def plot_lines(x, fsamps, ax=None, downsample=100, **kwargs):
    """
    Plot function samples as a set of line plots.

    Parameters
    ----------
    x: 1D array-like
        x values to plot

    fsamps: 2D array-like
        set of functions to plot at each x. As returned by
        :func:`fgivenx.compute_samples`

    ax: axes object
        :class:`matplotlib.pyplot.ax` to plot on.

    downsample: int, optional
        Reduce the number of samples to a viewable quantity. (Default 100)

    any other keywords are passed to :meth:`matplotlib.pyplot.ax.plot`
    """
    if ax is None:
        ax = matplotlib.pyplot.gca()
    if downsample < len(fsamps.T):
        indices = numpy.random.choice(len(fsamps.T), downsample, replace=False)
    else:
        indices = numpy.arange(len(fsamps.T))
    color = kwargs.pop('color', 'k')
    alpha = kwargs.pop('alpha', 0.1)
    for y in fsamps.T[indices]:
        ax.plot(x, y, color=color, alpha=alpha, **kwargs)
def plot_lines ( x , fsamps , ax = None , downsample = 100 , ** kwargs ) : if ax is None : ax = matplotlib . pyplot . gca ( ) if downsample < len ( fsamps . T ) : indices = numpy . random . choice ( len ( fsamps . T ) , downsample , replace = False ) else : indices = numpy . arange ( len ( fsamps . T ) ) color = kwargs . pop ( 'color' , 'k' ) alpha = kwargs . pop ( 'alpha' , 0.1 ) for y in fsamps . T [ indices ] : ax . plot ( x , y , color = color , alpha = alpha , ** kwargs )
Plot function samples as a set of line plots.

    Parameters
    ----------
    x: 1D array-like
        x values to plot

    fsamps: 2D array-like
        set of functions to plot at each x. As returned by
        :func:`fgivenx.compute_samples`

    ax: axes object
        :class:`matplotlib.pyplot.ax` to plot on.

    downsample: int, optional
        Reduce the number of samples to a viewable quantity. (Default 100)

    any other keywords are passed to :meth:`matplotlib.pyplot.ax.plot`