Package org.encog.persist

Examples of org.encog.persist.EncogWriteHelper

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
250
251
252
253
254
255
256
257
258
  /**
   * {@inheritDoc}
   */
  @Override
  public final void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final SVM svm2 = (SVM) obj;
    out.addSection("SVM");
    out.addSubSection("PARAMS");
    out.addProperties(svm2.getProperties());
    out.addSubSection("SVM-PARAM");
    out.writeProperty(PersistConst.INPUT_COUNT, svm2.getInputCount());
    out.writeProperty(PersistSVM.PARAM_C, svm2.getParams().C);
    out.writeProperty(PersistSVM.PARAM_CACHE_SIZE,
        svm2.getParams().cache_size);
    out.writeProperty(PersistSVM.PARAM_COEF0, svm2.getParams().coef0);
    out.writeProperty(PersistSVM.PARAM_DEGREE, svm2.getParams().degree);
    out.writeProperty(PersistSVM.PARAM_EPS, svm2.getParams().eps);
    out.writeProperty(PersistSVM.PARAM_GAMMA, svm2.getParams().gamma);
    out.writeProperty(PersistSVM.PARAM_KERNEL_TYPE,
        svm2.getParams().kernel_type);
    out.writeProperty(
        PersistSVM.PARAM_NUM_WEIGHT, svm2.getParams().nr_weight);
    out.writeProperty(PersistSVM.PARAM_NU, svm2.getParams().nu);
    out.writeProperty(PersistSVM.PARAM_P, svm2.getParams().p);
    out.writeProperty(PersistSVM.PARAM_PROBABILITY,
        svm2.getParams().probability);
    out.writeProperty(PersistSVM.PARAM_SHRINKING,
        svm2.getParams().shrinking);
    out.writeProperty(PersistSVM.PARAM_SVM_TYPE, svm2.getParams().svm_type);
    out.writeProperty(PersistSVM.PARAM_WEIGHT, svm2.getParams().weight);
    out.writeProperty(PersistSVM.PARAM_WEIGHT_LABEL,
        svm2.getParams().weight_label);
    if (svm2.getModel() != null) {
      out.addSubSection("SVM-MODEL");
      try {
        final ByteArrayOutputStream ba = new ByteArrayOutputStream();
        final DataOutputStream das = new DataOutputStream(ba);
        svm.svm_save_model(das, svm2.getModel());
        out.write(ba.toString("UTF-8"));
        das.close();
        ba.close();

      } catch (final IOException ex) {
        throw new PersistError(ex);
      }
    }

    out.flush();
  }
View Full Code Here
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
  /**
   * {@inheritDoc}
   */
  @Override
  public final 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.getOutputNeuronCount());
    out.flush();
  }
View Full Code Here
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
  /**
   * {@inheritDoc}
   */
  @Override
  public final 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");
    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
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
    try {
      String home = System.getProperty("user.home");
      file = new File(home, EncogWorkBench.CONFIG_FILENAME);

      OutputStream os = new FileOutputStream(file);
      EncogWriteHelper out = new EncogWriteHelper(os);
      out.addSection("ENCOG");
      out.addSubSection("TRAINING");

      out.writeProperty(EncogWorkBenchConfig.PROPERTY_DEFAULT_ERROR, this.defaultError);
      out.writeProperty(EncogWorkBenchConfig.PROPERTY_THREAD_COUNT, this.threadCount);
      out.writeProperty(EncogWorkBenchConfig.PROPERTY_USE_GPU, this.useOpenCL);
      out.writeProperty(EncogWorkBenchConfig.PROPERTY_ERROR_CALC, this.errorCalculation);
           
      out.flush();
      os.close();
    } catch (IOException ex) {
      if (file != null)
        EncogWorkBench.displayError("Can't write config file",
            file.toString());
View Full Code Here
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
   *
   * @param stream
   *            The output stream.
   */
  public final 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);
    }

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

    if (this.script.getSegregate().getSegregateTargets() != null) {
      saveSegregate(out);
    }
    saveSubSection(out, "GENERATE", "CONFIG");
    saveMachineLearning(out);
    saveTasks(out);
    out.flush();
  }
View Full Code Here
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final BAM bam = (BAM) obj;
    out.addSection("BAM");
    out.addSubSection("PARAMS");
    out.addProperties(bam.getProperties());
    out.addSubSection("NETWORK");

    out.writeProperty(PersistConst.PROPERTY_F1_COUNT, bam.getF1Count());
    out.writeProperty(PersistConst.PROPERTY_F2_COUNT, bam.getF2Count());
    out.writeProperty(PersistConst.PROPERTY_WEIGHTS_F1_F2,
        bam.getWeightsF1toF2());
    out.writeProperty(PersistConst.PROPERTY_WEIGHTS_F2_F1,
        bam.getWeightsF2toF1());

    out.flush();

  }
View Full Code Here
114
115
116
117
118
119
120
121
122
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
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
  /**
   * {@inheritDoc}
   */
  @Override
  public final void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final BayesianNetwork b = (BayesianNetwork) obj;
    out.addSection("BAYES-NETWORK");
    out.addSubSection("BAYES-PARAM");
    String queryType = "";
    String queryStr = b.getClassificationStructure();

    if( b.getQuery()!=null ) {
      queryType = b.getQuery().getClass().getSimpleName();
    }
   
    out.writeProperty("queryType", queryType);
    out.writeProperty("query", queryStr);
    out.writeProperty("contents", b.getContents());
    out.addSubSection("BAYES-PROPERTIES");
    out.addProperties(b.getProperties());

    out.addSubSection("BAYES-TABLE");
    for (BayesianEvent event : b.getEvents()) {
      for (TableLine line : event.getTable().getLines()) {
        if (line == null)
          continue;
        StringBuilder str = new StringBuilder();
        str.append("P(");

        str.append(BayesianEvent.formatEventName(event, line.getResult()));

        if (event.getParents().size() > 0) {
          str.append("|");
        }

        int index = 0;
        boolean first = true;
        for (BayesianEvent parentEvent : event.getParents()) {
          if (!first) {
            str.append(",");
          }
          first = false;
          int arg = line.getArguments()[index++];
          if (parentEvent.isBoolean()) {
            if (arg==0) {
              str.append("+");
            } else {
              str.append("-");
            }
          }
          str.append(parentEvent.getLabel());
          if (!parentEvent.isBoolean()) {
            str.append("=");
            if( arg>=parentEvent.getChoices().size()) {
              throw new BayesianError("Argument value " + arg + " is out of range for event " + parentEvent.toString());
            }
            str.append(parentEvent.getChoice(arg));
          }
        }
        str.append(")=");
        str.append(line.getProbability());
        str.append("\n");
        out.write(str.toString());
      }
    }

    out.flush();
  }
View Full Code Here
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
250
251
252
253
254
255
256
257
258
259
260
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
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final PrgPopulation pop = (PrgPopulation) obj;

    out.addSection("BASIC");
    out.addSubSection("PARAMS");
    out.addProperties(pop.getProperties());
    out.addSubSection("EPL-OPCODES");
    for (final ProgramExtensionTemplate temp : pop.getContext()
        .getFunctions().getOpCodes()) {
      out.addColumn(temp.getName());
      out.addColumn(temp.getChildNodeCount());
      out.writeLine();
    }
    out.addSubSection("EPL-SYMBOLIC");
    out.addColumn("name");
    out.addColumn("type");
    out.addColumn("enum");
    out.addColumn("enum_type");
    out.addColumn("enum_count");
    out.writeLine();

    // write the first line, the result
    out.addColumn("");
    out.addColumn(getType(pop.getContext().getResult()));
    out.addColumn(pop.getContext().getResult().getEnumType());
    out.addColumn(pop.getContext().getResult().getEnumValueCount());
    out.writeLine();

