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)
