plotex/plotex.py at master · stormi/plotex · GitHub

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# PlotEx: a tool for exploring puzzle plot constraints

# Version 1.1.1

# Andrew Plotkin <erkyrath@eblong.com>

# This script is in the public domain.

# For a full description, see <http://eblong.com/zarf/plotex/>

# This is the Python 2 version. For the Python 3 version, see plotex3.py.

# If you have Python 3 installed, you'll have to copy plotex3.py over

# plotex.py, or else change the "import plotex" lines in the examples to

# "import plotex3".

import sys

import optparse

class TrackMetaClass(type):

'''TrackMetaClass does some Python magic to catalog the members of a

class as it's being defined. We use this to catalog a scenario and set

it up properly. (Thanks to Zack Weinberg and Aahz for magic support.)

'''

def __init__(cls, name, bases, dict):

super(TrackMetaClass, cls).__init__(name, bases, dict)

states = {}

actions = {}

tests = {}

for (key, val) in dict.items():

if (key.startswith('_')):

continue

if (isinstance(val, Action)):

val.name = key

actions[key] = val

if (isinstance(val, State)):

val.name = key

states[key] = val

if (isinstance(val, Test)):

val.name = key

tests[key] = val

types = merge_typelists_of(actions.values() + states.values() + tests.values())

senses = {}

for key in types:

if (key is None):

# The Once action sometimes lacks a key. In those cases, it will

# generate a negative sense boolean.

continue

senses[key] = (not key.startswith('_'))

cls._statemap = states

cls._actionmap = actions

cls._testmap = tests

cls._typemap = types

cls._sensemap = senses

for val in states.values():

val.scenario = cls

for val in actions.values():

val.set_scenario(cls)

for val in tests.values():

val.set_scenario(cls)

def merge_typelists_of(ls):

'''Given a list of objects (actions and states), pull the type map

out of each one and return the union of all the maps. If they're not

all consistent, raise an exception.

'''

typedic = {}

for obj in ls:

for (key, val) in obj.typelist.items():

oldval = typedic.get(key)

if (oldval is None):

typedic[key] = val

continue

if (val != oldval):

raise Exception('Inconsistent types for key "%s"' % (key,))

return typedic

def infer_typelist(dic):

'''Given a dictionary of qualities (as you'd see it in a State or

Set definition), create a type map describing them. Each quality

must be a number (int), string (str), boolean (bool), or sequence

(set).

'''

res = {}

for (key, val) in dic.items():

typ = type(val)

if (typ in (int, long)):

res[key] = int

elif (typ in (str, unicode)):

res[key] = str

elif (typ is bool):

res[key] = bool

elif (typ in (tuple, list, set, frozenset)):

res[key] = set

else:

raise Exception('Value must be int, str, set, or bool: %s' % repr(val))

return res

def parse_states(scenario, optls):

'''Given a list of strings (as given on the command line), parse them

as states. Arguments can be separate strings or comma-separated.

Unrecognized states throw exceptions.

'''

res = set()

for val in optls:

ls = [ key.strip() for key in val.split(',') ]

for key in ls:

state = scenario._statemap.get(key)

if (not state):

raise Exception('No such state: "%s"' % (key,))

res.add(state)

return res

def parse_actions(scenario, optls):

'''Given a list of strings (as given on the command line), parse them

as actions. Arguments can be separate strings or comma-separated.

Unrecognized actions throw exceptions.

'''

res = set()

for val in optls:

ls = [ key.strip() for key in val.split(',') ]

for key in ls:

action = scenario._actionmap.get(key)

if (not action):

raise Exception('No such action: "%s"' % (key,))

res.add(action)

return res

def parse_qualities(scenario, optls):

'''Given a list of strings (as given on the command line), parse them

as qualities. Arguments can be separate strings or comma-separated.

Unrecognized qualities throw exceptions.

