MGP Decoder

The MGP Decoder interprets raw magnetic gauge phase signals into decoded phase values with accompanying metadata. It accepts standard MGP data assets such as time-stamped CSV or JSON dumps and produces traceable results suitable for engineering reports and publication-quality figures. The tool is designed for data engineers, lab technicians, and researchers who need a repeatable, auditable decoding workflow. By applying calibration profiles and standard mapping rules, it converts raw sensor signals into meaningful phase measurements while preserving timestamp integrity and provenance. Example: a dataset with fields timestamp, raw_signal, and sensor_id yields decoded_phase in degrees, a confidence score, and a quality flag.
Conceptually, decoding is a two-stage process: data conditioning and signal-to-phase mapping. First, the data parser certifies required fields, normalizes timestamps, and handles missing values. Next, a calibration profile applies a mapping (linear or piecewise) to produce decoded_phase, while computing a confidence metric from residuals and data completeness. The tool supports multiple profiles to compare datasets or reflect equipment setups. Output includes decoded_phase, confidence, flags, and optional traceability data such as profile_id and calibration_source. This design supports QA workflows and reproducibility.
Core value lies in automation, consistency, and exportability. Users gain reproducible results, reduced manual decoding effort, and ready-to-share artifacts for audits, R&D reports, or compliance documentation. Use cases include sensor calibration validation, batch analysis of MGP streams, cross-dataset comparisons, and export to CSV/JSON for downstream analytics. Unique differentiators include built-in validation rules against standard curves, multi-profile support, and explicit data lineage in the outputs.