Plots a normal distribution CDF with the given mean and variance.
    x-axis contains the mean, the y-axis shows the cumulative probability.

    Parameters
    ----------

    xs : list-like of scalars
        x values corresponding to the values in `y`s. Can be `None`, in which
        case range(len(ys)) will be used.

    ys : list-like of scalars
        list of probabilities to be plotted which should sum to 1.

    ax : matplotlib axes object, optional
        If provided, the axes to draw on, otherwise plt.gca() is used.

    xlim, ylim: (float,float), optional
        specify the limits for the x or y axis as tuple (low,high).
        If not specified, limits will be automatically chosen to be 'nice'

    xlabel : str,optional
        label for the x-axis

    ylabel : str, optional
        label for the y-axis

    label : str, optional
        label for the legend

    Returns
    -------
        axis of plot

def plot_discrete_cdf(xs, ys, ax=None, xlabel=None, ylabel=None,
                      label=None):
    """
    Plots a normal distribution CDF with the given mean and variance.
    x-axis contains the mean, the y-axis shows the cumulative probability.

    Parameters
    ----------

    xs : list-like of scalars
        x values corresponding to the values in `y`s. Can be `None`, in which
        case range(len(ys)) will be used.

    ys : list-like of scalars
        list of probabilities to be plotted which should sum to 1.

    ax : matplotlib axes object, optional
        If provided, the axes to draw on, otherwise plt.gca() is used.

    xlim, ylim: (float,float), optional
        specify the limits for the x or y axis as tuple (low,high).
        If not specified, limits will be automatically chosen to be 'nice'

    xlabel : str,optional
        label for the x-axis

    ylabel : str, optional
        label for the y-axis

    label : str, optional
        label for the legend

    Returns
    -------
        axis of plot
    """
    import matplotlib.pyplot as plt

    if ax is None:
        ax = plt.gca()

    if xs is None:
        xs = range(len(ys))
    ys = np.cumsum(ys)
    ax.plot(xs, ys, label=label)
    ax.set_xlabel(xlabel)
    ax.set_ylabel(ylabel)
    return ax