def interpolate_basis(self, basis, dt, dt_max,
                          norm=True):
        # Interpolate basis at the resolution of the data
        L,B = basis.shape
        t_int = np.arange(0.0, dt_max, step=dt)
        t_bas = np.linspace(0.0, dt_max, L)

        ibasis = np.zeros((len(t_int), B))
        for b in np.arange(B):
            ibasis[:,b] = np.interp(t_int, t_bas, basis[:,b])

        # Normalize so that the interpolated basis has volume 1
        if norm:
            # ibasis /= np.trapz(ibasis,t_int,axis=0)
            ibasis /= (dt * np.sum(ibasis, axis=0))

        if not self.allow_instantaneous:
            # Typically, the impulse responses are applied to times
            # (t+1:t+R). That means we need to prepend a row of zeros to make
            # sure the basis remains causal
            ibasis = np.vstack((np.zeros((1,B)), ibasis))

        return ibasis
dataset/ETHPy150Open slinderman/pyhawkes/pyhawkes/utils/basis.py/Basis.interpolate_basis/original