def test_frequent_directions_01(self):
np.random.seed(42)
inputs = np.random.rand(100, 500)
gradients = (inputs[i, :] for i in range(100))
ss = ActiveSubspaces(dim=50, method='exact')
evals, v = ss._frequent_directions(gradients=gradients)
self.assertEqual(v.shape, (500, 50))
self.assertEqual(evals.shape, (50,))
def test_frequent_directions_01(self):
np.random.seed(42)
grad = np.array(
[[-0.50183952, 0, 0, 0, 0, 0 ,0, 0, 0, 0, 0, 0, 0, 0, 0],
[-1.26638196, 0, 0, 0, 0, 0 ,0, 0, 0, 0, 0, 0, 0, 0, 0],
[ 0.43017941, 0, 0, 0, 0, 0 ,0, 0, 0, 0, 0, 0, 0, 0, 0],
[ 0.65008914, 0, 0, 0, 0, 0 ,0, 0, 0, 0, 0, 0, 0, 0, 0]])
gradients = (grad[i, :] for i in range(4))
ss = ActiveSubspaces(dim=2, method='exact', n_boot=150)
evals, v = ss._frequent_directions(gradients=gradients)
self.assertEqual(v.shape, (15, 2))
self.assertEqual(evals.shape, (2,))
