Author: tommaso
Date: Tue Jan 10 14:16:15 2012
New Revision: 1229550
URL: http://svn.apache.org/viewvc?rev=1229550&view=rev
Log:
fixed missing parameter in NNFactory tests
Modified:
labs/yay/trunk/core/src/test/java/org/apache/yay/NeuralNetworkFactoryTest.java
Modified:
labs/yay/trunk/core/src/test/java/org/apache/yay/NeuralNetworkFactoryTest.java
URL:
http://svn.apache.org/viewvc/labs/yay/trunk/core/src/test/java/org/apache/yay/NeuralNetworkFactoryTest.java?rev=1229550&r1=1229549&r2=1229550&view=diff
==============================================================================
---
labs/yay/trunk/core/src/test/java/org/apache/yay/NeuralNetworkFactoryTest.java
(original)
+++
labs/yay/trunk/core/src/test/java/org/apache/yay/NeuralNetworkFactoryTest.java
Tue Jan 10 14:16:15 2012
@@ -41,7 +41,7 @@ public class NeuralNetworkFactoryTest {
when(weightsMatrix.getColumns()).thenReturn(new ArrayList<Long[]>());
Set<WeightsMatrix> weightsMatrixes = new HashSet<WeightsMatrix>(1);
weightsMatrixes.add(weightsMatrix);
- NeuralNetworkFactory.create(weightsMatrixes);
+ NeuralNetworkFactory.create(weightsMatrixes, new
ArrayList<TrainingExample>());
fail("an empty weight matrix has no meaning");
} catch (InvalidWeightMatrixException e) {
// everything ok
@@ -55,7 +55,7 @@ public class NeuralNetworkFactoryTest {
when(weightsMatrix.getColumns()).thenReturn(null);
Set<WeightsMatrix> weightsMatrixes = new HashSet<WeightsMatrix>(1);
weightsMatrixes.add(weightsMatrix);
- NeuralNetworkFactory.create(weightsMatrixes);
+ NeuralNetworkFactory.create(weightsMatrixes, new
ArrayList<TrainingExample>());
fail("a null weight matrix is not a valid parameter");
} catch (InvalidWeightMatrixException e) {
// everything ok
@@ -70,7 +70,7 @@ public class NeuralNetworkFactoryTest {
weightsMatrix.addColumn(new Long[]{12l});
Set<WeightsMatrix> weightsMatrixes = new HashSet<WeightsMatrix>(1);
weightsMatrixes.add(weightsMatrix);
- NeuralNetwork neuralNetwork =
NeuralNetworkFactory.create(weightsMatrixes);
+ NeuralNetwork neuralNetwork =
NeuralNetworkFactory.create(weightsMatrixes, new ArrayList<TrainingExample>());
assertNotNull(neuralNetwork);
} catch (Exception e) {
fail(e.getLocalizedMessage());
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