class_docstr: Distribution with piecewise linear cdf, pdf is step function
  
  can be created from empiricial distribution or from a histogram (not done yet)
  
  work in progress, not finished
class_docstr_tok: ["Distribution","with","piecewise","linear","cdf",",","pdf","is","step","function","can","be","created","from","empiricial","distribution","or","from","a","histogram","(","not","done","yet",")","work","in","progress",",","not","finished"]
docstr: Return the empirical cdf.
  
  Methods available:
      Hazen:       (i-0.5)/N
          Weibull:     i/(N+1)
      Chegodayev:  (i-.3)/(N+.4)
      Cunnane:     (i-.4)/(N+.2)
      Gringorten:  (i-.44)/(N+.12)
      California:  (i-1)/N
  
  Where i goes from 1 to N.
docstr_tok: ["Return","the","empirical","cdf",".","Methods","available",":","Hazen",":","(","i-0.5",")","\/N","Weibull",":","i\/","(","N+1",")","Chegodayev",":","(","i-.3",")","\/","(","N+.4",")","Cunnane",":","(","i-.4",")","\/","(","N+.2",")","Gringorten",":","(","i-.44",")","\/","(","N+.12",")","California",":","(","i-1",")","\/N","Where","i","goes","from","1","to","N","."]
code: def empiricalcdf(self, data=None, method="Hazen"):
      """Return the empirical cdf.
  
      Methods available:
          Hazen:       (i-0.5)/N
              Weibull:     i/(N+1)
          Chegodayev:  (i-.3)/(N+.4)
          Cunnane:     (i-.4)/(N+.2)
          Gringorten:  (i-.44)/(N+.12)
          California:  (i-1)/N
  
      Where i goes from 1 to N.
      """
  
      if data is None:
          data = self.data
          i = self.ranking
      else:
          i = np.argsort(np.argsort(data)) + 1.0
  
      N = len(data)
      method = method.lower()
      if method == "hazen":
          cdf = (i - 0.5) / N
      elif method == "weibull":
          cdf = i / (N + 1.0)
      elif method == "california":
          cdf = (i - 1.0) / N
      elif method == "chegodayev":
          cdf = (i - 0.3) / (N + 0.4)
      elif method == "cunnane":
          cdf = (i - 0.4) / (N + 0.2)
      elif method == "gringorten":
          cdf = (i - 0.44) / (N + 0.12)
      else:
          raise ValueError(
              "Unknown method. Choose among Weibull, Hazen,"
              "Chegodayev, Cunnane, Gringorten and California."
          )
  
      return cdf
  
file_path: statsmodels/statsmodels/sandbox/stats/stats_dhuard.py
imports: import scipy.interpolate
  import numpy
label_desc: Use image node_id 2 for calling the HistDist obj's underlying member method code with example usage: obj.empiricalcdf(data, method) and returns: cdf