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autora.theorist.bsr.prior

get_prior_dict(prior_name='Uniform')

Get the dictionary of prior information as well as several list of key operator properties

Argument

prior_name: the name of the prior dictionary to use

Returns:

Name Type Description
ops_name_lst

the list of operator names
ops_weight_lst

the list of operator weights
prior_dict

the dictionary of operator prior information
Source code in temp_dir/bsr/src/autora/theorist/bsr/prior.py 
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def get_prior_dict(prior_name="Uniform"):
    """
    Get the dictionary of prior information as well as several list of key operator properties

    Argument:
        prior_name: the name of the prior dictionary to use

    Returns:
        ops_name_lst: the list of operator names
        ops_weight_lst: the list of operator weights
        prior_dict: the dictionary of operator prior information
    """
    ops_prior = _get_prior(prior_name)
    ops_init = _get_ops_init()
    ops_fn_and_arity = _get_ops_with_arity()

    ops_name_lst = list(ops_prior.keys())
    ops_weight_lst = list(ops_prior.values())
    prior_dict = {
        k: {
            "init": ops_init.get(k, {}),
            "fn": ops_fn_and_arity[k][0],
            "arity": ops_fn_and_arity[k][1],
            "weight": ops_prior[k],
        }
        for k in ops_prior
    }

    return ops_name_lst, ops_weight_lst, prior_dict

get_prior_list(prior_name='Uniform')

Get a dictionary of key prior properties

Argument

prior_name: the name of the prior dictionary to use

Returns:

Type Description

a dictionary that maps a prior property (e.g. name) to the list of such properties for each operator.
Source code in temp_dir/bsr/src/autora/theorist/bsr/prior.py 
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def get_prior_list(prior_name="Uniform"):
    """
    Get a dictionary of key prior properties

    Argument:
        prior_name: the name of the prior dictionary to use

    Returns:
        a dictionary that maps a prior property (e.g. `name`) to the list of such properties
            for each operator.
    """
    ops_prior = _get_prior(prior_name)
    ops_init = _get_ops_init()
    ops_fn_and_arity = _get_ops_with_arity()

    ops_name_lst = list(ops_prior.keys())
    ops_weight_lst = list(ops_prior.values())
    ops_init_lst = [ops_init.get(k, None) for k in ops_name_lst]
    ops_fn_lst = [ops_fn_and_arity[k][0] for k in ops_name_lst]
    ops_arity_lst = [ops_fn_and_arity[k][1] for k in ops_name_lst]
    return {
        "name": ops_name_lst,
        "weight": ops_weight_lst,
        "init": ops_init_lst,
        "fn": ops_fn_lst,
        "arity": ops_arity_lst,
    }

linear_init(**hyper_params)

Initialization function for the linear operator. Two parameters, slope (a) and intercept (b) are initialized.

Parameters:

Name Type Description Default
hyper_params

the dictionary for hyperparameters. Specifically, this function requires sigma_a and sigma_b to be present.

 {}

Returns: a dictionary with initialized a and b parameters.

Source code in temp_dir/bsr/src/autora/theorist/bsr/prior.py 
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def linear_init(**hyper_params) -> Dict:
    """
    Initialization function for the linear operator. Two parameters, slope
    (a) and intercept (b) are initialized.

    Arguments:
        hyper_params: the dictionary for hyperparameters. Specifically, this
            function requires `sigma_a` and `sigma_b` to be present.
    Returns:
        a dictionary with initialized `a` and `b` parameters.
    """
    sigma_a, sigma_b = hyper_params.get("sigma_a", 1), hyper_params.get("sigma_b", 1)
    return {
        "a": norm.rvs(loc=1, scale=np.sqrt(sigma_a)),
        "b": norm.rvs(loc=0, scale=np.sqrt(sigma_b)),
    }