +247,7 @@ def testFitMoments(self):
     def testObjective(self):
         """Test that model evaluation agrees with derivative evaluation in the objective object.
         """
-        image = self.psf.computeKernelImage()
+        image = self.psf.computeKernelImage(self.psf.getAveragePosition())
         msf = self.Algorithm.initializeResult(self.ctrl)
         self.Algorithm.fitMoments(msf, self.ctrl, image)
         moments = msf.evaluate().computeMoments()
@@ -286,7 +288,7 @@ def testFitProfile(self):
         """Test that fitProfile() does not modify the ellipticity, that it improves the fit, and
         that small perturbations to the zeroth-order amplitudes and radii do not improve the fit.
         """
-        image = self.psf.computeKernelImage()
+        image = self.psf.computeKernelImage(self.psf.getAveragePosition())
         msf = self.Algorithm.initializeResult(self.ctrl)
         self.Algorithm.fitMoments(msf, self.ctrl, image)
         prev = lsst.shapelet.MultiShapeletFunction(msf)
@@ -328,7 +330,7 @@ def testFitShapelets(self):
         that it improves the fit, and that small perturbations to the higher-order coefficients
         do not improve the fit.
         """
-        image = self.psf.computeKernelImage()
+        image = self.psf.computeKernelImage(self.psf.getAveragePosition())
         msf = self.Algorithm.initializeResult(self.ctrl)
         self.Algorithm.fitMoments(msf, self.ctrl, image)
         self.Algorithm.fitProfile(msf, self.ctrl, image)

diff --git a/tests/test_generalShapeletPsfApproxPlugins.py b/tests/test_generalShapeletPsfApproxPlugins.py
@@ -75,7 +75,8 @@ def tearDown(self):
     def checkResult(self, msf):
         # Because we're fitting multiple shapelets to a single Gaussian (a single 0th-order shapelet)
         # we should be able to fit with zero residuals, aside from (single-precision) round-off error.
-        dataImage = self.exposure.getPsf().computeImage()
+        pos = self.exposure.getPsf().getAveragePosition()
+        dataImage = self.exposure.getPsf().computeImage(pos)
         modelImage = dataImage.Factory(dataImage.getBBox())
         modelImage.getArray()[:, :] *= -1
         msf.evaluate().addToImage(modelImage)