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' ' ' ' . . . . & & & &r0r__graph__rules __clause_maps __node_facts __edge_facts__ipl__specific_node_labels__specific_edge_labels__non_fluent_graph_facts_node__non_fluent_graph_facts_edge__specific_graph_node_labels__specific_graph_edge_labels __programcSqSq[b[R5 Sq[b[R 5 [ 5 g)ztResets certain variables to None to be able to do pr.reason() multiple times in a program without memory blowing up N)rrr reset_factsr reset_graph reset_rulesrr0r-r*r*s@LLGMr0c[$)z Returns the rules )rrr0r- get_rulesrs  Nr0cHSq/q/q[b[R 5 gg)z Resets rules to none N)r__annotation_functions__head_functionsrrrr0r-rrs, Gr0c,[R5 g)z Resets settings to default N)settingsr*rr0r-reset_settingsr s NNr0pathr5c [RU[R5q[R (a)[R [R5uqq q q g[RRR[ R"5q[RRR[$R"5q [RR&R)[*R,[R.R1[R.R25S9q [RR&R)[*R,[R.R1[R.R5[R.R2[R.R2455S9q g)zXLoads graph from GraphMl file path into program :param path: Path for the GraphMl file key_type value_typeN)__graphml_parser parse_graphrrJrrAparse_graph_attributesr_rrrrnumbatypedr empty_list fact_node fact_type fact_edgeDictemptylabel label_typetypesListTypestringrrs r- load_graphmlrs**41I1IJG''DTDkDkltlGlGDH A%'DFbeA(- (8(8(C(CIDWDW(X%(- (8(8(C(CIDWDW(X%',{{'7'7'='=uGWGWdidododxdxy~zEzEzLzLeM'=(N$',{{'7'7'='=uGWGWdidododxdxy~zEzEzKzKMRMXMXM_M_afalalasasLtzuev'=(w$r0graphc [RU5q[R(a)[R [R 5uqqq q g[RRR[R 5q[RRR["R 5q[RR$R'[(R*[R,R/[R,R05S9q [RR$R'[(R*[R,R/[R,R3[R,R0[R,R0455S9q g)zLoad a networkx DiGraph into pyreason :param graph: Networkx DiGraph object to load into pyreason :type graph: nx.DiGraph :return: None rN)r load_graphrrrArr_rrrrrrrrrrrrrrrrrrr)rs r-rr&s))%0G''DTDkDkltlGlGDH A%'DFbeA(- (8(8(C(CIDWDW(X%(- (8(8(C(CIDWDW(X%',{{'7'7'='=uGWGWdidododxdxy~zEzEzLzLeM'=(N$',{{'7'7'='=uGWGWdidododxdxy~zEzEzKzKMRMXMXM_M_afalalasasLtzuev'=(w$r0c0[R"U5qg)zSLoad IPL from YAML file path into program :param path: Path for the YAML IPL file N) yaml_parser parse_iplrrs r- load_inconsistent_predicate_listr<s  ! !$ 'Er0pred1pred2cX[cd[RRR [R R [R[R455q[R[R"U5[R"U545 g)zAdd an inconsistent predicate pair to the IPL :param pred1: First predicate in the inconsistent pair :param pred2: Second predicate in the inconsistent pair N) rrrrrrrrrappendLabel)rrs r-add_inconsistent_predicaterEsg }   ++EKK,=,=u?O?OQVQaQa>b,cd LL%++e$ekk%&89:r0pr_rulecJ[c7[RRR [ R 5qUR R5c+UR RS[[535 [RUR 5 g)z_Add a rule to pyreason from text format. 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If reasoning again, this is the number of timesteps to reason for extra (no zero timestep), defaults to -1 :param convergence_threshold: Maximum number of interpretations that have changed between timesteps or fixed point operations until considered convergent. Program will end at convergence. -1 => no changes, perfect convergence, defaults to -1 :param convergence_bound_threshold: Maximum change in any interpretation (bounds) between timesteps or fixed point operations until considered convergent, defaults to -1 :param queries: A list of PyReason query objects that can be used