    // write the next lines, the variables
    for (final VariableMapping mapping : pop.getContext()
        .getDefinedVariables()) {
      out.addColumn(mapping.getName());
      out.addColumn(getType(mapping));
      out.addColumn(mapping.getEnumType());
      out.addColumn(mapping.getEnumValueCount());
      out.writeLine();
    }
    out.addSubSection("EPL-POPULATION");
    for (final Species species : pop.getSpecies()) {
      if (species.getMembers().size() > 0) {
        out.addColumn("s");
        out.addColumn(species.getAge());
        out.addColumn(species.getBestScore());
        out.addColumn(species.getGensNoImprovement());
        out.writeLine();
        for (final Genome genome : species.getMembers()) {
          final EncogProgram prg = (EncogProgram) genome;
          out.addColumn("p");
          if (Double.isInfinite(prg.getScore())
              || Double.isNaN(prg.getScore())) {
            out.addColumn("NaN");
            out.addColumn("NaN");
          } else {

            out.addColumn(prg.getScore());
            out.addColumn(prg.getAdjustedScore());
          }

          out.addColumn(prg.generateEPL());
          out.writeLine();
        }
      }
    }

    out.flush();
  }
View Full Code Here
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final CPN cpn = (CPN) obj;
    out.addSection("CPN");
    out.addSubSection("PARAMS");
    out.addProperties(cpn.getProperties());
    out.addSubSection("NETWORK");

    out.writeProperty(PersistConst.INPUT_COUNT, cpn.getInputCount());
    out.writeProperty(PersistConst.INSTAR, cpn.getInstarCount());
    out.writeProperty(PersistConst.OUTPUT_COUNT, cpn.getOutputCount());
    out.writeProperty(PersistCPN.PROPERTY_inputToInstar,
        cpn.getWeightsInputToInstar());
    out.writeProperty(PersistCPN.PROPERTY_instarToInput,
        cpn.getWeightsInstarToOutstar());
    out.writeProperty(PersistCPN.PROPERTY_winnerCount,
        cpn.getWinnerCount());

    out.flush();
  }
View Full Code Here
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
  /**
   * {@inheritDoc}
   */
  @Override
  public void save(final OutputStream os, final Object obj) {
    final EncogWriteHelper out = new EncogWriteHelper(os);
    final ART1 art1 = (ART1) obj;
    out.addSection("ART1");
    out.addSubSection("PARAMS");
    out.addProperties(art1.getProperties());
    out.addSubSection("NETWORK");

    out.writeProperty(ART.PROPERTY_A1, art1.getA1());
    out.writeProperty(ART.PROPERTY_B1, art1.getB1());
    out.writeProperty(ART.PROPERTY_C1, art1.getC1());
    out.writeProperty(ART.PROPERTY_D1, art1.getD1());
    out.writeProperty(PersistConst.PROPERTY_F1_COUNT, art1.getF1Count());
    out.writeProperty(PersistConst.PROPERTY_F2_COUNT, art1.getF2Count());
    out.writeProperty(ART.PROPERTY_NO_WINNER, art1.getNoWinner());
    out.writeProperty(ART.PROPERTY_L, art1.getL());
    out.writeProperty(ART.PROPERTY_VIGILANCE, art1.getVigilance());
    out.writeProperty(PersistConst.PROPERTY_WEIGHTS_F1_F2,
        art1.getWeightsF1toF2());
    out.writeProperty(PersistConst.PROPERTY_WEIGHTS_F2_F1,
        art1.getWeightsF2toF1());

    out.flush();

  }
View Full Code Here
TOP

Related Classes of org.encog.persist.EncogWriteHelper

  • org.encog.app.analyst.script.ScriptSave
  • org.encog.ca.universe.basic.PersistBasicUniverse
  • org.encog.EncogError
  • org.encog.ml.bayesian.PersistBayes
  • org.encog.ml.hmm.PersistHMM
  • org.encog.ml.prg.PersistPrgPopulation
  • org.encog.ml.svm.PersistSVM
  • org.encog.neural.art.PersistART1
  • org.encog.neural.bam.PersistBAM
  • org.encog.neural.cpn.PersistCPN
    • Copyright © 2018 www.massapicom. 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.