Source code for geomstats.geometry.poincare_half_space

"""The n-dimensional hyperbolic space.

Poincare half-space representation.

Lead author: Alice Le Brigant.

import math

import geomstats.backend as gs
from geomstats.geometry._hyperbolic import HyperbolicDiffeo, _Hyperbolic
from geomstats.geometry.base import VectorSpaceOpenSet
from geomstats.geometry.euclidean import Euclidean
from geomstats.geometry.poincare_ball import PoincareBall
from geomstats.geometry.pullback_metric import PullbackDiffeoMetric
from geomstats.vectorization import repeat_out

[docs] class PoincareHalfSpace(_Hyperbolic, VectorSpaceOpenSet): """Class for the n-dimensional Poincare half-space. Class for the n-dimensional Poincaré half space model. For other representations of hyperbolic spaces see the `Hyperbolic` class. Parameters ---------- dim : int Dimension of the hyperbolic space. """ def __init__(self, dim, equip=True): self.coords_type = "half-space" super().__init__( dim=dim, embedding_space=Euclidean(dim), intrinsic=True, equip=equip, )
[docs] @staticmethod def default_metric(): """Metric to equip the space with if equip is True.""" return PoincareHalfSpaceMetric
[docs] def belongs(self, point, atol=gs.atol): """Evaluate if a point belongs to the upper half space. Parameters ---------- point : array-like, shape=[..., dim] Point to be checked. atol : float Absolute tolerance to evaluate positivity of the last coordinate. Returns ------- belongs : array-like, shape=[...,] Array of booleans indicating whether the corresponding points belong to the upper half space. """ point_dim = point.shape[-1] belongs = point_dim == self.dim return gs.logical_and(belongs, point[..., -1] >= -atol)
[docs] def projection(self, point, atol=gs.atol): """Project a point in ambient space to the open set. The last coordinate is floored to `atol` if it is negative. Parameters ---------- point : array-like, shape=[..., dim_embedding] Point in ambient space. atol : float Tolerance to evaluate positivity. Returns ------- projected : array-like, shape=[..., dim_embedding] Projected point. """ last = gs.where(point[..., -1] < atol, atol, point[..., -1]) return gs.concatenate([point[..., :-1], last[..., None]], axis=-1)
[docs] class PoincareHalfSpaceMetric(PullbackDiffeoMetric): """Class for the metric of the n-dimensional hyperbolic space. Class for the metric of the n-dimensional hyperbolic space as embedded in the Poincaré half space model. """ def __init__(self, space): image_space = PoincareBall(dim=space.dim) super().__init__( space=space, image_space=image_space, diffeo=HyperbolicDiffeo(space.coords_type, image_space.coords_type), )
[docs] def inner_product(self, tangent_vec_a, tangent_vec_b, base_point): """Compute the inner-product of two tangent vectors at a base point. Parameters ---------- tangent_vec_a : array-like, shape=[..., dim + 1] First tangent vector at base point. tangent_vec_b : array-like, shape=[..., dim + 1] Second tangent vector at base point. base_point : array-like, shape=[..., dim + 1] Point in hyperbolic space. Returns ------- inner_prod : array-like, shape=[..., 1] Inner-product of the two tangent vectors. """ inner_prod = gs.sum(tangent_vec_a * tangent_vec_b, axis=-1) return inner_prod / base_point[..., -1] ** 2
[docs] def injectivity_radius(self, base_point=None): """Compute the radius of the injectivity domain. This is is the supremum of radii r for which the exponential map is a diffeomorphism from the open ball of radius r centered at the base point onto its image. In the case of the hyperbolic space, it does not depend on the base point and is infinite everywhere, because of the negative curvature. Parameters ---------- base_point : array-like, shape=[..., dim] Point on the manifold. Returns ------- radius : array-like, shape=[...,] Injectivity radius. """ radius = gs.array(math.inf) return repeat_out(self._space.point_ndim, radius, base_point)