def restrain(self, res, lb = -inf, ub = inf, sig = 1, scaled = False, ns =
{}):
"""Restrain an expression to specified bounds
res -- An equation string or Parameter to restrain.
lb -- The lower bound on the restraint evaluation (default -inf).
ub -- The lower bound on the restraint evaluation (default inf).
sig -- The uncertainty on the bounds (default 1).
scaled -- A flag indicating if the restraint is scaled (multiplied)
by the unrestrained point-average chi^2 (chi^2/numpoints)
(default False).
ns -- A dictionary of Parameters, indexed by name, that are used
in the equation string, but not part of the RecipeOrganizer
(default {}).
The penalty is calculated as
(max(0, lb - val, val - ub)/sig)**2
and val is the value of the calculated equation. This is multipled by
the average chi^2 if scaled is True.
Raises ValueError if ns uses a name that is already used for a
Parameter.
Raises ValueError if res depends on a Parameter that is not part of
the RecipeOrganizer and that is not defined in ns.
Returns the Restraint object for use with the 'unrestrain' method.
"""
if isinstance(res, basestring):
eqstr = res
eq = equationFromString(res, self._eqfactory, ns)
else:
eq = Equation(root = res)
eqstr = res.name
# Make and store the restraint
res = Restraint(eq, lb, ub, sig, scaled)
res.eqstr = eqstr
self.addRestraint(res)
return res
def restrain(self, res, lb=-inf, ub=inf, sig=1, scaled=False, ns={}):
"""Restrain an expression to specified bounds
res -- An equation string or Parameter to restrain.
lb -- The lower bound on the restraint evaluation (default -inf).
ub -- The lower bound on the restraint evaluation (default inf).
sig -- The uncertainty on the bounds (default 1).
scaled -- A flag indicating if the restraint is scaled (multiplied)
by the unrestrained point-average chi^2 (chi^2/numpoints)
(default False).
ns -- A dictionary of Parameters, indexed by name, that are used
in the equation string, but not part of the RecipeOrganizer
(default {}).
The penalty is calculated as
(max(0, lb - val, val - ub)/sig)**2
and val is the value of the calculated equation. This is multipled by
the average chi^2 if scaled is True.
Raises ValueError if ns uses a name that is already used for a
Parameter.
Raises ValueError if res depends on a Parameter that is not part of
the RecipeOrganizer and that is not defined in ns.
Returns the Restraint object for use with the 'unrestrain' method.
"""
if isinstance(res, basestring):
eqstr = res
eq = equationFromString(res, self._eqfactory, ns)
else:
eq = Equation(root=res)
eqstr = res.name
# Make and store the restraint
res = Restraint(eq, lb, ub, sig, scaled)
res.eqstr = eqstr
self.addRestraint(res)
return res
def testRestraint(self):
"""Test the Restraint class."""
p1 = Parameter("p1", 1)
p2 = Parameter("p2", 2)
factory = EquationFactory()
factory.registerArgument("p1", p1)
factory.registerArgument("p2", p2)
# Restrain 1 < p1 + p2 < 5
eq = equationFromString("p1 + p2", factory)
r = Restraint(eq, 1, 5)
# This should have no penalty
p1.setValue(1)
p2.setValue(1)
self.assertEqual(0, r.penalty())
# Make p1 + p2 = 0
# This should have a penalty of 1*(1 - 0)**2 = 1
p1.setValue(-1)
p2.setValue(1)
self.assertEqual(1, r.penalty())
# Make p1 + p2 = 8
# This should have a penalty of 1*(8 - 5)**2 = 9
p1.setValue(4)
p2.setValue(4)
self.assertEqual(9, r.penalty())
# Set the chi^2 to get a dynamic penalty
r.scaled = True
self.assertEqual(13.5, r.penalty(1.5))
# Make a really large number to check the upper bound
import numpy
r.ub = numpy.inf
p1.setValue(1e100)
self.assertEqual(0, r.penalty())
return
def testRestraint(self):
"""Test the Restraint class."""
p1 = Parameter("p1", 1)
p2 = Parameter("p2", 2)
factory = EquationFactory()
factory.registerArgument("p1", p1)
factory.registerArgument("p2", p2)
# Restrain 1 < p1 + p2 < 5
eq = equationFromString("p1 + p2", factory)
r = Restraint(eq, 1, 5)
# This should have no penalty
p1.setValue(1)
p2.setValue(1)
self.assertEquals(0, r.penalty())
# Make p1 + p2 = 0
# This should have a penalty of 1*(1 - 0)**2 = 1
p1.setValue(-1)
p2.setValue(1)
self.assertEquals(1, r.penalty())
# Make p1 + p2 = 8
# This should have a penalty of 1*(8 - 5)**2 = 9
p1.setValue(4)
p2.setValue(4)
self.assertEquals(9, r.penalty())
# Set the chi^2 to get a dynamic penalty
r.scaled = True
self.assertEquals(13.5, r.penalty(1.5))
# Make a really large number to check the upper bound
import numpy
r.ub = numpy.inf
p1.setValue(1e100)
self.assertEquals(0, r.penalty())
return