'''

res = set()

for val in optls:

ls = [ key.strip() for key in val.split(',') ]

for key in ls:

val = scenario._typemap.get(key)

if (not val):

raise Exception('No such quality: "%s"' % (key,))

res.add(key)

return res

def parse_tests(scenario, optls):

'''Given a list of strings (as given on the command line), parse them

as tests. Arguments can be separate strings or comma-separated.

Unrecognized tests throw exceptions.

'''

res = set()

for val in optls:

ls = [ key.strip() for key in val.split(',') ]

for key in ls:

test = scenario._testmap.get(key)

if (not test):

raise Exception('No such test: "%s"' % (key,))

res.add(test)

return res

class Graph:

'''Graph: The context structure for doing a run. You set up a graph

with some starting states, then tell it to run with some actions.

The graph object can also display its results neatly.

'''

def __init__(self, scenario, states):

self.scenario = scenario

self.startstates = states

self.states = {}

self.statels = []

self.seenmaxes = set()

self.maxls = []

def run(self, actions, limit=10000, noopt=False):

'''run(): Do the run. The results are stored within the Graph.

'''

improveactions = actions

changeactions = actions

if (not noopt):

improveactions = [ action for action in actions if (action.equivtype != EQUIV_LOSS) ]

changeactions = [ action for action in actions if (action.equivtype in (EQUIV_LOSS, EQUIV_UNKNOWN)) ]

#print '%d actions filtered to %d improve, %d change' % (len(actions), len(improveactions), len(changeactions))

newstates = []

for state in self.startstates:

newstate = self.find_maximal_state(state, improveactions)

if (newstate in newstates):

continue

newstates.append(newstate)

self.seenmaxes.add(newstate)

newnode = self.states[newstate]

newnode.history = self.states[state].maxing_actions

while (newstates):

if (len(self.seenmaxes) >= limit):

raise Exception('More than %d states!' % (limit,))

oldstate = newstates.pop(0)

oldnode = self.states[oldstate]

self.maxls.append(oldstate)

for action in changeactions:

newstate = action(oldstate)

if (not newstate):

continue

maxstate = self.find_maximal_state(newstate, improveactions)

if (maxstate == oldstate):

continue

if (maxstate in oldnode.ancestors):

continue

aclist = (action,) + self.states[newstate].maxing_actions

maxnode = self.states[maxstate]

if (maxstate in self.seenmaxes):

maxnode.ancestors.update(oldnode.ancestors)

maxnode.ancestors.add(oldstate)

else:

newstates.append(maxstate)

self.seenmaxes.add(maxstate)

maxnode.history = oldnode.history + aclist

maxnode.ancestors.update(oldnode.ancestors)

maxnode.ancestors.add(oldstate)

oldnode.children.append( (aclist, maxstate) )

maxnode.parents.append( (aclist, oldstate) )

def find_maximal_state(self, state, actions):

'''Do every possible actions that is strictly an improvement --

that is, every action that produces a better state. Return the

resulting state.

'''

node = self.states.get(state)

if (node):

return node.maximal

statechain = []

actchain = []

while True:

node = GraphNode(state)

self.states[state] = node

self.statels.append(state)

statechain.append(state)

found_improvement = False

for action in actions:

newstate = action(state)

if (not newstate):

continue

if (newstate == state):

continue

if not(newstate > state):

continue

# That action was an improvement

actchain.append(action)

found_improvement = True

if (newstate in self.states):

# We've run into a known state. (Might be maximal, or

# it might have its own maximal state.)

gotstate = newstate

gotnode = self.states[gotstate]

pos = 0

for newstate in statechain:

newnode = self.states[newstate]

newnode.maximal = gotnode.maximal

newnode.maxing_actions = tuple(actchain[pos:]) + gotnode.maxing_actions

pos = pos+1

return gotnode.maximal

state = newstate

break

if (not found_improvement):

