class TestOutputGaussian(unittest.TestCase):
def setUp(self):
nstates = 3
means = np.array([-0.5, 0.0, 0.5])
sigmas = np.array([0.2, 0.2, 0.2])
self.G = GaussianOutputModel(nstates, means=means, sigmas=sigmas)
# random Gaussian samples
self.obs = np.random.randn(10000)
def tearDown(self):
pass
def test_p_obs(self):
# compare results
self.G.set_implementation('c')
time1 = time.time()
for i in range(10):
p_c = self.G.p_obs(self.obs)
time2 = time.time()
t_c = time2 - time1
self.G.set_implementation('python')
time1 = time.time()
for i in range(10):
p_p = self.G.p_obs(self.obs)
time2 = time.time()
t_p = time2 - time1
assert (np.allclose(p_c, p_p))
# speed report
if print_speedup:
print('p_obs speedup c/python = ' + str(t_p / t_c))
class TestOutputGaussian(unittest.TestCase):
def setUp(self):
nstates = 3
means = np.array([-0.5, 0.0, 0.5])
sigmas = np.array([0.2, 0.2, 0.2])
self.G = GaussianOutputModel(nstates, means=means, sigmas=sigmas)
# random Gaussian samples
self.obs = np.random.randn((10000))
def tearDown(self):
pass
def test_p_obs(self):
# compare results
self.G.set_implementation('c')
time1 = time.time()
for i in range(10):
p_c = self.G.p_obs(self.obs)
time2 = time.time()
t_c = time2-time1
self.G.set_implementation('python')
time1 = time.time()
for i in range(10):
p_p = self.G.p_obs(self.obs)
time2 = time.time()
t_p = time2-time1
assert(np.allclose(p_c, p_p))
# speed report
if print_speedup:
print('p_obs speedup c/python = '+str(t_p/t_c))
