Design closed-loop start gating at the output layer
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评估
调研方向
首先检查现有的 open-loop stimulus.start 实现以及当前的 trigger/output 流程。只有在存在多种 trigger 输出模式之后，再重新考虑此 issue；预期结果是在计划的启动时间之前保持 classifier 评估和任何明确未进行 gating 的输出处于活动状态，同时实现 action 层路由和 laser gating。
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描述
Summary
As of 2026-04-11, stimulus.start is implemented for open-loop only. Closed-loop still begins classifier evaluation immediately at launch.
We discussed extending the same scheduling concept to closed-loop, but decided not to implement it yet because the correct semantics depend on future non-laser outputs such as notifications.
Problem
A naive closed-loop implementation would delay the classifier itself until the scheduled start time. That is too blunt if we later want trigger-driven behaviors that should remain active before laser output is armed, for example:
- notifications
- event logging
- counters / monitoring
Desired Direction
When closed-loop scheduling is added, the gate should apply to the output/action layer, not necessarily to classifier evaluation.
This should let us support behavior such as:
- classifier continues evaluating before the start gate
- UI/status can still reflect trigger state before the gate opens
- laser output remains suppressed until the configured start time
- future output modes may choose whether they obey the same gate
Design Questions
- Should gating be configured per output mode?
- Should
laserbe gated while futurenotifyactions remain active? - How should pre-gate trigger events appear in the UI and logs?
- Should the trigger/stim status panels explicitly show that stimulation is suppressed by schedule?
Proposed Follow-up
Revisit this after we add multiple trigger output modes. At that point:
- Define action-layer routing and output modes.
- Add a closed-loop start gate that applies to laser output.
- Decide whether other outputs (
notify, logging-only actions, etc.) should ignore or honor the same gate.
Current Decision
Do not implement closed-loop stimulus.start scheduling yet. Keep the open-loop implementation. Revisit after output modes are expanded.
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- Python
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