Merge pull request #357 from cogmission/v0.6.5-alpha-prep

prep for new version

Author: rhyolight

build.gradle

@@ -4,15 +4,15 @@ apply plugin: 'eclipse'
 apply plugin: 'signing'
 
 group = 'org.numenta'
-version = '0.6.5-SNAPSHOT'
+version = '0.6.5'
 archivesBaseName = 'htm.java'
 
 sourceCompatibility = 1.8
 targetCompatibility = 1.8
 
 jar {
     manifest {
-        attributes 'Implementation-Title': 'htm.java', 'Implementation-Version': '0.6.5-SNAPSHOT'
+        attributes 'Implementation-Title': 'htm.java', 'Implementation-Version': '0.6.5'
     }
 }
 

pom.xml

@@ -4,7 +4,7 @@
 
 	<groupId>org.numenta</groupId>
 	<artifactId>htm.java</artifactId>
-	<version>0.6.5-SNAPSHOT</version>
+	<version>0.6.5</version>
 	<name>htm.java</name>
 	<description>The Java version of Numenta's HTM technology</description>
 

src/test/java/org/numenta/nupic/network/LayerTest.java

@@ -1214,6 +1214,115 @@ public void onNext(Inference i) {
             e.printStackTrace();
         }
     }
+    
+    @Test
+    public void testMissingEncoderMap() {
+        Parameters p = NetworkTestHarness.getParameters().copy();
+        //p = p.union(NetworkTestHarness.getHotGymTestEncoderParams());
+        p.setParameterByKey(KEY.RANDOM, new MersenneTwister(42));
+        p.setParameterByKey(KEY.COLUMN_DIMENSIONS, new int[] { 2048 });
+        p.setParameterByKey(KEY.POTENTIAL_RADIUS, 200);
+        p.setParameterByKey(KEY.INHIBITION_RADIUS, 50);
+        p.setParameterByKey(KEY.GLOBAL_INHIBITIONS, true);
+
+//        System.out.println(p);
+
+        Map<String, Object> params = new HashMap<>();
+        params.put(KEY_MODE, Mode.PURE);
+        params.put(KEY_WINDOW_SIZE, 3);
+        params.put(KEY_USE_MOVING_AVG, true);
+        Anomaly anomalyComputer = Anomaly.create(params);
+
+        Layer<?> l = Network.createLayer("TestLayer", p)
+            .alterParameter(KEY.AUTO_CLASSIFY, true)
+            .add(anomalyComputer)
+            .add(new TemporalMemory())
+            .add(new SpatialPooler())
+            .add(Sensor.create(
+                FileSensor::create, 
+                SensorParams.create(
+                    Keys::path, "", ResourceLocator.path("rec-center-hourly-small.csv"))));
+
+        l.getConnections().printParameters();
+
+        l.subscribe(new Observer<Inference>() {
+            @Override public void onCompleted() {}
+            @Override public void onError(Throwable e) { System.out.println("error: " + e.getMessage()); e.printStackTrace();}
+            @Override
+            public void onNext(Inference i) {
+                if(flowReceived) return; // No need to set this value multiple times
+
+                flowReceived = i.getClassifiers().size() == 4 &&
+                    i.getClassifiers().get("timestamp") != null &&
+                        i.getClassifiers().get("consumption") != null;
+            }
+        });
+        
+        try {
+            l.close();
+            fail();
+        }catch(Exception e) {
+            assertEquals("Cannot initialize this Sensor's MultiEncoder with a null settings", e.getMessage());
+        }
+
+        try {
+            assertFalse(flowReceived);
+        }catch(Exception e) {
+            e.printStackTrace();
+        }
+        
+        ////////////////// Test catch with no Sensor ////////////////////
+        
+        p = NetworkTestHarness.getParameters().copy();
+        //p = p.union(NetworkTestHarness.getHotGymTestEncoderParams());
+        p.setParameterByKey(KEY.RANDOM, new MersenneTwister(42));
+        p.setParameterByKey(KEY.COLUMN_DIMENSIONS, new int[] { 2048 });
+        p.setParameterByKey(KEY.POTENTIAL_RADIUS, 200);
+        p.setParameterByKey(KEY.INHIBITION_RADIUS, 50);
+        p.setParameterByKey(KEY.GLOBAL_INHIBITIONS, true);
+
+        params = new HashMap<>();
+        params.put(KEY_MODE, Mode.PURE);
+        params.put(KEY_WINDOW_SIZE, 3);
+        params.put(KEY_USE_MOVING_AVG, true);
+        anomalyComputer = Anomaly.create(params);
+
+        l = Network.createLayer("TestLayer", p)
+            .alterParameter(KEY.AUTO_CLASSIFY, true)
+            .add(anomalyComputer)
+            .add(new TemporalMemory())
+            .add(new SpatialPooler())
+            .add(anomalyComputer)
+            .add(MultiEncoder.builder().name("").build());
+        
+        l.getConnections().printParameters();
+
+        l.subscribe(new Observer<Inference>() {
+            @Override public void onCompleted() {}
+            @Override public void onError(Throwable e) { System.out.println("error: " + e.getMessage()); e.printStackTrace();}
+            @Override
+            public void onNext(Inference i) {
+                if(flowReceived) return; // No need to set this value multiple times
+
+                flowReceived = i.getClassifiers().size() == 4 &&
+                    i.getClassifiers().get("timestamp") != null &&
+                        i.getClassifiers().get("consumption") != null;
+            }
+        });
+        
+        try {
+            l.close();
+            fail();
+        }catch(Exception e) {
+            assertEquals("No field encoding map found for specified MultiEncoder", e.getMessage());
+        }
+
+        try {
+            assertFalse(flowReceived);
+        }catch(Exception e) {
+            e.printStackTrace();
+        }
+    }
 
     private Parameters getArrayTestParams() {
         Map<String, Map<String, Object>> fieldEncodings = setupMap(

vocabulary.dictionary

@@ -214,3 +214,5 @@ depolarisation
 feedforward
 favour
 geo
+menuitem
+jfxtras