# This state is maximal.

pos = 0

for newstate in statechain:

newnode = self.states[newstate]

newnode.maximal = state

newnode.maxing_actions = tuple(actchain[pos:])

pos = pos+1

self.states[state].is_maximal = True

return state

def has(self, state):

return self.states.has_key(state)

def showlist(self, showmed=True, filters=[], histories=[]):

outls = []

for state in self.maxls:

node = self.states[state]

if (not showmed):

if (node.children):

continue

filtered = False

for filter in filters:

if (not state.dic.has_key(filter)):

filtered = True

if (filtered):

continue

for histac in histories:

if (histac not in node.history):

filtered = True

if (filtered):

continue

outls.append(state)

trumped = None

if (len(outls) <= 20):

trumped = set()

for state1 in outls:

if (state1 in trumped):

continue

for state2 in outls:

if (state2 in trumped):

continue

if (state1 == state2):

continue

if (state2 < state1):

trumped.add(state2)

return (outls, trumped)

def display(self, showmed=False, showin=False, showout=False, showdiff=False, showcount=False, filters=[], histories=[]):

(outls, trumped) = self.showlist(showmed, filters, histories)

if (not showcount):

difffrom = None

if (showdiff and len(outls) >= 2):

difffrom = outls[0]

for state in outls[1:]:

difffrom = difffrom & state

print '(common state: %s)' % (difffrom,)

for state in outls:

node = self.states[state]

val = ''

if (trumped is not None and state not in trumped):

val = '*'

if (difffrom is None):

print val+str(state)

else:

print val+state.printdiff(difffrom)

acs = [ ac.name for ac in node.history]

print ' (%d): %s' % (len(node.history), ', '.join(acs),)

#print ' ### ancs:', list(node.ancestors)

if (showin):

subls = [ '<= %s : %s' % (substate, ', '.join([ ac.name for ac in acls ])) for (acls, substate) in node.parents ]

for val in subls:

print ' %s' % (val,)

if (showout):

subls = [ '=> %s : %s' % (', '.join([ ac.name for ac in acls ]), substate) for (acls, substate) in node.children ]

for val in subls:

print ' %s' % (val,)

if (showmed):

summary = '%d maximal states' % (len(outls),)

else:

summary = '%d terminal states' % (len(outls),)

if (trumped):

val = len(outls) - len(trumped)

summary += ' (%d preferred)' % (val,)

if (filters):

summary += ' with "' + '", "'.join(filters) + '"'

if (histories):

subls = [ ac.name for ac in histories ]

subls.sort()

summary += ' with ' + ', '.join(subls)

#print '### (%d intermediate states)' % (len(self.states),)

print summary, 'reached'

def writegv(self, filename, filters=[], histories=[]):

(outls, trumped) = self.showlist()

(colorls, _) = self.showlist(True, filters, histories)

if (len(colorls) >= len(outls)):

colorls = ()

extrastart = [ state for state in self.startstates if not self.states[state].is_maximal ]

outls = extrastart + outls

nodenames = {}

pos = 1

for state in outls:

nodenames[state] = str(pos)

pos = pos+1

fl = open(filename, 'w')

fl.write('digraph PlotEx {\n')

fl.write('\n')

for state in outls:

node = self.states[state]

penwidth = 1

if (node.is_maximal and not node.children):

penwidth = 3

color = 'gray75'

if (state in colorls):

color = 'forestgreen'

if (not node.is_maximal):

color = 'white'

fl.write('# %s\n' % (state,))

fl.write('"%s" [ label="", shape=circle, width=0.2, style=filled, fillcolor=%s, penwidth=%d ];\n' % (nodenames[state], color, penwidth))

fl.write('\n')

if (node.is_maximal):

for (acls, child) in node.children:

label = '\\n'.join([ ac.name for ac in acls ])

fl.write(' "%s" -> "%s" [ label="%s" ];\n' % (nodenames[state], nodenames[child], label))

else:

acls = node.maxing_actions

label = '\\n'.join([ ac.name for ac in acls ])

fl.write(' "%s" -> "%s" [ label="%s", style=dashed ];\n' % (nodenames[state], nodenames[node.maximal], label))

fl.write('\n')

fl.write('}\n')

def writegml(self, filename, filters=[], histories=[]):

