R: Riemannian Metrics for Symmetric Positive Definite Matrices

# 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