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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def compress_repr(self) -> Optional[str]: """Try to find a compressed parameter value representation and return it. |Parameter.compress_repr| raises a |NotImplementedError| when failing to find a compressed representation. .. testsetup:: For the following examples, we define a 1-dimensional sequence handling time-dependent floating point values: Before and directly after defining the parameter shape, `nan` is returned: '?' test(?) test(?) Due to the time-dependence of the values of our test class, we need to specify a parameter and a simulation time step: Compression succeeds when all required values are identical: array([ 1., 1., 1., 1.]) '3.0' test(3.0) Method |Parameter.compress_repr| returns |None| in case the required values are not identical: test(1.0, 2.0, 3.0, 3.0) If some values are not required, indicate this by the `mask` descriptor: test(3.0, 3.0, 3.0, nan) test(3.0) For a shape of zero, the string representing includes an empty list: '[]' test([]) Method |Parameter.compress_repr| works similarly for different |Parameter| subclasses. The following examples focus on a 2-dimensional parameter handling integer values: '?' test(?) test(?) test(3) test([[3, 3, -999999], [3, 3, 3]]) test(3) test([[]]) """

        if not hasattr(self, 'value'):
            return '?'
        if not self:
            return f"{self.NDIM * '['}{self.NDIM * ']'}"
        unique = numpy.unique(self[self.mask])
        if sum(numpy.isnan(unique)) == len(unique.flatten()):
            unique = numpy.array([numpy.nan])
        else:
            unique = self.revert_timefactor(unique)
        if len(unique) == 1:
            return objecttools.repr_(unique[0])
        return None