def __init__(self, units, response, fixed=I, random=I):
self.units = units
self.m = len(self.units)
self.fixed = formula(fixed)
self.random = formula(random)
self.response = formula(response)
self.N = 0
for unit in self.units:
unit.Y = N.squeeze(unit.design(self.response))
unit.X = unit.design(self.fixed)
unit.Z = unit.design(self.random)
self.N += unit.X.shape[0]
# Determine size of fixed effects
d = self.units[0].design(self.fixed)
self.p = d.shape[1] # d.shape = p
self.a = N.zeros(self.p, N.float64)
# Determine size of D, and sensible initial estimates
# of sigma and D
d = self.units[0].design(self.random)
self.q = d.shape[1] # d.shape = q
self.D = N.zeros((self.q,)*2, N.float64)
self.sigma = 1.
self.dev = N.inf
def test_mul(self):
t1 = formula.term("t1")
t2 = formula.term("t2")
f = t1 * t2
self.assert_(isinstance(f, formula.formula))
intercept = formula.term("intercept")
f = t1 * intercept
self.assertEqual(str(f), str(formula.formula(t1)))
f = intercept * t1
self.assertEqual(str(f), str(formula.formula(t1)))
def __call__(self, formula, **extra):
"""
Return the corresponding design matrix from formula,
perform a check whether formula just has an intercept in it, in
which case the number of rows must be computed.
"""
if hasattr(self, 'n') and not extra.has_key('nrow'):
extra['nrow'] = self.n
return formula(namespace=self.dict, **extra)