desc.objectives.FixThetaSFL
- class desc.objectives.FixThetaSFL(eq, 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
([use_jit, verbose])Build constant arrays.
compute
(params[, constants])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.
equiv
(other)Compare equivalence between DESC objects.
grad
(*args, **kwargs)Compute gradient vector of self.compute_scalar wrt x.
hess
(*args, **kwargs)Compute Hessian matrix of self.compute_scalar wrt x.
jac_scaled
(*args, **kwargs)Compute Jacobian matrix of self.compute_scaled wrt x.
jac_scaled_error
(*args, **kwargs)Compute Jacobian matrix of self.compute_scaled_error wrt x.
jac_unscaled
(*args, **kwargs)Compute Jacobian matrix of self.compute_unscaled wrt x.
jit
()Apply JIT to compute methods, or re-apply after updating self.
jvp_scaled
(v, x[, constants])Compute Jacobian-vector product of self.compute_scaled.
jvp_scaled_error
(v, x[, constants])Compute Jacobian-vector product of self.compute_scaled_error.
jvp_unscaled
(v, x[, constants])Compute Jacobian-vector product of self.compute_unscaled.
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
(*things)Return a tuple of args required by this objective from optimizable things.
Attributes
Lower and upper bounds of the objective.
Whether the transforms have been precomputed (or not).
Constant parameters such as transforms and profiles.
Number of objective equations.
Whether the objective fixes individual parameters (or linear combo).
Whether the objective is a linear function (or nonlinear).
Name of objective (str).
normalizing scale factor.
Whether default "compute" method is a scalar or vector.
Target value(s) of the objective.
Optimizable things that this objective is tied to.
Weighting to apply to the Objective, relative to other Objectives.