def testdmu(self):
"Test LognormalRestraint(3) mu derivative"
gr = LognormalRestraint(*self.all)
for i in range(100):
map(self.change_value, self.all)
gr.evaluate(True)
self.assertAlmostEqual(Nuisance(self.mu).get_nuisance_derivative(),
self.deriv_mu(*self.all))
def testdsigma(self):
"Test LognormalRestraint(3) sigma derivative"
gr = LognormalRestraint(*self.all)
for i in range(100):
map(self.change_value, self.all)
gr.evaluate(True)
self.assertAlmostEqual(
Nuisance(self.sigma).get_nuisance_derivative(),
self.deriv_sigma(*self.all))
def testE(self):
"Test LognormalRestraint(3) score"
gr = LognormalRestraint(*self.all)
for i in range(100):
map(self.change_value, self.all)
e = gr.evaluate(False)
self.assertAlmostEqual(e, self.normal_e(*self.all))
def testSanityPE(self):
"Test if LognormalRestraint(13) prob is exp(-score)"
gr = LognormalRestraint(*self.all)
for i in range(100):
map(self.change_value, self.all)
self.assertAlmostEqual(gr.get_probability(),
exp(-gr.evaluate(False)), delta=0.001)
def testE(self):
"Test LognormalRestraint(3) score"
gr = LognormalRestraint(*self.all)
for i in range(100):
map(self.change_value, self.all)
e = gr.evaluate(False)
self.assertAlmostEqual(e, self.normal_e(*self.all))
def testSanityPE(self):
"Test if LognormalRestraint(13) prob is exp(-score)"
gr = LognormalRestraint(*self.all)
for i in range(100):
map(self.change_value, self.all)
self.assertAlmostEqual(gr.get_probability(),
exp(-gr.evaluate(False)),
delta=0.001)
def testSanityEP(self):
"Test if LognormalRestraint(13) score is -log(prob)"
gr = LognormalRestraint(*self.all)
for i in range(100):
map(self.change_value, self.all)
expected = gr.get_probability()
if expected == 0:
continue
self.assertAlmostEqual(-log(expected),
gr.evaluate(False), delta=0.001)
def testSanityEP(self):
"Test if LognormalRestraint(13) score is -log(prob)"
gr = LognormalRestraint(*self.all)
for i in range(100):
map(self.change_value, self.all)
expected = gr.get_probability()
if expected == 0:
continue
self.assertAlmostEqual(-log(expected),
gr.evaluate(False),
delta=0.001)