HFE System

Environment Setup

• (Optional) Activate the PlatformIO environment for firmware work: source /home/pocar-lab/platformio-venv/bin/activate
• Create a Python virtual environment for the supervisor + tooling: python3 -m venv .venv && source .venv/bin/activate
• Install Python dependencies: pip install -e .[analysis,notebooks]
• Install the analysis helpers for notebooks/CLI: pip install -e analysis

Firmware Workflow

• cd firmware
• platformio run -t upload

Supervisor API

• Configure config/config.yaml with the serial port, bind host/port, and (optionally) auth_token.
• Launch the API: bash scripts/start_supervisor.sh
• Override at runtime with env vars: SUPERVISOR_TOKEN (auth), SUP_HOST (host:port for clients), SUP_API (HTTP base URL).
• Typical SSH workflow:
  1. SSH into the lab host (no X forwarding needed).
  2. Activate the project environment if applicable (source .venv/bin/activate).
  3. Start the supervisor in one terminal:
     bash scripts/start_supervisor.sh
     Leave it running; it binds to 0.0.0.0:8000 for remote clients.

Live Clients

• Web GUI: http://<host>:8000/ui
  • Dark/light aware layout with responsive plot, live valve state, and per-sensor readouts.
  • Adjust setpoint/hysteresis/telemetry interval and choose which sensors feed the Auto/average logic via checkboxes; view each sensor's latest value as a chip.
  • Forward over SSH: ssh -L 8000:localhost:8000 <user>@<host> then browse http://localhost:8000/ui
  • Copy link with ?token=... if auth enabled, or load without token when Auth required: False.
  • The logging toggle starts streaming telemetry to data/raw/<timestamp>.csv on the supervisor host while buffering a local download; pressing it again ("Stop Logging") stops the server-side log and saves a copy to your browser.
• Serial/UI logger (legacy): python3 scripts/plot_temp.py (set PORT if needed).

Data Analysis

• Command-line pipeline: hfe-hx --input data/raw/<file>.csv
  • Outputs go to data/processed/ and data/reports/ (configurable via flags).
• Notebook: open analysis/notebooks/HX_performance_analysis.ipynb after installing the analysis package above.

Git / GitHub

• Use the VS Code Source Control pane to commit and push changes.