def test_circular_tuning_model(self): data = Series(self.sc.parallelize([(1, array([1.5, 2.3, 6.2, 5.1, 3.4, 2.1]))])) s = array([-pi/2, -pi/3, -pi/4, pi/4, pi/3, pi/2]) model = TuningModel.load(s, "circular") params = model.fit(data) tol = 1E-4 # to handle rounding errors assert(allclose(params.select('center').values().collect()[0], array([0.10692]), atol=tol)) assert(allclose(params.select('spread').values().collect()[0], array([1.61944]), atol=tol))
def test_gaussian_tuning_model(self): data = Series(self.sc.parallelize([(1, array([1.5, 2.3, 6.2, 5.1, 3.4, 2.1]))])) s = array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6]) model = TuningModel.load(s, "gaussian") params = model.fit(data) tol = 1E-4 # to handle rounding errors assert(allclose(params.select('center').values().collect()[0], array([0.36262]), atol=tol)) assert(allclose(params.select('spread').values().collect()[0], array([0.01836]), atol=tol))
def test_circularTuningModel(self): data = Series( self.sc.parallelize([(1, array([1.5, 2.3, 6.2, 5.1, 3.4, 2.1]))])) s = array([-pi / 2, -pi / 3, -pi / 4, pi / 4, pi / 3, pi / 2]) model = TuningModel.load(s, "circular") params = model.fit(data) tol = 1E-4 # to handle rounding errors assert (allclose(params.select('center').values().collect()[0], array([0.10692]), atol=tol)) assert (allclose(params.select('spread').values().collect()[0], array([1.61944]), atol=tol))
def test_gaussianTuningModel(self): data = Series( self.sc.parallelize([(1, array([1.5, 2.3, 6.2, 5.1, 3.4, 2.1]))])) s = array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6]) model = TuningModel.load(s, "gaussian") params = model.fit(data) tol = 1E-4 # to handle rounding errors assert (allclose(params.select('center').values().collect()[0], array([0.36262]), atol=tol)) assert (allclose(params.select('spread').values().collect()[0], array([0.01836]), atol=tol))