Exemplo n.º 1
0
    def testInnerProducts(self):
        """Test inner products"""

        width, height = 10, 20
        im1 = afwImage.ImageF(lsst.geom.Extent2I(width, height))
        val1 = 10
        im1.set(val1)

        im2 = im1.Factory(im1.getDimensions())
        val2 = 20
        im2.set(val2)

        self.assertEqual(afwImage.innerProduct(im1, im1),
                         width*height*val1*val1)
        self.assertEqual(afwImage.innerProduct(im1, im2),
                         width*height*val1*val2)

        im2[0, 0, afwImage.LOCAL] = 0
        self.assertEqual(afwImage.innerProduct(im1, im2),
                         (width*height - 1)*val1*val2)

        im2[0, 0, afwImage.LOCAL] = val2             # reinstate value
        im2[width - 1, height - 1, afwImage.LOCAL] = 1
        self.assertEqual(afwImage.innerProduct(im1, im2),
                         (width*height - 1)*val1*val2 + val1)
Exemplo n.º 2
0
    def testPca(self):
        """Test calculating PCA"""
        width, height = 200, 100
        numBases = 3
        numInputs = 3

        bases = []
        for i in range(numBases):
            im = afwImage.ImageF(width, height)
            array = im.getArray()
            x, y = np.indices(array.shape)
            period = 5*(i+1)
            fx = np.sin(2*math.pi/period*x + 2*math.pi/numBases*i)
            fy = np.sin(2*math.pi/period*y + 2*math.pi/numBases*i)
            array[x, y] = fx + fy
            bases.append(im)

        if display:
            mos = afwDisplay.utils.Mosaic(background=-10)
            afwDisplay.Display(frame=1).mtv(mos.makeMosaic(bases), title="Basis functions")

        inputs = []
        for i in range(numInputs):
            im = afwImage.ImageF(lsst.geom.Extent2I(width, height))
            im.set(0)
            for b in bases:
                im.scaledPlus(random.random(), b)

            inputs.append(im)
            self.ImageSet.addImage(im, 1.0)

        if display:
            mos = afwDisplay.utils.Mosaic(background=-10)
            afwDisplay.Display(frame=2).mtv(mos.makeMosaic(inputs), title="Inputs")

        self.ImageSet.analyze()

        eImages = []
        for img in self.ImageSet.getEigenImages():
            eImages.append(img)

        if display:
            mos = afwDisplay.utils.Mosaic(background=-10)
            afwDisplay.Display(frame=3).mtv(mos.makeMosaic(eImages), title="EigenImages")

        self.assertEqual(len(eImages), numInputs)

        # Test for orthogonality
        for i1, i2 in itertools.combinations(list(range(len(eImages))), 2):
            inner = afwImage.innerProduct(eImages[i1], eImages[i2])
            norm1 = eImages[i1].getArray().sum()
            norm2 = eImages[i2].getArray().sum()
            inner /= norm1*norm2
            self.assertAlmostEqual(inner, 0)
Exemplo n.º 3
0
    def testImagePca(self):
        # Test out the ImagePca behavior
        kc1 = self.makeCandidate(1, 0.0, 0.0)
        kc1.build(self.kList)
        kc2 = self.makeCandidate(2, 0.0, 0.0)
        kc2.build(self.kList)
        kc3 = self.makeCandidate(3, 0.0, 0.0)
        kc3.build(self.kList)

        imagePca = ipDiffim.KernelPcaD()
        kpv = ipDiffim.KernelPcaVisitorF(imagePca)
        kpv.processCandidate(kc1)
        kpv.processCandidate(kc2)
        kpv.processCandidate(kc3)

        imagePca.analyze()
        eigenImages = imagePca.getEigenImages()
        # NOTE : this needs to be changed once ticket #1649 is resolved
        for i in range(len(eigenImages)):
            for j in range(i, len(eigenImages)):
                print i, j, afwImage.innerProduct(eigenImages[i], eigenImages[j])