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brahmap.lbsim.LBSim_compute_GLS_maps

Source code in brahmap/lbsim/lbsim_GLS.py 
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def LBSim_compute_GLS_maps(
    nside: int,
    observations: Union[lbs.Observation, List[lbs.Observation]],
    pointings: Union[np.ndarray, List[np.ndarray], None] = None,
    hwp: Optional[lbs.HWP] = None,
    component: str = "tod",
    pointings_flag: Union[np.ndarray, None] = None,
    inv_noise_cov_operator: Union[DTypeNoiseCov, DTypeLBSNoiseCov, None] = None,
    threshold: float = 1.0e-5,
    dtype_float: Union[DTypeFloat, None] = None,
    LBSim_gls_parameters: LBSimGLSParameters = LBSimGLSParameters(),
) -> Union[LBSimGLSResult, tuple[LBSimProcessTimeSamples, LBSimGLSResult]]:
    if inv_noise_cov_operator is None:
        noise_weights = None
    else:
        noise_weights = inv_noise_cov_operator.diag

    processed_samples = LBSimProcessTimeSamples(
        nside=nside,
        observations=observations,
        pointings=pointings,
        hwp=hwp,
        pointings_flag=pointings_flag,
        solver_type=LBSim_gls_parameters.solver_type,
        noise_weights=noise_weights,
        output_coordinate_system=LBSim_gls_parameters.output_coordinate_system,
        threshold=threshold,
        dtype_float=dtype_float,
    )

    time_ordered_data = np.concatenate(
        [getattr(obs, component) for obs in observations], axis=None
    )

    gls_result = compute_GLS_maps_from_PTS(
        processed_samples=processed_samples,
        time_ordered_data=time_ordered_data,
        inv_noise_cov_operator=inv_noise_cov_operator,
        gls_parameters=LBSim_gls_parameters,
    )

    gls_result = LBSimGLSResult(
        nside=nside,
        coordinate_system=LBSim_gls_parameters.output_coordinate_system,
        **asdict(gls_result),
    )

    if LBSim_gls_parameters.return_processed_samples:
        return processed_samples, gls_result
    else:
        del processed_samples
        gc.collect()
        return gls_result