def test_sinusoid_wrong_not_scalar_offset():
t_init = 0
T = 5.
A = 1.5
time = np.linspace(0, 10, 11)
var = np.ones_like(time)
offset = var
with pytest.raises(TypeError) as excinfo:
sinusoid(t_init, T, A, time, offset=offset)
def test_sinusoid_wrong_not_scalar_offset():
t_init = 0
T = 5.
A = 1.5
time = np.linspace(0, 10, 11)
var = np.ones_like(time)
offset = var
with pytest.raises(TypeError) as excinfo:
sinusoid(t_init, T, A, time, offset=offset)
def test_sinusoid_wrong_size_var():
t_init = 0
T = 5.
A = 1.5
time = np.linspace(0, 10, 11)
var = np.ones([10])
with pytest.raises(ValueError) as excinfo:
sinusoid(t_init, T, A, time, offset=0, var=var)
assert ("ValueError: var and time must have the same size"
in excinfo.exconly())
def test_sinusoid_wrong_size_var():
t_init = 0
T = 5.
A = 1.5
time = np.linspace(0, 10, 11)
var = np.ones([10])
with pytest.raises(ValueError) as excinfo:
sinusoid(t_init, T, A, time, offset=0, var=var)
assert ("ValueError: var and time must have the same size"
in excinfo.exconly())
def test_sinusoid():
t_init = 0
T = 4.
A = 3.
time = np.linspace(0, 10, 11)
expected_input = np.zeros([11])
expected_input[0:5] = np.array([0, A / 2, 0, -A / 2, 0])
sinusoid_input = sinusoid(t_init, T, A, time)
assert_almost_equal(sinusoid_input, expected_input)
def test_sinusoid():
t_init = 0
T = 4.
A = 3.
time = np.linspace(0, 10, 11)
expected_input = np.zeros([11])
expected_input[0:5] = np.array([0, A/2, 0, -A/2, 0])
sinusoid_input = sinusoid(t_init, T, A, time)
assert_almost_equal(sinusoid_input, expected_input)
def test_sinusoid_phase():
t_init = 0
T = 4.
A = 3.
time = np.linspace(0, 10, 11)
phase = np.pi / 2
expected_input = np.zeros([11])
expected_input[0:5] += np.array([A / 2, 0, -A / 2, 0, A / 2])
sinusoid_input = sinusoid(t_init, T, A, time, phase=phase)
assert_almost_equal(sinusoid_input, expected_input)
def test_sinusoid_offset():
t_init = 0
T = 4.
A = 3.
time = np.linspace(0, 10, 11)
offset = 1
expected_input = np.zeros([11]) + offset
expected_input[0:5] += np.array([0, A / 2, 0, -A / 2, 0])
sinusoid_input = sinusoid(t_init, T, A, time, offset=offset)
assert_almost_equal(sinusoid_input, expected_input)
def test_sinusoid_phase():
t_init = 0
T = 4.
A = 3.
time = np.linspace(0, 10, 11)
phase= np.pi/2
expected_input = np.zeros([11])
expected_input[0:5] += np.array([A/2, 0, -A/2, 0, A/2])
sinusoid_input = sinusoid(t_init, T, A, time, phase=phase)
assert_almost_equal(sinusoid_input, expected_input)
def test_sinusoid_offset():
t_init = 0
T = 4.
A = 3.
time = np.linspace(0, 10, 11)
offset = 1
expected_input = np.zeros([11]) + offset
expected_input[0:5] += np.array([0, A/2, 0, -A/2, 0])
sinusoid_input = sinusoid(t_init, T, A, time, offset=offset)
assert_almost_equal(sinusoid_input, expected_input)
def test_sinusoid_var():
t_init = 0
T = 4.
A = 3.
time = np.linspace(0, 10, 11)
var = np.ones_like(time)
var[0::2] = -1
expected_input = var.copy()
expected_input[0:5] += np.array([0, A / 2, 0, -A / 2, 0])
sinusoid_input = sinusoid(t_init, T, A, time, offset=0, var=var)
assert_almost_equal(sinusoid_input, expected_input)
def test_sinusoid_var():
t_init = 0
T = 4.
A = 3.
time = np.linspace(0, 10, 11)
var = np.ones_like(time)
var[0::2] = -1
expected_input = var.copy()
expected_input[0:5] += np.array([0, A/2, 0, -A/2, 0])
sinusoid_input = sinusoid(t_init, T, A, time, offset=0, var=var)
assert_almost_equal(sinusoid_input, expected_input)
