def dspmt(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>):
t = np.asarray(t)<EOL>aryRsp1 = spmt(t, peak_delay=peak_delay, under_delay=under_delay,<EOL>peak_disp=peak_disp, under_disp=under_disp,<EOL>p_u_ratio=p_u_ratio)<EOL>aryRsp2 = spmt(t-<NUM_LIT:1>, peak_delay=peak_delay, under_delay=under_delay,<EOL>peak_disp=peak_disp, under_disp=under_disp,<EOL>p_u_ratio=p_u_ratio)<EOL>return aryRsp1 - aryRsp2<EOL>
SPM canonical HRF derivative, HRF 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 derivative function as used in SPM.
    [2] It is the numerical difference of the HRF sampled at time `t` minus the
    values sampled at time `t` -1

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