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