Examples of EncogWriteHelper

Examples of org.encog.persist.EncogWriteHelper

65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
   *
   * @param stream
   *            The output stream.
   */
  public void save(final OutputStream stream) {
    final EncogWriteHelper out = new EncogWriteHelper(stream);
    saveSubSection(out, "HEADER", "DATASOURCE");
    saveConfig(out);

    if (this.script.getFields() != null) {
      saveData(out);
      saveNormalize(out);
    }

    saveProcess(out);
   
    saveSubSection(out, "RANDOMIZE", "CONFIG");
    saveSubSection(out, "CLUSTER", "CONFIG");
    saveSubSection(out, "BALANCE", "CONFIG");
    saveSubSection(out, "CODE", "CONFIG");

    if (this.script.getSegregate().getSegregateTargets() != null) {
      saveSegregate(out);
    }
    saveSubSection(out, "GENERATE", "CONFIG");
    saveMachineLearning(out);
    saveTasks(out);
    out.flush();
  }
View Full Code Here

Examples of org.encog.persist.EncogWriteHelper

207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final BasicPNN pnn = (BasicPNN) obj;
    out.addSection("PNN");
    out.addSubSection("PARAMS");
    out.addProperties(pnn.getProperties());
    out.addSubSection("NETWORK");

    out.writeProperty(PersistConst.ERROR, pnn.getError());
    out.writeProperty(PersistConst.INPUT_COUNT, pnn.getInputCount());
    out.writeProperty(PersistConst.KERNEL,
        PersistBasicPNN.kernelToString(pnn.getKernel()));
    out.writeProperty(PersistConst.OUTPUT_COUNT, pnn.getOutputCount());
    out.writeProperty(PersistBasicPNN.PROPERTY_outputMode,
        PersistBasicPNN.outputModeToString(pnn.getOutputMode()));
    out.writeProperty(PersistConst.SIGMA, pnn.getSigma());

    out.addSubSection("SAMPLES");
   
    if (pnn.getSamples() != null) {
      for (final MLDataPair pair : pnn.getSamples()) {
        for (int i = 0; i < pair.getInput().size(); i++) {
          out.addColumn(pair.getInput().getData(i));
        }
        for (int i = 0; i < pair.getIdeal().size(); i++) {
          out.addColumn(pair.getIdeal().getData(i));
        }
        out.writeLine();
      }
    }

    out.flush();
  }
View Full Code Here

Examples of org.encog.persist.EncogWriteHelper

83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final SOM som = (SOM) obj;
    out.addSection("SOM");
    out.addSubSection("PARAMS");
    out.addProperties(som.getProperties());
    out.addSubSection("NETWORK");
    out.writeProperty(PersistConst.WEIGHTS, som.getWeights());
    out.writeProperty(PersistConst.INPUT_COUNT, som.getInputCount());
    out.writeProperty(PersistConst.OUTPUT_COUNT, som.getOutputCount());
    out.flush();
  }
View Full Code Here

Examples of org.encog.persist.EncogWriteHelper

88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final HopfieldNetwork hopfield = (HopfieldNetwork) obj;
    out.addSection("HOPFIELD");
    out.addSubSection("PARAMS");
    out.addProperties(hopfield.getProperties());
    out.addSubSection("NETWORK");
    out.writeProperty(PersistConst.WEIGHTS, hopfield.getWeights());
    out.writeProperty(PersistConst.OUTPUT, hopfield.getCurrentState()
        .getData());
    out.writeProperty(PersistConst.NEURON_COUNT, hopfield.getNeuronCount());
    out.flush();
  }
View Full Code Here

Examples of org.encog.persist.EncogWriteHelper

163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final BasicNetwork net = (BasicNetwork) obj;
    final FlatNetwork flat = net.getStructure().getFlat();
    out.addSection("BASIC");
    out.addSubSection("PARAMS");
    out.addProperties(net.getProperties());
    out.addSubSection("NETWORK");

