grasp.py 文件源码

def __init__(self, model, label, data=[]):
        """ Returns a new Model calibrated on the given data,
            which is a set of (vector, label)-tuples.
        """
        self._model = model
        self._label = label
        # Isotonic regression:
        y = ((model.predict(v)[label], label == x) for v, x in data)
        y = sorted(y) # monotonic
        y = zip(*y)
        y = list(y or ((),()))
        x = list(y[0])
        y = list(y[1])
        y = pav(y)
        x = [0] + x + [1]
        y = [0] + y + [1]
        f = {}
        i = 0
        # Linear interpolation:
        for p in range(100 + 1):
            p *= 0.01
            while x[i] < p:
                i += 1
            f[p] = (y[i-1] * (x[i] - p) + y[i] * (p - x[i-1])) / (x[i] - x[i-1])
        self._f = f