tdx_formula.py 文件源码

def CONV(self, param):
        df = pd.DataFrame(index = param[0].index)
        df['X'] = param[0]
        df['W'] = param[1]
        class Convolution:
            def __init__(self, N):
                self.N = N
                self.q = deque([], self.N)
                self.tq = deque([], self.N)
                self.s = 0
                self.t = 0

            def handleInput(self, row):
                if len(self.q) < self.N:
                    if pd.isnull(row['W']) or pd.isnull(row['X']):
                        return np.NaN
                    self.q.append(row['W'] * row['X'])
                    self.tq.append(row['W'])
                    self.s += row['W'] * row['X']
                    self.t += row['W']
                    return np.NaN
                ret = self.s / self.t
                self.s -= self.q[0]
                self.t -= self.tq[0]
                delta_s = row['W'] * row['X']
                delta_t = row['W']
                self.s += delta_s
                self.t += delta_t
                self.q.append(delta_s)
                self.tq.append(delta_t)
                return ret
        conv = Convolution(param[2])
        result = df.apply(conv.handleInput, axis = 1, reduce = True)
        return result


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