def test_few_samples(self):
g = kernel_smoothing(self.x,
self.y,
target_x=np.linspace(-5, 200, 5,
dtype=np.float32),
q=7)
self.assertTrue(g is not None, msg="None output")
self.assertEqual(len(g), 5)
def test_many_samples(self):
x_ref_count = getrefcount(self.x)
y_ref_count = getrefcount(self.y)
target_x_ref_count = getrefcount(self.target_x)
self.assertEqual(x_ref_count, y_ref_count)
self.assertEqual(x_ref_count, target_x_ref_count)
g = kernel_smoothing(self.x, self.y, target_x=self.target_x, q=7)
self.assertEqual(x_ref_count, getrefcount(self.x))
self.assertEqual(y_ref_count, getrefcount(self.y))
self.assertEqual(target_x_ref_count, getrefcount(self.target_x))
self.assertEqual(1, getrefcount(g))
def test_large_smoothing(self):
g = kernel_smoothing(self.x, self.y, f=1.5)
self.assertTrue(g is not None, msg="None output")
self.assertEqual(len(g), len(self.x))
def test_small(self):
g = kernel_smoothing(self.x, self.y, q=1)
self.assertTrue(g is not None, msg="None output")
self.assertEqual(len(g), len(self.x))
def test_nans(self):
x = [1, 2, 3, 4, 5, 6]
y = [1, np.nan, 3, 4, np.nan, 6]
g = kernel_smoothing(x, y, q=3)
self.assertTrue(g is not None, msg="None output")
self.assertEqual(len(g), len(x))
def test_numpy_float64(self):
x = np.arange(0, 10, 1, dtype=np.float64)
y = np.arange(0, 10, 1, dtype=np.float64)
g = kernel_smoothing(x, y, q=3)
self.assertTrue(g is not None, msg="None output")
self.assertEqual(len(g), len(x))