@Before public void setup() { random = new KeanuRandom(1); }
@Before public void setup() { random = new KeanuRandom(1); }
@Before public void setup() { random = new KeanuRandom(1); }
@Before public void setup() { random = new KeanuRandom(1); }
@Before public void setup() { random = new KeanuRandom(1); }
@Before public void setup() { random = new KeanuRandom(1); }
@Before public void setup() { random = new KeanuRandom(1); }
@Before public void setup() { random = new KeanuRandom(1); }
@Before public void setup() { random = new KeanuRandom(1); }
@Before public void setup() { this.random = new KeanuRandom(1); }
@Before public void setup() { random = new KeanuRandom(1); t1 = DoubleTensor.create(new double[]{0., 0.5, 0.8, 0.2}, 2, 2); }
@Before public void setup() { random = new KeanuRandom(1); UniformVertex testUniformVertex = new UniformVertex(new long[]{1, N}, lowerBound, upperBound); samples.addAll(testUniformVertex.sample(random).asFlatList()); }
@Before public void mockFilesToReadModelOutput() throws IOException { random = new KeanuRandom(1); weatherModel = new SimpleWeatherModel(inputToModel); inputToModel = new ConstantDoubleVertex(25.); }
@Before public void setup() { random = new KeanuRandom(1); v1 = new BernoulliVertex(pV1); v2 = new BernoulliVertex(pV2); }
@Test public void randomNumberGenerationIsPlatformIndependent() { KeanuRandom keanuRandom = new KeanuRandom(1); assertEquals(keanuRandom.nextDouble(), new MersenneTwister(1L).nextDouble()); assertEquals(keanuRandom.nextDouble(), 0.41782887182714457, 1e-16); } }
@Before public void setup() { random = new KeanuRandom(1); v1 = new BernoulliVertex(pV1); v2 = new BernoulliVertex(pV2); }
@Before public void setup() { random = new KeanuRandom(1); UniformIntVertex testUniformVertex = new UniformIntVertex(new long[]{1, N}, lowerBound, upperBound); samples.addAll(testUniformVertex.sample(random).asFlatList()); }
@Before public void setup() { random = new KeanuRandom(1); infectedOysters = new BernoulliVertex(0.4); infectedLamb = new BernoulliVertex(0.4); infectedToilet = new BernoulliVertex(0.1); }
@Before public void setup() { random = new KeanuRandom(1); xTrain = generateX(NUM_SAMPLES_TRAINING); yTrain = generateY(xTrain); xTest = generateX(NUM_SAMPLES_TESTING); yTest = generateY(xTest); }
@Before public void setup() { random = new KeanuRandom(1); A = new GaussianVertex(5, 1); A.setValue(5.0); B = new GaussianVertex(2, 1); B.setValue(2.0); C = A.plus(B); D = new GaussianVertex(C, 1); D.observe(7.5); }