class_docstr: The 'smoothest' approximation, df is computed through global minimization
  of the bending energy:
    E(f) = integral[(d2z/dx2 + d2z/dy2 + 2 d2z/dxdy)**2 dA]
class_docstr_tok: ["The","'smoothest","'","approximation",",","df","is","computed","through","global","minimization","of","the","bending","energy",":","E","(","f",")","=","integral","[","(","d2z\/dx2","+","d2z\/dy2","+","2","d2z\/dxdy",")","*","*","2","dA","]"]
code: def __init__(self, Interpolator):
      self._eccs = Interpolator._eccs
      super().__init__(Interpolator)
  
imports: import numpy
  from matplotlib import _api
  from matplotlib.tri import Triangulation
  from matplotlib.tri._trifinder import TriFinder
  from matplotlib.tri._tritools import TriAnalyzer
label_desc: Use image node_id 1 to create a new _DOF_estimator_min_E object from inherited base classes: _DOF_estimator_geom with example: obj = _DOF_estimator_min_E(Interpolator)