def test_eq_hsq(self):
'''
Gencov should be the same as hsq if z1 = z2, hsq + intercept_hsq are 0 and
all intermediate rg's are > 0 (because Hsq.weights lower-bounds the hsq guess at 0
but Gencov.weights lower-bounds the rho_g guess at -1). The setup below guarantees
that all intermediate rho_g guesses will be 1
'''
self.ld = np.abs(np.random.normal(size=100).reshape((50, 2))) + 2
self.z1 = (np.sum(self.ld, axis=1) + 10).reshape((50, 1))
gencov = reg.Gencov(self.z1,
self.z1,
self.ld,
self.w_ld,
self.N1,
self.N1,
self.M,
0,
0,
0,
0,
n_blocks=3,
intercept_gencov=1)
hsq = reg.Hsq(np.square(self.z1),
self.ld,
self.w_ld,
self.N1,
self.M,
n_blocks=3,
intercept=1)
print(gencov.summary(['asdf', 'asdf']))
print(hsq.summary(['asdf', 'asdf']))
assert_array_almost_equal(gencov.tot, hsq.tot)
assert_array_almost_equal(gencov.tot_se, hsq.tot_se)
assert_array_almost_equal(gencov.tot_cov, hsq.tot_cov)
def test_summary(self):
# not much to test; we can at least make sure no errors at runtime
self.gencov.summary(['asdf'])
self.ld += np.arange(4).reshape((4, 1))
self.z1 += np.arange(4).reshape((4, 1))
gencov = reg.Gencov(self.z1, self.z2, self.ld, self.w_ld, self.N1, self.N2,
self.M, self.hsq1, self.hsq2, 1.0, 1.0, n_blocks=3)
gencov.summary(['asdf'])
def setUp(self):
self.ld = np.abs(np.random.normal(size=100).reshape((50, 2))) + 2
self.z1 = np.random.normal(size=50).reshape((50, 1))
self.z2 = np.random.normal(size=50).reshape((50, 1))
self.w_ld = np.random.normal(size=50).reshape((50, 1))
self.N1 = 9 * np.ones((50, 1))
self.N2 = 7 * np.ones((50, 1))
self.M = np.matrix((700, 222))
self.hsq1 = 0.5
self.hsq2 = 0.6
self.gencov = reg.Gencov(self.z1, self.z2, self.ld, self.w_ld, self.N1, self.N2,
self.M, self.hsq1, self.hsq2, 1.0, 1.0, n_blocks=3, intercept_gencov=1)
def setUp(self):
self.z1 = np.ones((4, 1)) * 4
self.z2 = np.ones((4, 1))
self.ld = np.ones((4, 1))
self.w_ld = np.ones((4, 1))
self.N1 = 9 * np.ones((4, 1))
self.N2 = 7 * np.ones((4, 1))
self.M = np.matrix((7))
self.hsq1 = 0.5
self.hsq2 = 0.6
self.gencov = reg.Gencov(self.z1, self.z2, self.ld, self.w_ld, self.N1, self.N2,
self.M, self.hsq1, self.hsq2, 1.0, 1.0, n_blocks=3, intercept_gencov=1)