Java Code Examples for org.numenta.nupic.encoders.MultiEncoder#addEncoder()
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org.numenta.nupic.encoders.MultiEncoder#addEncoder() .
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Example 1
Source File: RunLayer.java From htm.java with GNU Affero General Public License v3.0 | 6 votes |
public static MultiEncoder createEncoder() { MultiEncoder encoder = MultiEncoder.builder().name("").build(); ScalarEncoder se = ScalarEncoder.builder() .n(50) .w(21) .minVal(0) .maxVal(100) .periodic(false) .clipInput(true) .name("value") .build(); encoder.addEncoder("value", se); DateEncoder de = DateEncoder.builder() .timeOfDay(21, 9.5) .name("timestamp") .build(); encoder.addEncoder("timestamp", de); return encoder; }
Example 2
Source File: LayerTest.java From htm.java with GNU Affero General Public License v3.0 | 5 votes |
@Test public void TestMakeClassifiersWithInvalidInferredFieldsKey() { // Setup Parameters Parameters p = Parameters.getAllDefaultParameters(); Map<String, Class<? extends Classifier>> inferredFieldsMap = new HashMap<>(); inferredFieldsMap.put("field1", Classifier.class); p.set(KEY.INFERRED_FIELDS, inferredFieldsMap); // Create MultiEncoder and add the fields' encoders to it MultiEncoder me = MultiEncoder.builder().name("").build(); me.addEncoder( "field1", RandomDistributedScalarEncoder.builder().resolution(1).build() ); // Create a Layer with Parameters and MultiEncoder Layer<Map<String, Object>> l = new Layer<>( p, me, new SpatialPooler(), new TemporalMemory(), true, null ); // Make sure the makeClassifiers() method throws exception due to // absence of KEY.INFERRED_FIELDS in the Parameters object try { NamedTuple nt = l.makeClassifiers(l.getEncoder()); } catch (IllegalStateException e) { assertTrue(e.getMessage().contains("Invalid Classifier class token")); } }
Example 3
Source File: LayerTest.java From htm.java with GNU Affero General Public License v3.0 | 4 votes |
@Test public void testMakeClassifiers() { // Setup Parameters Parameters p = Parameters.getAllDefaultParameters(); Map<String, Class<? extends Classifier>> inferredFieldsMap = new HashMap<>(); inferredFieldsMap.put("field1", CLAClassifier.class); inferredFieldsMap.put("field2", SDRClassifier.class); inferredFieldsMap.put("field3", null); p.set(KEY.INFERRED_FIELDS, inferredFieldsMap); // Create MultiEncoder and add the fields' encoders to it MultiEncoder me = MultiEncoder.builder().name("").build(); me.addEncoder( "field1", RandomDistributedScalarEncoder.builder().resolution(1).build() ); me.addEncoder( "field2", RandomDistributedScalarEncoder.builder().resolution(1).build() ); me.addEncoder( "field3", RandomDistributedScalarEncoder.builder().resolution(1).build() ); // Create a Layer with Parameters and MultiEncoder Layer<Map<String, Object>> l = new Layer<>( p, me, new SpatialPooler(), new TemporalMemory(), true, null ); // Make sure the makeClassifiers() method matches each // field to the specified Classifier type NamedTuple nt = l.makeClassifiers(l.getEncoder()); assertEquals(nt.get("field1").getClass(), CLAClassifier.class); assertEquals(nt.get("field2").getClass(), SDRClassifier.class); assertEquals(nt.get("field3"), null); }