API Documentation
This section provides detailed API documentation for all LINE Solver Python modules.
API Sections:
- Core Modules
- Cache Algorithms
cache_lrum_map_levelstats()cache_t_lrum_map()cache_ttl_lrum_map()cache_erec()cache_erec_aux()cache_prob_erec()cache_cost()cache_cost_pathcheck()cache_mva()cache_spm_size()cache_xi_iter()cache_spm()cache_prob_spm()cache_prob_fpi()cache_miss()cache_xi_fp()cache_miss_fpi()cache_miss_spm()cache_mva_miss()cache_miss_asy()cache_miss_rmf()cache_rmf_lna()cache_miss_sfifo_rmf()cache_miss_fifo_rmf()cache_is()cache_prob_is()cache_miss_is()logmeanexp()cache_t_hlru()cache_ttl_hlru()cache_ttl_lrua()cache_rrm_meanfield_ode()cache_rrm_meanfield()cache_gamma_lp()cache_gamma()
- Loss Networks
- Layered Stochastic Networks
- Markov Chain Utilities
- Matrix-Analytic Methods
- Non-Product-Form Networks
- Polling Systems
- Product-Form Queueing Networks
- Queueing Systems
- Stochastic Network Utilities
- Trace Analysis
- Utilities and Constants
Overview
Core Modules - Networks, nodes, classes, distributions, solvers
Cache Algorithms - Cache performance analysis
Loss Networks - Analysis of networks with blocking
Layered Stochastic Networks - Layered queueing network analysis
Markov Chain Utilities - CTMC and DTMC analysis tools
Matrix-Analytic Methods - QBD processes and matrix-analytic solutions
Non-Product-Form Networks - Approximations for intractable queueing networks
Polling Systems - Analysis of gated, exhaustive, and k-limited polling
Product-Form Queueing Networks - MVA, convolution, and normalizing constant methods
Queueing Systems - Single-station queueing system analysis
Stochastic Network Utilities - Network analysis and transformation utilities
Trace Analysis - Empirical trace characterisation and fitting
Utilities and Constants - Helper functions, constants, and enumerations
Module Locations
Category |
Python Path |
Description |
|---|---|---|
Cache API |
line_solver.api.cache |
Cache analysis algorithms |
Constants |
line_solver.constants |
Enumerations and global constants |
Core |
line_solver.lang |
Network, Node, and JobClass definitions |
Distributions |
line_solver.distributions |
Exp, Erlang, PH, MAP, etc. |
Layered Networks |
line_solver.layered |
LayeredNetwork, Task, Activity |
LossN API |
line_solver.api.lossn |
Loss network algorithms |
LSN API |
line_solver.api.lsn |
Layered stochastic network utilities |
MAM API |
line_solver.api.mam |
Matrix-analytic methods |
MC API |
line_solver.api.mc |
Markov chain analysis |
NPFQN API |
line_solver.api.npfqn |
Non-product-form network approximations |
PFQN API |
line_solver.api.pfqn |
Product-form queueing network algorithms |
Polling API |
line_solver.api.polling |
Polling system algorithms |
Qsys API |
line_solver.api.qsys |
Single queueing system formulas |
SN API |
line_solver.api.sn |
Stochastic network utilities |
Solvers |
line_solver.solvers |
MVA, CTMC, FLD, MAM, etc. |
Trace API |
line_solver.api.trace |
Trace characterisation and fitting |
License
Copyright (c) 2012-2026, QORE Lab, Imperial College London All rights reserved.