def test_latin_hypercube_equally_spaced(self):
"""Test that generate_latin_hypercube_points returns properly spaced points.
Sampling from a latin hypercube results in a set of points that in each dimension are drawn
uniformly from sub-intervals of the domain this tests that every sub-interval in each dimension
contains exactly one point.
"""
for domain in self.domains_to_test:
for num_points in self.num_points_to_test:
domain_bounds = domain._domain_bounds
points = generate_latin_hypercube_points(
num_points, domain_bounds)
for dim in xrange(domain.dim):
# This size of each slice
sub_domain_width = domain_bounds[dim].length / float(
num_points)
# Sort in dim dimension
points = sorted(points, key=lambda points: points[dim])
for i, point in enumerate(points):
# This point must fall somewhere within the slice
min_val = domain_bounds[dim].min + sub_domain_width * i
max_val = min_val + sub_domain_width
assert min_val <= point[dim] <= max_val
def test_latin_hypercube_within_domain(self):
"""Test that generate_latin_hypercube_points returns points within the domain."""
for domain in self.domains_to_test:
for num_points in self.num_points_to_test:
points = generate_latin_hypercube_points(num_points, domain._domain_bounds)
for point in points:
assert domain.check_point_inside(point) is True
def test_latin_hypercube_within_domain(self):
"""Test that generate_latin_hypercube_points returns points within the domain."""
for domain in self.domains_to_test:
for num_points in self.num_points_to_test:
points = generate_latin_hypercube_points(num_points, domain._domain_bounds)
for point in points:
assert domain.check_point_inside(point) is True
def generate_uniform_random_points_in_domain(self, num_points, random_source=None):
r"""Generate ``num_points`` on a latin-hypercube (i.e., like a checkerboard).
See python.geometry_utils.generate_latin_hypercube_points for more details.
:param num_points: max number of points to generate
:type num_points: int >= 0
:param random_source: random source producing uniform random numbers (e.g., numpy.random.uniform) (UNUSED)
:type random_source: callable yielding uniform random numbers in [0,1]
:return: uniform random sampling of points from the domain
:rtype: array of float64 with shape (num_points, dim)
"""
# TODO(GH-56): Allow users to pass in a random source.
return generate_latin_hypercube_points(num_points, self._domain_bounds)
def test_latin_hypercube_equally_spaced(self):
"""Test that generate_latin_hypercube_points returns properly spaced points.
Sampling from a latin hypercube results in a set of points that in each dimension are drawn
uniformly from sub-intervals of the domain this tests that every sub-interval in each dimension
contains exactly one point.
"""
for domain in self.domains_to_test:
for num_points in self.num_points_to_test:
domain_bounds = domain._domain_bounds
points = generate_latin_hypercube_points(num_points, domain_bounds)
for dim in xrange(domain.dim):
# This size of each slice
sub_domain_width = domain_bounds[dim].length / float(num_points)
# Sort in dim dimension
points = sorted(points, key=lambda points: points[dim])
for i, point in enumerate(points):
# This point must fall somewhere within the slice
min_val = domain_bounds[dim].min + sub_domain_width * i
max_val = min_val + sub_domain_width
assert min_val <= point[dim] <= max_val
