Riemannian Metrics for Symmetric Positive Definite Matrices

---

Documentation for package ‘riemtan’ version 0.2.5

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

airm	Pre-configured Riemannian metrics for SPD matrices
airm_exp	Compute the AIRM Exponential
airm_log	Compute the AIRM Logarithm
airm_unvec	Compute the Inverse Vectorization (AIRM)
airm_vec	Compute the AIRM Vectorization of Tangent Space
bures_wasserstein	Pre-configured Riemannian metrics for SPD matrices
bures_wasserstein_exp	Compute the Bures-Wasserstein Exponential
bures_wasserstein_log	Compute the Bures-Wasserstein Logarithm
bures_wasserstein_unvec	Compute the Bures-Wasserstein Inverse Vectorization
bures_wasserstein_vec	Compute the Bures-Wasserstein Vectorization
compute_frechet_mean	Compute the Frechet Mean
configure_progress	Configure Progress Handlers
create_parquet_backend	Create ParquetBackend from Directory
CSample	CSample Class
CSuperSample	CSuperSample Class
default_ref_pt	Default reference point
dexp	Differential of Matrix Exponential Map
dlog	Differential of Matrix Logarithm Map
euclidean	Pre-configured Riemannian metrics for SPD matrices
euclidean_exp	Compute the Euclidean Exponential
euclidean_log	Compute the Euclidean Logarithm
euclidean_unvec	Compute the Inverse Vectorization (Euclidean)
euclidean_vec	Vectorize at Identity Matrix (Euclidean)
get_n_workers	Get Current Number of Parallel Workers
half_underscore	Half-underscore operation for use in the log-Cholesky metric
id_matr	Create an Identity Matrix
is_parallel_enabled	Check if Parallel Processing is Enabled
is_progress_available	Check if Progress Reporting is Available
ListBackend	ListBackend Class
log_cholesky	Pre-configured Riemannian metrics for SPD matrices
log_cholesky_exp	Compute the Log-Cholesky Exponential
log_cholesky_log	Compute the Log-Cholesky Logarithm
log_cholesky_unvec	Compute the Log-Cholesky Inverse Vectorization
log_cholesky_vec	Compute the Log-Cholesky Vectorization
log_euclidean	Pre-configured Riemannian metrics for SPD matrices
log_euclidean_exp	Compute the Log-Euclidean Exponential
log_euclidean_log	Compute the Log-Euclidean Logarithm
log_euclidean_unvec	Compute the Inverse Vectorization (Euclidean)
log_euclidean_vec	Vectorize at Identity Matrix (Euclidean)
metric	Metric Object Constructor
metrics	Pre-configured Riemannian metrics for SPD matrices
parallel_config	Parallel Processing Configuration for riemtan
ParquetBackend	ParquetBackend Class
progress_utils	Progress Reporting Utilities for riemtan
relocate	Relocate Tangent Representations to a New Reference Point
reset_parallel_plan	Reset Parallel Plan to Sequential
rspdnorm	Generate Random Samples from a Riemannian Normal Distribution
safe_logm	Wrapper for the matrix logarithm
set_parallel_plan	Set Parallel Processing Plan
should_parallelize	Decide Whether to Use Parallel Processing
spd_isometry_from_identity	Reverse isometry from tangent space at identity to tangent space at P
spd_isometry_to_identity	Isometry from tangent space at P to tangent space at identity
TangentImageHandler	TangentImageHandler Class
validate_backend	Validate Backend Object
validate_conns	Validate Connections
validate_exp_args	Validate arguments for Riemannian logarithms
validate_log_args	Validate arguments for Riemannian logarithms
validate_metric	Validate Metric
validate_parquet_dir	Validate Parquet Directory Structure
validate_parquet_directory	Validate Parquet Directory
validate_tan_imgs	Validate Tangent Images
validate_unvec_args	Validate arguments for inverse vectorization
validate_vec_args	Validate arguments for vectorization
validate_vec_imgs	Validate Vector Images
vec_at_id	Vectorize at Identity Matrix
write_connectomes_to_parquet	Write Connectomes to Parquet Files