- pylops.optimization.leastsquares.normal_equations_inversion(Op, y, Regs, x0=None, Weight=None, dataregs=None, epsI=0.0, epsRs=None, NRegs=None, epsNRs=None, engine='scipy', show=False, **kwargs_solver)¶
Inversion of normal equations.
Solve the regularized normal equations for a system of equations given the operator
Op, a data weighting operator
Weightand optionally a list of regularization terms
Operator to invert of size \([N \times M]\)
Data of size \([N \times 1]\)
Regularization operators (
Noneto avoid adding regularization)
Initial guess of size \([M \times 1]\)
Regularization data (must have the same number of elements as
Regularization dampings (must have the same number of elements as
Normal regularization operators (
Noneto avoid adding regularization). Such operators must apply the chain of the forward and the adjoint in one go. This can be convenient in cases where a faster implementation is available compared to applying the forward followed by the adjoint.
Regularization dampings for normal operators (must have the same number of elements as
Solver to use (
Display normal equations solver log
Arbitrary keyword arguments for chosen solver (
pylops.optimization.solver.cgare used for engine
When user does not supply
atol, it is set to “legacy”.