Exemple #1
0
 def adjust_for_precedence(self, weights):
     prec = {pitch.pc(p):w for p,w in self.precedences.items()}
     
     for k in weights.keys():
         if k not in prec:
             prec[k] = 1
     
     for p in self.prev_picks:
         pcp = pitch.pc(p)
         if pcp in prec:
             prec[pcp] *= 0.5
     
     mult = {k: prec[pitch.pc(k)] for k in weights.keys()}
     mult = w.scale(mult, float(self.precedence) / self.left_to_select)
     return w.normalize(w.apply(mult, weights))
Exemple #2
0
    def choose(weights):
        '''Choose one item out of a weighted list.'''
        weights = w.probabilitize(weights)
        rand = random.random()
        choice = None
        for k, v in weights.items():
            if rand <= v:
                choice = k
                break;
            rand = rand - v
        return choice
    
    ### Utility functions
    @staticmethod
    def identity(x, y): # to be overrided when dealing with pitch classes
        return x == y
    
    ### Cleaning operations
    def clean(self):
        self.max_length = len(self.weighted_items) * 2 - 1
        self.normalize()
    
    def normalize(self):
        self.weighted_items = w.normalize(self.weighted_items)

if __name__ == '__main__':
    dm = DataMap({1:0.001, 2:1, 3:5})
    weights = dm.weighted_items
    print weights
    print w.scale(weights, 0.1)