Predict

predict(rc, steps::Integer, ps, st; initialdata=nothing)
predict(rc, data::AbstractMatrix, ps, st)

Run the model either in (1) closed-loop (auto-regressive) mode for a fixed number of steps, or in (2) teacher-forced (point-by-point) mode over a given input sequence.

1) Auto-regressive rollout

Behavior

• Rolls the model forward for steps time steps.
• At each step, the model’s output becomes the next input.

Arguments

• rc: The reservoir chain / model.
• steps: Number of time steps to generate.
• ps: Model parameters.
• st: Model states.

Keyword Arguments

• initialdata=nothing: Column vector used as the first input. Has to be provided.

Returns

• output: Generated outputs of shape (out_dims, steps).
• st: Final model state after steps steps.

2) Teacher-forced / point-by-point

• Feeds each column of data as input; the model state is threaded across time, and an output is produced for each input column.

Arguments

• rc: The reservoir chain / model.
• data: Input sequence of shape (in_dims, T) (columns are time).
• ps: Model parameters.
• st: Model states.

Returns

• output: Outputs for each input column, shape (out_dims, T).
• st: Updated minal model states.