diff options
Diffstat (limited to 'test/test_optim.py')
| -rw-r--r-- | test/test_optim.py | 17 |
1 files changed, 7 insertions, 10 deletions
diff --git a/test/test_optim.py b/test/test_optim.py index 41f9cbe..67e9d13 100644 --- a/test/test_optim.py +++ b/test/test_optim.py @@ -32,9 +32,7 @@ def test_conditional_gradient(nx): def fb(G): return 0.5 * nx.sum(G ** 2) - ab = nx.from_numpy(a) - bb = nx.from_numpy(b) - Mb = nx.from_numpy(M, type_as=ab) + ab, bb, Mb = nx.from_numpy(a, b, M) reg = 1e-1 @@ -74,9 +72,7 @@ def test_conditional_gradient_itermax(nx): def fb(G): return 0.5 * nx.sum(G ** 2) - ab = nx.from_numpy(a) - bb = nx.from_numpy(b) - Mb = nx.from_numpy(M, type_as=ab) + ab, bb, Mb = nx.from_numpy(a, b, M) reg = 1e-1 @@ -118,9 +114,7 @@ def test_generalized_conditional_gradient(nx): reg1 = 1e-3 reg2 = 1e-1 - ab = nx.from_numpy(a) - bb = nx.from_numpy(b) - Mb = nx.from_numpy(M, type_as=ab) + ab, bb, Mb = nx.from_numpy(a, b, M) G, log = ot.optim.gcg(a, b, M, reg1, reg2, f, df, verbose=True, log=True) Gb, log = ot.optim.gcg(ab, bb, Mb, reg1, reg2, fb, df, verbose=True, log=True) @@ -142,9 +136,12 @@ def test_line_search_armijo(nx): pk = np.array([[-0.25, 0.25], [0.25, -0.25]]) gfk = np.array([[23.04273441, 23.0449082], [23.04273441, 23.0449082]]) old_fval = -123 + + xkb, pkb, gfkb = nx.from_numpy(xk, pk, gfk) + # Should not throw an exception and return 0. for alpha alpha, a, b = ot.optim.line_search_armijo( - lambda x: 1, nx.from_numpy(xk), nx.from_numpy(pk), nx.from_numpy(gfk), old_fval + lambda x: 1, xkb, pkb, gfkb, old_fval ) alpha_np, anp, bnp = ot.optim.line_search_armijo( lambda x: 1, xk, pk, gfk, old_fval |