metrics.py 文件源码

def stat_power(control, trial, ci=0.975):
    '''
    Calculates statistical power.

    Parameters
    ----------
    control : array-type
        Control population sample.

    trial: array-type
        Trial population sample.

    Returns
    -------
    Float

    '''

    # Calculate the mean, se and me-(4 std)
    control = np.log(control)
    trial = np.log(trial)

    control_mean = np.mean(control)
    trial_mean = np.mean(trial)

    control_se = np.std(control, ddof=1) / np.sqrt(control.shape[0])
    trial_se = np.std(trial, ddof=1) / np.sqrt(trial.shape[0])

    # Create a normal distribution based on mean and se
    null_norm = sc.norm(control_mean, control_se)
    alt_norm = sc.norm(trial_mean, trial_se)

    # Calculate the rejection values (X*)
    reject_low = null_norm.ppf((1 - ci) / 2)
    reject_high = null_norm.ppf(ci + (1 - ci) / 2)

    # Calculate power
    power_lower = alt_norm.cdf(reject_low)
    power_higher = 1 - alt_norm.cdf(reject_high)
    power = (power_lower + power_higher) * 100
    return power