def test_integer_perfect_recon():
# Check that an integer input is correctly coerced into a floating point
# array and reconstructed
A = np.array([1,2,3,4], dtype=np.int32)
Yl, Yh = dtwavexfm(A)
B = dtwaveifm(Yl, Yh)
assert np.max(np.abs(A-B)) < 1e-12
def test_integer_perfect_recon():
# Check that an integer input is correctly coerced into a floating point
# array and reconstructed
A = np.array([1, 2, 3, 4], dtype=np.int32)
Yl, Yh = dtwavexfm(A)
B = dtwaveifm(Yl, Yh)
assert np.max(np.abs(A - B)) < 1e-12
def test_float32_input():
# Check that an float32 input is correctly output as float32
Yl, Yh = dtwavexfm(np.array([1, 2, 3, 4]).astype(np.float32))
assert np.issubsctype(Yl.dtype, np.float32)
assert np.all(list(np.issubsctype(x.dtype, np.complex64) for x in Yh))
recon = dtwaveifm(Yl, Yh)
assert np.issubsctype(recon.dtype, np.float32)
def test_float32_input():
# Check that an float32 input is correctly output as float32
Yl, Yh = dtwavexfm(np.array([1, 2, 3, 4]).astype(np.float32))
assert np.issubsctype(Yl.dtype, np.float32)
assert np.all(list(np.issubsctype(x.dtype, np.complex64) for x in Yh))
recon = dtwaveifm(Yl, Yh)
assert np.issubsctype(recon.dtype, np.float32)
def test_reconstruct_2d():
# Reconstruction up to tolerance
vec = np.random.rand(630, 20)
Yl, Yh = dtwavexfm(vec)
vec_recon = dtwaveifm(Yl, Yh)
assert np.all(np.abs(vec_recon - vec) < TOLERANCE)
def test_reconstruct_2d():
# Reconstruction up to tolerance
vec = np.random.rand(630, 20)
Yl, Yh = dtwavexfm(vec)
vec_recon = dtwaveifm(Yl, Yh)
assert np.all(np.abs(vec_recon - vec) < TOLERANCE)
def test_simple_custom_filter():
vec = np.random.rand(630)
Yl, Yh = dtwavexfm(vec, 4, biort('legall'), qshift('qshift_06'))
vec_recon = dtwaveifm(Yl, Yh, biort('legall'), qshift('qshift_06'))
assert np.max(np.abs(vec_recon - vec)) < TOLERANCE
def test_perfect_recon():
vec = np.random.rand(630)
Yl, Yh = dtwavexfm(vec)
vec_recon = dtwaveifm(Yl, Yh)
assert np.max(np.abs(vec_recon - vec)) < TOLERANCE
def test_simple_custom_filter():
vec = np.random.rand(630)
Yl, Yh = dtwavexfm(vec, 4, biort('legall'), qshift('qshift_06'))
vec_recon = dtwaveifm(Yl, Yh, biort('legall'), qshift('qshift_06'))
assert np.max(np.abs(vec_recon - vec)) < TOLERANCE
def test_perfect_recon():
vec = np.random.rand(630)
Yl, Yh = dtwavexfm(vec)
vec_recon = dtwaveifm(Yl, Yh)
assert np.max(np.abs(vec_recon - vec)) < TOLERANCE