(outls, trumped) = self.showlist()

(colorls, _) = self.showlist(True, filters, histories)

if (len(colorls) >= len(outls)):

colorls = ()

extrastart = [ state for state in self.startstates if not self.states[state].is_maximal ]

outls = extrastart + outls

nodenames = {}

pos = 1

for state in outls:

nodenames[state] = pos

pos = pos+1

fl = open(filename, 'w')

fl.write('graph [\n')

fl.write(' directed 1\n\n')

for state in outls:

node = self.states[state]

penwidth = 1

if (node.is_maximal and not node.children):

penwidth = 3

color = 'gray75'

if (state in colorls):

color = 'forestgreen'

if (not node.is_maximal):

color = 'white'

fl.write(' comment "%s"\n' % (state,))

fl.write(' node [ id %d ]\n' % (nodenames[state],))

fl.write('\n')

if (node.is_maximal):

for (acls, child) in node.children:

label = ' '.join([ ac.name for ac in acls ])

fl.write(' edge [ source %d target %d label "%s" ]\n' % (nodenames[state], nodenames[child], label))

else:

acls = node.maxing_actions

label = ' '.join([ ac.name for ac in acls ])

fl.write(' edge [ source %d target %d label "%s" ]\n' % (nodenames[state], nodenames[node.maximal], label))

fl.write('\n')

fl.write(']\n')

class GraphNode:

'''GraphNode: Context information for a single state in a Graph.

(We never store information in the State itself -- that's immutable.)

'''

def __init__(self, state):

self.state = state

self.maximal = None

self.is_maximal = False

self.children = []

self.parents = []

self.history = ()

self.ancestors = set()

class State:

'''State: One state in the plot diagram. A state is set up with a

bunch of qualities.

The most interesting thing you can do with states is compare them.

State1 < state2 if state1's qualities are a subset of state2's.

This is a partial ordering; it is not necessarily true that

(x < y or x == y or x > y). Sometimes two states are just different,

in non-overlapping ways.

You can also compute state1 & state2, which is the greatest common

factor (the largest state which is <= both of them). (This doesn't

quite work out for negative-sense string qualities, but what does,

really?)

(Any operation between two states must be within a common Scenario.)

You will normally create a State as described in the documentation:

State(key1=val1, key2=val2, ...)

The constructor supports an alternate form: State(dic, newkeys).

However, this should only be used internally, by the PlotEx run()

algorithm. (It skips some of the type-checking and state-fixing,

on the assumption that the caller has done some of that work

already.)

'''

name = None

scenario = None

def __init__(self, __dic=None, __newkeys=None, **kargs):

if (__dic is None):

__dic = kargs

if (global_scenario is None):

self.typelist = infer_typelist(__dic)

else:

self.typelist = None

self.scenario = global_scenario

self.hashcache = None

if (not __dic):

self.dic = {}

return

self.dic = __dic

State.canonize(self.dic, __newkeys)

def __repr__(self):

keyls = self.dic.keys()

keyls.sort(key=lambda x:x.upper())

ls = []

for key in keyls:

val = self.dic[key]

if (isinstance(val, frozenset)):

val = list(val)

val.sort()

val = '[' + ','.join(str(subval) for subval in val) + ']'

if (val is True):

ls.append('%s' % (key,))

else:

ls.append('%s=%s' % (key, val))

joined = ' '.join(ls)

if (self.name):

return '<"%s": %s>' % (self.name, joined)

else:

return '<%s>' % (joined,)

def printdiff(self, other):

'''Return a string representation of the state, not by itself, but

in comparison to some other state. Only quality differences will be

displayed.

