def test_bootstrap_ranges(self):
np.random.seed(42)
X = np.random.normal(size=(50,3))
f = np.random.normal(size=(50,1))
df = np.random.normal(size=(50,3))
weights = np.ones((50,1)) / 50
e, W = ss.active_subspace(df, weights)
ssmethod = lambda X, f, df, weights: ss.active_subspace(df, weights)
d = ss.bootstrap_ranges(e, W, None, None, df, weights, ssmethod, nboot=10)
e, W = ss.normalized_active_subspace(df, weights)
ssmethod = lambda X, f, df, weights: ss.normalized_active_subspace(df, weights)
d = ss.bootstrap_ranges(e, W, None, None, df, weights, ssmethod, nboot=10)
e, W = ss.active_subspace_x(X, df, weights)
ssmethod = lambda X, f, df, weights: ss.active_subspace_x(X, df, weights)
d = ss.bootstrap_ranges(e, W, X, None, df, weights, ssmethod, nboot=10)
e, W = ss.normalized_active_subspace(df, weights)
ssmethod = lambda X, f, df, weights: ss.normalized_active_subspace(df, weights)
d = ss.bootstrap_ranges(e, W, None, None, df, weights, ssmethod, nboot=10)
e, W = ss.swarm_subspace(X, f, weights)
ssmethod = lambda X, f, df, weights: ss.swarm_subspace(X, f, weights)
d = ss.bootstrap_ranges(e, W, X, f, None, weights, ssmethod, nboot=10)
e, W = ss.ols_subspace(X, f, weights)
ssmethod = lambda X, f, df, weights: ss.ols_subspace(X, f, weights)
d = ss.bootstrap_ranges(e, W, X, f, None, weights, ssmethod, nboot=10)
e, W = ss.qphd_subspace(X, f, weights)
ssmethod = lambda X, f, df, weights: ss.qphd_subspace(X, f, weights)
d = ss.bootstrap_ranges(e, W, X, f, None, weights, ssmethod, nboot=10)
e, W = ss.sir_subspace(X, f, weights)
ssmethod = lambda X, f, df, weights: ss.sir_subspace(X, f, weights)
d = ss.bootstrap_ranges(e, W, X, f, None, weights, ssmethod, nboot=10)
e, W = ss.phd_subspace(X, f, weights)
ssmethod = lambda X, f, df, weights: ss.phd_subspace(X, f, weights)
d = ss.bootstrap_ranges(e, W, X, f, None, weights, ssmethod, nboot=10)
e, W = ss.save_subspace(X, f, weights)
ssmethod = lambda X, f, df, weights: ss.save_subspace(X, f, weights)
d = ss.bootstrap_ranges(e, W, X, f, None, weights, ssmethod, nboot=10)
#### UNDER CONSTRUCTION
#e, W = ss.mave_subspace(X, f, weights)
#ssmethod = lambda X, f, df, weights: ss.mave_subspace(X, f, weights)
#d = ss.bootstrap_ranges(e, W, X, f, None, weights, ssmethod, nboot=10)
e, W = ss.opg_subspace(X, f, weights)
ssmethod = lambda X, f, df, weights: ss.opg_subspace(X, f, weights)
d = ss.bootstrap_ranges(e, W, X, f, None, weights, ssmethod, nboot=10)
def test_phd_subspace(self):
np.random.seed(42)
X = np.random.normal(size=(50,3))
f = np.random.normal(size=(50,1))
weights = np.ones((50,1)) / 50
e, W = ss.phd_subspace(X, f, weights)
np.testing.assert_array_less(e[1], e[0])
np.testing.assert_array_less(np.zeros((3,)), W[0,:])