class_docstr: Generic 1D Kernel object.
  Can be constructed by selecting a standard named Kernel,
  or providing a lambda expression and domain.
  The domain allows some algorithms to run faster for finite domain kernels.
class_docstr_tok: ["Generic","1D","Kernel","object",".","Can","be","constructed","by","selecting","a","standard","named","Kernel",",","or","providing","a","lambda","expression","and","domain",".","The","domain","allows","some","algorithms","to","run","faster","for","finite","domain","kernels","."]
docstr: Returns the integral of the square of the kernal from -inf to inf
code: def L2Norm(self):
      """Returns the integral of the square of the kernal from -inf to inf"""
      if self._L2Norm is None:
          L2Func = lambda x: (self.norm_const * self._shape(x)) ** 2
          if self.domain is None:
              self._L2Norm = scipy.integrate.quad(L2Func, -inf, inf)[0]
          else:
              self._L2Norm = scipy.integrate.quad(
                  L2Func, self.domain[0], self.domain[1]
              )[0]
      return self._L2Norm
  
imports: from statsmodels.compat.python import lzip, lfilter
  import numpy
  import scipy.integrate
  from scipy.special import factorial
  from numpy import exp, multiply, square, divide, subtract, inf
label_desc: Use image node_id 11 for calling the CustomKernel obj's underlying member method code with example usage: obj.L2Norm() and returns: self