Examples of cc.mallet.types.SparseMatrixn

cc.mallet.types.SparseMatrixn
Implementation of Matrix that allows arbitrary number of dimensions. This implementation simply uses a flat array. Created: Tue Sep 16 14:52:37 2003 @author Charles Sutton @version $Id: SparseMatrixn.java,v 1.1 2007/10/22 21:37:39 mccallum Exp $


    int[] idxs1 = new int[] { 0, 1, 3 };
    double[] vals1 = new double[]{ 2.0, 4.0, 8.0 };


    TableFactor ptl1 = new TableFactor (vars);
    ptl1.setValues (new SparseMatrixn (szs, idxs1, vals1));


    TableFactor ans = new TableFactor (vars[0], new double[] { 6, 8 });


    Factor ptl2 = ptl1.marginalize (vars[0]);

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    int[] idxs1 = new int[] { 0, 1, 3 };
    double[] vals1 = new double[]{ 2.0, 4.0, 8.0 };


    TableFactor ptl1 = new TableFactor (vars);
    ptl1.setValues (new SparseMatrixn (szs, idxs1, vals1));


    TableFactor ans = new TableFactor (vars[0], new double[] { 4, 8 });


    Factor ptl2 = ptl1.extractMax (vars[0]);

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     int[] szs = { 2, 2 };


     int[] idxs1 = new int[] { 1, 3 };
     double[] vals1 = new double[]{ 4.0, 8.0 };


    LogTableFactor ptl1 = LogTableFactor.makeFromMatrix (vars, new SparseMatrixn (szs, idxs1, vals1));


    AssignmentIterator it = ptl1.assignmentIterator ();
    assertEquals (1, it.indexOfCurrentAssn ());
    assertEquals (Math.log (4), ptl1.logValue (it), 1e-5);
    assertEquals (Math.log (4), ptl1.logValue (it.assignment ()), 1e-5);

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    int[] idxs2 = new int[] { 0, 3 };
    double[] vals2 = new double [] { 0.5, 0.5 };


    double[] vals3 = new double [] { 1.0, 0, 4.0 };


    LogTableFactor ptl1 = LogTableFactor.makeFromMatrix (vars, new SparseMatrixn (szs, idxs1, vals1));
    LogTableFactor ptl2 = LogTableFactor.makeFromMatrix (vars, new SparseMatrixn (szs, idxs2, vals2));
    LogTableFactor ans = LogTableFactor.makeFromMatrix (vars, new SparseMatrixn (szs, idxs1, vals3));


    Factor ptl3 = ptl1.multiply (ptl2);


    assertTrue ("Tast failed! Expected: "+ans+" Actual: "+ptl3, ans.almostEquals (ptl3));
  }

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    int[] idxs2 = new int[] { 0, 3 };
    double[] vals2 = new double [] { 0.5, 0.5 };


    double[] vals3 = new double [] { 4.0, 0, 16.0 };


    LogTableFactor ptl1 = LogTableFactor.makeFromMatrix  (vars, new SparseMatrixn (szs, idxs1, vals1));
    LogTableFactor ptl2 = LogTableFactor.makeFromMatrix (vars, new SparseMatrixn (szs, idxs2, vals2));
    LogTableFactor ans = LogTableFactor.makeFromMatrix (vars, new SparseMatrixn (szs, idxs1, vals3));


    ptl1.divideBy (ptl2);


    assertTrue ("Tast failed! Expected: "+ans+" Actual: "+ptl1, ans.almostEquals (ptl1));
  }

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    int[] szs = { 2, 2 };


    int[] idxs1 = new int[] { 0, 1, 3 };
    double[] vals1 = new double[]{ 2.0, 4.0, 8.0 };


    LogTableFactor ptl1 = LogTableFactor.makeFromMatrix (vars, new SparseMatrixn (szs, idxs1, vals1));
    LogTableFactor ans = LogTableFactor.makeFromValues (vars[0], new double[] { 6, 8 });


    Factor ptl2 = ptl1.marginalize (vars[0]);


    assertTrue ("Tast failed! Expected: "+ans+" Actual: "+ptl2+" Orig: "+ptl1, ans.almostEquals (ptl2));

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    return makeFromValues (new Variable[]{var}, vals2);
  }


  public static LogTableFactor makeFromMatrix (Variable[] vars, SparseMatrixn values)
  {
    SparseMatrixn logValues = (SparseMatrixn) values.cloneMatrix ();
    for (int i = 0; i < logValues.numLocations (); i++) {
      logValues.setValueAtLocation (i, Math.log (logValues.valueAtLocation (i)));
    }
    Flops.log (logValues.numLocations ());
    return new LogTableFactor (vars, logValues);
  }

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    double[] vals = new double[numRows ()];
    for (int ri = 0; ri < numRows (); ri++) {
      idxs[ri] = singleIndex (ri);
      vals[ri]++;
    }
    SparseMatrixn matrix = new SparseMatrixn (Utils.toSizesArray (varr), idxs, vals);
    return new TableFactor (varr, matrix);
  }

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    double[] vals2 = new double [] { 0.5, 0.5 };


    double[] vals3 = new double [] { 1.0, 0, 4.0 };


    TableFactor ptl1 = new TableFactor (vars);
    ptl1.setValues (new SparseMatrixn (szs, idxs1, vals1));


    TableFactor ptl2 = new TableFactor (vars);
    ptl2.setValues (new SparseMatrixn (szs, idxs2, vals2));


    TableFactor ans = new TableFactor (vars);
    ans.setValues (new SparseMatrixn (szs, idxs1, vals3));


    Factor ptl3 = ptl1.multiply (ptl2);


    assertTrue ("Tast failed! Expected: "+ans+" Actual: "+ptl3, ans.almostEquals (ptl3));
  }

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    double[] vals2 = new double [] { 0.5, 0.5 };


    double[] vals3 = new double [] { 4.0, 0, 16.0 };


    TableFactor ptl1 = new TableFactor (vars);
    ptl1.setValues (new SparseMatrixn (szs, idxs1, vals1));


    TableFactor ptl2 = new TableFactor (vars);
    ptl2.setValues (new SparseMatrixn (szs, idxs2, vals2));


    TableFactor ans = new TableFactor (vars);
    ans.setValues (new SparseMatrixn (szs, idxs1, vals3));


    ptl1.divideBy (ptl2);


    assertTrue ("Tast failed! Expected: "+ans+" Actual: "+ptl1, ans.almostEquals (ptl1));
  }

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Related Classes of cc.mallet.types.SparseMatrixn

cc.mallet.grmm.test.TestLogTableFactor

cc.mallet.grmm.test.TestTableFactor

cc.mallet.grmm.types.Assignment

cc.mallet.grmm.types.LogTableFactor

cc.mallet.grmm.util.Matrices

cc.mallet.types.tests.TestSparseMatrixn

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