TestPredictor

class TestPredictor:
    """Iterate a KNearest predictor and return its success rate."""

    def __init__(self, predictor, times=1000):
        #set the KNearest predictor
        self.predictor = predictor 
        #set number of iterations   
        self.times = times

    def test(self, k=1):
        results = []
        #iteration
        for i in range(self.times):
            #pick a random class
            ac = random.randint(0, len(self.predictor.ds.classes)-1)
            #use it to generate a point
            tp = self.predictor.ds.classes[ac].generate()
            #test the predictor on it
            pc = self.predictor.predict(tp, k=k)
            #if it got it right it gets a cookie
            if pc == ac: 
                results.append(1)
            else:
                results.append(0)
        #return the mean result
        return float(sum(results))/float(len(results))