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//==============================================================================
//
// Copyright (c) 2002-
// Authors:
// * Dave Parker <david.parker@comlab.ox.ac.uk> (University of Oxford, formerly University of Birmingham)
//
//------------------------------------------------------------------------------
//
// This file is part of PRISM.
//
// PRISM is free software; you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation; either version 2 of the License, or
// (at your option) any later version.
//
// PRISM is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with PRISM; if not, write to the Free Software Foundation,
// Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
//
//==============================================================================
// includes
#include "PrismHybrid.h"
#include <math.h>
#include <util.h>
#include <cudd.h>
#include <dd.h>
#include <odd.h>
#include <dv.h>
#include "sparse.h"
#include "hybrid.h"
#include "PrismHybridGlob.h"
#include "jnipointer.h"
#include "prism.h"
#include <new>
// local prototypes
static void mult_rec(HDDNode *hdd, int level, int row_offset, int col_offset, int code);
static void mult_rm(RMSparseMatrix *rmsm, int row_offset, int col_offset, int code);
static void mult_cmsr(CMSRSparseMatrix *cmsrsm, int row_offset, int col_offset, int code);
// globals (used by local functions)
static HDDNode *zero;
static int num_levels;
static bool compact_sm;
static double *sm_dist;
static int sm_dist_shift;
static int sm_dist_mask;
static double *soln = NULL, *soln2 = NULL, *soln3 = NULL;
//------------------------------------------------------------------------------
JNIEXPORT jlong __jlongpointer JNICALL Java_hybrid_PrismHybrid_PH_1NondetReachReward
(
JNIEnv *env,
jclass cls,
jlong __jlongpointer t, // trans matrix
jlong __jlongpointer sr, // state rewards
jlong __jlongpointer trr, // transition rewards
jlong __jlongpointer od, // odd
jlong __jlongpointer rv, // row vars
jint num_rvars,
jlong __jlongpointer cv, // col vars
jint num_cvars,
jlong __jlongpointer ndv, // nondet vars
jint num_ndvars,
jlong __jlongpointer g, // 'goal' states
jlong __jlongpointer in, // 'inf' states
jlong __jlongpointer m, // 'maybe' states
jboolean min // min or max probabilities (true = min, false = max)
)
{
// cast function parameters
DdNode *trans = jlong_to_DdNode(t); // trans matrix
DdNode *state_rewards = jlong_to_DdNode(sr); // state rewards
DdNode *trans_rewards = jlong_to_DdNode(trr); // transition rewards
ODDNode *odd = jlong_to_ODDNode(od); // reachable states
DdNode **rvars = jlong_to_DdNode_array(rv); // row vars
DdNode **cvars = jlong_to_DdNode_array(cv); // col vars
DdNode **ndvars = jlong_to_DdNode_array(ndv); // nondet vars
DdNode *goal = jlong_to_DdNode(g); // 'goal' states
DdNode *inf = jlong_to_DdNode(in); // 'inf' states
DdNode *maybe = jlong_to_DdNode(m); // 'maybe' states
// mtbdds
DdNode *reach = NULL, *a = NULL;
// model stats
int n, nm;
// flags
bool compact_r;
// hybrid stuff
HDDMatrices *hddms = NULL, *hddms2 = NULL;
HDDMatrix *hddm = NULL;
HDDNode *hdd = NULL;
// vectors
double *rew_vec = NULL, *tmpsoln = NULL;
DistVector *rew_dist = NULL;
// timing stuff
long start1, start2, start3, stop;
double time_taken, time_for_setup, time_for_iters;
// misc
int i, j, k, iters;
double d, x, sup_norm, kb, kbt;
bool done;
// exception handling around whole function
try {
// start clocks
start1 = start2 = util_cpu_time();
