def test_run_optimization(self): f, _ = newton_rhapson( x=a([ [0.0, 1.0], [1.0, 1.0], [-1.0, 0.0], [2.0, 2.0], [1.5, -1.0] ]), f0=a([ [0.0], [0.0], [0.0], [0.0], [0.0], ]), comparisons=a([ [3, 1], [0, 1], [2, 1], [4, 0], [2, 4], ]), kernelfunc=default_kernel, Hfunc=compute_H, gfunc=compute_g, sigma=2, maxiter=20, ) self.assertTrue(f[3][0] > f[1][0]) self.assertTrue(f[0][0] > f[1][0]) self.assertTrue(f[2][0] > f[1][0]) self.assertTrue(f[4][0] > f[0][0]) self.assertTrue(f[2][0] > f[4][0])
def test_run_optimization(self): f, _ = newton_rhapson( x=a([[0.0, 1.0], [1.0, 1.0], [-1.0, 0.0], [2.0, 2.0], [1.5, -1.0]]), f0=a([ [0.0], [0.0], [0.0], [0.0], [0.0], ]), comparisons=a([ [3, 1], [0, 1], [2, 1], [4, 0], [2, 4], ]), kernelfunc=default_kernel, Hfunc=compute_H, gfunc=compute_g, sigma=2, maxiter=20, ) self.assertTrue(f[3][0] > f[1][0]) self.assertTrue(f[0][0] > f[1][0]) self.assertTrue(f[2][0] > f[1][0]) self.assertTrue(f[4][0] > f[0][0]) self.assertTrue(f[2][0] > f[4][0])
def test_one_iteration_yields_expected_result(self): ''' Taking our results from the computation of H in the last test, H^-1: [ -1.066045352 -0.661325899 -0.301834093 -0.661325899 -1.045461463 -0.027289758 -0.301834093 -0.027289758 -1.066045352 ] b (computed fresh): [ [-.603424068] [0.0] [.603424068] ] g: [ [-9.616613948] [4.388339650] [1.558974488] ] Then, we compute that H^-1 * g: [ [6.879072286] [1.729331837] [1.120927715] ] ''' f1, _ = newton_rhapson( x=a([ [0.0, 1.0], [1.0, 1.0], [-1.0, 0.0], ]), f0=a([ [6.0], [1.0], [2.0], ]), comparisons=a([ [0, 2], [2, 0], ]), kernelfunc=default_kernel, Hfunc=compute_H, gfunc=compute_g, sigma=2.0, maxiter=1, ) self.assertAlmostEqual( f1, a([ [-.879072286], [-.729331837], [.879072285], ]))
def test_one_iteration_yields_expected_result(self): ''' Taking our results from the computation of H in the last test, H^-1: [ -1.066045352 -0.661325899 -0.301834093 -0.661325899 -1.045461463 -0.027289758 -0.301834093 -0.027289758 -1.066045352 ] b (computed fresh): [ [-.603424068] [0.0] [.603424068] ] g: [ [-9.616613948] [4.388339650] [1.558974488] ] Then, we compute that H^-1 * g: [ [6.879072286] [1.729331837] [1.120927715] ] ''' f1, _ = newton_rhapson( x=a([ [0.0, 1.0], [1.0, 1.0], [-1.0, 0.0], ]), f0=a([ [6.0], [1.0], [2.0], ]), comparisons=a([ [0, 2], [2, 0], ]), kernelfunc=default_kernel, Hfunc=compute_H, gfunc=compute_g, sigma=2.0, maxiter=1, ) self.assertAlmostEqual(f1, a([ [-.879072286], [-.729331837], [.879072285], ]))