How lorenniiis/qsp-telemetry-flight-lab works
QSP Telemetry Flight Lab is a local dashboard for cleaning flight telemetry and comparing simulator performance in VR versus monitor mode. The main workflow is to prepare or load a CSV, preprocess and filter it, then request scenario- and participant-specific metrics, visualizations, and statistical interpretation; metrics can also be exported. The README documents dashboard capabilities, but the supplied tree does not include its UI assets, and excerpts of both processing modules are partial, so the graph focuses on evidenced module boundaries and documented stages.
Main entry points: app.py Request handler · analysis.py Scenario metrics · clean_telemetry.py Archive cleaner
Components 15
Data preparation
- Archive cleaner
clean_telemetry.py
Local application
- HTTP server
app.py - Request handler
app.py - Data store
app.py
Analysis
- Input preprocessing
analysis.py - Demo data
analysis.py - Scenario metrics
analysis.py - Participant scores
analysis.py - Hotelling T²
analysis.py - Interpretation
analysis.py
Results
- Analysis dashboard
- Metrics export
app.py
Other components
- Researcher
- Study ZIP
- Telemetry CSV
Connections 20
- Researcher → HTTP server: starts or opens
- Researcher → Study ZIP: selects source
- Study ZIP → Archive cleaner: reads archive
- Archive cleaner → Telemetry CSV: writes cleaned data
- Researcher → Telemetry CSV: loads CSV
- Telemetry CSV → Request handler: uploads CSV
- Request handler → Data store: loads or resets
- HTTP server → Request handler: dispatches requests
- Data store → Demo data: creates initial data
- Data store → Input preprocessing: preprocesses input
- Request handler → Data store: requests analysis
- Data store → Scenario metrics: builds analysis
- Scenario metrics → Participant scores: computes participant metrics
- Scenario metrics → Hotelling T²: tests group differences
- Scenario metrics → Interpretation: builds interpretation
- Request handler → Analysis dashboard: returns analysis JSON
- Request handler → Participant scores: requests export metrics
- Request handler → Metrics export: returns CSV
- Researcher → Analysis dashboard: views results
- Researcher → Metrics export: downloads metrics