fwd3()#
- fwd3(states: ndarray, dt: float, inputs=None)[source]#
Third-order forward difference for estimating the first derivative.
\[\frac{\textup{d}}{\textup{d}t}\q(t)\bigg|_{t = t_j} \approx \frac{1}{6\delta t} (-11\q(t_j) + 18\q(t_{j+1}) - 9\q(t_{j+2}) + 2\q(t_{j+3}))\]where \(\delta t = t_{j+1} - t_j\) for all \(j\).
- Parameters:
- states(r, k) ndarray
State snapshots:
states[:, j]
is the state at time \(t_j\).- dtfloat
Time step between snapshots.
- inputs(m, k) or (k,) ndarray or None
Inputs corresponding to the states, if applicable.
- Returns:
- _states(r, k - 3) ndarray
State snapshots, excluding the last three snapshots.
- ddts(r, k - 3) ndarray
Time derivative estimates corresponding to the state snapshots.
- _inputs(m, k - 3) or (k - 3,) ndarray or None
Inputs corresponding to
_states
, if applicable. Only returned ifinputs
is notNone
.