def test_akima(self):
dtype = np.float32
emd = EMD()
emd.splineKind = 'akima'
emd.DTYPE = dtype
arr = lambda x: np.array(x)
# Test error: len(X)!=len(Y)
with self.assertRaises(ValueError):
akima(arr([0]), arr([1, 2]), arr([0, 1, 2]))
# Test error: any(dt) <= 0
with self.assertRaises(ValueError):
akima(arr([1, 0, 2]), arr([1, 2]), arr([0, 1, 2]))
with self.assertRaises(ValueError):
akima(arr([0, 0, 2]), arr([1, 2]), arr([0, 1, 1]))
# Test for correct responses
T = np.array([0, 1, 2, 3, 4], dtype)
S = np.array([0, 1, -1, -1, 5], dtype)
t = np.array([i / 2. for i in range(9)], dtype)
_t, s = emd.spline_points(t, np.array((T, S)))
s_true = np.array([
S[0], 0.9125, S[1], 0.066666, S[2], -1.35416667, S[3], 1.0625, S[4]
], dtype)
self.assertTrue(np.allclose(s_true, s), "Comparing akima with true")
s_np = akima(np.array(T), np.array(S), np.array(t))
self.assertTrue(np.allclose(s, s_np), "Shouldn't matter if with numpy")
def test_cubic(self):
dtype = np.float64
emd = EMD()
emd.splineKind = 'cubic'
emd.DTYPE = dtype
T = np.array([0, 1, 2, 3, 4], dtype=dtype)
S = np.array([0, 1, -1, -1, 5], dtype=dtype)
t = np.arange(9, dtype=dtype) / 2.
# TODO: Something weird with float32.
# Seems to be SciPy problem.
_t, s = emd.spline_points(t, np.array((T, S)))
s_true = np.array([S[0], 1.203125, S[1], 0.046875, \
S[2], -1.515625, S[3], 1.015625, S[4]], dtype=dtype)
self.assertTrue(np.allclose(s, s_true), "Comparing cubic")
T = T[:-2].copy()
S = S[:-2].copy()
t = np.arange(5, dtype=dtype) / 2.
_t, s3 = emd.spline_points(t, np.array((T, S)))
s3_true = np.array([S[0], 0.78125, S[1], 0.28125, S[2]], dtype=dtype)
self.assertTrue(np.allclose(s3, s3_true), "Compare cubic 3pts")
def test_unsupporter_spline(self):
emd = EMD()
emd.splineKind = "waterfall"
S = np.random.random(20)
with self.assertRaises(ValueError):
emd.emd(S)
def test_slinear(self):
dtype = np.float64
emd = EMD()
emd.splineKind = 'slinear'
emd.DTYPE = dtype
T = np.array([0, 1, 2, 3, 4], dtype=dtype)
S = np.array([0, 1, -1, -1, 5], dtype=dtype)
t = np.arange(9, dtype=dtype) / 2.
_t, s = emd.spline_points(t, np.array((T, S)))
s_true = np.array([S[0], 0.5, S[1], 0, \
S[2], -1, S[3], 2, S[4]], dtype=dtype)
self.assertTrue(np.allclose(s, s_true), "Comparing SLinear")