Interpolates all pairs between two :class:`BaseKerning` objects:

        **minKerning** and **maxKerning**. The interpolation occurs on a
        0 to 1.0 range where **minKerning** is located at 0 and
        **maxKerning** is located at 1.0. The kerning data is replaced by
        the interpolated kerning.

        * **factor** is the interpolation value. It may be less than 0
          and greater than 1.0. It may be an :ref:`type-int-float`,
          ``tuple`` or ``list``. If it is a ``tuple`` or ``list``,
          the first number indicates the x factor and the second number
          indicates the y factor.
        * **round** is a ``bool`` indicating if the result should be rounded to
          ``int``\s. The default behavior is to round interpolated kerning.
        * **suppressError** is a ``bool`` indicating if incompatible data should
          be ignored or if an error should be raised when such incompatibilities
          are found. The default behavior is to ignore incompatible data.

            >>> myKerning.interpolate(kerningOne, kerningTwo)

def interpolate(self, factor, minKerning, maxKerning, round=True, suppressError=True):
        """
        Interpolates all pairs between two :class:`BaseKerning` objects:

        **minKerning** and **maxKerning**. The interpolation occurs on a
        0 to 1.0 range where **minKerning** is located at 0 and
        **maxKerning** is located at 1.0. The kerning data is replaced by
        the interpolated kerning.

        * **factor** is the interpolation value. It may be less than 0
          and greater than 1.0. It may be an :ref:`type-int-float`,
          ``tuple`` or ``list``. If it is a ``tuple`` or ``list``,
          the first number indicates the x factor and the second number
          indicates the y factor.
        * **round** is a ``bool`` indicating if the result should be rounded to
          ``int``\s. The default behavior is to round interpolated kerning.
        * **suppressError** is a ``bool`` indicating if incompatible data should
          be ignored or if an error should be raised when such incompatibilities
          are found. The default behavior is to ignore incompatible data.

            >>> myKerning.interpolate(kerningOne, kerningTwo)
        """
        factor = normalizers.normalizeInterpolationFactor(factor)
        if not isinstance(minKerning, BaseKerning):
            raise TypeError(("Interpolation to an instance of %r can not be "
                             "performed from an instance of %r.") % (
                self.__class__.__name__, minKerning.__class__.__name__))
        if not isinstance(maxKerning, BaseKerning):
            raise TypeError(("Interpolation to an instance of %r can not be "
                             "performed from an instance of %r.") % (
                self.__class__.__name__, maxKerning.__class__.__name__))
        round = normalizers.normalizeBoolean(round)
        suppressError = normalizers.normalizeBoolean(suppressError)
        self._interpolate(factor, minKerning, maxKerning,
                          round=round, suppressError=suppressError)