code: def getci(self, alpha):
      if self.t == 0 or self.rmin == self.rmax:
          return [self.rmin, self.rmax]
  
      sumvlow = (
          (
              float(self.sumwsqrsq)
              - 2 * self.rmin * float(self.sumwsqr)
              + self.rmin**2 * float(self.sumwsq)
          )
          / (self.rmax - self.rmin) ** 2
          - 2
          * (
              float(self.sumwrxhatlow)
              - self.rmin * float(self.sumwxhatlow)
          )
          / (self.rmax - self.rmin)
          + float(self.sumxhatlowsq)
      )
      sumXlow = (float(self.sumwr) - float(self.sumw) * self.rmin) / (
          self.rmax - self.rmin
      )
      l = self.lblogwealth(
          t=self.t,
          sumXt=sumXlow,
          v=sumvlow,
          eta=self.eta,
          s=self.s,
          alpha=alpha / 2,
      )
  
      sumvhigh = (
          (
              float(self.sumwsqrsq)
              - 2 * self.rmax * float(self.sumwsqr)
              + self.rmax**2 * float(self.sumwsq)
          )
          / (self.rmax - self.rmin) ** 2
          + 2
          * (
              float(self.sumwrxhathigh)
              - self.rmax * float(self.sumwxhathigh)
          )
          / (self.rmax - self.rmin)
          + float(self.sumxhathighsq)
      )
      sumXhigh = (float(self.sumw) * self.rmax - float(self.sumwr)) / (
          self.rmax - self.rmin
      )
      u = 1 - self.lblogwealth(
          t=self.t,
          sumXt=sumXhigh,
          v=sumvhigh,
          eta=self.eta,
          s=self.s,
          alpha=alpha / 2,
      )
      return self.rmin + l * (self.rmax - self.rmin), self.rmin + u * (
          self.rmax - self.rmin
      )
  
file_path: vowpal_wabbit/python/tests/confidence_sequence.py
imports: from cmath import sqrt
label_desc: Use image node_id 3 for calling the confidence_sequence obj's underlying member method code with example usage: obj.getci(alpha) and returns: unknown,  unknown, list