def setParameter(self,parametername,parametervalue):
if not parametername in ['maxdepth','mindepth','randomseed']:
print __doc__
raise Exception("Invalid parameter '%s' for gameguidance." % parametername)
GuidanceBase.setParameter(self,parametername,parametervalue)
if parametername=='randomseed':
self._rndchoose=random.Random(parametervalue).choice
def setParameter(self,parametername,parametervalue):
if not parametername in ['randomseed']:
print __doc__
raise Exception("Invalid parameter '%s' for gameguidance." % parametername)
GuidanceBase.setParameter(self,parametername,parametervalue)
if parametername=='randomseed':
self._rndchoose=random.Random(parametervalue).choice
def setParameter(self,parametername,parametervalue):
if not parametername in ['lookahead','randomseed','rerouteafter']:
print __doc__
raise Exception("Invalid parameter '%s' for gameguidance." % parametername)
GuidanceBase.setParameter(self,parametername,parametervalue)
if parametername=='randomseed':
self._rndchoose=random.Random(parametervalue).choice
elif parametername=='rerouteafter':
self._steps_to_reroute=self.getParameter(parametername)
def setParameter(self, paramname, paramvalue):
accepted = ("numtabuactions", "numtabustates", "numtabutransitions")
if paramname == "numtabuactions":
self._NUM_TABU_ACTIONS = self._parseSize(paramname, paramvalue)
elif paramname == "numtabustates":
self._NUM_TABU_STATES = self._parseSize(paramname, paramvalue)
elif paramname == "numtabutransitions":
self._NUM_TABU_TRANSITIONS = self._parseSize(paramname, paramvalue)
else:
print __doc__
raise Exception("Invalid parameter '%s' for tabuguidance. Accepted parameters: %s" % paramname, accepted)
GuidanceBase.setParameter(self, paramname, paramvalue)
def setParameter(self, paramname, paramvalue):
accepted = ("numtabuactions", "numtabustates", "numtabutransitions")
if paramname == 'numtabuactions':
self._NUM_TABU_ACTIONS = self._parseSize(paramname, paramvalue)
elif paramname == 'numtabustates':
self._NUM_TABU_STATES = self._parseSize(paramname, paramvalue)
elif paramname == 'numtabutransitions':
self._NUM_TABU_TRANSITIONS = self._parseSize(paramname, paramvalue)
else:
print __doc__
raise Exception(
"Invalid parameter '%s' for tabuguidance. Accepted parameters: %s"
% paramname, accepted)
GuidanceBase.setParameter(self, paramname, paramvalue)
def setParameter(self, name, value):
accepted = ("transitionweight", "searchorder", "searchdepth",
"maxtransitions", "searchconstraint")
if name == "transitionweight":
if isinstance(value, str) and value.startswith('kw:'):
kww = float(value[3:])
self._transitionweight = \
lambda t: kww if 'kw_' in str(t.getAction()) else 0
else:
if value < 0:
self.log("WARNING! Negative transition weight " +
"doesn't make sense!")
self._transitionweight = lambda t: value
elif name == "searchorder":
if value == "bestfirst":
self._toHeap = lambda p, badness: (badness, len(p), p)
self._fromHeap = lambda values: (values[2], values[0])
elif value == "shortestfirst":
self._toHeap = lambda p, badness: (len(p), badness, p)
self._fromHeap = lambda values: (values[2], values[1])
else:
raise ValueError("Invalid searchorder: '%s'" % (value, ))
elif name in ("searchdepth", "searchradius"):
self._searchDepth = value
elif name == "maxtransitions":
self._maxTransitions = value
elif name == "greedy":
self._greedy = value
elif name == "searchconstraint":
if value == "nocrossingpaths":
self._seco = NO_CROSSING_PATHS
elif value == "noloops":
self._seco = NO_LOOPS
elif value == "noconstraint":
self._seco = NONE
else:
raise ValueError("Invalid searchconstraint '%s'" % value)
else:
print __doc__
raise ValueError("Invalid parameter '%s' for newguidance. " %
name +
"Accepted parameters: %s" % ",".join(accepted))
GuidanceBase.setParameter(self, name, value)
def setParameter(self, name, value):
accepted = ("transitionweight", "searchorder", "searchdepth", "maxtransitions", "searchconstraint")
if name == "transitionweight":
if isinstance(value, str) and value.startswith("kw:"):
kww = float(value[3:])
self._transitionweight = lambda t: kww if "kw_" in str(t.getAction()) else 0
else:
if value < 0:
self.log("WARNING! Negative transition weight " + "doesn't make sense!")
self._transitionweight = lambda t: value
elif name == "searchorder":
if value == "bestfirst":
self._toHeap = lambda p, badness: (badness, len(p), p)
self._fromHeap = lambda values: (values[2], values[0])
elif value == "shortestfirst":
self._toHeap = lambda p, badness: (len(p), badness, p)
self._fromHeap = lambda values: (values[2], values[1])
else:
raise ValueError("Invalid searchorder: '%s'" % (value,))
elif name in ("searchdepth", "searchradius"):
self._searchDepth = value
elif name == "maxtransitions":
self._maxTransitions = value
elif name == "greedy":
self._greedy = value
elif name == "searchconstraint":
if value == "nocrossingpaths":
self._seco = NO_CROSSING_PATHS
elif value == "noloops":
self._seco = NO_LOOPS
elif value == "noconstraint":
self._seco = NONE
else:
raise ValueError("Invalid searchconstraint '%s'" % value)
else:
print __doc__
raise ValueError(
"Invalid parameter '%s' for newguidance. " % name + "Accepted parameters: %s" % ",".join(accepted)
)
GuidanceBase.setParameter(self, name, value)
