class_docstr: Univariate density estimation by orthonormal series expansion
  
  
  Uses an orthonormal polynomial basis to approximate a univariate density.
  
  
  currently all arguments can be given to fit, I might change it to requiring
  arguments in __init__ instead.
class_docstr_tok: ["Univariate","density","estimation","by","orthonormal","series","expansion","Uses","an","orthonormal","polynomial","basis","to","approximate","a","univariate","density",".","currently","all","arguments","can","be","given","to","fit",",","I","might","change","it","to","requiring","arguments","in","__init__","instead","."]
code: def __init__(self, polybase=None, order=5):
      if polybase is not None:
          self.polybase = polybase
          self.polys = polys = [polybase(i) for i in range(order)]
      # try:
      # self.offsetfac = 0.05
      # self.offsetfac = polys[0].offsetfactor #polys maybe not defined yet
      self._corfactor = 1
      self._corshift = 0
  
imports: from scipy import stats, integrate, special
  import numpy
label_desc: Use image node_id 1 to create a new DensityOrthoPoly object  with example: obj = DensityOrthoPoly(polybase, order)