Support for different TF representations is inconsistent

[ggventurini]

Sometimes a TF can be provided only with "simplified zpk form", ie (ndarray zeros, ndarray poles, scalar gain), sometimes an LTI object from scipy is accepted too, sometimes a tuple representation like (ndarray num, ndarray den) is also valid.

• Evaluate adding an helper method
• Ensure consistency across the package

[ggventurini]

Support for different representations is provided through:

• _is_zpk(), _is_num_den(), _is_A_B_C_D() for checking
• _get_zpk(), _get_num_den() for switching in between.

Notice we need the latter two because scipy provides similar functionality but has no support for the ABCD matrix representation, which python-deltasigma supports, coherently with the MATLAB toolbox.

Also, a method _is_ABCD(), which would theoretically complement the _is*() above, was not implemented since if no info is given about the TF, the best we can do is return is_instance(np.ndarray), which the user can do himself.

Converting between ABCD and A,B,C,D representations is done elsewhere, through _partitionABCD().

Finally, commit e31c1ac9ef01139e98942222ba47f3d8f3049860 should be the last change set required to close this issue, if I did not miss anything.