code: def is_orthonormal(self):
          
          a, b, c, d, e, f, g, h, i = self
          return (
              self.is_conformal
              and abs(1.0 - (a * a + d * d)) < EPSILON
              and abs(1.0 - (b * b + e * e)) < EPSILON
          )
docs: True if the transform is orthonormal, which means that the
          transform represents a rigid motion, which has no effective scaling or
          shear. Mathematically, this means that the axis vectors of the
          transform matrix are perpendicular and unit-length.  Applying an
          orthonormal transform to a shape always results in a congruent shape.