Python matplotlib.pyplot 模块，interactive() 实例源码

def analyze_lusolve(N):
    plt.clf()
    plt.interactive(True)
    I = InteractiveLUMatrix(N)
    plt.show(block=True)
    I.disconnect()

def interactive_matplotlib_context(on=True):
    old_mode = plt.isinteractive()
    plt.interactive(on)
    yield
    plt.interactive(old_mode)

def plot_data_dict(data_dict, plots = None, mode = 'static', hang = True, figure = None, size = None, **plot_preference_kwargs):
    """
    Make a plot of data in the format defined in data_dict
    :param data_dict: dict<str: plottable_data>
    :param plots: Optionally, a dict of <key: IPlot> identifying the plot objects to use (keys should
        be the same as those in data_dict).
    :return: The plots (same ones you provided if you provided them)
    """

    assert mode in ('live', 'static')
    if isinstance(data_dict, list):
        assert all(len(d) == 2 for d in data_dict), "You can provide data as a list of 2 tuples of (plot_name, plot_data)"
        data_dict = OrderedDict(data_dict)

    if plots is None:
        plots = {k: get_plot_from_data(v, mode = mode, **plot_preference_kwargs) for k, v in data_dict.items()}

    if figure is None:
        if size is not None:
            from pylab import rcParams
            rcParams['figure.figsize'] = size
        figure = plt.figure()
    n_rows, n_cols = vector_length_to_tile_dims(len(data_dict))
    for i, (k, v) in enumerate(data_dict.items()):
        plt.subplot(n_rows, n_cols, i + 1)
        plots[k].update(v)
        plots[k].plot()
        plt.title(k, fontdict = {'fontsize': 8})
    oldhang = plt.isinteractive()
    plt.interactive(not hang)
    plt.show()
    plt.interactive(oldhang)
    return figure, plots