def test_pdf_no_adjustment(self):
causes = ['c']
effects = ['d']
admissable_set = []
variable_types={'a': 'u','b': 'u','c': 'u','d' : 'u'}
effect = CausalEffect(self.discrete,causes,effects,admissable_set,variable_types)
# p(d=1|do(c=0) = 0.45, p(d=1|b=0) = 0.40
p = effect.pdf(pd.DataFrame({ 'd' : [1], 'c' : [0]}))
print p
assert( abs( 0.40 - p ) < 0.02 )
def test_pdf_no_adjustment(self):
causes = ['c']
effects = ['d']
admissable_set = []
variable_types = {'a': 'u', 'b': 'u', 'c': 'u', 'd': 'u'}
effect = CausalEffect(self.discrete, causes, effects, admissable_set,
variable_types)
# p(d=1|do(c=0) = 0.45, p(d=1|b=0) = 0.40
p = effect.pdf(pd.DataFrame({'d': [1], 'c': [0]}))
print p
assert (abs(0.40 - p) < 0.02)
def test_pdf_continuous(self):
causes = ['c']
effects = ['d']
admissable_set = ['a']
variable_types={'a': 'c','b': 'c','c': 'c','d' : 'c'}
effect = CausalEffect(self.X,causes,effects,admissable_set,variable_types)
c = np.mean(effect.support['c'])
d = np.mean(effect.support['d'])
e1 = effect.pdf(pd.DataFrame({ 'd' : [d], 'c' : [ 0.9 * c]}))
e2 = effect.pdf(pd.DataFrame({ 'd' : [d], 'c' : [ 1.1 * c]}))
print e2, e1, e2 - e1, (e2 - e1) / e2
assert( abs(e2 - e1) / e2 < 0.05 )
def test_pdf_continuous(self):
causes = ['c']
effects = ['d']
admissable_set = ['a']
variable_types = {'a': 'c', 'b': 'c', 'c': 'c', 'd': 'c'}
effect = CausalEffect(self.X, causes, effects, admissable_set,
variable_types)
c = np.mean(effect.support['c'])
d = np.mean(effect.support['d'])
e1 = effect.pdf(pd.DataFrame({'d': [d], 'c': [0.9 * c]}))
e2 = effect.pdf(pd.DataFrame({'d': [d], 'c': [1.1 * c]}))
print e2, e1, e2 - e1, (e2 - e1) / e2
assert (abs(e2 - e1) / e2 < 0.05)
