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294 lines
7.4 KiB
294 lines
7.4 KiB
//==============================================================================
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//
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// Copyright (c) 2002-
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// Authors:
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// * Dave Parker <david.parker@comlab.ox.ac.uk> (University of Oxford)
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//
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//------------------------------------------------------------------------------
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//
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// This file is part of PRISM.
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//
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// PRISM is free software; you can redistribute it and/or modify
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// it under the terms of the GNU General Public License as published by
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// the Free Software Foundation; either version 2 of the License, or
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// (at your option) any later version.
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//
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// PRISM is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU General Public License
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// along with PRISM; if not, write to the Free Software Foundation,
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// Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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//
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//==============================================================================
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package simulator;
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import java.util.*;
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import parser.*;
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import prism.*;
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public class TransitionList
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{
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private ArrayList<Choice> choices = new ArrayList<Choice>();
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private ArrayList<Integer> transitionIndices = new ArrayList<Integer>();
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private ArrayList<Integer> transitionOffsets = new ArrayList<Integer>();
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private int numChoices = 0;
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private int numTransitions = 0;
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private double probSum = 0.0;
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// TODO: document this
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public class Ref
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{
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public int i;
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public int offset;
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//int index;
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//Choice ch;
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}
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public void clear()
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{
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choices.clear();
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transitionIndices.clear();
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transitionOffsets.clear();
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numChoices = 0;
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numTransitions = 0;
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probSum = 0.0;
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}
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public void add(Choice tr)
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{
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int i, n;
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choices.add(tr);
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n = tr.size();
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for (i = 0; i < n; i++) {
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transitionIndices.add(choices.size() - 1);
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transitionOffsets.add(i);
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}
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numChoices++;
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numTransitions += tr.size();
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probSum += tr.getProbabilitySum();
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}
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/**
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* Check the validity of the available transitions for a given model type.
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* Throw a PrismExecption if an error is found.
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*/
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public void checkValid(ModelType modelType) throws PrismException
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{
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for (Choice ch : choices) {
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ch.checkValid(modelType);
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}
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}
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// ACCESSORS
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/**
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* Get the number of choices.
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*/
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public int getNumChoices()
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{
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return numChoices;
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}
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/**
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* Get the number of transitions.
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*/
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public int getNumTransitions()
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{
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return numTransitions;
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}
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/**
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* Get the total sum of all probabilities (or rates).
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*/
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public double getProbabilitySum()
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{
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return probSum;
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}
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// Get access to Choice objects
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/**
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* Get the ith choice.
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*/
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public Choice getChoice(int i)
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{
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return choices.get(i);
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}
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/**
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* Get the choice containing a transition of a given index.
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*/
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public Choice getChoiceOfTransition(int index)
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{
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return choices.get(transitionIndices.get(index));
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}
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// Get index/offset info
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/**
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* Get the index of the choice containing a transition of a given index.
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*/
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public int getChoiceIndexOfTransition(int index)
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{
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return transitionIndices.get(index);
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}
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/**
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* Get the offset of a transition within its containing choice.
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*/
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public int getChoiceOffsetOfTransition(int index)
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{
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return transitionOffsets.get(index);
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}
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/**
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* Get the (total) index of a transition from the index of its containing choice and its offset within it.
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*/
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public int getTotalIndexOfTransition(int i, int offset)
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{
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return transitionOffsets.get(i);
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}
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// Random selection of a choice
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/**
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* Get a reference to a transition according to a total probability (rate) sum, x.
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* i.e.the first transition for which the sum of probabilities of all prior transitions
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* (across all choices) exceeds x.
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* Note: this only really makes sense for models where these are rates, rather than probabilities.
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* @param x Probability (or rate) sum
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* @param ref Empty transition reference to store result
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*/
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public void getChoiceIndexByProbabilitySum(double x, Ref ref)
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{
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int i;
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Choice choice;
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double d = 0.0, tot = 0.0;
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// Add up choice prob/rate sums to find choice
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for (i = 0; x >= tot && i < numChoices; i++) {
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d = getChoice(i).getProbabilitySum();
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tot += d;
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}
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ref.i = i - 1;
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// Pick transition within choice
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choice = getChoice(i - 1);
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if (choice.size() > 1) {
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ref.offset = choice.getIndexByProbabilitySum(x - (tot - d));
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} else {
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ref.offset = 0;
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}
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}
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// Direct access to transition info
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/**
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* Get a string describing the action/module of a transition, specified by its index.
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*/
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public String getTransitionModuleOrAction(int index)
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{
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return getChoiceOfTransition(index).getModuleOrAction();
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}
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/**
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* Get the probability/rate of a transition, specified by its index.
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*/
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public double getTransitionProbability(int index)
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{
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return getChoiceOfTransition(index).getProbability(transitionOffsets.get(index));
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}
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/**
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* Get a string describing the updates making up a transition, specified by its index.
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* This is in abbreviated form, i.e. x'=1, rather than x'=x+1.
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* Format is: x'=1, y'=0, with empty string for empty update.
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* Only variables updated are included in list (even if unchanged).
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*/
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public String getTransitionUpdateString(int index, State currentState) throws PrismLangException
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{
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return getChoiceOfTransition(index).getUpdateString(transitionOffsets.get(index), currentState);
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}
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/**
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* Get a string describing the updates making up a transition, specified by its index.
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* This is in full, i.e. of the form x'=x+1, rather than x'=1.
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* Format is: (x'=x+1) & (y'=y-1), with empty string for empty update.
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* Only variables updated are included in list.
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* Note that expressions may have been simplified from original model.
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*/
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public String getTransitionUpdateStringFull(int index)
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{
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return getChoiceOfTransition(index).getUpdateStringFull(transitionOffsets.get(index));
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}
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/**
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* Get the target of a transition (as a new State object), specified by its index.
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*/
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public State computeTransitionTarget(int index, State currentState) throws PrismLangException
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{
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return getChoiceOfTransition(index).computeTarget(transitionOffsets.get(index), currentState);
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}
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/**
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* Is there a deadlock (i.e. no available transitions)?
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*/
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public boolean isDeadlock()
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{
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return numChoices == 0;
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}
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/**
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* Are the choices deterministic? (i.e. a single probability 1.0 transition)
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*/
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public boolean isDeterministic()
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{
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return numTransitions == 1 && getChoice(0).getProbability(0) == 1.0;
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}
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/**
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* Is there a deterministic self-loop, i.e. do all transitions go to the current state.
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*/
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public boolean isDeterministicSelfLoop(State currentState)
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{
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// TODO: make more efficient, and also limit calls to it
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// (e.g. only if already stayed in state twice?)
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int i, n;
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State newState = new State(currentState);
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try {
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for (Choice ch : choices) {
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n = ch.size();
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for (i = 0; i < n; i++) {
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ch.computeTarget(i, currentState, newState);
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if (!currentState.equals(newState)) {
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// Found a non-loop
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return false;
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}
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}
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}
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} catch (PrismLangException e) {
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// If anything goes wrong when evaluating, just return false.
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return false;
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}
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// All targets loop
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return true;
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}
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@Override
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public String toString()
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{
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String s = "";
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boolean first = true;
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for (Choice ch : choices) {
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if (first)
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first = false;
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else
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s += ", ";
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s += ch.toString();
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}
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return s;
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}
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}
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