rinciple provides a very fast way to evaluate the plasma contribution to the magnetic signals. It has the potential of being a fast matching method. The performance of this method is hindered by the accuracy of the poloidal magnetic field computed from the equilibrium solver. A flux reconstruction package has been implemented which integrates a vacuum field solver using a filament model for the plasma, a multilayer perception neural network as an interface, and the volume integration of plasma current density using Green's functions as a matching method for the current profile parameters. The flux reconstruction package is applied to compare with the ASEQ and EFIT data.  The use of a variational method permits the Grad-Shafranov (GS) equation to be solved by reducing the problem of solving the 0D non-linear partial differential equation to the problem of minimizing a function of several variables. This high speed algorithm approximately solves the GS equation given a parameterization of the plasma boundary and the current profile (p