to filter the ruleset based on the query. Default is None :param again: Whether to reason again on an existing interpretation, defaults to False :param restart: Whether to restart the program time from 0 when reasoning again, defaults to True :return: The final interpretation after reasoning. z %Y%m%d-%H%M%S./_.txtaT) max_usage)rretvalz Program used z MB of memory)timestrftime __timestamprr:rr>sysstdoutrrGmp memory_usage_reasonprint _reason_again) rrrrrr start_mem mem_usageinterps r-reasonr+s@--0KBx889;-tLcR I%  " "$7I "9]x;C1DPT]a!b I OI$7#8 F G MY?ZdF M  " "$7I "UjAI1JVZcg!h I OI$7#8 F G M#97LjF Mr0c [R(a.[S[RS[S3S5[ l[cI[[R"55 [R(a[R"S5 [c [S5e[ c7["R$R&R)[*R,5q[.c7["R$R&R)[0R,5q[2cd["R$R&R)["R4R7[8R:[8R:455q["R$R<R?[8R:["R4RA["R4RB5S9q"["R$R<R?[8R:["R4RA["R4R7["R4RB["R4RB455S9q#[HRK5H2upEU[D;a[DURMU5 M)U[DU'M4 [NRK5H2upFU[F;a[FURMU5 M)U[FU'M4 ["R$R&R)[*R,5n["R$R&R)[0R,5nURM["R$R'[ 55 URM["R$R'[.55 URM[P5 URM[R5 [RT(d S[l+[Y[Z5n [Y[\5n [R(a [_S 5 Ub[`Rb"U[5q[V V s0sHDoRe5[g[iU Rk555V s0sHoU _M sn _MF sn n q6[i[Rn5[i[Rp5:a[R(a [_S 5 [Rs5n ["R$R&R)[tRv5q[yU 5H=up[{U 5un [lU Re5'[R}U 5 M? 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B [[%%001D1DEN[[%%001D1DEN%++**<89%++**<897878  0 0#!!78+,N 01 //A^ee]dXY__&uS=Q7R(S7R!A7R(SS]deM 7==C ..    Q R||~ ++""--dnn=l+DA2A!2D /A}Q__./ NN1 , %QewxPxPRZReRegogNgNPXPcPcemeAeACKChChjrjEjEGOG[G[]e]x]xzBzMzMNI%;I"%;I"%%iHcemeueuvNLL -)Tes/8[(' [#3[(#[(c [cS5e[RRR [ R 5n[RRR [R 5nUR[RR[55 UR[RR[55 [RXX#XE[R5nU$)Nz;To run `reason_again` you need to have reasoned once before)rrrrrrrrr3rr reason_againrr7)rrrrr?r@rDs r-r'r'$s  _"__ [[%%001D1DEN[[%%001D1DEN%++**<89%++**<89++I@UuCU]UeUefN r0folderc[R(dS5e[[[5nUR X5 g)aaSaves the trace of the program. This includes every change that has occurred to the interpretation. If `atom_trace` was set to true this gives us full explainability of why interpretations changed :param interpretation: the output of `pyreason.reason()`, the final interpretation :param folder: the folder in which to save the result, defaults to './' Gstore interpretation changes setting is off, turn on to save rule traceN)rrcrr rsave_rule_trace)rDrGoutputs r-rJrJ4s3  0 0{2{{ 0 K /F >2r0c[R(dS5e[[[5nUR U5$)aReturns the trace of the program as 2 pandas dataframes (one for nodes, one for edges). This includes every change that has occurred to the interpretation. If `atom_trace` was set to true this gives us full explainability of why interpretations changed :param interpretation: the output of `pyreason.reason()`, the final interpretation :returns two pandas dataframes (nodes, edges) representing the changes that occurred during reasoning rI)rrcrr rget_rule_trace)rDrKs r-rMrMAs6  0 0{2{{ 0 K /F   00r0lowerlabelsrsort_by descendingc[R(dS5e[UR5nUR XX#U5nU$)aFilters and sorts the node changes in the interpretation and returns as a list of Pandas dataframes that are easy to access :param interpretation: the output of `pyreason.reason()`, the final interpretation :param labels: A list of strings, labels that are in the interpretation