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Fraction Scan

puma.fraction_scan.get_fx_values #

Calculate the fraction values which are to be tested.

Parameters:

Name Type Description Default
resolution int

Resolution of the fraction values, by default 100

 100

Returns:

Type Description
numpy.ndarray

Array with the fraction values that are to be used.
Source code in puma/fraction_scan.py 
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def get_fx_values(resolution: int = 100) -> np.ndarray:
    """Calculate the fraction values which are to be tested.

    Parameters
    ----------
    resolution : int, optional
        Resolution of the fraction values, by default 100

    Returns
    -------
    np.ndarray
        Array with the fraction values that are to be used.
    """
    return np.concatenate((
        np.logspace(-3, -1, resolution // 2),
        np.linspace(0.1, 1.0, resolution // 2),
    ))

puma.fraction_scan.get_efficiency #

Calculate the efficiency for a given set of scores that are above a certain threshold.

Parameters:

Name Type Description Default
scores numpy.ndarray

Array of the output scores.

 required
fx float

Cut threshold for which needs to be passed.

 required

Returns:

Type Description
float

Efficiency (in percent) how many scores pass the threshold.
Source code in puma/fraction_scan.py 
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def get_efficiency(scores: np.ndarray, fx: float) -> float:
    """Calculate the efficiency for a given set of scores that are above a certain threshold.

    Parameters
    ----------
    scores : np.ndarray
        Array of the output scores.
    fx : float
        Cut threshold for which needs to be passed.

    Returns
    -------
    float
        Efficiency (in percent) how many scores pass the threshold.
    """
    return np.sum(scores > fx) / len(scores)

puma.fraction_scan.get_optimal_fraction_value #

After calculating a fraction scan, find the optimal fraction value.

Parameters:

Name Type Description Default
fraction_scan numpy.ndarray

2D array of efficiency (or rejection) scores for each fraction value.

 required
fraction_space numpy.ndarray

1D array of fraction values.

 required
rej bool

If True, find the maximum rejection values else find the minimum efficiency values, by default False.

 False

Returns:

Type Description
tuple[numpy.ndarray, numpy.ndarray]

Returns the optimal fraction value (index) and the actual value.
Source code in puma/fraction_scan.py 
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def get_optimal_fraction_value(
    fraction_scan: np.ndarray,
    fraction_space: np.ndarray,
    rej: bool = False,
) -> tuple[np.ndarray, np.ndarray]:
    """After calculating a fraction scan, find the optimal fraction value.

    Parameters
    ----------
    fraction_scan : np.ndarray
        2D array of efficiency (or rejection) scores for each fraction value.
    fraction_space : np.ndarray
        1D array of fraction values.
    rej : bool, optional
        If True, find the maximum rejection values else find the minimum efficiency values, by
        default False.

    Returns
    -------
    tuple[np.ndarray, np.ndarray]
        Returns the optimal fraction value (index) and the actual value.
    """
    # normalise x- and y-axes
    xs, ys = fraction_scan[:, 0], fraction_scan[:, 1]
    xs = xs / max(xs)
    ys = ys / max(ys)

    # if rej=True get maximum distance to origin
    opt_idx = np.argmax(xs**2 + ys**2) if rej else np.argmin(xs**2 + ys**2)

    return opt_idx, fraction_space[opt_idx]