本文整理汇总了Java中cc.mallet.grmm.util.ModelReader类的典型用法代码示例。如果您正苦于以下问题：Java ModelReader类的具体用法？Java ModelReader怎么用？Java ModelReader使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
ModelReader类属于cc.mallet.grmm.util包，在下文中一共展示了ModelReader类的9个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: main
import cc.mallet.grmm.util.ModelReader; //导入依赖的package包/类
public static void main (String[] args) throws Exception {
BufferedReader r = new BufferedReader (new StringReader (mdlExample));
FactorGraph fg = new ModelReader().readModel (r);
fg.dump();
Inferencer inf = new JunctionTreeInferencer();
inf.computeMarginals (fg);
for (int vi = 0; vi < 4; vi++) {
Variable var = fg.getVariable (vi);
System.out.println (inf.lookupMarginal (var).dumpToString());
}
System.out.println("+++++++++");
OutputStreamWriter osw = new OutputStreamWriter(System.out);
ModelWriter.writeModel (fg, osw);
osw.close();
}
示例2: testContinousSample
import cc.mallet.grmm.util.ModelReader; //导入依赖的package包/类
public void testContinousSample () throws IOException
{
ModelReader reader = new ModelReader ();
FactorGraph fg = reader.readModel (new BufferedReader (new StringReader (uniformMdlstr)));
Randoms r = new Randoms (324143);
Assignment allAssn = new Assignment ();
for (int i = 0; i < 10000; i++) {
Assignment row = fg.sample (r);
allAssn.addRow (row);
}
Variable x1 = fg.findVariable ("x1");
Assignment assn1 = (Assignment) allAssn.marginalize (x1);
int[] col = assn1.getColumnInt (x1);
double mean = MatrixOps.sum (col) / ((double)col.length);
assertEquals (0.5, mean, 0.025);
}
示例3: testContinousSample2
import cc.mallet.grmm.util.ModelReader; //导入依赖的package包/类
public void testContinousSample2 () throws IOException
{
ModelReader reader = new ModelReader ();
FactorGraph fg = reader.readModel (new BufferedReader (new StringReader (uniformMdlstr2)));
Randoms r = new Randoms (324143);
Assignment allAssn = new Assignment ();
for (int i = 0; i < 10000; i++) {
Assignment row = fg.sample (r);
allAssn.addRow (row);
}
Variable x1 = fg.findVariable ("x2");
Assignment assn1 = (Assignment) allAssn.marginalize (x1);
int[] col = assn1.getColumnInt (x1);
double mean = MatrixOps.sum (col) / ((double)col.length);
assertEquals (0.5, mean, 0.01);
Variable x2 = fg.findVariable ("x2");
Assignment assn2 = (Assignment) allAssn.marginalize (x2);
int[] col2 = assn2.getColumnInt (x2);
double mean2 = MatrixOps.sum (col2) / ((double)col2.length);
assertEquals (0.5, mean2, 0.025);
}
示例4: testSliceInFg
import cc.mallet.grmm.util.ModelReader; //导入依赖的package包/类
public void testSliceInFg () throws IOException
{
ModelReader reader = new ModelReader ();
FactorGraph fg = reader.readModel (new BufferedReader (new StringReader (mdlstr)));
Variable u1 = fg.findVariable ("u1");
Variable u2 = fg.findVariable ("u2");
Assignment assn = new Assignment (new Variable[] { u1, u2 }, new double[] { 6.0, 6.0 });
FactorGraph fg2 = (FactorGraph) fg.slice (assn);
fg2.dump ();
assertEquals (2, fg2.factors ().size ());
assertEquals (1.0/20, fg2.value (new Assignment ()), 1e-5);
fg2.addFactor (new ConstantFactor (10.0));
assertEquals (0.5, fg2.value (new Assignment ()), 1e-5);
}
示例5: ignoretestContinousSample
import cc.mallet.grmm.util.ModelReader; //导入依赖的package包/类
public void ignoretestContinousSample () throws IOException
{
ModelReader reader = new ModelReader ();
FactorGraph fg = reader.readModel (new BufferedReader (new StringReader (uniformMdlstr)));
Randoms r = new Randoms (324143);
Assignment allAssn = new Assignment ();
for (int i = 0; i < 10000; i++) {
Assignment row = fg.sample (r);
allAssn.addRow (row);
}
Variable x1 = fg.findVariable ("x1");
Assignment assn1 = (Assignment) allAssn.marginalize (x1);
int[] col = assn1.getColumnInt (x1);
double mean = MatrixOps.sum (col) / ((double)col.length);
assertEquals (0.5, mean, 0.025);
}
示例6: ignoretestContinousSample2
import cc.mallet.grmm.util.ModelReader; //导入依赖的package包/类
public void ignoretestContinousSample2 () throws IOException
{
ModelReader reader = new ModelReader ();
FactorGraph fg = reader.readModel (new BufferedReader (new StringReader (uniformMdlstr2)));
Randoms r = new Randoms (324143);
Assignment allAssn = new Assignment ();
for (int i = 0; i < 10000; i++) {
Assignment row = fg.sample (r);
allAssn.addRow (row);
}
Variable x1 = fg.findVariable ("x2");
Assignment assn1 = (Assignment) allAssn.marginalize (x1);
int[] col = assn1.getColumnInt (x1);
double mean = MatrixOps.sum (col) / ((double)col.length);
assertEquals (0.5, mean, 0.01);
Variable x2 = fg.findVariable ("x2");
Assignment assn2 = (Assignment) allAssn.marginalize (x2);
int[] col2 = assn2.getColumnInt (x2);
double mean2 = MatrixOps.sum (col2) / ((double)col2.length);
assertEquals (0.5, mean2, 0.025);
}
示例7: testSliceInFg
import cc.mallet.grmm.util.ModelReader; //导入依赖的package包/类
public void testSliceInFg () throws IOException
{
ModelReader reader = new ModelReader ();
FactorGraph fg = reader.readModel (new BufferedReader (new StringReader (TestBetaFactor.mdlstr)));
Variable u1 = fg.findVariable ("u1");
Variable u2 = fg.findVariable ("u2");
Assignment assn = new Assignment (new Variable[] { u1, u2 }, new double[] { 0.25, 0.85 });
FactorGraph fg2 = (FactorGraph) fg.slice (assn);
assertEquals (2, fg2.factors ().size ());
assertEquals (0.59261 * 1.13202, fg2.value (new Assignment ()), 1e-5);
}
示例8: testAllFactorsOf
import cc.mallet.grmm.util.ModelReader; //导入依赖的package包/类
public void testAllFactorsOf () throws IOException
{
ModelReader reader = new ModelReader ();
FactorGraph fg = reader.readModel (new BufferedReader (new StringReader (uniformMdlstr2)));
Variable var = new Variable (2);
var.setLabel ("v0");
List lst = fg.allFactorsOf (var);
assertEquals (0, lst.size ());
}
示例9: testJtConstant
import cc.mallet.grmm.util.ModelReader; //导入依赖的package包/类
public void testJtConstant () throws IOException
{
FactorGraph masterFg = new ModelReader ().readModel (new BufferedReader (new StringReader (gridStr)));
JunctionTreeInferencer jt = new JunctionTreeInferencer ();
Assignment assn = masterFg.sampleContinuousVars (new cc.mallet.util.Randoms (3214));
FactorGraph fg = (FactorGraph) masterFg.slice (assn);
jt.computeMarginals (fg);
}