开始↓ 导入数据 → 读取CSV文件 → 转换时间戳格式 ↓ 数据预处理 → 检查缺失值 → 生成故障事件表 ↓ 时间序列分析 → 划分正常/故障时间段 → 传感器数据可视化 ↓ 故障标签生成 → 标记故障时间段为1,其余为0 ↓ 相关性分析 → 计算传感器间相关性 → 热力图展示 ↓ 模型准备 → 平衡数据集 → 划分...
On the daily chart, this lineisthe midpoint of the52-day high-lowrange, whichisa little less than3months. The default calculation settingis52periods, but can be adjusted. This valueisplotted26periodsinthe futureandforms the slower Cloud boundary. Chikou Span (Lagging Span): Close plotted26day...
From the probability distribution of the future portfolio value f(w), at a given confidence level c, we compute the worst possible realisation W* such that the probability of exceeding this value is c, i.e. Put another way, the probability of the portfolio value being lower than W*, p=...
oddvalues = {key: value for (key, value) in dictionary.items() if value % 2 != 0} print(oddvalues)Output: {'first_num': 1, 'third_num': 3} 02 枚举函数 Enumerate (枚举) 是一个很有用的函数,用于迭代对象,如列表、字典或文件。该函数生成一个元组,其中包括通过对象迭代获得的值以及循环...
P(转换)=P(C1→C2→C3→转换)+P(C2→C3→转换)=0.5*0.5*1*0.6+0.5*1*0.6=0.15+0.3=0.45 如果要弄清楚渠道C1在用户转化路径中的贡献,使用移除效应原则。即如果想要在用户路径中找到某个渠道的贡献,可以通过删除该渠道并查看在没有该渠道的情况下发生了多少次转化。
coef,p=kendalltau(data1,data2) We can demonstrate the calculation on the test dataset, where we do expect a significant positive association to be reported. The complete example is listed below. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 # calculate...
coef,p=kendalltau(data1,data2) We can demonstrate the calculation on the test dataset, where we do expect a significant positive association to be reported. The complete example is listed below. 1 2 3 4 5 6 7 8 9 10 11 12 13 ...
DTerm = delta_error / delta_time # Remember last time and last error for next calculation self.last_time = self.current_time self.last_error = error self.output = self.PTerm + \ (self.Ki * self.ITerm) + (self.Kd * self.DTerm) def setKp(self, proportional_gain): """Determines...
Returns---adf : floatThe test statistic.pvalue : floatMacKinnon"s approximate p-value based on MacKinnon (1994, 2010).usedlag : intThe number of lags used.nobs : intThe number of observations used for the ADF regression and calculationof the critical values.critical values : dictCritical ...
The value of definite integral calculation is -0.9978134302969512 The approximated maximum is 0.9999971463877178 The approximated minimum is -0.9999996829318346 也在数学的角度上符合了我们的预判(sine的最大值为1,最小值为-1,$\int_{-\mathrm{\pi}}^{\frac{\mathrm{\pi}}{2}}{\sin \left( \mathrm{x...