// get number of states
n = odd->eoff + odd->toff;
// get reachable states
reach = odd->dd;
// filter out rows (goal states and infinity states) from matrix
Cudd_Ref(trans);
Cudd_Ref(maybe);
a = DD_Apply(ddman, APPLY_TIMES, trans, maybe);
// build hdds for matrix
PH_PrintToMainLog(env, "\nBuilding hybrid MTBDD matrices... ");
hddms = build_hdd_matrices_mdp(a, NULL, rvars, cvars, num_rvars, ndvars, num_ndvars, odd);
nm = hddms->nm;
kb = hddms->mem_nodes;
kbt = kb;
PH_PrintToMainLog(env, "[nm=%d, levels=%d, nodes=%d] ", hddms->nm, hddms->num_levels, hddms->num_nodes);
PH_PrintMemoryToMainLog(env, "[", kb, "]\n");
// add sparse bits
PH_PrintToMainLog(env, "Adding sparse bits... ");
add_sparse_matrices_mdp(hddms, compact);
kb = hddms->mem_sm;
kbt += kb;
PH_PrintToMainLog(env, "[levels=%d-%d, num=%d, compact=%d/%d] ", hddms->l_sm_min, hddms->l_sm_max, hddms->num_sm, hddms->compact_sm, hddms->nm);
PH_PrintMemoryToMainLog(env, "[", kb, "]\n");
// multiply transition rewards by transition probs and sum rows
// (note also filters out unwanted states at the same time)
Cudd_Ref(trans_rewards);
Cudd_Ref(a);
trans_rewards = DD_Apply(ddman, APPLY_TIMES, trans_rewards, a);
trans_rewards = DD_SumAbstract(ddman, trans_rewards, cvars, num_cvars);
trans_rewards = DD_Apply(ddman, APPLY_TIMES, trans_rewards, DD_SetVectorElement(ddman, DD_Constant(ddman, 0), cvars, num_cvars, 0, 1));
// build hdds for transition rewards matrix
PH_PrintToMainLog(env, "Building hybrid MTBDD matrices for rewards... ");
hddms2 = build_hdd_matrices_mdp(trans_rewards, hddms, rvars, cvars, num_rvars, ndvars, num_ndvars, odd);
kb = hddms2->mem_nodes;
kbt = kb;
PH_PrintToMainLog(env, "[nm=%d, levels=%d, nodes=%d] ", hddms2->nm, hddms2->num_levels, hddms2->num_nodes);
PH_PrintMemoryToMainLog(env, "[", kb, "]\n");
// add sparse bits
PH_PrintToMainLog(env, "Adding sparse bits... ");
add_sparse_matrices_mdp(hddms2, compact);
kb = hddms2->mem_sm;
kbt += kb;
PH_PrintToMainLog(env, "[levels=%d-%d, num=%d, compact=%d/%d] ", hddms2->l_sm_min, hddms2->l_sm_max, hddms2->num_sm, hddms2->compact_sm, hddms2->nm);
PH_PrintMemoryToMainLog(env, "[", kb, "]\n");
// remove goal and infinity states from state rewards vector
Cudd_Ref(state_rewards);
Cudd_Ref(maybe);
state_rewards = DD_Apply(ddman, APPLY_TIMES, state_rewards, maybe);
// put state rewards in a vector
PH_PrintToMainLog(env, "Creating rewards vector... ");
rew_vec = mtbdd_to_double_vector(ddman, state_rewards, rvars, num_rvars, odd);
// try and convert to compact form if required
compact_r = false;
if (compact) {
if ((rew_dist = double_vector_to_dist(rew_vec, n))) {
compact_r = true;
delete rew_vec; rew_vec = NULL;
}
}
kb = (!compact_r) ? n*8.0/1024.0 : (rew_dist->num_dist*8.0+n*2.0)/1024.0;
kbt += kb;
if (compact_r) PH_PrintToMainLog(env, "[dist=%d, compact] ", rew_dist->num_dist);
PH_PrintMemoryToMainLog(env, "[", kb, "]\n");
// create solution/iteration vectors
PH_PrintToMainLog(env, "Allocating iteration vectors... ");
soln = new double[n];
soln2 = new double[n];
soln3 = new double[n];
kb = n*8.0/1024.0;
kbt += 3*kb;
PH_PrintMemoryToMainLog(env, "[3 x ", kb, "]\n");
// print total memory usage
PH_PrintMemoryToMainLog(env, "TOTAL: [", kbt, "]\n");
// initial solution is zero
for (i = 0; i < n; i++) {
soln[i] = 0;
}
// get setup time
stop = util_cpu_time();
time_for_setup = (double)(stop - start2)/1000;
start2 = stop;
start3 = stop;
// start iterations
iters = 0;
done = false;
