Package jline.api.infer
Class InferQuickModel
java.lang.Object
jline.api.infer.InferQuickModel
Convenience factory for the single-layer networks the inference estimators fit.
The model is named quickModel and has one Queue QueueStation<i>
per entry of stations, with that discipline and servers[i] servers,
and one class Class<c> per row of demands, served at station i by
Exp.fitMean(demands[c][i]).
OPEN: a Source mySource and a Sink mySink, every class routed
serially Source, QueueStation1, ..., QueueStationM, Sink. No arrival process is
set: the estimators supply it. CLOSED: class c has jobs[c] jobs referenced
at QueueStation1 and follows routing[c] (an M x M station-to-station
matrix) when given, and the cycle 1, 2, ..., M, 1 otherwise.
Port of MATLAB infer_quick_model.m and the Python-native infer_quick_model.
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Method Summary
Modifier and TypeMethodDescriptionstatic Networkinfer_quick_model(boolean isOpen, SchedStrategy[] stations, double[][] demands) Serial routing, one server per station and one job per closed class.static Networkinfer_quick_model(boolean isOpen, SchedStrategy[] stations, double[][] demands, int[] servers, int[] jobs, double[][][] routing)
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Method Details
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infer_quick_model
public static Network infer_quick_model(boolean isOpen, SchedStrategy[] stations, double[][] demands) Serial routing, one server per station and one job per closed class. -
infer_quick_model
public static Network infer_quick_model(boolean isOpen, SchedStrategy[] stations, double[][] demands, int[] servers, int[] jobs, double[][][] routing) - Parameters:
isOpen- true for an open network, false for a closed onestations- (M) scheduling discipline of each queuedemands- (K x M) mean service demand of class c at station iservers- (M) server count per station, or null for one eachjobs- (K) population per closed class, or null for one eachrouting- (K x M x M) per-class station routing of a closed model, or null for serial- Returns:
- the linked network
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