class TestFiguresOfMerit(unittest.TestCase): def setUp(self): self.invertor = Invertor() self.invertor.d_max = 100.0 # Test array self.ntest = 5 self.x_in = numpy.ones(self.ntest) for i in range(self.ntest): self.x_in[i] = 1.0*(i+1) x, y, err = load("sphere_80.txt") # Choose the right d_max... self.invertor.d_max = 160.0 # Set a small alpha self.invertor.alpha = .0007 # Set data self.invertor.x = x self.invertor.y = y self.invertor.err = err # Perform inversion #out, cov = self.invertor.invert(10) self.out, self.cov = self.invertor.lstsq(10) def test_positive(self): """ Test whether P(r) is positive """ self.assertEqual(self.invertor.get_positive(self.out), 1) def test_positive_err(self): """ Test whether P(r) is at least 1 sigma greater than zero for all r-values """ self.assertTrue(self.invertor.get_pos_err(self.out, self.cov)>0.9)
class TestFiguresOfMerit(unittest.TestCase): def setUp(self): self.invertor = Invertor() self.invertor.d_max = 100.0 # Test array self.ntest = 5 self.x_in = numpy.ones(self.ntest) for i in range(self.ntest): self.x_in[i] = 1.0 * (i + 1) x, y, err = load("sphere_80.txt") # Choose the right d_max... self.invertor.d_max = 160.0 # Set a small alpha self.invertor.alpha = .0007 # Set data self.invertor.x = x self.invertor.y = y self.invertor.err = err # Perform inversion #out, cov = self.invertor.invert(10) self.out, self.cov = self.invertor.lstsq(10) def test_positive(self): """ Test whether P(r) is positive """ self.assertEqual(self.invertor.get_positive(self.out), 1) def test_positive_err(self): """ Test whether P(r) is at least 1 sigma greater than zero for all r-values """ self.assertTrue(self.invertor.get_pos_err(self.out, self.cov) > 0.9)