public static boolean are_d_connected(AbstractVariable x1, AbstractVariable x2, Vector evidence)
throws RemoteException {
// Find all paths between x1 and x2, then see if there is some path which is
// d-connecting given the evidence. If so, return true, otherwise false.
Hashtable path_sets = new Hashtable(); // HEY !!! THIS OUGHT TO BE CACHED SOMEWHERE !!!
PathAnalysis.compile_paths(x1, x2, path_sets);
Vector path_set = (Vector) path_sets.get(new VariablePair(x1, x2));
if (path_set == null)
// No connections whatsoever.
return false;
Enumeration path_set_enum = path_set.elements();
while (path_set_enum.hasMoreElements()) {
AbstractVariable[] path = (AbstractVariable[]) path_set_enum.nextElement();
if (is_d_connecting(path, evidence)) {
System.err.print("PathAnalysis.are_d_connected: path ");
int i;
for (i = 0; i < path.length; i++) System.err.print(path[i].get_name() + " ");
System.err.print("is d-connected given evidence ");
for (i = 0; i < evidence.size(); i++)
System.err.print(((AbstractVariable) evidence.elementAt(i)).get_name() + " ");
System.err.println("");
return true;
}
}
return false;
}
/**
* Check the helpers currently stored in the helper cache to see if any of them can handle the
* sequence we've just been given. This avoids pinging the belief network context to get a helper
* list.
*/
public static Class find_helper_class1(
Vector seq, String helper_type, int[] max_class_score, int[] max_count_score)
throws ClassNotFoundException {
int[] class_score1 = new int[1], count_score1 = new int[1];
max_class_score[0] = -1;
max_count_score[0] = -1;
Class cmax_score = null;
for (Enumeration e = helper_cache.keys(); e.hasMoreElements(); ) {
try {
HelperCacheKey key = (HelperCacheKey) e.nextElement();
if (!key.helper_type.equals(helper_type)) continue;
Class c = (Class) helper_cache.get(key);
SeqTriple[] sm = (SeqTriple[]) invoke_description(c);
if (sm == null) continue; // apparently not a helper class
if (MatchClassPattern.matches(sm, seq, class_score1, count_score1)) {
if (class_score1[0] > max_class_score[0]
|| (class_score1[0] == max_class_score[0] && count_score1[0] > max_count_score[0])) {
cmax_score = c;
max_class_score[0] = class_score1[0];
max_count_score[0] = count_score1[0];
}
}
} catch (Exception e2) {
} // eat it; stagger forward
}
if (Global.debug > 1)
System.err.println(
"PiHelperLoader.find_helper_class1: helper "
+ (cmax_score == null ? "is NOT" : "is")
+ " in cache.");
if (cmax_score == null) // no luck; try to get a helper list from the bnc & plunge ahead
return find_helper_class0(seq, helper_type, max_class_score, max_count_score);
else // success!
return cmax_score;
}
/**
* This method returns a <tt>Class</tt> for a helper which can handle the list of distributions
* specified by <tt>seq1</tt>. We maintain a cache of recently-loaded helpers, so check the cache
* before going to the trouble of searching for a helper. The cache is blown away every
* <tt>HELPER_CACHE_REFRESH</tt> seconds.
*
* <p>If we can't find a helper in the cache, we must search through the list of available helpers
* to find an appropriate one. First try to find helper using class sequence as specified by
* <tt>seq</tt>. Whether or not that succeeds, promote any <tt>Gaussian</tt> in the sequence to
* <tt>MixGaussians</tt>, and try again. If we get a better match on the second try, return the
* helper thus found.
*/
public static Class find_helper_class(Vector seq1, String helper_type)
throws ClassNotFoundException {
// Let's see if an appropriate helper is in the cache.
// If the cache is too old, empty it and search for the helper anew.
if (System.currentTimeMillis() - cache_timestamp > HELPER_CACHE_REFRESH) {
helper_cache = new Hashtable();
cache_timestamp = System.currentTimeMillis();
// Go on and search for appropriate helper.
} else {
HelperCacheKey key = new HelperCacheKey(helper_type, seq1);
Class helper_class = (Class) helper_cache.get(key);
if (helper_class != null) {
if (Global.debug > -1)
System.err.println(
"PiHelperLoader.find_helper_class: found helper class: "
+ helper_class
+ "; no need to search.");
return helper_class;
}
// else no luck; we have to search for helper.
}
// Well, we didn't find a helper in the cache, so let's go to work.
if (Global.debug > -1)
System.err.println(
"PiHelperLoader.find_helper_class: DID NOT FIND HELPER CLASS; NOW SEARCH.");
Class c1 = null, c2 = null;
ClassNotFoundException cnfe1 = null, cnfe2 = null;
int[] class_score1 = new int[1], count_score1 = new int[1];
int[] class_score2 = new int[1], count_score2 = new int[1];
try {
c1 = find_helper_class1(seq1, helper_type, class_score1, count_score1);
} catch (ClassNotFoundException e) {
cnfe1 = e;
} // hang on, we may need to re-throw later.
Class gaussian_class = Class.forName("riso.distributions.Gaussian");
MixGaussians mog = new MixGaussians(1, 1);
Vector seq2 = new Vector(seq1.size());
for (int i = 0; i < seq1.size(); i++)
if (gaussian_class.isAssignableFrom((Class) seq1.elementAt(i)))
seq2.addElement(mog.getClass());
else seq2.addElement(seq1.elementAt(i));
try {
c2 = find_helper_class1(seq2, helper_type, class_score2, count_score2);
} catch (ClassNotFoundException e) {
cnfe2 = e;
}
if (cnfe1 == null && cnfe2 == null) {
// Both matched; see which one fits better.