    out.writeProperty(BasicNetwork.TAG_BEGIN_TRAINING,
        flat.getBeginTraining());
    out.writeProperty(BasicNetwork.TAG_CONNECTION_LIMIT,
        flat.getConnectionLimit());
    out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_OFFSET,
        flat.getContextTargetOffset());
    out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_SIZE,
        flat.getContextTargetSize());
    out.writeProperty(BasicNetwork.TAG_END_TRAINING, flat.getEndTraining());
    out.writeProperty(BasicNetwork.TAG_HAS_CONTEXT, flat.getHasContext());
    out.writeProperty(PersistConst.INPUT_COUNT, flat.getInputCount());
    out.writeProperty(BasicNetwork.TAG_LAYER_COUNTS, flat.getLayerCounts());
    out.writeProperty(BasicNetwork.TAG_LAYER_FEED_COUNTS,
        flat.getLayerFeedCounts());
    out.writeProperty(BasicNetwork.TAG_LAYER_CONTEXT_COUNT,
        flat.getLayerContextCount());
    out.writeProperty(BasicNetwork.TAG_LAYER_INDEX, flat.getLayerIndex());
    out.writeProperty(PersistConst.OUTPUT, flat.getLayerOutput());
    out.writeProperty(PersistConst.OUTPUT_COUNT, flat.getOutputCount());
    out.writeProperty(BasicNetwork.TAG_WEIGHT_INDEX, flat.getWeightIndex());
    out.writeProperty(PersistConst.WEIGHTS, flat.getWeights());
    out.writeProperty(BasicNetwork.TAG_BIAS_ACTIVATION,
        flat.getBiasActivation());
    out.addSubSection("ACTIVATION");
    for (final ActivationFunction af : flat.getActivationFunctions()) {
      String sn = af.getClass().getSimpleName();
      // if this is an Encog class then only add the simple name, so it works with C#
      if( sn.startsWith("org.encog.") ) {
        out.addColumn(sn);
      } else {
        out.addColumn(af.getClass().getName());
      }
      for (int i = 0; i < af.getParams().length; i++) {
        out.addColumn(af.getParams()[i]);
      }
      out.writeLine();
    }

    out.flush();
  }
View Full Code Here

Examples of org.encog.persist.EncogWriteHelper

99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final BoltzmannMachine boltz = (BoltzmannMachine) obj;
    out.addSection("BOLTZMANN");
    out.addSubSection("PARAMS");
    out.addProperties(boltz.getProperties());
    out.addSubSection("NETWORK");
    out.writeProperty(PersistConst.WEIGHTS, boltz.getWeights());
    out.writeProperty(PersistConst.OUTPUT, boltz.getCurrentState()
        .getData());
    out.writeProperty(PersistConst.NEURON_COUNT, boltz.getNeuronCount());

    out.writeProperty(PersistConst.THRESHOLDS, boltz.getThreshold());
    out.writeProperty(BoltzmannMachine.ANNEAL_CYCLES,
        boltz.getAnnealCycles());
    out.writeProperty(BoltzmannMachine.RUN_CYCLES, boltz.getRunCycles());
    out.writeProperty(PersistConst.TEMPERATURE, boltz.getTemperature());

    out.flush();

  }
View Full Code Here

Examples of org.encog.persist.EncogWriteHelper

261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
    return result;
  }

  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final NEATPopulation pop = (NEATPopulation) obj;
    out.addSection("NEAT-POPULATION");
    out.addSubSection("CONFIG");
    out.writeProperty(PersistConst.ACTIVATION_CYCLES,
        pop.getActivationCycles());

    if (pop.isHyperNEAT()) {
      out.writeProperty(NEATPopulation.PROPERTY_NEAT_ACTIVATION,
          PersistNEATPopulation.TYPE_CPPN);
    } else {
      final ActivationFunction af = pop.getActivationFunctions()
          .getList().get(0).getObj();
      out.writeProperty(NEATPopulation.PROPERTY_NEAT_ACTIVATION, af);
    }

    out.writeProperty(PersistConst.INPUT_COUNT, pop.getInputCount());
    out.writeProperty(PersistConst.OUTPUT_COUNT, pop.getOutputCount());
    out.writeProperty(NEATPopulation.PROPERTY_CYCLES,
        pop.getActivationCycles());
    out.writeProperty(NEATPopulation.PROPERTY_POPULATION_SIZE,
        pop.getPopulationSize());
    out.writeProperty(NEATPopulation.PROPERTY_SURVIVAL_RATE,
        pop.getSurvivalRate());
    out.addSubSection("INNOVATIONS");
    if (pop.getInnovations() != null) {
      for (final String key : pop.getInnovations().getInnovations()
          .keySet()) {
        final NEATInnovation innovation = pop.getInnovations()
            .getInnovations().get(key);
        out.addColumn(key);
        out.addColumn(innovation.getInnovationID());
        out.addColumn(innovation.getNeuronID());
        out.writeLine();
      }
    }

    out.addSubSection("SPECIES");

    // make sure the best species goes first
    final Species bestSpecies = pop.determineBestSpecies();
    if (bestSpecies != null) {
      saveSpecies(out, bestSpecies);
    }

    // now write the other species, other than the best one
    for (final Species species : pop.getSpecies()) {
      if (species != bestSpecies) {
        saveSpecies(out, species);
      }
    }
    out.flush();
  }
View Full Code Here

