API Documentation
This section provides detailed API documentation for all LINE Solver Python modules.
API Sections:
- Core Modules
- Cache Algorithms
cache_erec()cache_erec_aux()cache_prob_erec()cache_mva()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_is()cache_prob_is()cache_miss_is()logmeanexp()cache_t_lrum()cache_t_hlru()cache_ttl_lrum()cache_ttl_hlru()cache_ttl_lrua()cache_rrm_meanfield_ode()cache_rrm_meanfield()cache_gamma_lp()
- Loss Networks
- Layered Stochastic Networks
- Markov Chain Utilities
- Matrix-Analytic Methods
map_infgen()map_piq()map_pie()map_lambda()map_mean()map_var()map_scv()map_moment()map_scale()map_normalize()map_isfeasible()exp_map()erlang_map()hyperexp_map()map_exponential()map_erlang()map_hyperexp()map_gamma()map_sumind()map_cdf()map_pdf()map_sample()map_skew()map_kurt()map_acf()map_acfc()map_idc()map_count_mean()map_count_var()map_varcount()map_count_moment()map_mmpp2()map_gamma2()map_rand()map_randn()map_renewal()map_embedded()map_sum()map_super()map_mixture()map_max()map_timereverse()map_mark()map_stochcomp()map_kpc()map_bernstein()map_pntiter()map_pntquad()map2_fit()map_joint()map_issym()map_feastol()map_feasblock()map_block()map_largemap()mmap_infgen()mmap_normalize()mmap_super_safe()mmap_mark()mmap_scale()mmap_hide()mmap_compress()mmap_exponential()mmap_issym()mmap_isfeasible()mmap_lambda()mmap_count_lambda()mmap_pie()mmap_pc()mmap_embedded()mmap_sample()mmap_rand()mmap_timereverse()mmap_sum()mmap_super()mmap_mixture()mmap_max()mmap_maps()mmap_count_mean()mmap_count_var()mmap_count_idc()mmap_count_mcov()mmap_idc()mmap_sigma()mmap_sigma2()mmap_forward_moment()mmap_backward_moment()mmap_cross_moment()mmap_modulate()ldqbd()LdqbdResultLdqbdOptionsMAPBMAP1Resultsolver_mam_map_bmap_1()BMAPMAP1Resultsolver_mam_bmap_map_1()QBDResultqbd_R()qbd_R_logred()qbd_rg()qbd_blocks_mapmap1()qbd_bmapbmap1()qbd_mapmap1()qbd_raprap1()qbd_setupdelayoff()map_ccdf_derivative()map_jointpdf_derivative()map_factorial_moment()map_joint_moment()map_m1ps_cdf_respt()map_compute_R()map_m1ps_h_recursive()map_m1ps_sojourn()mmdp_isfeasible()
- Non-Product-Form Networks
- Polling Systems
- Product-Form Queueing Networks
pfqn_mva()pfqn_mva_single_class()pfqn_bs()pfqn_aql()pfqn_sqni()pfqn_qd()pfqn_qdlin()pfqn_qli()pfqn_fli()pfqn_bsfcfs()pfqn_joint()pfqn_ca()pfqn_nc()pfqn_panacea()pfqn_propfair()pfqn_ls()pfqn_linearizer()pfqn_gflinearizer()pfqn_egflinearizer()SchedStrategypfqn_mvald()pfqn_mvams()pfqn_mvamx()pfqn_xzabalow()pfqn_xzabaup()pfqn_qzgblow()pfqn_qzgbup()pfqn_xzgsblow()pfqn_xzgsbup()pfqn_le()pfqn_cub()pfqn_mci()pfqn_grnmol()pfqn_le_fpi()pfqn_le_fpiZ()pfqn_le_hessian()pfqn_le_hessianZ()pfqn_ncld()pfqn_gld()pfqn_gldsingle()pfqn_mushift()pfqn_comomrm_ld()pfqn_fnc()PfqnNcResultPfqnComomrmLdResultPfqnFncResultpfqn_unique()pfqn_expand()pfqn_combine_mi()PfqnUniqueResultpfqn_lldfun()pfqn_mu_ms()pfqn_nc_sanitize()pfqn_cdfun()pfqn_ljdfun()factln()factln_vec()softmin()oner()multichoose()matchrow()pfqn_comom()pfqn_comomrm()pfqn_comomrm_orig()pfqn_comomrm_ms()pfqn_procomom2()ComomResultpfqn_mmint2()pfqn_mmint2_gausslegendre()pfqn_mmint2_gausslaguerre()pfqn_mmsample2()logsumexp()pfqn_schmidt()pfqn_schmidt_ext()SchmidtResultpprod()hashpop()pfqn_recal()pfqn_mvaldmx()pfqn_mvaldmx_ec()pfqn_mvaldms()pfqn_linearizerms()pfqn_linearizermx()pfqn_conwayms()ljd_linearize()ljd_delinearize()ljcd_interpolate()infradius_h()infradius_hnorm()pfqn_kt()pfqn_ab_amva()pfqn_ab_core()AbAmvaResultpfqn_rd()RdOptionsRdResultpfqn_nrl()pfqn_nrp()pfqn_lap()laplaceapprox()num_hess()pfqn_stdf()pfqn_stdf_heur()
