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319 lines
10 KiB
319 lines
10 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, formerly University of Birmingham)
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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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// includes
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#include "PrismSparse.h"
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#include <math.h>
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#include <util.h>
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#include <cudd.h>
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#include <dd.h>
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#include <odd.h>
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#include <dv.h>
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#include "sparse.h"
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#include "PrismSparseGlob.h"
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#include "jnipointer.h"
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//------------------------------------------------------------------------------
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JNIEXPORT jlong __jlongpointer JNICALL Java_sparse_PrismSparse_PS_1NondetReachReward
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(
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JNIEnv *env,
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jclass cls,
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jlong __jlongpointer t, // trans matrix
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jlong __jlongpointer sr, // state rewards
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jlong __jlongpointer trr, // transition rewards
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jlong __jlongpointer od, // odd
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jlong __jlongpointer rv, // row vars
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jint num_rvars,
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jlong __jlongpointer cv, // col vars
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jint num_cvars,
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jlong __jlongpointer ndv, // nondet vars
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jint num_ndvars,
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jlong __jlongpointer g, // 'goal' states
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jlong __jlongpointer in, // 'inf' states
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jlong __jlongpointer m, // 'maybe' states
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jboolean min // min or max probabilities (true = min, false = max)
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)
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{
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// cast function parameters
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DdNode *trans = jlong_to_DdNode(t); // trans matrix
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DdNode *state_rewards = jlong_to_DdNode(sr); // state rewards
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DdNode *trans_rewards = jlong_to_DdNode(trr); // transition rewards
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ODDNode *odd = jlong_to_ODDNode(od); // reachable states
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DdNode **rvars = jlong_to_DdNode_array(rv); // row vars
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DdNode **cvars = jlong_to_DdNode_array(cv); // col vars
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DdNode **ndvars = jlong_to_DdNode_array(ndv); // nondet vars
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DdNode *goal = jlong_to_DdNode(g); // 'goal' states
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DdNode *inf = jlong_to_DdNode(in); // 'inf' states
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DdNode *maybe = jlong_to_DdNode(m); // 'maybe' states
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// mtbdds
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DdNode *a;
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// model stats
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int n, nc, nc_r;
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long nnz, nnz_r;
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// sparse matrix
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NDSparseMatrix *ndsm, *ndsm_r;
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// vectors
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double *sr_vec, *soln, *soln2, *tmpsoln, *inf_vec;
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// timing stuff
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long start1, start2, start3, stop;
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double time_taken, time_for_setup, time_for_iters;
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// adversary stuff
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bool adv = true, adv_loop = false;
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FILE *fp_adv = NULL;
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int adv_l, adv_h;
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// misc
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int i, j, k, k_r, l1, h1, l2, h2, l2_r, h2_r, iters;
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double d1, d2, kb, kbt;
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bool done, first;
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// start clocks
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start1 = start2 = util_cpu_time();
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// get number of states
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n = odd->eoff + odd->toff;
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// filter out rows (goal states and infinity states) from matrix
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Cudd_Ref(trans);
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Cudd_Ref(maybe);
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a = DD_Apply(ddman, APPLY_TIMES, trans, maybe);
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// also remove goal and infinity states from state rewards vector
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Cudd_Ref(state_rewards);
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Cudd_Ref(maybe);
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state_rewards = DD_Apply(ddman, APPLY_TIMES, state_rewards, maybe);
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// and from transition rewards matrix
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Cudd_Ref(trans_rewards);
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Cudd_Ref(maybe);
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trans_rewards = DD_Apply(ddman, APPLY_TIMES, trans_rewards, maybe);
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// build sparse matrix (probs)
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PS_PrintToMainLog(env, "\nBuilding sparse matrix (transitions)... ");
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ndsm = build_nd_sparse_matrix(ddman, a, rvars, cvars, num_rvars, ndvars, num_ndvars, odd);
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// get number of transitions/choices
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nnz = ndsm->nnz;
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nc = ndsm->nc;
