Package org.apache.mahout.math

Examples of org.apache.mahout.math.DenseVector.norm()

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          if (previousEigen == null) {
            previousEigen = currentEigen.clone();
          } else {
            double dot = currentEigen.dot(previousEigen);
            if (dot > 0) {
              dot /= (currentEigen.norm(2) * previousEigen.norm(2));
            }
           // log.info("Current pass * previous pass = {}", dot);
          }
        }
      }
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      }
      // converged!
      double eigenValue = state.getStatusProgress().get(state.getStatusProgress().size() - 1).getEigenValue();
      // it's actually more efficient to do this to normalize than to call currentEigen = currentEigen.normalize(),
      // because the latter does a clone, which isn't necessary here.
      currentEigen.assign(new TimesFunction(), 1 / currentEigen.norm(2));
      eigens.assignRow(i, currentEigen);
      eigenValues.add(eigenValue);
      state.setCurrentEigenValues(eigenValues);
      log.info("Found eigenvector {}, eigenvalue: {}", i, eigenValue);
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    FeatureVectorEncoder enc = new ContinuousValueEncoder("foo");
    Vector v1 = new DenseVector(20);
    enc.addToVector("-123", v1);
    assertEquals(-123, v1.minValue(), 0);
    assertEquals(0, v1.maxValue(), 0);
    assertEquals(123, v1.norm(1), 0);

    v1 = new DenseVector(20);
    enc.addToVector("123", v1);
    assertEquals(123, v1.maxValue(), 0);
    assertEquals(0, v1.minValue(), 0);
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    v1 = new DenseVector(20);
    enc.addToVector("123", v1);
    assertEquals(123, v1.maxValue(), 0);
    assertEquals(0, v1.minValue(), 0);
    assertEquals(123, v1.norm(1), 0);

    Vector v2 = new DenseVector(20);
    enc.setProbes(2);
    enc.addToVector("123", v2);
    assertEquals(123, v2.maxValue(), 0);
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    Vector v2 = new DenseVector(20);
    enc.setProbes(2);
    enc.addToVector("123", v2);
    assertEquals(123, v2.maxValue(), 0);
    assertEquals(2 * 123, v2.norm(1), 0);

    v1 = v2.minus(v1);
    assertEquals(123, v1.maxValue(), 0);
    assertEquals(123, v1.norm(1), 0);

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    TextValueEncoder enc = new TextValueEncoder("text");
    Vector v1 = new DenseVector(200);
    enc.addToVector("test1 and more", v1);
    enc.flush(1, v1);
    // should set 6 distinct locations to 1
    assertEquals(6.0, v1.norm(1), 0);
    assertEquals(1.0, v1.maxValue(), 0);

    // now some fancy weighting
    StaticWordValueEncoder w = new StaticWordValueEncoder("text");
    w.setDictionary(ImmutableMap.<String, Double>of("word1", 3.0, "word2", 1.5));
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    InteractionValueEncoder enc = new InteractionValueEncoder("interactions", wv, cv);
    Vector v1 = new DenseVector(200);
    enc.addInteractionToVector("a","1.0",1.0, v1);
    int k = enc.getProbes();
    // should set k distinct locations to 1
    assertEquals((float) k, v1.norm(1), 0);
    assertEquals(1.0, v1.maxValue(), 0);

    // adding same interaction again should increment weights
    enc.addInteractionToVector("a","1.0",1.0,v1);
    assertEquals((float) k*2, v1.norm(1), 0);
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    assertEquals((float) k, v1.norm(1), 0);
    assertEquals(1.0, v1.maxValue(), 0);

    // adding same interaction again should increment weights
    enc.addInteractionToVector("a","1.0",1.0,v1);
    assertEquals((float) k*2, v1.norm(1), 0);
    assertEquals(2.0, v1.maxValue(), 0);

    Vector v2 = new DenseVector(20000);
    enc.addInteractionToVector("a","1.0",1.0,v2);
    wv.addToVector("a", v2);
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    enc.addInteractionToVector("a","1.0",1.0,v2);
    wv.addToVector("a", v2);
    cv.addToVector("1.0", v2);
    k = enc.getProbes();
    //this assumes no hash collision
    assertEquals((float) (k + wv.getProbes()+cv.getProbes()), v2.norm(1), 1.0e-3);
  }

  @Test
  public void testAddToVectorUsesProductOfWeights(){
    WordValueEncoder wv = new StaticWordValueEncoder("word");
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    InteractionValueEncoder enc = new InteractionValueEncoder("interactions", wv, cv);
    Vector v1 = new DenseVector(200);
    enc.addInteractionToVector("a","0.9",0.5, v1);
    int k = enc.getProbes();
    // should set k distinct locations to 0.9*0.5
    assertEquals((float) k*0.5*0.9, v1.norm(1), 0);
    assertEquals(0.5*0.9, v1.maxValue(), 0);
  }

  @Test
  public void testAddToVectorWithTextValueEncoder(){
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