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"""
Test functions for models.formula
"""
import string
import numpy as N
import numpy.random as R
import numpy.linalg as L
from numpy.testing import assert_almost_equal, NumpyTest, NumpyTestCase
from scipy.sandbox.models import utils, formula, contrast
class test_term(NumpyTestCase):
def test_init(self):
t1 = formula.term("trivial")
sqr = lambda x: x*x
t2 = formula.term("not_so_trivial", sqr, "sqr")
self.assertRaises(ValueError, formula.term, "name", termname=0)
def test_str(self):
t = formula.term("name")
s = str(t)
def test_add(self):
t1 = formula.term("t1")
t2 = formula.term("t2")
f = t1 + t2
self.assert_(isinstance(f, formula.formula))
self.assert_(f.hasterm(t1))
self.assert_(f.hasterm(t2))
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)))
class test_formula(NumpyTestCase):
def setUp(self):
self.X = R.standard_normal((40,10))
self.namespace = {}
self.terms = []
for i in range(10):
name = '%s' % string.uppercase[i]
self.namespace[name] = self.X[:,i]
self.terms.append(formula.term(name))
self.formula = self.terms[0]
for i in range(1, 10):
self.formula += self.terms[i]
self.formula.namespace = self.namespace
def test_namespace(self):
space1 = {'X':N.arange(50), 'Y':N.arange(50)*2}
space2 = {'X':N.arange(20), 'Y':N.arange(20)*2}
X = formula.term('X')
Y = formula.term('Y')
X.namespace = space1
assert_almost_equal(X(), N.arange(50))
Y.namespace = space2
assert_almost_equal(Y(), N.arange(20)*2)
f = X + Y
f.namespace = space1
self.assertEqual(f().shape, (2,50))
assert_almost_equal(Y(), N.arange(50)*2)
assert_almost_equal(X(), N.arange(50))
f.namespace = space2
self.assertEqual(f().shape, (2,20))
assert_almost_equal(Y(), N.arange(20)*2)
assert_almost_equal(X(), N.arange(20))
def test_termcolumns(self):
t1 = formula.term("A")
t2 = formula.term("B")
f = t1 + t2 + t1 * t2
def other(val):
return N.array([3.2*val,4.342*val**2, 5.234*val**3])
q = formula.quantitative(['other%d' % i for i in range(1,4)], termname='other', func=t1, transform=other)
f += q
q.namespace = f.namespace = self.formula.namespace
assert_almost_equal(q(), f()[f.termcolumns(q)])
def test_str(self):
s = str(self.formula)
def test_call(self):
x = self.formula()
self.assertEquals(N.array(x).shape, (10, 40))
def test_design(self):
x = self.formula.design()
self.assertEquals(x.shape, (40, 10))
def test_product(self):
prod = self.terms[0] * self.terms[2]
self.formula += prod
x = self.formula.design()
p = self.formula['A*C']
col = self.formula.termcolumns(prod, dict=False)
assert_almost_equal(N.squeeze(x[:,col]), self.X[:,0] * self.X[:,2])
assert_almost_equal(N.squeeze(p()), self.X[:,0] * self.X[:,2])
def test_intercept1(self):
prod = self.terms[0] * self.terms[2]
self.formula += formula.I
icol = self.formula.names().index('intercept')
assert_almost_equal(self.formula()[icol], N.ones((40,)))
def test_intercept2(self):
prod = self.terms[0] * self.terms[2]
self.formula += formula.I
icol = self.formula.names().index('intercept')
assert_almost_equal(self.formula()[icol], N.ones((40,)))
def test_intercept3(self):
prod = self.terms[0] * formula.I
prod.namespace = self.formula.namespace
assert_almost_equal(N.squeeze(prod()), self.terms[0]())
def test_contrast1(self):
term = self.terms[0] + self.terms[2]
c = contrast.Contrast(term, self.formula)
c.getmatrix()
col1 = self.formula.termcolumns(self.terms[0], dict=False)
col2 = self.formula.termcolumns(self.terms[1], dict=False)
test = [[1] + [0]*9, [0]*2 + [1] + [0]*7]
assert_almost_equal(c.matrix, test)
def test_contrast2(self):
dummy = formula.term('zero')
self.namespace['zero'] = N.zeros((40,), N.float64)
term = dummy + self.terms[2]
c = contrast.Contrast(term, self.formula)
c.getmatrix()
test = [0]*2 + [1] + [0]*7
assert_almost_equal(c.matrix, test)
def test_contrast3(self):
X = self.formula.design()
P = N.dot(X, L.pinv(X))
dummy = formula.term('noise')
resid = N.identity(40) - P
self.namespace['noise'] = N.transpose(N.dot(resid, R.standard_normal((40,5))))
terms = dummy + self.terms[2]
terms.namespace = self.formula.namespace
c = contrast.Contrast(terms, self.formula)
c.getmatrix()
self.assertEquals(c.matrix.shape, (10,))
def test_power(self):
t = self.terms[2]
t2 = t**2
t.namespace = t2.namespace = self.formula.namespace
assert_almost_equal(t()**2, t2())
def test_quantitative(self):
t = self.terms[2]
sint = formula.quantitative('t', func=t, transform=N.sin)
t.namespace = sint.namespace = self.formula.namespace
assert_almost_equal(N.sin(t()), sint())
def test_factor1(self):
f = ['a','b','c']*10
fac = formula.factor('ff', set(f))
fac.namespace = {'ff':f}
self.assertEquals(list(fac.values()), f)
def test_factor2(self):
f = ['a','b','c']*10
fac = formula.factor('ff', set(f))
fac.namespace = {'ff':f}
self.assertEquals(fac().shape, (3,30))
def test_factor3(self):
f = ['a','b','c']*10
fac = formula.factor('ff', set(f))
fac.namespace = {'ff':f}
m = fac.main_effect(reference=1)
self.assertEquals(m().shape, (2,30))
def test_factor4(self):
f = ['a','b','c']*10
fac = formula.factor('ff', set(f))
fac.namespace = {'ff':f}
m = fac.main_effect(reference=2)
r = N.array([N.identity(3)]*10)
r.shape = (30,3)
r = r.T
_m = N.array([r[0]-r[2],r[1]-r[2]])
assert_almost_equal(_m, m())
def test_contrast4(self):
f = self.formula + self.terms[5] + self.terms[5]
estimable = False
c = contrast.Contrast(self.terms[5], f)
c.getmatrix()
self.assertEquals(estimable, False)
if __name__ == "__main__":
NumpyTest().run()
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