desc.objectives.FixThetaSFL

class desc.objectives.FixThetaSFL(eq=None, name='Theta SFL')Source

Fixes lambda=0 so that poloidal angle is the SFL poloidal angle.

Parameters:

• eq (Equilibrium) – Equilibrium that will be optimized to satisfy the Objective.

• name (str, optional) – Name of the objective function.

Methods

build([eq, use_jit, verbose])	Build constant arrays.
compute(L_lmn, **kwargs)	Compute Theta SFL errors.
compute_scalar(*args, **kwargs)	Compute the scalar form of the objective.
compute_scaled(*args, **kwargs)	Compute and apply weighting and normalization.
compute_scaled_error(*args, **kwargs)	Compute and apply the target/bounds, weighting, and normalization.
compute_unscaled(*args, **kwargs)	Compute the raw value of the objective.
copy([deepcopy])	Return a (deep)copy of this object.
eq(other)	Compare equivalence between DESC objects.
jit()	Apply JIT to compute methods, or re-apply after updating self.
load(load_from[, file_format])	Initialize from file.
print_value(*args, **kwargs)	Print the value of the objective.
save(file_name[, file_format, file_mode])	Save the object.
xs(eq)	Return a tuple of args required by this objective from the Equilibrium eq.

Attributes

args	Names (str) of arguments to the compute functions.
bounds	Lower and upper bounds of the objective.
built	Whether the transforms have been precomputed (or not).
constants	Constant parameters such as transforms and profiles.
derivatives	Derivatives of the function wrt the argument given by the dict keys.
dim_f	Number of objective equations.
dimensions	Dimensions of the argument given by the dict keys.
fixed	Whether the objective fixes individual parameters (or linear combo).
linear	Whether the objective is a linear function (or nonlinear).
name	Name of objective function (str).
normalization	normalizing scale factor.
scalar	Whether default "compute" method is a scalar or vector.
target	Target value(s) of the objective.
weight	Weighting to apply to the Objective, relative to other Objectives.