'''

keyset = set(self.dic.keys()).union(other.dic.keys())

keyls = list(keyset)

keyls.sort(key=lambda x:x.upper())

ls = []

for key in keyls:

typ = self.scenario._typemap[key]

sense = self.scenario._sensemap[key]

if (typ is bool):

val = self.dic.get(key)

otherval = other.dic.get(key)

if (val and not otherval):

ls.append('+%s' % (key,))

elif (otherval and not val):

ls.append('-%s' % (key,))

elif (typ is str):

val = self.dic.get(key)

otherval = other.dic.get(key)

if (val and otherval != val):

ls.append('%s=%s' % (key, val))

elif (otherval and not val):

ls.append('-%s' % (key,))

elif (typ is int):

val = self.dic.get(key, 0)

otherval = other.dic.get(key, 0)

if (val > otherval):

ls.append('%s=+%d' % (key, val-otherval))

elif (otherval and not val):

ls.append('%s=-%d' % (key, otherval-val))

elif (typ is set):

val = self.dic.get(key, set())

otherval = other.dic.get(key, set())

subls = []

for subkey in (val - otherval):

subls.append('+'+subkey)

for subkey in (otherval - val):

subls.append('-'+subkey)

subls.sort()

if (subls):

sublsval = '[' + ','.join(str(subval) for subval in subls) + ']'

ls.append('%s=%s' % (key, sublsval))

else:

ls.append('???')

joined = ' '.join(ls)

if (self.name):

return '<"%s": %s>' % (self.name, joined)

else:

return '<%s>' % (joined,)

def __eq__(self, other):

return (self.dic == other.dic)

def __ne__(self, other):

return (self.dic != other.dic)

def __gt__(self, other):

return (self != other) and self.contains(other)

def __ge__(self, other):

return self.contains(other)

def __lt__(self, other):

return (self != other) and other.contains(self)

def __le__(self, other):

return other.contains(self)

def __and__(self, other):

dic = {}

keyset = set(self.dic.keys()).union(other.dic.keys())

for key in keyset:

typ = self.scenario._typemap[key]

sense = self.scenario._sensemap[key]

val = self.dic.get(key)

otherval = other.dic.get(key)

if (sense):

if ((val is None) or (otherval is None)):

continue

if (typ is bool):

dic[key] = (val and otherval)

if (typ is int):

dic[key] = min(val, otherval)

if (typ is set):

dic[key] = val.intersection(otherval)

if (typ is str):

if (val == otherval):

dic[key] = val

else:

if (val is None):

dic[key] = otherval

continue

if (otherval is None):

dic[key] = val

continue

if (typ is bool):

dic[key] = (val or otherval)

if (typ is int):

dic[key] = max(val, otherval)

if (typ is set):

dic[key] = val.union(otherval)

if (typ is str):

if (val == otherval):

dic[key] = val

res = State(dic) # canonize all keys, this is not speed-critical

res.scenario = self.scenario

return res

def __hash__(self):

if (self.hashcache is None):

ls = self.dic.items()

ls.sort()

self.hashcache = hash(tuple(ls))

return self.hashcache

def canonize(dic, changedkeys=None):

'''Modify a dictionary to be a legal state dict (no false values,

sets values in frozenset form).

'''

if (changedkeys is None):

changedkeys = dic.keys()

for key in changedkeys:

val = dic[key]

if (not val):

del dic[key]

elif (type(val) in (tuple, list)):

dic[key] = frozenset(val)

canonize = staticmethod(canonize)

def copy(self):

res = State()

res.scenario = self.scenario

res.dic = dict(self.dic)

return res

def addquality(self, key, val):

'''Return a new state which is a copy of this one, with one quality

added (or changed). The value must be of the correct type, or castable

to it.