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// print out info
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PS_PrintToMainLog(env, "[n=%d, nc=%d, nnz=%d, k=%d] ", n, nc, nnz, ndsm->k);
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kb = (nnz*12.0+nc*4.0+n*4.0)/1024.0;
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kbt = kb;
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PS_PrintToMainLog(env, "[%.1f KB]\n", kb);
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// build sparse matrix (rewards)
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PS_PrintToMainLog(env, "Building sparse matrix (transition rewards)... ");
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ndsm_r = build_sub_nd_sparse_matrix(ddman, a, trans_rewards, rvars, cvars, num_rvars, ndvars, num_ndvars, odd);
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// get number of transitions/choices
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nnz_r = ndsm_r->nnz;
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nc_r = ndsm_r->nc;
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// print out info
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PS_PrintToMainLog(env, "[n=%d, nc=%d, nnz=%d, k=%d] ", n, nc_r, nnz_r, ndsm_r->k);
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kb = (nnz_r*12.0+nc_r*4.0+n*4.0)/1024.0;
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kbt += kb;
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PS_PrintToMainLog(env, "[%.1f KB]\n", kb);
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// get vector for state rewards
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PS_PrintToMainLog(env, "Creating vector for state rewards... ");
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sr_vec = mtbdd_to_double_vector(ddman, state_rewards, rvars, num_rvars, odd);
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kb = n*8.0/1024.0;
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kbt += kb;
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PS_PrintToMainLog(env, "[%.1f KB]\n", kb);
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// create solution/iteration vectors
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PS_PrintToMainLog(env, "Allocating iteration vectors... ");
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soln = new double[n];
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soln2 = new double[n];
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kb = n*8.0/1024.0;
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kbt += 2*kb;
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PS_PrintToMainLog(env, "[2 x %.1f KB]\n", kb);
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// print total memory usage
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PS_PrintToMainLog(env, "TOTAL: [%.1f KB]\n", kbt);
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// initial solution is zero
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for (i = 0; i < n; i++) {
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soln[i] = 0;
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}
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// get setup time
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stop = util_cpu_time();
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time_for_setup = (double)(stop - start2)/1000;
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start2 = stop;
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// start iterations
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iters = 0;
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done = false;
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PS_PrintToMainLog(env, "\nStarting iterations...\n");
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// open file to store adversary (if required)
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if (adv) {
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fp_adv = fopen("adv.tra", "w");
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fprintf(fp_adv, "%d ?\n", n);
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}
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while ((!done && iters < max_iters) || adv_loop) {
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iters++;
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// PS_PrintToMainLog(env, "iter %d\n", iters);
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// start3 = util_cpu_time();
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// store local copies of stuff
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// firstly for transition matrix
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double *non_zeros = ndsm->non_zeros;
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unsigned char *row_counts = ndsm->row_counts;
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int *row_starts = (int *)ndsm->row_counts;
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unsigned char *choice_counts = ndsm->choice_counts;
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int *choice_starts = (int *)ndsm->choice_counts;
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bool use_counts = ndsm->use_counts;
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unsigned int *cols = ndsm->cols;
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// and then for transition rewards matrix
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// (note: we don't need row_counts/row_starts for
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// this since choice structure mirrors transition matrix)
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double *non_zeros_r = ndsm_r->non_zeros;
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unsigned char *choice_counts_r = ndsm_r->choice_counts;
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int *choice_starts_r = (int *)ndsm_r->choice_counts;
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bool use_counts_r = ndsm_r->use_counts;
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unsigned int *cols_r = ndsm_r->cols;
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// do matrix multiplication and min/max
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h1 = h2 = h2_r = 0;
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// loop through states
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for (i = 0; i < n; i++) {
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d1 = 0.0;
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first = true;
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// get pointers to nondeterministic choices for state i
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if (!use_counts) { l1 = row_starts[i]; h1 = row_starts[i+1]; }
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else { l1 = h1; h1 += row_counts[i]; }
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// loop through those choices
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for (j = l1; j < h1; j++) {
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// compute the reward value for state i for this iteration
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// start with state reward for this state
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d2 = sr_vec[i];
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// get pointers to transitions
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if (!use_counts) { l2 = choice_starts[j]; h2 = choice_starts[j+1]; }
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else { l2 = h2; h2 += choice_counts[j]; }
