geometry.manifolds.euclidean.Euclidean

class geometry.manifolds.euclidean.Euclidean(dimension)[source]

This is the usual Euclidean space of finite dimension; this is mostly used for debugging.

There is no proper Haar measure; as an arbitrary choice, the sample_uniform() returns a sample from a Gaussian distribution centered at 0.

Methods

assert_close(a, b[, atol, msg]) Asserts that two points on the manifold are close to the given tolerance.
distance(a, b) Computes the geodesic distance between two points.
embed_in(M, my_point) Embeds a point on this manifold to the target manifold M.
friendly(a) Returns a friendly description string for a point on the manifold.
from_yaml(yaml_structure) Recovers a value from a Yaml structure.
geodesic(a, b, t) Returns the point interpolated along the geodesic.
get_dimension() Returns the intrinsic dimension of this manifold.
norm(v) Return the norm of a vector in the algebra.
project_from(M, his_point) Projects a point on a bigger manifold to this manifold.
tangent_bundle() Returns the manifold corresponding to the tangent bundle.
zero() Returns the zero element for this algebra.
belongs  
belongs_ts  
can_convert_to  
can_represent  
convert_to  
embeddable_in  
embedding  
expmap  
interesting_points  
isomorphism  
logmap  
normalize  
project  
project_to  
project_ts  
relations_descriptions  
riemannian_mean  
sample_uniform  
to_yaml  
belongs(x)[source]

Raises an Exception if the point does not belong to this manifold.

This function wraps some checks around belongs_(), which is implemented by the subclasses.

interesting_points()[source]

Returns a list of “interesting points” on this manifold that should be used for testing various properties.

normalize(a)[source]

Normalizes the coordinates to the canonical representation for this manifold. See TorusW.

project(x)[source]

Projects a vector onto this Lie Algebra.

riemannian_mean(points)[source]

TODO: work out exceptions

sample_uniform()[source]