Create probabilistic sequencer
create_prob_sequencerBuild a Markov-chain step sequencer that transitions between states on each beat, outputting state and trigger channels for probabilistic rhythm generation.
Instructions
Build a Markov-chain step sequencer. On each beat boundary the COMP transitions from the current state to a next state sampled from the per-state weighted-transition table. Outputs two CHOP channels: 'state' (current state index) and 'trigger' (pulse on state change). Generative sibling of create_euclidean_sequencer and create_beat_grid_sequencer — great for evolving, probabilistic rhythms and generative state machines. NOTE: beat-callback timing requires a live TD session with time.play=1.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Container COMP name. | prob_seq |
| parent_path | No | Parent COMP path. | /project1 |
| bpm | No | Tempo written to Beat CHOP when no bpm_source is provided. | |
| division | No | Beat subdivision (1/4→1, 1/8→2, 1/16→4 beats-per-measure). | 1/8 |
| states | Yes | Markov states. Each state has a unique id, a weight (initial distribution), and a transitions map (keys = state ids, values ≥ 0). | |
| startState | No | Initial state id. If omitted, sampled from state weights. | |
| bpm_source | No | Path to an existing Beat CHOP / tempo source. Omit to build a new one. | |
| seed | No | If set, seeds Python random for reproducible runs. |