def test_siso_ynext_derivatives(self):
mdl = Linear(N=2, M=2)
dy, du, dparams = mdl.derivatives(y=[1, 2],
u=[2, 3],
params=[10, 20, 30, 40])
assert_array_almost_equal(dy, [[[10], [20]]])
assert_array_almost_equal(du, [[[30], [40]]])
assert_array_almost_equal(dparams, [[1, 2, 2, 3]])
def test_fir_model_derivatives(self):
mdl = Linear(N=0, M=2, Ny=1, Nu=1)
y = []
u = [2, 1]
params = [1, 2]
dy, du, dparams = mdl.derivatives(y, u, params)
assert_array_almost_equal(du, [[[1], [2]]])
assert_array_almost_equal(dy, np.reshape([], (1, 0, 1)))
assert_array_almost_equal(dparams, [[2, 1]])
def test_ar_model_derivatives(self):
mdl = Linear(N=3, M=0, Ny=1, Nu=0)
y = [1, 2, 3]
u = []
params = [1, 2, 3]
dy, du, dparams = mdl.derivatives(y, u, params)
assert_array_almost_equal(dy, [[[1], [2], [3]]])
assert_array_almost_equal(du, np.reshape([], (1, 0, 0)))
assert_array_almost_equal(dparams, [[1, 2, 3]])
def test_tito_ynext_derivatives(self):
mdl = Linear(N=2, M=2, Ny=2, Nu=2)
y = [[1, 2], [2, 3]]
u = [[2, 3], [3, 4]]
dy, du, dparams = mdl.derivatives(
y=y,
u=u,
params=[10, 20, 0, 0, 0, 0, 50, 60, 30, 40, 0, 0, 0, 0, 70, 80])
assert_array_almost_equal(dy, [[[10, 20], [0, 0]], [[0, 0], [50, 60]]])
assert_array_almost_equal(du, [[[30, 40], [0, 0]], [[0, 0], [70, 80]]])
assert_array_almost_equal(
dparams, [[1, 2, 2, 3, 0, 0, 0, 0, 2, 3, 3, 4, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 2, 2, 3, 0, 0, 0, 0, 2, 3, 3, 4]])
def test_fir_model_numerical_derivatives(self):
mdl = Linear(N=0, M=2, Ny=1, Nu=1)
y = []
u = [2, 1]
params = [1, 2]
dy, du, dparams = mdl.derivatives(y, u, params)
dy_numeric, du_numeric, \
dparams_numeric = mdl._numeric_derivatives(y, u, params)
assert_array_almost_equal(dy, dy_numeric)
assert_array_almost_equal(du, du_numeric)
assert_array_almost_equal(dparams, dparams_numeric)
def test_siso_numerical_approx(self):
# Define model
N = 2
M = 2
Ny = 1
Nu = 1
mdl = Linear(N, M)
Nparams = mdl.Nparams
# Define ynext and derivatives
y = np.array([1.23, 2.41])
u = np.array([2.54, 23])
params = [1, 5.46, 3.23, 4]
dy, du, dparams = mdl.derivatives(y, u, params)
# Compute the same derivatives numerically
dy_numeric, du_numeric, \
dparams_numeric = mdl._numeric_derivatives(y, u,
params)
# Check
assert_array_almost_equal(dy, dy_numeric)
assert_array_almost_equal(du, du_numeric)
assert_array_almost_equal(dparams, dparams_numeric)
def test_mimo_numerical_approx_twoinputs_threeoutputs(self):
# Define model
N = 3
M = 2
Ny = 2
Nu = 3
mdl = Linear(N, M, Ny, Nu)
Nparams = mdl.Nparams
# Define ynext and derivatives
y = np.array([[12, 2.41], [3, 1.23], [2.41, 5]])
u = np.array([[4.5, 6.4, 10], [2.23, 2.41, 521]])
params = np.arange(Nparams)
dy, du, dparams = mdl.derivatives(y, u, params)
# Compute the same derivatives numerically
dy_numeric, du_numeric, \
dparams_numeric = mdl._numeric_derivatives(y, u,
params)
# Check
assert_array_almost_equal(dy, dy_numeric)
assert_array_almost_equal(du, du_numeric)
assert_array_almost_equal(dparams, dparams_numeric)
