class_docstr: Univariate empirical cumulative distribution estimator.
class_docstr_tok: ["Univariate","empirical","cumulative","distribution","estimator","."]
docstr: Inner function for ECDF of one variable.
docstr_tok: ["Inner","function","for","ECDF","of","one","variable","."]
code: def _eval_univariate(self, x, weights):
      """Inner function for ECDF of one variable."""
      sorter = x.argsort()
      x = x[sorter]
      weights = weights[sorter]
      y = weights.cumsum()
  
      if self.stat in ["percent", "proportion"]:
          y = y / y.max()
      if self.stat == "percent":
          y = y * 100
  
      x = np.r_[-np.inf, x]
      y = np.r_[0, y]
  
      if self.complementary:
          y = y.max() - y
  
      return y, x
  
imports: from numbers import Number
  from statistics import NormalDist
  import numpy
  import pandas
  from .algorithms import bootstrap
  from .utils import _check_argument
label_desc: Use image node_id 3 for calling the ECDF obj's underlying member method code with example usage: obj._eval_univariate(x, weights) and returns: y,  x