that are to be filtered :param bound: The bound that will filter any interpretation that is not in it. the default does not filter anything, defaults to interval.closed(0,1) :param sort_by: String that is either 'lower' or 'upper', sorts by the lower/upper bound, defaults to 'lower' :param descending: A bool that sorts by descending/ascending order, defaults to True :return: A list of Pandas dataframes that contain the filtered and sorted interpretations that are easy to access zMstore interpretation changes setting is off, turn on to filter and sort nodes)rrcr rfilter_and_sort_nodesrDrPrrQrRfilterer filtered_dfs r-rTrTOM  0 0B3BB 0n))*H00YcdK r0c[R(dS5e[UR5nUR XX#U5nU$)aFilters and sorts the edge changes in the interpretation and returns as a list of Pandas dataframes that are easy to access :param interpretation: the output of `pyreason.reason()`, the final interpretation :param labels: A list of strings, labels that are in the interpretation that are to be filtered :param bound: The bound that will filter any interpretation that is not in it. the default does not filter anything, defaults to interval.closed(0,1) :param sort_by: String that is either 'lower' or 'upper', sorts by the lower/upper bound, defaults to 'lower' :param descending: A bool that sorts by descending/ascending order, defaults to True :return: A list of Pandas dataframes that contain the filtered and sorted interpretations that are easy to access zMstore interpretation changes setting is off, turn on to filter and sort edges)rrcr rfilter_and_sort_edgesrUs r-rZrZ_rXr0)F)r[r[NFT)r)v importlibnetworkxr-rrr!pandaspdmemory_profilerr#r/typingrrrrrpyreason.scripts.utils.outputrpyreason.scripts.utils.filterr pyreason.scripts.program.programr %pyreason.scripts.utils.graphml_parserr "pyreason.scripts.utils.yaml_parserscriptsutilsr"pyreason.scripts.utils.rule_parser rule_parser%pyreason.scripts.utils.filter_rulesetr6r55pyreason.scripts.numba_wrapper.numba_types.label_type numba_wrapper numba_typesrr4pyreason.scripts.numba_wrapper.numba_types.rule_typerrpyreason.scripts.facts.factr pyreason.scripts.rules.ruler $pyreason.scripts.threshold.thresholdrpyreason.scripts.query.queryr9pyreason.scripts.numba_wrapper.numba_types.fact_node_typefact_node_typer9pyreason.scripts.numba_wrapper.numba_types.fact_edge_typefact_edge_typer8pyreason.scripts.numba_wrapper.numba_types.interval_type interval_typeinterval&pyreason.scripts.utils.reorder_clausesrutil find_spec3pyreason.scripts.learning.classification.classifierr/pyreason.scripts.learning.utils.model_interfacerr&rrr.__annotations__rrrdictrrrrrrrrrrrr rrrr*rrrr{rrrrrrurr rrintfloatr+r%r'rJ DataFramerMclosedIntervalrTrZrr0r-rs 88004?8888>>EECC,,:.MMMMKKB >>G$0]U $  AB ]&]&B !%"** $&*%++"" #* $ x~$+/ hu{{''(/+/ hu{{''(/$(x   !(59!1!12959!1!129<@x (8(89@<@x (8(89@;?hu{{'7'78?;?hu{{'7'78? # 8G # ? ;*  wswtw(wbjjwTw,(3(4( ;c ;# ;$ ; !d !t ! @3@T@d@"DT2 ,h ,4 , & &T &"c"s"^c"swx}s~"OS"fj"JVr  3C 3 1eBLL",,,F&G 1W_VeVefghiVjzATX $s) HDUDU ux OS  W_VeVefghiVjzATX $s) HDUDU ux OS r0