def ddspmt(t, peak_delay=<NUM_LIT:6>, under_delay=<NUM_LIT:16>, peak_disp=<NUM_LIT:1>, under_disp=<NUM_LIT:1>,<EOL>p_u_ratio=<NUM_LIT:6>):
_spm_dd_func = partial(spmt, peak_delay=peak_delay,<EOL>under_delay=under_delay,<EOL>under_disp=under_disp, p_u_ratio=p_u_ratio,<EOL>peak_disp=<NUM_LIT>)<EOL>return (spmt(t) - _spm_dd_func(t)) / <NUM_LIT><EOL>
SPM canonical HRF dispersion derivative, values for time values `t`

    Parameters
    ----------
    t : array-like
        vector of times at which to sample HRF

    Returns
    -------
    hrf : array
        vector length ``len(t)`` of samples from HRF at times `t`

    Notes
    -----
    [1] This is the canonical HRF dispersion derivative function as used in SPM
    [2] It is the numerical difference between the HRF sampled at time `t`, and
    values at `t` for another HRF shape with a small change in the peak
    dispersion parameter (``peak_disp`` in func:`spm_hrf_compat`).

    References:
    -----
    [1] http://nipy.org/
    [2] https://github.com/fabianp/hrf_estimation