def test_nuisance_down(self):
n = IMP.Particle(self.m)
Nuisance.setup_particle(n, 1.0)
Nuisance(n).set_lower(0.5)
Nuisance(n).set_upper(1.5)
n.set_value(Nuisance.get_nuisance_key(), 0.1)
self.rs.evaluate(False)
self.assertAlmostEqual(n.get_value(Nuisance.get_nuisance_key()),
0.5, delta=1e-7)
self.assertAlmostEqual(self.rs.values[0], 0.5)
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 testdmu(self):
"Test LognormalRestraint(3) mu derivative"
gr = LognormalRestraint(*self.all)
self.m.add_restraint(gr)
for i in range(100):
map(self.change_value, self.all)
self.m.evaluate(True)
self.assertAlmostEqual(
Nuisance(self.mu).get_nuisance_derivative(),
self.deriv_mu(*self.all))
def testdmu(self):
"Test GaussianRestraint(3) mu derivative"
gr = GaussianRestraint(*self.all)
for i in range(100):
map(self.change_value, self.all)
map(self.change_sign, self.locations)
gr.evaluate(True)
self.assertAlmostEqual(
Nuisance(self.mu).get_nuisance_derivative(),
self.deriv_mu(*self.all))
def testdx(self):
"Test GaussianRestraint(3) x derivative"
gr = GaussianRestraint(*self.all)
self.m.add_restraint(gr)
for i in xrange(100):
map(self.change_value, self.all)
map(self.change_sign, self.locations)
self.m.evaluate(True)
self.assertAlmostEqual(
Nuisance(self.x).get_nuisance_derivative(),
self.deriv_x(*self.all))
def change_value(self, p, min=0.1, max=100):
try:
n = Nuisance(p)
except:
return
n.set_nuisance(random.uniform(min, max))
def get_value(self, p):
try:
v = Nuisance(p).get_nuisance()
except:
v = p
return v
def change_sign(self, p):
try:
n = Nuisance(p)
except:
return
n.set_nuisance(n.get_nuisance() * (2 * random.randint(2) - 1))
