def from_config()

in aepsych/strategy.py [0:0]

• 29 lines of code
• 5 McCabe index (conditional complexity)

    def from_config(cls, config: Config, name: str):
        gen_cls = config.getobj(name, "generator", fallback=SobolGenerator)
        generator = gen_cls.from_config(config)

        model_cls = config.getobj(name, "model", fallback=None)
        if model_cls is not None:
            model = model_cls.from_config(config)
        else:
            model = None

        acqf_cls = config.getobj(name, "acqf", fallback=None)
        if acqf_cls is not None and hasattr(generator, "acqf"):
            if generator.acqf is None:
                generator.acqf = acqf_cls
                generator.acqf_kwargs = generator._get_acqf_options(acqf_cls, config)

        n_trials = config.getint(name, "n_trials")
        refit_every = config.getint(name, "refit_every", fallback=1)

        lb = config.gettensor(name, "lb")
        ub = config.gettensor(name, "ub")
        dim = config.getint(name, "dim", fallback=None)

        outcome_type = config.get(name, "outcome_type", fallback="single_probit")

        return cls(
            lb=lb,
            ub=ub,
            dim=dim,
            model=model,
            generator=generator,
            n_trials=n_trials,
            refit_every=refit_every,
            outcome_type=outcome_type,
        )