Package org.apache.mahout.math

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

69
70
71
72
73
74
75
76
77
    InteractionValueEncoder enc = new InteractionValueEncoder("interactions", wv, tv);
    Vector v1 = new DenseVector(200);
    enc.addInteractionToVector("a","some text here",1.0, v1);
    int k = enc.getProbes();
    // should interact "a" with each of "some","text" and "here"
    assertEquals((float) k*3, v1.norm(1), 0);
  }

}
View Full Code Here
34
35
36
37
38
39
40
41
42
43
44
    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));
View Full Code Here
75
76
77
78
79
80
81
82
83
84
85
    enc.addToVector("test1 and more", v1);
    enc.flush(1, v1);

    //should be the same as text test above, since we are splitting on whitespace
    // should set 6 distinct locations to 1
    assertEquals(6.0, v1.norm(1), 0);
    assertEquals(1.0, v1.maxValue(), 0);

    v1 = new DenseVector(200);
    enc.addToVector("", v1);
    enc.flush(1, v1);
View Full Code Here
81
82
83
84
85
86
87
88
89
90
91
    assertEquals(1.0, v1.maxValue(), 0);

    v1 = new DenseVector(200);
    enc.addToVector("", v1);
    enc.flush(1, v1);
    assertEquals(0.0, v1.norm(1), 0);
    assertEquals(0.0, v1.maxValue(), 0);

    v1 = new DenseVector(200);
    StringBuilder builder = new StringBuilder(5000);
    for (int i = 0; i < 1000; i++){//lucene's internal buffer length request is 4096, so let's make sure we can handle larger size
View Full Code Here
92
93
94
95
96
97
98
99
100
      builder.append("token_").append(i).append(' ');
    }
    enc.addToVector(builder.toString(), v1);
    enc.flush(1, v1);
    //System.out.println(v1);
    assertEquals(2000.0, v1.norm(1), 0);
    assertEquals(19.0, v1.maxValue(), 0);
  }
}
View Full Code Here
160
161
162
163
164
165
166
167
168
169
170
      Vector v = new DenseVector(numCols);
      for(int col = 0; col < numCols; col++) {
        double val = r.nextGaussian();
        v.set(col, val);
      }
      v.assign(Functions.MULT, 1/((row + 1) * v.norm(2)));
      matrix.assignRow(row, v);
    }
    if(symmetric) {
      return matrix.times(matrix.transpose());
    }
View Full Code Here
202
203
204
205
206
207
208
209
210
211
212
          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);
          }
        }
      }
View Full Code Here
212
213
214
215
216
217
218
219
220
221
222
      }
      // 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);
View Full Code Here
160
161
162
163
164
165
166
167
168
169
170
      Vector v = new DenseVector(numCols);
      for (int col = 0; col < numCols; col++) {
        double val = r.nextGaussian();
        v.set(col, val);
      }
      v.assign(Functions.MULT, 1/((row + 1) * v.norm(2)));
      matrix.assignRow(row, v);
    }
    if (symmetric) {
      return matrix.times(matrix.transpose());
    }
View Full Code Here
200
201
202
203
204
205
206
207
208
209
210
          if (previousEigen == null) {
            previousEigen = currentEigen.clone();
          } else {
            double dot = currentEigen.dot(previousEigen);
            if (dot > 0.0) {
              dot /= currentEigen.norm(2) * previousEigen.norm(2);
            }
           // log.info("Current pass * previous pass = {}", dot);
          }
        }
      }
View Full Code Here
TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.