def test_new_raphson(self):
p = 0.1
g = 0.95
i = 0
b = self.b_range[i]
j = self.j_range[i] - 1
n = self.n_range_b[i]
x = np.random.random(n)
x.sort()
bound = hanson_koopmans_cmh(x, p, g, j=j, method='newton-raphson')[0]
b_ = np.log(bound / x[j]) / np.log(x[0] / x[j])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
bound = hanson_koopmans_cmh(x,
p,
g,
j=j,
method='newton-raphson',
max_iter=50)[0]
b_ = np.log(bound / x[j]) / np.log(x[0] / x[j])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
bound = hanson_koopmans_cmh(x,
p,
g,
j=j,
method='newton-raphson',
tol=1e-6)[0]
b_ = np.log(bound / x[j]) / np.log(x[0] / x[j])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
def test_fall_back(self):
p = 0.01
g = 0.95
n = 300
x = np.random.random(n)
x.sort()
bound = hanson_koopmans_cmh(x, p, g)[0]
self.assertTrue(np.isclose(bound, x[0]))
def test_random_shapes(self):
M = [3, 10, 20]
N = [5, 10, 20]
J = [1, 2]
for m in M:
for n in N:
for j in J:
x = np.random.random((m, n))
bounds = hanson_koopmans_cmh(x, 0.1, 0.95, j=j)
_m = bounds.size
self.assertTrue(_m == m)
def test_a_basis(self):
p = 0.01
g = 0.95
for i, b in enumerate(self.a_range):
n = self.n_range[i]
j = n - 1
x = np.random.random(n)
x.sort()
bound = hanson_koopmans_cmh(x, p, g)[0]
b_ = np.log(bound / x[j]) / np.log(x[0] / x[j])
self.assertTrue(np.isclose(b, b_, rtol=1e-4, atol=1e-5))
def test_b_basis(self):
p = 0.1
g = 0.95
for i, b in enumerate(self.b_range):
j = self.j_range[i] - 1
n = self.n_range_b[i]
x = np.random.random(n)
x.sort()
bound = hanson_koopmans_cmh(x, p, g, j=j)[0]
b_ = np.log(bound / x[j]) / np.log(x[0] / x[j])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
def test_step_size(self):
p = 0.1
g = 0.95
i = 0
b = self.b_range[i]
j = self.j_range[i] - 1
n = self.n_range_b[i]
x = np.random.random(n)
x.sort()
bound = hanson_koopmans_cmh(x, p, g, j=j, step_size=1e-5)[0]
b_ = np.log(bound / x[j]) / np.log(x[0] / x[j])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
def test_value_error_upper(self):
with self.assertRaises(ValueError):
x = np.random.random((10, 10))
hanson_koopmans_cmh(x, 0.9, 0.95)
def test_value_error_shape(self):
with self.assertRaises(ValueError):
x = np.random.random((1, 2, 4, 3))
hanson_koopmans_cmh(x, 0.1, 0.9)
