mlpg_c

Maximum Likelihood Parameter Generation (MLPG) implementation in C for Python

Install

pip install mlpg_c

Usage of mlpg_solve

from mlpg_c import mlpg_c as mlpg

param_gen = mlpg.mlpg_solve(jnt_sd_mat, prec_vec, coef_vec)

Variable desc.

param_gen: generated parameter trajectory: T x dim

jnt_sd_mat: joint static-delta feature vector sequence: T x (dim*2)

prec_vec: vector of diagonal precision (inverse covariance) matrix: (dim*2) x 1

coef_vec: vector of delta coefficients: n_coeff x 1. e.g.: [-0.5,0.5,0.0]

Usage of mlpg_solve_seq

from mlpg_c import mlpg_c as mlpg

param_gen = mlpg.mlpg_solve_seq(jnt_sd_mat, prec_mat, coef_vec)

Variable desc.

param_gen: generated parameter trajectory: T x dim

jnt_sd_mat: joint static-delta feature vector sequence: T x (dim*2)

prec_mat: sequence of diagonal precision (inverse covariance) matrices: T x (dim*2)

coef_vec: vector of delta coefficients: n_coeff x 1, e.g.: [-0.5,0.5,0.0]

To-do:

• demo
• full precision matrix
• docs