def test_proj_simplex(size, z):
rng = np.random.RandomState(0)
v = rng.rand(size)
w = project_simplex(v, z=z)
w2 = project_simplex_bisection(v, z=z, max_iter=100)
np.testing.assert_array_almost_equal(w, w2, 3)
def test_proj_simplex():
rng = np.random.RandomState(0)
v = rng.rand(100)
w = project_simplex(v, z=10)
w2 = project_simplex_bisection(v, z=10, max_iter=100)
assert_array_almost_equal(w, w2, 3)
v = rng.rand(3)
w = project_simplex(v, z=1)
w2 = project_simplex_bisection(v, z=1, max_iter=100)
assert_array_almost_equal(w, w2, 3)
v = rng.rand(2)
w = project_simplex(v, z=1)
w2 = project_simplex_bisection(v, z=1, max_iter=100)
assert_array_almost_equal(w, w2, 3)
def test_proj_simplex():
rng = np.random.RandomState(0)
v = rng.rand(100)
w = project_simplex(v, z=10)
w2 = project_simplex_bisection(v, z=10, max_iter=100)
assert_array_almost_equal(w, w2, 3)
v = rng.rand(3)
w = project_simplex(v, z=1)
w2 = project_simplex_bisection(v, z=1, max_iter=100)
assert_array_almost_equal(w, w2, 3)
v = rng.rand(2)
w = project_simplex(v, z=1)
w2 = project_simplex_bisection(v, z=1, max_iter=100)
assert_array_almost_equal(w, w2, 3)
def test_fista_regression_simplex():
rng = np.random.RandomState(0)
w = project_simplex(rng.rand(10))
X = rng.randn(1000, 10)
y = np.dot(X, w)
reg = FistaRegressor(penalty="simplex", max_iter=100, verbose=0)
reg.fit(X, y)
y_pred = reg.predict(X)
error = np.sqrt(np.mean((y - y_pred)**2))
assert_almost_equal(error, 0.000, 3)
assert_true(np.all(reg.coef_ >= 0))
assert_almost_equal(np.sum(reg.coef_), 1.0, 3)
def test_fista_regression_simplex():
rng = np.random.RandomState(0)
w = project_simplex(rng.rand(10))
X = rng.randn(1000, 10)
y = np.dot(X, w)
reg = FistaRegressor(penalty="simplex", max_iter=100, verbose=0)
reg.fit(X, y)
y_pred = reg.predict(X)
error = np.sqrt(np.mean((y - y_pred) ** 2))
assert_almost_equal(error, 0.000, 3)
assert_true(np.all(reg.coef_ >= 0))
assert_almost_equal(np.sum(reg.coef_), 1.0, 3)
def test_fista_regression_l1_ball():
rng = np.random.RandomState(0)
alpha = 5.0
w = project_simplex(rng.randn(10), alpha)
X = rng.randn(1000, 10)
y = np.dot(X, w)
reg = FistaRegressor(penalty="l1-ball", alpha=alpha, max_iter=100, verbose=0)
reg.fit(X, y)
y_pred = reg.predict(X)
error = np.sqrt(np.mean((y - y_pred) ** 2))
np.testing.assert_almost_equal(error, 0.000, 3)
np.testing.assert_almost_equal(np.sum(np.abs(reg.coef_)), alpha, 3)
def test_fista_regression_l1_ball():
rng = np.random.RandomState(0)
alpha = 5.0
w = project_simplex(rng.randn(10), alpha)
X = rng.randn(1000, 10)
y = np.dot(X, w)
reg = FistaRegressor(penalty="l1-ball", alpha=alpha, max_iter=100, verbose=0)
reg.fit(X, y)
y_pred = reg.predict(X)
error = np.sqrt(np.mean((y - y_pred) ** 2))
assert_almost_equal(error, 0.000, 3)
assert_almost_equal(np.sum(np.abs(reg.coef_)), alpha, 3)