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// and get pointers to transition rewards
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if (!use_counts_r) { l2_r = choice_starts_r[j]; h2_r = choice_starts_r[j+1]; }
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else { l2_r = h2_r; h2_r += choice_counts_r[j]; }
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// loop through transitions
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for (k = l2; k < h2; k++) {
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// find corresponding transition reward if any
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k_r = l2_r; while (k_r < h2_r && cols_r[k_r] != cols[k]) k_r++;
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// if there is one, add reward * prob to reward value
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if (k_r < h2_r) { d2 += non_zeros_r[k_r] * non_zeros[k]; k_r++; }
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// add prob * corresponding reward from previous iteration
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d2 += non_zeros[k] * soln[cols[k]];
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}
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// see if this value is the min/max so far
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if (first || min&&(d2<d1) || !min&&(d2>d1)) {
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d1 = d2;
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if (adv_loop) { adv_l = l2; adv_h = h2; }
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}
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first = false;
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}
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// set vector element
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// (if there were no choices from this state, reward is zero)
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soln2[i] = (h1 > l1) ? d1 : 0;
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// store adversary info (if required)
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if (adv_loop) if (h1 > l1)
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for (k = adv_l; k < adv_h; k++) fprintf(fp_adv, "%d %d %g\n", i, cols[k], non_zeros[k]);
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}
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// check convergence
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// (note: doing outside loop means may not need to check all elements)
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switch (term_crit) {
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case TERM_CRIT_ABSOLUTE:
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done = true;
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for (i = 0; i < n; i++) {
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if (fabs(soln2[i] - soln[i]) > term_crit_param) {
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done = false;
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break;
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}
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}
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break;
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case TERM_CRIT_RELATIVE:
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done = true;
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for (i = 0; i < n; i++) {
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if (fabs(soln2[i] - soln[i])/soln2[i] > term_crit_param) {
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done = false;
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break;
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}
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}
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break;
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}
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// prepare for next iteration
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tmpsoln = soln;
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soln = soln2;
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soln2 = tmpsoln;
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// if we're done, but adversary generation is required, go round once more
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if (done && adv) adv_loop = !adv_loop;
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// PS_PrintToMainLog(env, "%.2f %.2f sec\n", ((double)(util_cpu_time() - start3)/1000), ((double)(util_cpu_time() - start2)/1000)/iters);
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}
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// stop clocks
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stop = util_cpu_time();
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time_for_iters = (double)(stop - start2)/1000;
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time_taken = (double)(stop - start1)/1000;
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// print iterations/timing info
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PS_PrintToMainLog(env, "\nIterative method: %d iterations in %.2f seconds (average %.6f, setup %.2f)\n", iters, time_taken, time_for_iters/iters, time_for_setup);
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// set reward for infinity states to infinity
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if (soln != NULL) {
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// first, generate vector for inf
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inf_vec = mtbdd_to_double_vector(ddman, inf, rvars, num_rvars, odd);
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// go thru setting elements of soln to infinity
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for (i = 0; i < n; i++) if (inf_vec[i] > 0) soln[i] = HUGE_VAL;
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}
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// close file to store adversary (if required)
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if (adv) {
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fclose(fp_adv);
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}
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// free memory
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Cudd_RecursiveDeref(ddman, a);
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Cudd_RecursiveDeref(ddman, state_rewards);
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Cudd_RecursiveDeref(ddman, trans_rewards);
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free_nd_sparse_matrix(ndsm);
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free_nd_sparse_matrix(ndsm_r);
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delete sr_vec;
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delete soln2;
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// if the iterative method didn't terminate, this is an error
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if (!done) { delete soln; PS_SetErrorMessage("Iterative method did not converge within %d iterations.\nConsider using a different numerical method or increasing the maximum number of iterations", iters); return 0; }
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return ptr_to_jlong(soln);
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}
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//------------------------------------------------------------------------------
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