Question

我在运行github代码时遇到错误。我认为代码是完美的，但我认为我正面临一些依赖性问题。任何人都可以告诉我可能是这个错误背后的原因。我正在使用python 2.7。

from __future__ import division, print_function
.
.     
def time_step(self, xt):
    xt = np.reshape(xt, newshape=self.dimensions)
    ret_val = 0.
    self.buffer.append(xt)
    self.present.time_step(xt)
    if self.t >= self.buffer_len:
        pst_xt = self.buffer[0]
        self.past.time_step(pst_xt)
        if self.t >= self.present.theta + self.past.theta:
            ret_val = self.comparison_function(self.present, self.past,
                                               self.present.alpha)
    self.ma_window.append(ret_val)
    if self.t % self.ma_recalc_delay == 0:
        self.anomaly_mean = bn.nanmean(self.ma_window)
        self.anomaly_std = bn.nanstd(self.ma_window, ddof=self.ddof)
    if self.anomaly_std is None or self.t < len(self.ma_window):
        anomaly_density = 0
    else:
        normalized_score = (ret_val - self.anomaly_mean)/self.anomaly_std
        if -4 <= normalized_score <= 4:
            anomaly_density = CDF_TABLE[round(normalized_score, 3)]
        elif normalized_score > 4:
            anomaly_density = 1.
        else:
            anomaly_density = 0.
    self.t += 1
    return ret_val, anomaly_density

给出错误的代码行如下，

normalized_score = (ret_val - self.anomaly_mean)/self.anomaly_std

Answer 1

将其包裹在try except中，我使用0作为值，但您可以根据需要更改它：

try:
    normalized_score = (ret_val - self.anomaly_mean)/self.anomaly_std
except ZeroDivisionError:
    normalized_score = 0

ZeroDivisionError：即使在使用python future module

1 个答案: