def plot_increments(ax, increment_borders, label=None, *args, **kwargs):
    """Plot the increment borders from a list.  The first and last one

    :param ax: the axis on which to draw
    :param list increment_borders: the borders of the increments
    :param str label: the label to apply to one of the vertical lines
    """

    ax.axvline(x=increment_borders[1], label=label, *args, **kwargs)

    for increment in increment_borders[1:-1]:
        ax.axvline(x=increment, *args, **kwargs)

def plot_vegas_weighted_distribution(ax, points, dist,
                                     increment_borders, *args, **kwargs):
    """Plot the distribution with VEGAS weights applied.

    :param ax: axis
    :param points: points
    :param dist: distribution
    :param increment_borders: increment borders
    """

    num_increments = increment_borders.size
    weighted_dist = dist.copy()

    for left_border, right_border in zip(increment_borders[:-1],
                                        increment_borders[1:]):
        length = right_border - left_border
        mask = (left_border <= points) & (points <= right_border)
        weighted_dist[mask] = dist[mask]*num_increments*length

    ax.plot(points, weighted_dist, *args, **kwargs)

"""
Some shorthands for common plotting tasks related to the investigation
of monte-carlo methods in one rimension.

Author: Valentin Boettcher <hiro at protagon.space>
"""

import matplotlib.pyplot as plt

def draw_histo(points, xlabel, bins=20):
    heights, edges = np.histogram(points, bins)
    centers = (edges[1:] + edges[:-1])/2
    deviations = np.sqrt(heights)

    fig, ax = set_up_plot()
    ax.errorbar(centers, heights, deviations, linestyle='none', color='orange')
    ax.step(edges,  [heights[0], *heights], color='#1f77b4')

    ax.set_xlabel(xlabel)
    ax.set_xlim([points.min(), points.max()])
    return fig, ax