def test_fall_back(self):
p = 0.01
g = 0.95
n = 300
x = np.random.random(n)
x.sort()
bound = hanson_koopmans(x, p, g)[0]
self.assertTrue(np.isclose(bound, x[0]))
def test_halley(self):
i = 0
row = self.data[i]
n = int(row[0])
j = n-1
p = row[1]
g = row[2]
b = row[3]
x = np.random.random(n)
x.sort()
bound = hanson_koopmans(x, p, g, method='halley')[0]
b_ = (x[j] - bound) / (x[j] - x[0])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
bound = hanson_koopmans(x, p, g, method='halley', max_iter=50)[0]
b_ = (x[j] - bound) / (x[j] - x[0])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
bound = hanson_koopmans(x, p, g, method='halley', tol=1e-6)[0]
b_ = (x[j] - bound) / (x[j] - x[0])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
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(x, 0.1, 0.95, j=j)
_m = bounds.size
self.assertTrue(_m == m)
def test_upper_table_bounds(self):
j = 1
for i, row in enumerate(self.data):
n = int(row[0])
p = 1.0-row[1]
g = row[2]
b = row[3]
x = np.random.random(n) + 1000.
x.sort()
bound = hanson_koopmans(x, p, g, j=1)[0]
b_ = (bound - x[n-j-1]) / (x[-1] - x[n-j-1])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
def test_step_size(self):
i = 0
row = self.data[i]
n = int(row[0])
j = n-1
p = row[1]
g = row[2]
b = row[3]
x = np.random.random(n)
x.sort()
bound = hanson_koopmans(x, p, g, step_size=1e-6)[0]
b_ = (x[j] - bound) / (x[j] - x[0])
self.assertTrue(np.isclose(b, b_, rtol=1e-3, atol=1e-4))
def test_value_error(self):
with self.assertRaises(ValueError):
x = np.random.random((1, 2, 4, 3))
hanson_koopmans(x, 0.1, 0.9)