Package index • riemtan

All functions

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_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_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_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_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

airm log_euclidean euclidean log_cholesky bures_wasserstein: 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