def _decorate_objective(self, cost, ExtraArgs=None):
"""decorate cost function with bounds, penalties, monitors, etc"""
#print ("@", cost, ExtraArgs, max)
raw = cost
if ExtraArgs is None: ExtraArgs = ()
from python_map import python_map
if self._map != python_map:
#FIXME: EvaluationMonitor fails for MPI, throws error for 'pp'
from mystic.monitors import Null
evalmon = Null()
else: evalmon = self._evalmon
fcalls, cost = wrap_function(cost, ExtraArgs, evalmon)
if self._useStrictRange:
indx = list(self.popEnergy).index(self.bestEnergy)
ngen = self.generations #XXX: no random if generations=0 ?
for i in range(self.nPop):
self.population[i] = self._clipGuessWithinRangeBoundary(self.population[i], (not ngen) or (i is indx))
cost = wrap_bounds(cost, self._strictMin, self._strictMax)
cost = wrap_penalty(cost, self._penalty)
if self._reducer:
#cost = reduced(*self._reducer)(cost) # was self._reducer = (f,bool)
cost = reduced(self._reducer, arraylike=True)(cost)
# hold on to the 'wrapped' and 'raw' cost function
self._cost = (cost, raw, ExtraArgs)
self._live = True
return cost
def _decorate_objective(self, cost, ExtraArgs=None):
"""decorate the cost function with bounds, penalties, monitors, etc"""
#print("@%r %r %r" % (cost, ExtraArgs, max))
raw = cost
if ExtraArgs is None: ExtraArgs = ()
self._fcalls, cost = wrap_function(cost, ExtraArgs, self._evalmon)
if self._useStrictRange:
if self.generations:
#NOTE: pop[0] was best, may not be after resetting simplex
for i, j in enumerate(self._setSimplexWithinRangeBoundary()):
self.population[i + 1] = self.population[0].copy()
self.population[i + 1][i] = j
else:
self.population[0] = self._clipGuessWithinRangeBoundary(
self.population[0])
cost = wrap_bounds(cost, self._strictMin, self._strictMax)
cost = wrap_penalty(cost, self._penalty)
cost = wrap_nested(cost, self._constraints)
if self._reducer:
#cost = reduced(*self._reducer)(cost) # was self._reducer = (f,bool)
cost = reduced(self._reducer, arraylike=True)(cost)
# hold on to the 'wrapped' and 'raw' cost function
self._cost = (cost, raw, ExtraArgs)
self._live = True
return cost
def _decorate_objective(self, cost, ExtraArgs=None):
"""decorate cost function with bounds, penalties, monitors, etc"""
#print("@%r %r %r" % (cost, ExtraArgs, max))
raw = cost
if ExtraArgs is None: ExtraArgs = ()
from mystic.python_map import python_map
if self._map != python_map:
#FIXME: EvaluationMonitor fails for MPI, throws error for 'pp'
from mystic.monitors import Null
evalmon = Null()
else:
evalmon = self._evalmon
fcalls, cost = wrap_function(cost, ExtraArgs, evalmon)
if self._useStrictRange:
indx = list(self.popEnergy).index(self.bestEnergy)
ngen = self.generations #XXX: no random if generations=0 ?
for i in range(self.nPop):
self.population[i] = self._clipGuessWithinRangeBoundary(
self.population[i], (not ngen) or (i is indx))
cost = wrap_bounds(cost, self._strictMin, self._strictMax)
cost = wrap_penalty(cost, self._penalty)
if self._reducer:
#cost = reduced(*self._reducer)(cost) # was self._reducer = (f,bool)
cost = reduced(self._reducer, arraylike=True)(cost)
# hold on to the 'wrapped' and 'raw' cost function
self._cost = (cost, raw, ExtraArgs)
self._live = True
return cost
def _RegisterObjective(self, cost, ExtraArgs=None):
"""decorate cost function with bounds, penalties, monitors, etc"""
if ExtraArgs == None: ExtraArgs = ()
self._fcalls, cost = wrap_function(cost, ExtraArgs, self._evalmon)
if self._useStrictRange:
for i in range(self.nPop):
self.population[i] = self._clipGuessWithinRangeBoundary(self.population[i])
cost = wrap_bounds(cost, self._strictMin, self._strictMax)
cost = wrap_penalty(cost, self._penalty)
# hold on to the 'wrapped' cost function
self._cost = (cost, ExtraArgs)
return cost
def _RegisterObjective(self, cost, ExtraArgs=None):
"""decorate cost function with bounds, penalties, monitors, etc"""
if ExtraArgs == None: ExtraArgs = ()
self._fcalls, cost = wrap_function(cost, ExtraArgs, self._evalmon)
if self._useStrictRange:
for i in range(self.nPop):
self.population[i] = self._clipGuessWithinRangeBoundary(self.population[i])
cost = wrap_bounds(cost, self._strictMin, self._strictMax)
cost = wrap_penalty(cost, self._penalty)
cost = wrap_nested(cost, self._constraints)
if self._reducer:
#cost = reduced(*self._reducer)(cost) # was self._reducer = (f,bool)
cost = reduced(self._reducer, arraylike=True)(cost)
# hold on to the 'wrapped' cost function
self._cost = (cost, ExtraArgs)
return cost
def _RegisterObjective(self, cost, ExtraArgs=None):
"""decorate cost function with bounds, penalties, monitors, etc"""
if ExtraArgs == None: ExtraArgs = ()
#FIXME: EvaluationMonitor fails for MPI, throws error for 'pp'
from python_map import python_map
if self._map != python_map:
self._fcalls = [0] #FIXME: temporary patch for removing the following line
else:
self._fcalls, cost = wrap_function(cost, ExtraArgs, self._evalmon)
if self._useStrictRange:
for i in range(self.nPop):
self.population[i] = self._clipGuessWithinRangeBoundary(self.population[i])
cost = wrap_bounds(cost, self._strictMin, self._strictMax)
cost = wrap_penalty(cost, self._penalty)
# hold on to the 'wrapped' cost function
self._cost = (cost, ExtraArgs)
return cost
def _decorate_objective(self, cost, ExtraArgs=None):
"""decorate cost function with bounds, penalties, monitors, etc"""
#print ("@", cost, ExtraArgs, max)
raw = cost
if ExtraArgs is None: ExtraArgs = ()
self._fcalls, cost = wrap_function(cost, ExtraArgs, self._evalmon)
if self._useStrictRange:
indx = list(self.popEnergy).index(self.bestEnergy)
ngen = self.generations #XXX: no random if generations=0 ?
