def test_from_points(arrays):
points = Points(arrays)
assume(not points.are_collinear(tol=1))
# The plane must contain each point.
plane = Plane.from_points(*points)
points = points.set_dimension(plane.dimension)
for point in points:
assert plane.contains_point(point, abs_tol=ATOL)
# The plane of best fit should be the same
# as the plane from three points.
plane_fit = Plane.best_fit(points)
assert plane_fit.is_close(plane, abs_tol=ATOL)
def test_best_fit_plane(data):
n_points = data.draw(st.integers(min_value=3, max_value=5))
points = Points([data.draw(arrays_fixed(3)) for _ in range(n_points)])
assume(not points.are_collinear(tol=ATOL))
plane_fit = Plane.best_fit(points)
# The best fit plane could have a higher dimension than the points
# (e.g., 2D points have a 3D plane of best fit).
# So, we convert the points dimension to that of the best fit plane.
dim_fit = plane_fit.dimension
points = points.set_dimension(dim_fit)
plane = data.draw(planes(dim_fit))
error_plane = plane.sum_squares(points)
error_fit = plane_fit.sum_squares(points)
assert error_fit <= error_plane + ATOL