"""
=================================
Box plots with custom fill colors
=================================

This plot illustrates how to create two types of box plots
(rectangular and notched), and how to fill them with custom
colors by accessing the properties of the artists of the
box plots. Additionally, the ``labels`` parameter is used to
provide x-tick labels for each sample.

A good general reference on boxplots and their history can be found
here: http://vita.had.co.nz/papers/boxplots.pdf
"""

import matplotlib.pyplot as plt
import numpy as np

if __name__ == "__main__":

    # Random test data
    np.random.seed(123)
    all_data = [np.random.normal(0, std, 100) for std in range(1, 10)]

    fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))

    # rectangular box plot
    bplot1 = axes[0].boxplot(all_data,
                             vert=True,   # vertical box aligmnent
                             patch_artist=True)   # fill with color

    # notch shape box plot
    bplot2 = axes[1].boxplot(all_data,
                             notch=True,  # notch shape
                             vert=True,   # vertical box aligmnent
                             patch_artist=True)   # fill with color

    # fill with colors
    colors = ['pink', 'lightblue', 'lightgreen']
    for bplot in (bplot1, bplot2):
        for patch, color in zip(bplot['boxes'], colors):
            patch.set_facecolor(color)

    # adding horizontal grid lines
    for ax in axes:
        ax.yaxis.grid(True)
        ax.set_xticks([y+1 for y in range(len(all_data))], )
        ax.set_xlabel('xlabel')
        ax.set_ylabel('ylabel')

    # add x-tick labels
    plt.setp(axes, xticks=[y+1 for y in range(len(all_data))],
             xticklabels=['x1', 'x2', 'x3', 'x4'])

    plt.show()