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))
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))
