def test_fit(self):
""" Make sure updates occur in the Tikhanov Factors"""
rcomp = ResComp(**RES)
t, U = make_data()
rcomp.update_tikhanov_factors(t, U)
assert not np.all(rcomp.Rhat == 0.0)
assert not np.all(rcomp.Yhat == 0.0)
def test_predict_unseen(self):
""" Predict on unseen data """
rcomp = ResComp(**RES)
tr, ts, Utr, Uts = make_train_test_data()
rcomp.train(tr, Utr, window=10, overlap=0.9)
pre = rcomp.predict(ts, Uts[0, :])
error = np.mean(np.linalg.norm(pre - Uts, ord=2, axis=0)**2)**(1/2)
assert error < 1.0
def test_predict(self):
""" Test that the reservoir can learn a simple signal"""
rcomp = ResComp(**RES)
t, U = make_data()
rcomp.train(t, U)
pre = rcomp.predict(t[500:], U[500, :])
error = np.max(np.linalg.norm(pre - U[500:, :], ord=np.inf, axis=0))
assert error < 0.5
def test_drive(self):
""" Drive the internal ode """
t, U = make_data()
rcomp = ResComp(**RES)
r0 = rcomp.W_in @ U[0, :]
out = rcomp.internal_state_response(t, U, r0)
m, n = out.shape
assert m == len(t) and n == rcomp.res_sz
def test_window(self):
""" Make sure each partition is smaller than the given time window """
rcomp = ResComp(**RES)
for window in [.5, 3, 1001]:
for timef in [random_time_array, uniform_time_array]:
times = timef(1000)
idxs = rcomp._partition(times, window, 0)
for i,j in idxs:
sub = times[i:j]
assert sub[-1] - sub[0] <= window + 1e-12
def test_init_args(self):
combos = itertools.product(*ADJCOMBOS.values())
keys = list(PARAMCOMBOS.keys())
for args in combos:
I, prms = identity_adj(*args)
rcomp = ResComp(I)
assert params_match(rcomp, keys, prms)
A, prms = nonuniform_adj(*args)
rcomp = ResComp(A)
assert params_match(rcomp, keys, prms)
def test_overlap(self):
""" Ensure that overlap is correct on average """
rcomp = ResComp(**RES)
for window in [30, 100]:
for overlap in [.1, .9,]:
T = 1000
for times in [random_time_array(T), uniform_time_array(T)]:
idxs = rcomp._partition(times, window, overlap)
prev = None
over = 0.0
for i,j in idxs:
sub = times[i:j]
if prev is not None:
inters = set(sub).intersection(set(prev))
over += len(inters) / len(sub)
prev = sub
assert np.abs(over/len(idxs) - overlap) < .05
def test_init_noargs(self):
kwargs = dict()
combos = itertools.product(*PARAMCOMBOS.values())
keys = list(PARAMCOMBOS.keys())
for c in combos:
# For each combination of parameters, make a dictionary of kwargs
for k, v in zip(keys, c):
kwargs[k] = v
# Initialize a reservoir computer
rcomp = ResComp(**kwargs)
# Check that the initialized rcomp has the right internal data
assert params_match(rcomp, keys, c)
def test_jacobian(self):
kwargs = dict()
combos = itertools.product(*PARAMCOMBOS.values())
keys = list(PARAMCOMBOS.keys())
for c in combos:
# For each combination of parameters, make a dictionary of kwargs
for k, v in zip(keys, c):
kwargs[k] = v
# Initialize a reservoir computer
kwargs["res_sz"] = 10
rcomp = ResComp(**kwargs)
# Check that the initialized rcomp has the correct jacobian
err = jacobian_err(rcomp)
assert err < 1e-8 , print("\n", kwargs, "Jacobian err:", err)