- Queueing Systems
qsys_mapdc()qsys_mapd1()qsys_mm1()qsys_mmk()qsys_mg1()qsys_gm1()qsys_mminf()qsys_mginf()qsys_gig1_approx_allencunneen()qsys_gig1_approx_kingman()qsys_gig1_approx_marchal()qsys_gig1_approx_whitt()qsys_gig1_approx_heyman()qsys_gig1_approx_kobayashi()qsys_gig1_approx_gelenbe()qsys_gig1_approx_kimura()qsys_gigk_approx()qsys_gig1_ubnd_kingman()qsys_gigk_approx_kingman()qsys_mg1_prio()qsys_mg1_srpt()qsys_mg1_fb()qsys_mg1_lrpt()qsys_mg1_psjf()qsys_mg1_setf()qsys_mm1k_loss()qsys_mg1k_loss()qsys_mg1k_loss_mgs()qsys_mxm1()QueueResultph_to_map()qsys_phph1()qsys_mapph1()qsys_mapm1()qsys_mapmc()qsys_mapmap1()qsys_mapg1()QueueTypeBmapMatrixPhDistributionQbdStatespaceRetrialQueueResultRetrialQueueAnalyzerqsys_bmapphnn_retrial()qsys_is_retrial()RetrialInfo
- Stochastic Network Utilities
MatrixArrayNetworkStructNodeTypeSchedStrategyRoutingStrategyDropStrategysn_get_demands_chain()SnGetDemandsResultsn_deaggregate_chain_results()SnDeaggregateResultProductFormParamssn_get_product_form_params()sn_get_residt_from_respt()sn_get_state_aggr()sn_set_arrival()sn_set_service()sn_set_servers()sn_set_population()sn_set_priority()sn_set_routing()sn_refresh_visits()sn_set_fork_fanout()sn_set_service_batch()sn_nonmarkov_toph()ChainParamssn_get_arvr_from_tput()sn_get_node_arvr_from_tput()sn_get_node_tput_from_tput()sn_get_product_form_chain_params()sn_set_routing_prob()sn_is_closed_model()sn_is_open_model()sn_is_mixed_model()sn_is_population_model()sn_has_closed_classes()sn_has_open_classes()sn_has_mixed_classes()sn_has_single_class()sn_has_multi_class()sn_has_multiple_closed_classes()sn_has_single_chain()sn_has_multi_chain()sn_has_fcfs()sn_has_ps()sn_has_inf()sn_has_lcfs()sn_has_lcfspr()sn_has_lcfs_pi()sn_has_siro()sn_has_dps()sn_has_dps_prio()sn_has_gps()sn_has_gps_prio()sn_has_ps_prio()sn_has_hol()sn_has_lps()sn_has_setf()sn_has_sept()sn_has_lept()sn_has_sjf()sn_has_ljf()sn_has_polling()sn_has_homogeneous_scheduling()sn_has_multi_class_fcfs()sn_has_multi_class_heter_fcfs()sn_has_multi_class_heter_exp_fcfs()sn_has_multi_server()sn_has_load_dependence()sn_has_joint_dependence()sn_has_fork_join()sn_has_priorities()sn_has_class_switching()sn_has_fractional_populations()sn_has_sd_routing()sn_has_product_form()sn_has_product_form_not_het_fcfs()sn_has_product_form_except_multi_class_heter_exp_fcfs()sn_is_state_valid()sn_print()sn_print_routing_matrix()sn_refresh_process_fields()sn_rtnodes_to_rtorig()
- 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
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. |
License
Copyright (c) 2012-2026, QORE Lab, Imperial College London All rights reserved.