def test_linear_constraint_repr():
r = np.eye(10)
lc = LinearConstraint(r, require_pandas=False)
assert hex(id(lc)) in lc.__repr__()
assert '10 constraints' in lc.__repr__()
assert isinstance(lc.q, pd.Series)
assert np.all(lc.q == 0)
assert lc.q.shape == (10,)
assert isinstance(lc.r, pd.DataFrame)
assert np.all(lc.r.values == np.eye(10))
def test_linear_constraint_errors():
r = np.zeros((2, 5))
r[0, 0] = r[1, 1] = 1
r_df = pd.DataFrame(r)
q = np.zeros(2)
with pytest.raises(TypeError):
LinearConstraint(r)
with pytest.raises(TypeError):
LinearConstraint(r_df, q)
with pytest.raises(TypeError):
LinearConstraint([[0, 0, 1]])
with pytest.raises(ValueError):
LinearConstraint(r[0], require_pandas=False)
with pytest.raises(TypeError):
LinearConstraint(r_df, q)
with pytest.raises(TypeError):
LinearConstraint(r_df, [0, 0])
with pytest.raises(TypeError, match="q must be a Series or"):
LinearConstraint(r=np.eye(2), q=[0, 0], require_pandas=False)
with pytest.raises(ValueError, match="r is incompatible"):
LinearConstraint(r=np.eye(4),
q=np.zeros(4),
require_pandas=False,
num_params=5)
with pytest.raises(ValueError, match="Constraint inputs are"):
LinearConstraint(r=np.eye(4), q=np.zeros(2), require_pandas=False)
def test_linear_constraint():
r = np.zeros((2, 5))
r[0, 0] = r[1, 1] = 1
lc = LinearConstraint(r, require_pandas=False)
assert np.all(lc.t[:2] == 0)
assert np.all(np.sum(lc.t, 1)[2:] == 1)
assert np.all(lc.a == 0)
x = np.random.randn(200, 5)
y = np.random.randn(200, 1)
xt = x @ lc.t
bc = lstsq(xt, y)[0]
ec = y - xt @ bc
b = lstsq(x[:, 2:], y)[0]
e = y - x[:, 2:] @ b
assert_allclose(ec.T @ ec, e.T @ e)
lc = LinearConstraint(r, require_pandas=False)
assert np.all(lc.a == 0)
def add_constraints(self, r, q=None):
r"""
Parameters
----------
r : DataFrame
Constraint matrix. nconstraints by nparameters
q : Series, optional
Constraint values (nconstraints). If not set, set to 0
Notes
-----
Constraints are of the form
.. math ::
r \beta = q
The property `param_names` can be used to determine the order of
parameters.
"""
self._constraints = LinearConstraint(r, q=q, num_params=len(self._param_names),
require_pandas=True)
def test_linear_constraint_errors():
r = np.zeros((2, 5))
r[0, 0] = r[1, 1] = 1
r_df = pd.DataFrame(r)
q = np.zeros(2)
with pytest.raises(TypeError):
LinearConstraint(r)
with pytest.raises(TypeError):
LinearConstraint(r_df, q)
with pytest.raises(TypeError):
LinearConstraint([[0, 0, 1]])
with pytest.raises(ValueError):
LinearConstraint(r[0], require_pandas=False)
with pytest.raises(TypeError):
LinearConstraint(r_df, q)
with pytest.raises(TypeError):
LinearConstraint(r_df, [0, 0])