for i in range(self.nPop):
self.population[i] = self._clipGuessWithinRangeBoundary(self.population[i], (not ngen) or (i is indx))
cost = wrap_bounds(cost, self._strictMin, self._strictMax)
cost = wrap_penalty(cost, self._penalty)
if self._reducer:
#cost = reduced(*self._reducer)(cost) # was self._reducer = (f,bool)
cost = reduced(self._reducer, arraylike=True)(cost)
# hold on to the 'wrapped' and 'raw' cost function
self._cost = (cost, raw, ExtraArgs)
self._live = True
return cost
def _decorate_objective(self, cost, ExtraArgs=None):
"""decorate cost function with bounds, penalties, monitors, etc"""
#print("@%r %r %r" % (cost, ExtraArgs, max))
raw = cost
if ExtraArgs is None: ExtraArgs = ()
self._fcalls, cost = wrap_function(cost, ExtraArgs, self._evalmon)
if self._useStrictRange:
indx = list(self.popEnergy).index(self.bestEnergy)
ngen = self.generations #XXX: no random if generations=0 ?
for i in range(self.nPop):
self.population[i] = self._clipGuessWithinRangeBoundary(self.population[i], (not ngen) or (i is indx))
cost = wrap_bounds(cost, self._strictMin, self._strictMax)
cost = wrap_penalty(cost, self._penalty)
if self._reducer:
#cost = reduced(*self._reducer)(cost) # was self._reducer = (f,bool)
cost = reduced(self._reducer, arraylike=True)(cost)
# hold on to the 'wrapped' and 'raw' cost function
self._cost = (cost, raw, ExtraArgs)
self._live = True
return cost
def _decorate_objective(self, cost, ExtraArgs=None):
"""decorate the cost function with bounds, penalties, monitors, etc
input::
- cost is the objective function, of the form y = cost(x, *ExtraArgs),
where x is a candidate solution, and ExtraArgs is the tuple of positional
arguments required to evaluate the objective."""
#print("@%r %r %r" % (cost, ExtraArgs, max))
evalmon = self._evalmon
raw = cost
if ExtraArgs is None: ExtraArgs = ()
self._fcalls, cost = wrap_function(cost, ExtraArgs, evalmon)
if self._useStrictRange:
if self.generations:
#NOTE: pop[0] was best, may not be after resetting simplex
for i, j in enumerate(self._setSimplexWithinRangeBoundary()):
self.population[i + 1] = self.population[0].copy()
self.population[i + 1][i] = j
else:
self.population[0] = self._clipGuessWithinRangeBoundary(
self.population[0])
cost = wrap_bounds(cost, self._strictMin,
self._strictMax) #XXX: remove?
from mystic.constraints import and_
constraints = and_(self._constraints,
self._strictbounds,
onfail=self._strictbounds)
else:
constraints = self._constraints
cost = wrap_penalty(cost, self._penalty)
cost = wrap_nested(cost, constraints)
if self._reducer:
#cost = reduced(*self._reducer)(cost) # was self._reducer = (f,bool)
cost = reduced(self._reducer, arraylike=True)(cost)
# hold on to the 'wrapped' and 'raw' cost function
self._cost = (cost, raw, ExtraArgs)
self._live = True
return cost
def _decorate_objective(self, cost, ExtraArgs=None):
"""decorate the cost function with bounds, penalties, monitors, etc"""
#print ("@", cost, ExtraArgs, max)
raw = cost
if ExtraArgs is None: ExtraArgs = ()
self._fcalls, cost = wrap_function(cost, ExtraArgs, self._evalmon)
if self._useStrictRange:
if self.generations:
#NOTE: pop[0] was best, may not be after resetting simplex
for i,j in enumerate(self._setSimplexWithinRangeBoundary()):
self.population[i+1] = self.population[0].copy()
self.population[i+1][i] = j
else:
self.population[0] = self._clipGuessWithinRangeBoundary(self.population[0])
cost = wrap_bounds(cost, self._strictMin, self._strictMax)
cost = wrap_penalty(cost, self._penalty)
cost = wrap_nested(cost, self._constraints)
if self._reducer:
#cost = reduced(*self._reducer)(cost) # was self._reducer = (f,bool)
cost = reduced(self._reducer, arraylike=True)(cost)
# hold on to the 'wrapped' and 'raw' cost function
self._cost = (cost, raw, ExtraArgs)
self._live = True
return cost