def seuclidean(u, v, V):
 u = _validate_vector(u)
 v = _validate_vector(v)
 V = _validate_vector(V, dtype=np.float64)
 if ((V.shape[0] != u.shape[0]) or (u.shape[0] != v.shape[0])):
  raise TypeError('V must be a 1-D array of the same dimension as u and v.')
 return np.sqrt((((u - v) ** 2) / V).sum())

def seuclidean ( u , v , V ) : u = _validate_vector ( u ) v = _validate_vector ( v ) V = _validate_vector ( V , dtype = np . float64 ) if ( ( V . shape [ 0 ] != u . shape [ 0 ] ) or ( u . shape [ 0 ] != v . shape [ 0 ] ) ) : raise TypeError ( 'V must be a 1-D array of the same dimension as u and v.' ) return np . sqrt ( ( ( ( u - v ) ** 2 ) / V ) . sum ( ) )
returns the standardized euclidean distance between two 1-d arrays .