mask-ddpm/docs/architecture.md

Architecture Overview

System Diagram (text)

            +--------------------+
            |  Program Generator |
            | (Type 1 setpoints) |
            +---------+----------+
                      |
                      v
            +-----------------------+
            | Controller / Actuator |
            | (Type 2/3 modules)    |
            +---------+-------------+
                      |
                      v
        +----------------------------+
        |  Diffusion (Residuals)     |
        |  - Continuous PVs          |
        |  - Discrete mask diffusion |
        +---------+------------------+
                  |
                  v
     +-----------------------------+
     | Post-processing             |
     | - Derived tags (Type 5)     |
     | - KS-only resample baseline |
     +-----------------------------+

Core Components

• Stage‑1 Temporal GRU: learns trend for continuous features.
• Diffusion Backbone: Transformer (default) or GRU; predicts residuals + discrete logits.
• Post-hoc Calibration: optional quantile calibration to align 1D CDFs.
• KS-only Baseline: Type1/2/3/5/6 empirical resampling for rapid KS reduction (diagnostic; may hurt joint realism).

Feature-Type Split

1. Type 1: Setpoints/demands → program generator
2. Type 2: Controller outputs → small emulator / conditional head
3. Type 3: Actuators/valves → spike‑and‑slab / dwell-time model
4. Type 4: Process PVs (multi‑modal/heavy tail) → diffusion with conditioning
5. Type 5: Derived tags → deterministic reconstruction (or empirical KS baseline)
6. Type 6: Auxiliary/vibration → narrow-band AR/SSM or empirical KS baseline

Data Flow

• Input CSV → stats/vocab → normalized batches
• Trend GRU → residual diffusion → inverse transforms → export