seaborn绘图将继承jupyter笔记本中的先前图形定义

Question

我已在此笔记本顶部定义了全局figsize：

import seaborn as sns

matplotlib.rcParams['figure.figsize'] = (16, 8)

当我调用将返回数字的函数时：

def plot_cross_validation_metric(
    df_cv, metric, rolling_window=0.1, ax=None, figsize=(10, 6)
):
    """
    df_cv: The output from fbprophet.diagnostics.cross_validation.
    metric: Metric name, one of ['mse', 'rmse', 'mae', 'mape', 'coverage'].
    rolling_window: Proportion of data to use for rolling average of metric.
        In [0, 1]. Defaults to 0.1.
    ax: Optional matplotlib axis on which to plot. If not given, a new figure
        will be created.
    figsize: Optional tuple width, height in inches.

    Returns
    -------
    a matplotlib figure.
    """
    if ax is None:
        fig = plt.figure(facecolor='w', figsize=figsize)
        ax = fig.add_subplot(111)
    else:
        fig = ax.get_figure()
    # Get the metric at the level of individual predictions, and with the rolling window.
    df_none = performance_metrics(df_cv, metrics=[metric], rolling_window=0)
    df_h = performance_metrics(df_cv, metrics=[metric], rolling_window=rolling_window)

    # Some work because matplotlib does not handle timedelta
    # Target ~10 ticks.
    tick_w = max(df_none['horizon'].astype('timedelta64[ns]')) / 10.
    # Find the largest time resolution that has <1 unit per bin.
    dts = ['D', 'h', 'm', 's', 'ms', 'us', 'ns']
    dt_names = [
        'days', 'hours', 'minutes', 'seconds', 'milliseconds', 'microseconds',
        'nanoseconds'
    ]
    dt_conversions = [
        24 * 60 * 60 * 10 ** 9,
        60 * 60 * 10 ** 9,
        60 * 10 ** 9,
        10 ** 9,
        10 ** 6,
        10 ** 3,
        1.,
    ]
    for i, dt in enumerate(dts):
        if np.timedelta64(1, dt) < np.timedelta64(tick_w, 'ns'):
            break

    x_plt = df_none['horizon'].astype('timedelta64[ns]').astype(np.int64) / float(dt_conversions[i])
    x_plt_h = df_h['horizon'].astype('timedelta64[ns]').astype(np.int64) / float(dt_conversions[i])

    ax.plot(x_plt, df_none[metric], '.', alpha=0.5, c='gray')
    ax.plot(x_plt_h, df_h[metric], '-', c='b')
    ax.grid(True)

    ax.set_xlabel('Horizon ({})'.format(dt_names[i]))
    ax.set_ylabel(metric)
    return fig

如果我将sns.plot放在该图之后，则输出图将继承先前的参数。

如果将其放在另一个块中将不会继承

如何避免此问题？