Rapid processing of experimental data for key plasma profiles on EAST tokamak

To address the inefficiency and heavy manual dependence workflow of the diagnostic data processing of kinetic profiles and transport analysis for the core region plasmas on the EAST tokamak, this study develops an integrated and rapid processing framework for experimental plasma data. With only the discharge number as input, the framework automatically retrieves multi-diagnostic signals from the MDSplus database and applies a local robust outlier detection method based on an iteratively weighted spline reference curve for anomaly detection and data cleaning. High-quality radial kinetic profiles of electron temperature, electron density, and ion temperature are obtained using a segmented multi-function fitting strategy combined with smooth transition algorithm based on gradient integration. Based on the profiles, the framework automatically extracts the required inputs for auxiliary heating modules and integrates fast lower hybrid wave and electron cyclotron wave heating models to compute power deposition and current drive profiles. The ONETWO transport code is then employed to invert electron and ion thermal diffusivities, enabling a fully automated workflow from experimental diagnostics to transport parameter estimation. The performance of the proposed framework is validated using EAST discharge No. 63948, where the complete processing of 35 time slices for a single discharge is completed within ∼20 s. Compared with conventional transport analysis workflows, the developed program significantly improves computational efficiency while maintaining physical consistency, providing an effective tool for rapid between-shot transport analysis on EAST and practical support for quasi real-time transport evaluation and discharge scenario optimization.