performance/compare.py
def tdist95conf_level(df):
    """Approximate the 95% confidence interval for Student's T distribution.

    Given the degrees of freedom, returns an approximation to the 95%
    confidence interval for the Student's T distribution.

    Args:
        df: An integer, the number of degrees of freedom.

    Returns:
        A float.
    """
    df = int(round(df))
    highest_table_df = len(_T_DIST_95_CONF_LEVELS)
    if df >= 200:
        return 1.960
    if df >= 100:
        return 1.984
    if df >= 80:
        return 1.990
    if df >= 60:
        return 2.000
    if df >= 50:
        return 2.009
    if df >= 40:
        return 2.021
    if df >= highest_table_df:
        return _T_DIST_95_CONF_LEVELS[highest_table_df - 1]
    return _T_DIST_95_CONF_LEVELS[df]
def tdist95conf_level(df):
    """Approximate the 95% confidence interval for Student's T distribution.

    Given the degrees of freedom, returns an approximation to the 95%
    confidence interval for the Student's T distribution.

    Args:
        df: An integer, the number of degrees of freedom.

    Returns:
        A float.
    """
    df = int(round(df))
    highest_table_df = len(_T_DIST_95_CONF_LEVELS)
    if df >= 200:
        return 1.960
    if df >= 100:
        return 1.984
    if df >= 80:
        return 1.990
    if df >= 60:
        return 2.000
    if df >= 50:
        return 2.009
    if df >= 40:
        return 2.021
    if df >= highest_table_df:
        return _T_DIST_95_CONF_LEVELS[highest_table_df - 1]
    return _T_DIST_95_CONF_LEVELS[df]
Approximate the 95% confidence interval for Student's T distribution.

    Given the degrees of freedom, returns an approximation to the 95%
    confidence interval for the Student's T distribution.

    Args:
        df: An integer, the number of degrees of freedom.

    Returns:
        A float.