'''

typ = self.scenario._typemap[key]

dic = dict(self.dic)

if (typ is bool):

dic[key] = bool(val)

elif (typ is int):

dic[key] = int(val)

elif (typ is str):

dic[key] = str(val)

elif (typ is set):

dic[key] = dic.get(key, set()).union(set[val])

res = State(dic) # canonize all keys

res.scenario = self.scenario

return res

def contains(self, other):

'''X.contains(Y) is the basic comparison -- X is a subset of (or

equal to) Y.

'''

for (key, oval) in other.dic.items():

if (not self.scenario._sensemap[key]):

continue

if (not self.atleast(key, oval)):

return False

for (key, ival) in self.dic.items():

if (self.scenario._sensemap[key]):

continue

if (not other.atleast(key, ival)):

return False

return True

def atleast(self, key, val):

'''X.atleast(key, val) tests whether the key quality is val or better.

(This does *not* account for negative-sense keys, so don't call it

on them.)

'''

if (not val):

return True

ival = self.dic.get(key)

if (ival is None):

return False

typ = self.scenario._typemap[key]

if (typ is int):

if (ival < val):

return False

elif (typ is set):

if (not ival.issuperset(frozenset(val))):

return False

else:

if (ival != val):

return False

return True

def atmost(self, key, val):

'''X.atmost(key, val) tests whether the key quality is val or worse.

(Call this for negative-sense keys.)

'''

ival = self.dic.get(key)

if (not val and not ival):

return True

if (not val):

return False

if (ival is None):

return True

typ = self.scenario._typemap[key]

if (typ is int):

if (ival > val):

return False

elif (typ is set):

if (not ival.issubset(frozenset(val))):

return False

else:

if (ival != val):

return False

return True

class Test:

name = '???'

scenario = None

def __init__(self, **dic):

self.startstatelist = []

val = dic.pop('start', None)

if (val is not None):

if (type(val) not in (list, tuple)):

self.startstatelist.append(val)

else:

for state in val:

self.startstatelist.append(state)

self.blockactions = set()

val = dic.pop('block', None)

if (val is not None):

if (type(val) not in (list, tuple)):

self.blockactions.add(val)

else:

for ac in val:

self.blockactions.add(ac)

self.includeactions = []

val = dic.pop('includes', None)

if (val is not None):

if (type(val) not in (list, tuple)):

self.includeactions.append(val)

else:

for ac in val:

self.includeactions.append(ac)

self.excludeactions = []

val = dic.pop('excludes', None)

if (val is not None):

if (type(val) not in (list, tuple)):

self.excludeactions.append(val)

else:

for ac in val:

self.excludeactions.append(ac)

self.canactions = []

val = dic.pop('can', None)

if (val is not None):

if (type(val) not in (list, tuple)):

self.canactions.append(val)

else:

for ac in val:

self.canactions.append(ac)

self.cannotactions = []

val = dic.pop('cannot', None)

if (val is not None):

if (type(val) not in (list, tuple)):

self.cannotactions.append(val)

else:

for ac in val:

self.cannotactions.append(ac)

self.getqualities = []

val = dic.pop('gets', None)

if (val is not None):

if (type(val) not in (list, tuple)):

self.getqualities.append(val)

else:

for ac in val:

self.getqualities.append(ac)

self.getnotqualities = []

val = dic.pop('getsnot', None)

if (val is not None):

if (type(val) not in (list, tuple)):

self.getnotqualities.append(val)

else:

for ac in val:

self.getnotqualities.append(ac)

if (dic):

raise TypeError('Test() got unknown argument: %s' % (', '.join(dic.keys()),))

ls = list(self.blockactions) + self.startstatelist + self.canactions + self.cannotactions

self.typelist = merge_typelists_of(ls)

def __repr__(self):

return '<Test "%s">' % (self.name,)

def set_scenario(self, scen):

self.scenario = scen

for state in self.startstatelist:

state.scenario = scen

for ac in self.canactions + self.cannotactions:

ac.set_scenario(scen)

def startstates(self):

if (not self.startstatelist):

state = self.scenario._statemap['Start']

return [state]

return self.startstatelist

def actions(self):

