(coefficients, t0, t1, t)
return total
Evaluate polynomial interpolation at the given time point.

    Args:
        coefficients: list of Tensor coefficients as created by `interp_fit`.
        t0: scalar float64 Tensor giving the start of the interval.
        t1: scalar float64 Tensor giving the end of the interval.
        t: scalar float64 Tensor giving the desired interpolation point.

    Returns:
        Polynomial interpolation of the coefficients at time `t`.
Evaluate polynomial interpolation at the given time point.
Evaluate polynomial interpolation at the given time point .
def _interp_evaluate(coefficients, t0, t1, t):
    """Evaluate polynomial interpolation at the given time point.

    Args:
        coefficients: list of Tensor coefficients as created by `interp_fit`.
        t0: scalar float64 Tensor giving the start of the interval.
        t1: scalar float64 Tensor giving the end of the interval.
        t: scalar float64 Tensor giving the desired interpolation point.

    Returns:
        Polynomial interpolation of the coefficients at time `t`.
    """

    assert (t0 <= t) & (t <= t1), 'invalid interpolation, fails `t0 <= t <= t1`: {}, {}, {}'.format(t0, t, t1)
    x = (t - t0) / (t1 - t0)
    x = x.to(coefficients[0].dtype)

    total = coefficients[0] + x * coefficients[1]
    x_power = x
    for coefficient in coefficients[2:]:
        x_power = x_power * x
        total = total + x_power * coefficient

    return total
def _interp_evaluate ( coefficients , t0 , t1 , t ) : assert ( t0 <= t ) & ( t <= t1 ) , 'invalid interpolation, fails `t0 <= t <= t1`: {}, {}, {}' . format ( t0 , t , t1 ) x = ( t - t0 ) / ( t1 - t0 ) x = x . to ( coefficients [ 0 ] . dtype ) total = coefficients [ 0 ] + x * coefficients [ 1 ] x_power = x for coefficient in coefficients [ 2 : ] : x_power = x_power * x total = total + x_power * coefficient return total