(x_axis='num_of_queries')
Class to gathering, process and visualize active learning experiment results.

    Normally, the results should be a list which contains k elements. Each element represents
    one fold experiment result.
    Legal result object includes:
        - StateIO object.
        - A list contains n performances for n queries.
        - A list contains n tuples with 2 elements, in which, the first
          element is the x_axis (e.g., iteration, accumulative_cost),
          and the second element is the y_axis (e.g., the performance)

    Functions include:
        - Line chart (different x,y,axis, mean±std bars)
        - Paired t-test

    Parameters
    ----------
    x_axis: str, optional (default='num_of_queries')
        The x_axis when analysing the result.
        x_axis should be one of ['num_of_queries', 'cost'],
        if 'cost' is given, your experiment results must contains the
        cost value for each performance value.

    Returns
    -------
    analyser: BaseAnalyser
        The experiment analyser object
Class to gathering, process and visualize active learning experiment results.
Class to gathering process and visualize active learning experiment results .
def ExperimentAnalyser(x_axis='num_of_queries'):
    """Class to gathering, process and visualize active learning experiment results.

    Normally, the results should be a list which contains k elements. Each element represents
    one fold experiment result.
    Legal result object includes:
        - StateIO object.
        - A list contains n performances for n queries.
        - A list contains n tuples with 2 elements, in which, the first
          element is the x_axis (e.g., iteration, accumulative_cost),
          and the second element is the y_axis (e.g., the performance)

    Functions include:
        - Line chart (different x,y,axis, mean±std bars)
        - Paired t-test

    Parameters
    ----------
    x_axis: str, optional (default='num_of_queries')
        The x_axis when analysing the result.
        x_axis should be one of ['num_of_queries', 'cost'],
        if 'cost' is given, your experiment results must contains the
        cost value for each performance value.

    Returns
    -------
    analyser: BaseAnalyser
        The experiment analyser object

    """
    if x_axis not in ['num_of_queries', 'cost']:
        raise ValueError("x_axis should be one of ['num_of_queries', 'cost'].")
    if x_axis == 'num_of_queries':
        return _NumOfQueryAnalyser()
    else:
        return _CostEffectiveAnalyser()
def ExperimentAnalyser ( x_axis = 'num_of_queries' ) : if x_axis not in [ 'num_of_queries' , 'cost' ] : raise ValueError ( "x_axis should be one of ['num_of_queries', 'cost']." ) if x_axis == 'num_of_queries' : return _NumOfQueryAnalyser ( ) else : return _CostEffectiveAnalyser ( )