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.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.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_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_opg_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.opg_subspace(X, f, weights) np.testing.assert_array_less(e[1], e[0])
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.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.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)