PH_PrintToMainLog(env, "\nStarting iterations...\n");
while (!done && iters < max_iters) {
iters++;
// initialise array for storing mins/maxs to -1s
// (allows us to keep track of rows not visited)
for (i = 0; i < n; i++) {
soln2[i] = -1;
}
// do matrix multiplication and min/max
for (i = 0; i < nm; i++) {
// start off all negative
// (need to keep track of rows not visited)
for (j = 0; j < n; j++) {
soln3[j] = -1;
}
// matrix multiply
// store stuff to be used globally
hddm = hddms->choices[i];
hdd = hddm->top;
zero = hddm->zero;
num_levels = hddm->num_levels;
compact_sm = hddm->compact_sm;
if (compact_sm) {
sm_dist = hddm->dist;
sm_dist_shift = hddm->dist_shift;
sm_dist_mask = hddm->dist_mask;
}
// do traversal
mult_rec(hdd, 0, 0, 0, 1);
// add transition rewards
// store stuff to be used globally
hddm = hddms2->choices[i];
hdd = hddm->top;
zero = hddm->zero;
num_levels = hddm->num_levels;
compact_sm = hddm->compact_sm;
if (compact_sm) {
sm_dist = hddm->dist;
sm_dist_shift = hddm->dist_shift;
sm_dist_mask = hddm->dist_mask;
}
// do traversal
mult_rec(hdd, 0, 0, 0, 2);
// min/max
for (j = 0; j < n; j++) {
if (soln3[j] >= 0) {
if (soln2[j] < 0) {
soln2[j] = soln3[j];
} else if (min) {
if (soln3[j] < soln2[j]) soln2[j] = soln3[j];
} else {
if (soln3[j] > soln2[j]) soln2[j] = soln3[j];
}
}
}
}
// add state rewards
if (!compact_r) {
for (i = 0; i < n; i++) { if(soln2[i] < 0) soln2[i] = 0; soln2[i] += rew_vec[i]; }
} else {
for (i = 0; i < n; i++) { if(soln2[i] < 0) soln2[i] = 0; soln2[i] += rew_dist->dist[rew_dist->ptrs[i]]; }
}
// check convergence
sup_norm = 0.0;
for (i = 0; i < n; i++) {
x = fabs(soln2[i] - soln[i]);
if (term_crit == TERM_CRIT_RELATIVE) {
x /= soln2[i];
}
if (x > sup_norm) sup_norm = x;
}
if (sup_norm < term_crit_param) {
done = true;
}
// print occasional status update
if ((util_cpu_time() - start3) > UPDATE_DELAY) {
PH_PrintToMainLog(env, "Iteration %d: max %sdiff=%f", iters, (term_crit == TERM_CRIT_RELATIVE)?"relative ":"", sup_norm);
PH_PrintToMainLog(env, ", %.2f sec so far\n", ((double)(util_cpu_time() - start2)/1000));
start3 = util_cpu_time();
}
// prepare for next iteration
tmpsoln = soln;
soln = soln2;
soln2 = tmpsoln;
}
// stop clocks
stop = util_cpu_time();
time_for_iters = (double)(stop - start2)/1000;
time_taken = (double)(stop - start1)/1000;
// print iterations/timing info
PH_PrintToMainLog(env, "\nIterative method: %d iterations in %.2f seconds (average %.6f, setup %.2f)\n", iters, time_taken, time_for_iters/iters, time_for_setup);
// if the iterative method didn't terminate, this is an error
if (!done) { delete soln; soln = NULL; PH_SetErrorMessage("Iterative method did not converge within %d iterations.\nConsider using a different numerical method or increasing the maximum number of iterations", iters); }
// catch exceptions: register error, free memory
} catch (std::bad_alloc e) {
PH_SetErrorMessage("Out of memory");
if (soln) delete[] soln;
soln = 0;
}
// free memory
if (a) Cudd_RecursiveDeref(ddman, a);
if (state_rewards) Cudd_RecursiveDeref(ddman, state_rewards);
if (trans_rewards) Cudd_RecursiveDeref(ddman, trans_rewards);
if (hddms) delete hddms;
if (hddms2) delete hddms2;
if (rew_vec) delete[] rew_vec;
if (rew_dist) delete rew_dist;
if (soln2) delete soln2;
if (soln3) delete soln3;
return ptr_to_jlong(soln);
}
//------------------------------------------------------------------------------
static void mult_rec(HDDNode *hdd, int level, int row_offset, int col_offset, int code)
{
HDDNode *e, *t;
