Plasma equilibrium is the basis for various tokamak research topics, such as plasma performance evaluation, plasma control, and physical analysis of instability, etc. In this study, we have developed a Python-based toolkit with a graphical user interface (GUI) to reconstruct the tokamak plasma equilibrium, which is called the Py-EFIT program. The main implementation steps of Py-EFIT program are introduced. Firstly, various magnetic diagnostic signals and machine structure of Experimental Advanced Superconducting Tokamak (EAST) are utilized as the inputs for computation. Secondly, the plasma magnetic flux distribution is numerically determined based on these inputs according to the plasma equilibrium reconstruction principle. Finally, a GUI of Py-EFIT program is developed for function execution and visualization of results. This program provides a convenient and user-friendly platform for plasma equilibrium calculation. It has been successfully applied for experimental analysis and plasma equilibrium reconstruction on EAST, which also indicates its potential for practical applications in more tokamak devices. Program summaryProgram title: Py-EFITCPC Library link to program files:https://doi.org/10.17632/85f8kj7hvp.1Licensing provisions: GNU General Public License 3Programming language: PythonNature of problem: Plasma equilibrium is the basis for many tokamak research topics, such as plasma performance evaluation, plasma control, physical analysis, etc. But plasma equilibrium cannot be obtained from experimental measurements directly, it has to be calculated through ‘equilibrium reconstruction’ technique. This program (Py-EFIT) provides an efficient, open-source, user-friendly, expandable, and portable computation platform for equilibrium reconstruction calculation.Solution method: 1. Code initialization, including grid mesh division and parameter declaration; 2. Give flux function an initial guess; 3. Construct plasma current matrix and response matrix; 4. Solve for plasma current based on diagnostic signals; 5. Calculate updated flux function based on Green-function method; 6. Refine flux value at magnetic axis and X-points; 7. Evaluate the difference between two iteration steps; 8. Output results until convergence condition is satisfied.
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