interp_linear

interp_linear(prev_data: Tensor, next_data: Tensor, sample_at: Tensor, step_time: float, **kwargs) → Tensor

Interpolates between previous and next states linearlly.

\[D(t_s) = D(0) + \left( \frac{D(\Delta t) - D(0)}{\Delta t} \right)t_s\]

Parameters:

• prev_data (torch.Tensor) – most recent observation prior to sample time, \(D(t=0)\).

• next_data (torch.Tensor) – most recent observation subsequent to sample time, \(D(t=\Delta t)\).

• sample_at (torch.Tensor) – relative time at which to sample data, \(t_s\).

• step_time (float) – length of time between the prior and subsequent observations, \(\Delta t\).

Returns:

interpolated data at sample time, \(D(t=t_s)\).

Return type:

torch.Tensor