// if it's the zero node
if (hdd == zero) {
return;
}
// or if we've reached a submatrix
// (check for non-null ptr but, equivalently, we could just check if level==l_sm)
else if (hdd->sm.ptr) {
if (!compact_sm) {
mult_rm((RMSparseMatrix *)hdd->sm.ptr, row_offset, col_offset, code);
} else {
mult_cmsr((CMSRSparseMatrix *)hdd->sm.ptr, row_offset, col_offset, code);
}
return;
}
// or if we've reached the bottom
else if (level == num_levels) {
//printf("(%d,%d)=%f\n", row_offset, col_offset, hdd->type.val);
switch (code) {
case 1:
if (soln3[row_offset] < 0) soln3[row_offset] = 0;
soln3[row_offset] += soln[col_offset] * hdd->type.val;
break;
case 2:
if (soln3[row_offset] < 0) soln3[row_offset] = 0;
soln3[row_offset] += hdd->type.val;
break;
}
return;
}
// otherwise recurse
e = hdd->type.kids.e;
if (e != zero) {
mult_rec(e->type.kids.e, level+1, row_offset, col_offset, code);
mult_rec(e->type.kids.t, level+1, row_offset, col_offset+e->off.val, code);
}
t = hdd->type.kids.t;
if (t != zero) {
mult_rec(t->type.kids.e, level+1, row_offset+hdd->off.val, col_offset, code);
mult_rec(t->type.kids.t, level+1, row_offset+hdd->off.val, col_offset+t->off.val, code);
}
}
//-----------------------------------------------------------------------------------
static void mult_rm(RMSparseMatrix *rmsm, int row_offset, int col_offset, int code)
{
int i2, j2, l2, h2, r;
int sm_n = rmsm->n;
int sm_nnz = rmsm->nnz;
double *sm_non_zeros = rmsm->non_zeros;
unsigned char *sm_row_counts = rmsm->row_counts;
int *sm_row_starts = (int *)rmsm->row_counts;
bool sm_use_counts = rmsm->use_counts;
unsigned int *sm_cols = rmsm->cols;
// loop through rows of submatrix
l2 = sm_nnz; h2 = 0;
for (i2 = 0; i2 < sm_n; i2++) {
// loop through entries in this row
if (!sm_use_counts) { l2 = sm_row_starts[i2]; h2 = sm_row_starts[i2+1]; }
else { l2 = h2; h2 += sm_row_counts[i2]; }
for (j2 = l2; j2 < h2; j2++) {
switch (code) {
case 1:
r = row_offset + i2;
if (soln3[r] < 0) soln3[r] = 0;
soln3[r] += soln[col_offset + sm_cols[j2]] * sm_non_zeros[j2];
break;
case 2:
r = row_offset + i2;
if (soln3[r] < 0) soln3[r] = 0;
soln3[r] += sm_non_zeros[j2];
break;
}
//printf("(%d,%d)=%f\n", row_offset + i2, col_offset + sm_cols[j2], sm_non_zeros[j2]);
}
}
}
//-----------------------------------------------------------------------------------
static void mult_cmsr(CMSRSparseMatrix *cmsrsm, int row_offset, int col_offset, int code)
{
int i2, j2, l2, h2, r;
int sm_n = cmsrsm->n;
int sm_nnz = cmsrsm->nnz;
unsigned char *sm_row_counts = cmsrsm->row_counts;
int *sm_row_starts = (int *)cmsrsm->row_counts;
bool sm_use_counts = cmsrsm->use_counts;
unsigned int *sm_cols = cmsrsm->cols;
// loop through rows of submatrix
l2 = sm_nnz; h2 = 0;
for (i2 = 0; i2 < sm_n; i2++) {
// loop through entries in this row
if (!sm_use_counts) { l2 = sm_row_starts[i2]; h2 = sm_row_starts[i2+1]; }
else { l2 = h2; h2 += sm_row_counts[i2]; }
for (j2 = l2; j2 < h2; j2++) {
switch (code) {
case 1:
r = row_offset + i2;
if (soln3[r] < 0) soln3[r] = 0;
soln3[r] += soln[col_offset + (int)(sm_cols[j2] >> sm_dist_shift)] * sm_dist[(int)(sm_cols[j2] & sm_dist_mask)];
break;
case 2:
r = row_offset + i2;
if (soln3[r] < 0) soln3[r] = 0;
soln3[r] += sm_dist[(int)(sm_cols[j2] & sm_dist_mask)];
break;
}
//`("(%d,%d)=%f\n", row_offset + i2, col_offset + (int)(sm_cols[j2] >> sm_dist_shift), sm_dist[(int)(sm_cols[j2] & sm_dist_mask)]);
}
}
}
//------------------------------------------------------------------------------