actions = [ action for action in self.scenario._actionmap.values() if action not in self.blockactions ]

return actions

def verify(self, graph):

states = graph.states.keys()

for qual in self.getqualities:

states = [ state for state in states if state.dic.has_key(qual) ]

if (not states):

return False

for ac in self.canactions:

states = [ state for state in states if ac(state) ]

if (not states):

return False

for ac in self.includeactions:

states = [ state for state in states if (ac in graph.states[state].history) ]

if (not states):

return False

for qual in self.getnotqualities:

ls = [ state for state in states if state.dic.has_key(qual) ]

if (ls):

return False

for ac in self.cannotactions:

ls = [ state for state in states if ac(state) ]

if (ls):

return False

for ac in self.excludeactions:

ls = [ state for state in states if (ac in graph.states[state].history) ]

if (ls):

return False

return True

# When running, it is handy to know whether a given action will strictly

# improve the state (stay in the same maximal class), or always lose

# something (a different maximal class). Often, though, we don't know

# either.

EQUIV_UNKNOWN = '????' # We don't know

EQUIV_SAME = 'SAME' # Does not change the state at all

EQUIV_IMPROVE = 'IMPR' # Definitely an improvement

EQUIV_LOSS = 'LOSS' # Definitely a loss of something

class Action:

'''Action: An abstract action in a scenario. Calling Action(State)

will return a new State, or None if the Action isn't possible in that

state.

'''

name = '???'

scenario = None

equivtype = EQUIV_UNKNOWN

unnamedcount = 0

def __repr__(self):

return '<Action "%s">' % (self.name,)

def __call__(self, state):

raise NotImplementedError('Action type not implemented')

def subactions(self):

return None

def set_scenario(self, scen):

self.scenario = scen

ls = self.subactions()

if ls:

for ac in ls:

ac.set_scenario(scen)

class Set(Action):

def __init__(self, **dic):

self.typelist = infer_typelist(dic)

self.params = dic

self.keylist = dic.keys()

allbool = True

pos = 0

for (key, val) in dic.items():

if (self.typelist[key] is not bool):

allbool = False

break

if ((not key.startswith('_') and val)

or (key.startswith('_') and not val)):

pos += 1

if (allbool):

if (pos == len(dic)):

self.equivtype = EQUIV_IMPROVE

else:

self.equivtype = EQUIV_LOSS

def __call__(self, state):

dic = state.dic.copy()

dic.update(self.params)

return State(dic, self.keylist)

class Reset(Action):

def __init__(self, **dic):

self.typelist = infer_typelist(dic)

self.params = dic

State.canonize(self.params)

def __call__(self, state):

dic = self.params.copy()

return State(dic, ())

class Has(Action):

equivtype = EQUIV_SAME

def __init__(self, **dic):

self.typelist = infer_typelist(dic)

self.params = dic

def __call__(self, state):

for (key, val) in self.params.items():

if (self.scenario._sensemap[key]):

if (not state.atleast(key, val)):

return

else:

if (not state.atmost(key, val)):

return

return state

class HasAny(Action):

equivtype = EQUIV_SAME

def __init__(self, **dic):

self.typelist = infer_typelist(dic)

self.params = dic

def __call__(self, state):

for (key, val) in self.params.items():

if (self.scenario._sensemap[key]):

if (state.atleast(key, val)):

return state

else:

if (state.atmost(key, val)):

return state

return

class Lose(Action):

def __init__(self, *keys):

self.typelist = {}

self.keys = keys

pos = 0

for key in keys:

if (not key.startswith('_')):

pos += 1

if (pos > 0):

self.equivtype = EQUIV_LOSS

else:

self.equivtype = EQUIV_IMPROVE

def __call__(self, state):

olddic = state.dic

for key in self.keys:

if (key not in olddic):

return

dic = olddic.copy()

for key in self.keys:

dic.pop(key)

return State(dic, ())

class Once(Action):

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