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brahmap.core.GLSParameters

A data class encapsulating the configuration parameters for the Generalized Least Squares (GLS) map-making algorithm.

Attributes:

Name Type Description
solver_type SolverType

The map-making solver configuration to use (e.g. \(I\), \(QU\), \(IQU\))
use_iterative_solver bool

Whether to enforce the use of an iterative solver (like PCG) for map-making
isolver_threshold float

The numerical tolerance threshold for the iterative solver to declare convergence
isolver_max_iterations int

The maximum number of iterations allowed for the iterative solver
callback_function Callable

A callable function executed at each iteration of the solver
return_processed_samples bool

Whether the GLS solver function should return the processed time samples container
return_hit_map bool

Whether the function should the pixel hit map
Source code in brahmap/core/GLS.py 
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@dataclass
class GLSParameters:
    """A data class encapsulating the configuration parameters for the
    Generalized Least Squares (GLS) map-making algorithm.

    Attributes
    ----------
    solver_type : SolverType
        The map-making solver configuration to use (e.g. $I$, $QU$, $IQU$)
    use_iterative_solver : bool
        Whether to enforce the use of an iterative solver (like PCG) for map-making
    isolver_threshold : float
        The numerical tolerance threshold for the iterative solver to
        declare convergence
    isolver_max_iterations : int
        The maximum number of iterations allowed for the iterative solver
    callback_function : Callable
        A callable function executed at each iteration of the solver
    return_processed_samples : bool
        Whether the GLS solver function should return the processed time
        samples container
    return_hit_map : bool
        Whether the function should the pixel hit map
    """

    solver_type: SolverType = SolverType.IQU
    use_iterative_solver: bool = True
    isolver_threshold: float = 1.0e-12
    isolver_max_iterations: int = 100
    callback_function: Callable | None = None
    return_processed_samples: bool = False
    return_hit_map: bool = False