def test_composed_param():
param1 = Parameter('param1', 1.)
param2 = Parameter('param2', 2.)
param3 = Parameter('param3', 3., floating=False)
param4 = Parameter(
'param4',
4.) # needed to make sure it does not only take all params as deps
a = ztf.log(3. * param1) * tf.square(param2) - param3
param_a = ComposedParameter('param_as', tensor=a)
assert isinstance(param_a.get_dependents(only_floating=True), OrderedSet)
assert param_a.get_dependents(only_floating=True) == {param1, param2}
assert param_a.get_dependents(only_floating=False) == {
param1, param2, param3
}
a_unchanged = zfit.run(a)
assert a_unchanged == zfit.run(param_a)
assert zfit.run(param2.assign(3.5))
a_changed = zfit.run(a)
assert a_changed == zfit.run(param_a)
assert a_changed != a_unchanged
with pytest.raises(LogicalUndefinedOperationError):
param_a.assign(value=5.)
with pytest.raises(LogicalUndefinedOperationError):
param_a.load(value=5., session=zfit.run.sess)
def test_param_func():
param1 = Parameter('param1', 1.)
param2 = Parameter('param2', 2.)
param3 = Parameter('param3', 3., floating=False)
param4 = Parameter('param4', 4.)
a = ztf.log(3. * param1) * tf.square(param2) - param3
func = SimpleFunc(func=lambda self, x: a * x, obs=obs1)
new_func = param4 * func
new_func_equivalent = func * param4
result1 = zfit.run(new_func.func(x=rnd_test_values))
result1_equivalent = zfit.run(new_func_equivalent.func(x=rnd_test_values))
result2 = zfit.run(func.func(x=rnd_test_values) * param4)
np.testing.assert_array_equal(result1, result2)
np.testing.assert_array_equal(result1_equivalent, result2)