original_docstring: returns the kernel weight for the independent multivariate kernel
docstring: returns the kernel weight for the independent multivariate kernel
docstring_tokens: returns the kernel weight for the independent multivariate kernel
code: def _kernweight(self, x ):
          """returns the kernel weight for the independent multivariate kernel"""
          if isinstance( self._kernels, CustomKernel ):
              ## Radial case
              #d = x.T * x
              #x is matrix, 2d, element wise sqrt looks wrong
              #d = np.sqrt( x.T * x )
              x = np.asarray(x)
              #d = np.sqrt( (x * x).sum(-1) )
              d = (x * x).sum(-1)
              return self._kernels( np.asarray(d) )
code_tokens: def _kernweight ( self , x ) : if isinstance ( self . _kernels , CustomKernel ) : x = np . asarray ( x ) d = ( x * x ) . sum ( - 1 ) return self . _kernels ( np . asarray ( d ) )
short_docstring: returns the kernel weight for the independent multivariate kernel
short_docstring_tokens: returns the kernel weight for the independent multivariate kernel
comment: """returns the kernel weight for the independent multivariate kernel"""$SEP$## Radial case$SEP$#d = x.T * x$SEP$#x is matrix, 2d, element wise sqrt looks wrong$SEP$#d = np.sqrt( x.T * x )$SEP$#d = np.sqrt( (x * x).sum(-1) )