import numpy as np

from vizier._src.pyvizier.multimetric import hypervolume
from absl.testing import absltest


class HypervolumeTest(absltest.TestCase):

  def testParetoHypervolume(self):
    x = np.random.normal()
    y = np.random.normal()
    points = np.array([[x, y], [y, x]])
    origin = np.array([-1, -1])
    pf = hypervolume.ParetoFrontier(points, origin)
    self.assertAlmostEqual(
        pf.hypervolume(),
        max(2 * (x + 1) * (y + 1) - min(x + 1, y + 1)**2, 0.0),
        delta=0.15)

  def testParetoHypervolumeCumulative(self):
    points = np.random.normal(size=(100, 4))
    origin = np.zeros(4)

    pf = hypervolume.ParetoFrontier(points, origin)
    cumulative_vol = pf.hypervolume(is_cumulative=True)
    self.assertLen(cumulative_vol, len(points))
    for i in range(len(points)):
      if i < len(points) - 1:
        self.assertGreaterEqual(cumulative_vol[i + 1], cumulative_vol[i])
      else:
        self.assertAlmostEqual(cumulative_vol[i], pf.hypervolume())

  def testDimensionMismatchInit(self):
    points = np.array([[2, 1], [1, 2], [0, 0]])
    origin_3d = np.array([-1, -1, 1])
    # Dimension mismatch.
    with self.assertRaisesRegex(ValueError, 'Dimension mismatch'):
      hypervolume.ParetoFrontier(points, origin_3d)

  def testDimensionMismatchHypervolume(self):
    points = np.array([[2, 1], [1, 2], [0, 0]])
    origin_3d = np.array([-1, -1, 1])
    pf = hypervolume.ParetoFrontier(points, origin=np.array([0, 0]))
    # Dimension mismatch.
    with self.assertRaisesRegex(ValueError, 'Dimension mismatch'):
      pf.hypervolume(additional_points=origin_3d[..., np.newaxis])


if __name__ == '__main__':
  absltest.main()

import numpy as np

from vizier._src.pyvizier.multimetric import hypervolume
from absl.testing import absltest


class HypervolumeTest(absltest.TestCase):

  def testParetoHypervolume(self):
    x = np.random.normal()
    y = np.random.normal()
    points = np.array([[x, y], [y, x]])
    origin = np.array([-1, -1])
    pf = hypervolume.ParetoFrontier(points, origin)
    self.assertAlmostEqual(
        pf.hypervolume(),
        max(2 * (x + 1) * (y + 1) - min(x + 1, y + 1)**2, 0.0),
        delta=0.3)

  def testParetoHypervolumeCumulative(self):
    points = np.random.normal(size=(100, 4))
    origin = np.zeros(4)

    pf = hypervolume.ParetoFrontier(points, origin)
    cumulative_vol = pf.hypervolume(is_cumulative=True)
    self.assertLen(cumulative_vol, len(points))
    for i in range(len(points)):
      if i < len(points) - 1:
        self.assertGreaterEqual(cumulative_vol[i + 1], cumulative_vol[i])
      else:
        self.assertAlmostEqual(cumulative_vol[i], pf.hypervolume())

  def testDimensionMismatchInit(self):
    points = np.array([[2, 1], [1, 2], [0, 0]])
    origin_3d = np.array([-1, -1, 1])
    # Dimension mismatch.
    with self.assertRaisesRegex(ValueError, 'Dimension mismatch'):
      hypervolume.ParetoFrontier(points, origin_3d)

  def testDimensionMismatchHypervolume(self):
    points = np.array([[2, 1], [1, 2], [0, 0]])
    origin_3d = np.array([-1, -1, 1])
    pf = hypervolume.ParetoFrontier(points, origin=np.array([0, 0]))
    # Dimension mismatch.
    with self.assertRaisesRegex(ValueError, 'Dimension mismatch'):
      pf.hypervolume(additional_points=origin_3d[..., np.newaxis])


if __name__ == '__main__':
  absltest.main()

Change hypervolume test threshold again