Examples of org.encog.persist.EncogWriteHelper

194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final RBFNetwork net = (RBFNetwork) obj;
    final FlatNetworkRBF flat = (FlatNetworkRBF) net.getFlat();
    out.addSection("RBF-NETWORK");
    out.addSubSection("PARAMS");
    out.addProperties(net.getProperties());
    out.addSubSection("NETWORK");
    out.writeProperty(BasicNetwork.TAG_BEGIN_TRAINING,
        flat.getBeginTraining());
    out.writeProperty(BasicNetwork.TAG_CONNECTION_LIMIT,
        flat.getConnectionLimit());
    out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_OFFSET,
        flat.getContextTargetOffset());
    out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_SIZE,
        flat.getContextTargetSize());
    out.writeProperty(BasicNetwork.TAG_END_TRAINING, flat.getEndTraining());
    out.writeProperty(BasicNetwork.TAG_HAS_CONTEXT, flat.getHasContext());
    out.writeProperty(PersistConst.INPUT_COUNT, flat.getInputCount());
    out.writeProperty(BasicNetwork.TAG_LAYER_COUNTS, flat.getLayerCounts());
    out.writeProperty(BasicNetwork.TAG_LAYER_FEED_COUNTS,
        flat.getLayerFeedCounts());
    out.writeProperty(BasicNetwork.TAG_LAYER_CONTEXT_COUNT,
        flat.getLayerContextCount());
    out.writeProperty(BasicNetwork.TAG_LAYER_INDEX, flat.getLayerIndex());
    out.writeProperty(PersistConst.OUTPUT, flat.getLayerOutput());
    out.writeProperty(PersistConst.OUTPUT_COUNT, flat.getOutputCount());
    out.writeProperty(BasicNetwork.TAG_WEIGHT_INDEX, flat.getWeightIndex());
    out.writeProperty(PersistConst.WEIGHTS, flat.getWeights());
    out.writeProperty(BasicNetwork.TAG_BIAS_ACTIVATION,
        flat.getBiasActivation());
    out.addSubSection("ACTIVATION");
    for (final ActivationFunction af : flat.getActivationFunctions()) {
      out.addColumn(af.getClass().getSimpleName());
      for (int i = 0; i < af.getParams().length; i++) {
        out.addColumn(af.getParams()[i]);
      }
      out.writeLine();
    }
    out.addSubSection("RBF");
    for (final RadialBasisFunction rbf : flat.getRBF()) {
      out.addColumn(rbf.getClass().getSimpleName());
      out.addColumn(rbf.getWidth());
      out.addColumn(rbf.getPeak());
      for (int i = 0; i < rbf.getCenters().length; i++) {
        out.addColumn(rbf.getCenters()[i]);
      }
      out.writeLine();
    }

    out.flush();
  }
View Full Code Here

Examples of org.encog.persist.EncogWriteHelper

85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final TrainingContinuation cont = (TrainingContinuation) obj;
    out.addSection("CONT");
    out.addSubSection("PARAMS");
    out.writeProperty("type", cont.getTrainingType());
    for (final String key : cont.getContents().keySet()) {
      final double[] list = (double[]) cont.get(key);
      out.writeProperty(key, list);
    }
    out.flush();
  }
View Full Code Here

Examples of org.encog.persist.EncogWriteHelper

123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
  /**
   * {@inheritDoc}
   */
  @Override
  public final void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final HiddenMarkovModel net = (HiddenMarkovModel) obj;

    out.addSection("HMM");
    out.addSubSection("PARAMS");
    out.addProperties(net.getProperties());
    out.addSubSection("CONFIG");

    out.writeProperty(HiddenMarkovModel.TAG_STATES,net.getStateCount());
    if( net.getItems()!=null ) {
      out.writeProperty(HiddenMarkovModel.TAG_ITEMS,net.getItems());
    }
    out.writeProperty(HiddenMarkovModel.TAG_PI,net.getPi());
    out.writeProperty(HiddenMarkovModel.TAG_TRANSITION,new Matrix(net.getTransitionProbability()));
   
    for( int i=0; i<net.getStateCount();i++) {
      out.addSubSection("DISTRIBUTION-"+i); 
      StateDistribution sd = net.getStateDistribution(i);
      out.writeProperty(HiddenMarkovModel.TAG_DIST_TYPE, sd.getClass().getSimpleName());
     
      if( sd instanceof ContinousDistribution ) {
        ContinousDistribution cDist = (ContinousDistribution)sd;
        out.writeProperty(HiddenMarkovModel.TAG_MEAN, cDist.getMean());
        out.writeProperty(HiddenMarkovModel.TAG_COVARIANCE, cDist.getCovariance());
       
      } else if( sd instanceof DiscreteDistribution ) {
        DiscreteDistribution dDist = (DiscreteDistribution)sd;
        out.writeProperty(HiddenMarkovModel.TAG_PROBABILITIES, new Matrix(dDist.getProbabilities()));
      }
    }

    out.flush();
  }
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.