Game Idea Generator

-=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- (c) WidthPadding Industries 1987 0\|650\|0 -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=- -=+=-
Socoder -> Off Topic -> Game Idea Generator
Thu, 30 Jan 2014, 20:59
Dabz	Game idea generator, lol: Linkage -=-=- Intel Core i5 6400 2.7GHz, NVIDIA GeForce GTX 1070 (8GB), 8Gig DDR4 RAM, 256GB SSD, 1TB HDD, Windows 10 64bit
Thu, 30 Jan 2014, 20:59
dna	That actually is a clever little piece of software for generating those lines. -=-=- DNA
Fri, 31 Jan 2014, 01:57
spinal	"An artsy game where you startle dead bodies in realtime." Nice! -=-=- Check out my excellent homepage!
Fri, 31 Jan 2014, 06:40
Dabz	What made me laugh was "An indie game where you invade castles with friendship" Cute Dabz -=-=- Intel Core i5 6400 2.7GHz, NVIDIA GeForce GTX 1070 (8GB), 8Gig DDR4 RAM, 256GB SSD, 1TB HDD, Windows 10 64bit
Fri, 31 Jan 2014, 15:15
dna	Here is the source for generating that but using python. Might be of use to some in a game somewhere. #!/usr/bin/env python # -- coding: utf-8 -- # # A contextual markov chain sentence generator. # # The main class of the module, MarkovGenerator, takes sentences and # exerpts of human conversation, and constructs a markov chain from # that knowledge. It can then probabalistically construct new # sentences based on its knowledge of what constitutes probably # conversation. import re import random import collections import pickle import gzip PROPOSITION_SEPARATOR = r'[,:;]' SENTENCE_TERMINATOR = r'[?!.]+' SMILEY = r"[:;8=][o\-']?[()\[\]/\\\?pPdD$]+" URL = r"\b\w+://\S\b" PROPOSITION_SEPARATOR_RE = re.compile( r'(?x)' + PROPOSITION_SEPARATOR, re.UNICODE) SENTENCE_TERMINATOR_RE = re.compile(r'(?x)' + SENTENCE_TERMINATOR, re.UNICODE) SPLIT_RE = re.compile(r'''(?x) ( %s \| # A URL %s \| # A smiley %s \| # One of these is considered a separator [()] \| # Parentesis %s \| # Several of these in a row also \s+ # Last resort, whitespace. )''' % (URL, SMILEY, PROPOSITION_SEPARATOR, SENTENCE_TERMINATOR), re.UNICODE) class MarkovToken(object): def __init__(self, token): self.token = token if PROPOSITION_SEPARATOR_RE.match(token): self.space_before, self.end = False, False elif SENTENCE_TERMINATOR_RE.match(token): self.space_before, self.end = False, True else: self.space_before, self.end = True, False def output(self): if self.space_before: return [' ', self.token] else: return [self.token] def __str__(self): return self.token def __repr__(self): return "<token '%s'>" % self.token def __eq__(self, other): return (self.token == other.token and self.end == other.end and self.space_before == other.space_before) def __ne__(self, other): return not (self == other) def __hash__(self): return (hash(self.token) ^ (hash(self.end) << 2) ^ (hash(self.space_before) << 3)) class MarkovTokenFactory(object): def __init__(self): self.tokens = {} self.cnt = {} def __call__(self, s): self.cnt[s] = self.cnt.get(s, 0) + 1 if s in self.tokens: return self.tokens[s] else: tok = MarkovToken(s) self.tokens[s] = tok return tok class MarkovGenerator(object): def __init__(self, context=2): self.tokens = {} self.context = context self.factory = MarkovTokenFactory() def lex(self, sentence): return [self.factory(x.strip()) for x in SPLIT_RE.split(sentence) if x.strip()] def markov_sequence(self, tokens, context): sequence = collections.deque((None,)context) for token in tokens: yield tuple(sequence), token if token.end: sequence = collections.deque((None,)context) else: sequence.popleft() sequence.append(token) def learn(self, sentence): tokens = self.lex(sentence) if len(tokens) < 4: return tokens[-1].end = True for context,next in self.markov_sequence(tokens, self.context): weight = self.tokens.setdefault(context, {}).setdefault(next, 0) self.tokens[context][next] = weight+1 def say(self, start_word=None): sequence = collections.deque((None,)*self.context) if start_word: sequence.popleft() sequence.append(start_word) # Tried to start a sentence, but unknown start word. if tuple(sequence) not in self.tokens: return None sentence = [] while not sentence or not sentence[-1].end: context = tuple(sequence) next_dict = self.tokens[context] total = sum(next_dict.itervalues()) select = random.randint(1, total+1) for next_word,weight in next_dict.iteritems(): total -= weight if total <= select: sentence.append(next_word) sequence.popleft() sequence.append(next_word) break return ''.join([''.join(x.output()) for x in sentence]) def save(self, filename): f = gzip.GzipFile(filename, 'wb') data_to_save = (self.context, self.factory, self.tokens) pickle.dump(data_to_save, f, -1) f.close() def load(self, filename): f = gzip.GzipFile(filename, 'rb') (self.context, self.factory, self.tokens) = pickle.load(f) f.close() if __name__ == '__main__': import sys m = MarkovGenerator(2) m.learn(file(sys.argv[1]).read()) print m.say() --v -=-=- DNA
Fri, 31 Jan 2014, 16:40
Jayenkai	Bloody hell, that is the scruffiness, ugliest code I've seen in a long long time.. -=-=- ''Load, Next List!''
Fri, 31 Jan 2014, 16:58
dna	Yes it is but here's another one that does the same thing class CFG(object): def __init__(self): self.prod = defaultdict(list) def add_prod(self, lhs, rhs): """ Add production to the grammar. 'rhs' can be several productions separated by '\|'. Each production is a sequence of symbols separated by whitespace. Usage: grammar.add_prod('NT', 'VP PP') grammar.add_prod('Digit', '1\|2\|3\|4') """ prods = rhs.split('\|') for prod in prods: self.prod[lhs].append(tuple(prod.split())) def gen_random(self, symbol): """ Generate a random sentence from the grammar, starting with the given symbol. """ sentence = '' # select one production of this symbol randomly rand_prod = random.choice(self.prod[symbol]) for sym in rand_prod: # for non-terminals, recurse if sym in self.prod: sentence += self.gen_random(sym) else: sentence += sym + ' ' return sentence --v Easier to read and to convert to BB -=-=- DNA
Fri, 31 Jan 2014, 17:17
shroom_monk	Code doesn't seem that scruffy to me! Also, it's not entirely fair to say the second snippet does the same thing as the first. While both the Markov Chain and Context-Free Grammar methods could both produce similar results, it's a bit like equating a hammer to a nailgun - sure, they both nail things together, but the way in which they do it is different enough to matter. -=-=- A mushroom a day keeps the doctor away... Keep It Simple, Shroom!
Fri, 31 Jan 2014, 18:39
steve_ancell	It's scruffy!, not enough whitespace. LOL
Sat, 01 Feb 2014, 02:51
shroom_monk	Where would you put more whitespace? Seems clearly formatted enough to me... Only real issue is that comments are fairly sparse. -=-=- A mushroom a day keeps the doctor away... Keep It Simple, Shroom!
Sat, 01 Feb 2014, 06:27
steve_ancell	You've obviously never seen my code!. LOL
Mon, 03 Feb 2014, 15:01
dna	It's great for Blitz