import numpy as np
import matplotlib.pyplot as plt

#x = np.random.randn( 40, 10 )
#np.save('boxwhiskerdata', x )
x = np.load('boxwhiskerdata.npy')

plt.xkcd()
fig = plt.figure( figsize=(6,4) )
ax = fig.add_subplot( 1, 1, 1 )
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.set_xlabel('Experiment')
ax.set_ylabel('x')
ax.set_ylim( -4.0, 4.0)
ax.annotate('Median',
            xy=(3.9, 0.1), xycoords='data',
            xytext=(3.5, -2.5), textcoords='data', ha='right',
            arrowprops=dict(arrowstyle="->", relpos=(0.8,1.0),
            connectionstyle="angle3,angleA=-110,angleB=60") )
ax.annotate('1. quartile',
            xy=(5.8, -0.7), xycoords='data',
            xytext=(5.5, -3.5), textcoords='data', ha='right',
            arrowprops=dict(arrowstyle="->", relpos=(0.5,1.0),
            connectionstyle="angle3,angleA=30,angleB=70") )
ax.annotate('3. quartile',
            xy=(6.1, 0.6), xycoords='data',
            xytext=(6.5, 3.0), textcoords='data', ha='left',
            arrowprops=dict(arrowstyle="->", relpos=(0.0,0.0),
            connectionstyle="angle3,angleA=30,angleB=70") )
ax.annotate('minimum',
            xy=(6.1, -2.3), xycoords='data',
            xytext=(7.2, -3.3), textcoords='data', ha='left',
            arrowprops=dict(arrowstyle="->", relpos=(0.0,0.5),
            connectionstyle="angle3,angleA=10,angleB=100") )
ax.annotate('maximum',
            xy=(5.9, 2.8), xycoords='data',
            xytext=(4.9, 3.5), textcoords='data', ha='right',
            arrowprops=dict(arrowstyle="->", relpos=(1.0,0.5),
            connectionstyle="angle3,angleA=0,angleB=120") )
ax.boxplot( x, whis=100.0 )
plt.tight_layout()
plt.savefig('boxwhisker.pdf')
plt.show()