// Break ties in favor of the helper for non-promoted messages.
if (class_score1[0] >= class_score2[0]
|| (class_score1[0] == class_score2[0] && count_score1[0] >= count_score2[0])) {
if (Global.debug > 1)
System.err.println(
"\taccept helper " + c1 + " for non-promoted classes instead of " + c2);
if (Global.debug > 1)
System.err.println(
"\t\t"
+ class_score1[0]
+ ", "
+ class_score2[0]
+ "; "
+ count_score1[0]
+ ", "
+ count_score2[0]);
helper_cache.put(new HelperCacheKey(helper_type, seq1), c1);
return c1;
} else {
if (Global.debug > 1)
System.err.println("\taccept helper " + c2 + " for promoted classes instead of " + c1);
if (Global.debug > 1)
System.err.println(
"\t\t"
+ class_score1[0]
+ ", "
+ class_score2[0]
+ "; "
+ count_score1[0]
+ ", "
+ count_score2[0]);
helper_cache.put(new HelperCacheKey(helper_type, seq1), c2);
return c2;
}
} else if (cnfe1 == null && cnfe2 != null) {
// Only the first try matched, return it.
helper_cache.put(new HelperCacheKey(helper_type, seq1), c1);
return c1;
} else if (cnfe1 != null && cnfe2 == null) {
// Only the second try matched, return it.
helper_cache.put(new HelperCacheKey(helper_type, seq1), c2);
return c2;
} else {
// Neither try matched. Re-throw the exception generated by the first try.
throw cnfe1;
}
}
public static void main(String[] args) {
boolean do_compile_all = false;
String bn_name = "", x1_name = "", x2_name = "";
Vector evidence_names = new Vector();
for (int i = 0; i < args.length; i++) {
if (args[i].charAt(0) != '-') continue;
switch (args[i].charAt(1)) {
case 'b':
bn_name = args[++i];
break;
case 'a':
do_compile_all = true;
break;
case 'x':
if (args[i].charAt(2) == '1') x1_name = args[++i];
else if (args[i].charAt(2) == '2') x2_name = args[++i];
else System.err.println("PathAnalysis.main: " + args[i] + " -- huh???");
break;
case 'e':
evidence_names.addElement(args[++i]);
break;
default:
System.err.println("PathAnalysis.main: " + args[i] + " -- huh???");
}
}
try {
BeliefNetworkContext bnc = new BeliefNetworkContext(null);
bnc.add_path("/bechtel/users10/krarti/dodier/belief-nets/assorted");
AbstractBeliefNetwork bn = bnc.load_network(bn_name);
Hashtable path_sets;
Enumeration p;
if ((p = PathAnalysis.has_directed_cycle(bn)) == null)
System.err.println("PathAnalysis: no directed cycles found in " + bn_name);
else {
System.err.println("PathAnalysis.main: " + bn_name + " has a directed cycle; quit.");
System.err.print(" cycle is: ");
while (p.hasMoreElements()) {
System.err.print(((AbstractVariable) p.nextElement()).get_name());
if (p.hasMoreElements()) System.err.print(" -> ");
else System.err.println("");
}
System.exit(1);
}
Vector evidence = new Vector();
if (evidence_names.size() > 0) {
for (int i = 0; i < evidence_names.size(); i++)
evidence.addElement(bn.name_lookup((String) (evidence_names.elementAt(i))));
}
if (do_compile_all) {
path_sets = PathAnalysis.compile_all_paths(bn);
} else {
AbstractVariable x1 = (AbstractVariable) bn.name_lookup(x1_name);
AbstractVariable x2 = (AbstractVariable) bn.name_lookup(x2_name);
path_sets = new Hashtable();
PathAnalysis.compile_paths(x1, x2, path_sets);
if (PathAnalysis.are_d_connected(x1, x2, evidence))
System.err.print(
x1.get_name() + " and " + x2.get_name() + " are d-connected given evidence ");
else
System.err.print(
x1.get_name() + " and " + x2.get_name() + " are NOT d-connected given evidence ");
for (int i = 0; i < evidence.size(); i++)
System.err.print(((AbstractVariable) evidence.elementAt(i)).get_name() + " ");
System.err.println("");
}
System.err.println("PathAnalysis.main: results of path finding:");
AbstractVariable[] u = bn.get_variables();
for (int i = 0; i < u.length; i++) {
System.err.println(" --- paths from: " + u[i].get_name() + " ---");
for (int j = i + 1; j < u.length; j++) {
VariablePair vp = new VariablePair(u[i], u[j]);
Vector path_set = (Vector) path_sets.get(vp);
if (path_set == null) continue;
Enumeration path_set_enum = path_set.elements();
while (path_set_enum.hasMoreElements()) {
AbstractVariable[] path = (AbstractVariable[]) path_set_enum.nextElement();
System.err.print(" path: ");
for (int k = 0; k < path.length; k++) System.err.print(path[k].get_name() + " ");
System.err.println("");
}
}
}
System.exit(0);
} catch (Exception e) {
System.err.println("PathAnalysis.main:");
e.printStackTrace();
System.exit(1);
}
}