importmatplotlib.pyplotaspltimportnumpyasnpdefadjacent_values(vals,q1,q3):upper_adjacent_value=q3+(q3-q1)*1.5upper_adjacent_value=np.clip(upper_adjacent_value,q3,vals[-1])lower_adjacent_value=q1-(q3-q1)*1.5lower_adjacent_value=np.clip(lower_adjacent_value,vals[0],q1)returnlower_adjacent_value,upper_adjacent_valuedefset_axis_style(ax,labels):ax.set_xticks(np.arange(1,len(labels)+1),labels=labels)ax.set_xlim(0.25,len(labels)+0.75)ax.set_xlabel('Sample name')# create test datanp.random.seed(19680801)data=[sorted(np.random.normal(0,std,100))forstdinrange(1,5)]fig,(ax1,ax2,ax3)=plt.subplots(nrows=1,ncols=3,figsize=(9,3),sharey=True)ax1.set_title('Default violin plot')ax1.set_ylabel('Observed values')ax1.violinplot(data)ax2.set_title('Set colors of violins')ax2.set_ylabel('Observed values')ax2.violinplot(data,facecolor=[('yellow',0.3),('blue',0.3),('red',0.3),('green',0.3)],linecolor='black',)# Note that when passing a sequence of colors, the method will repeat the sequence if# less colors are provided than data distributions.ax3.set_title('Customized violin plot')parts=ax3.violinplot(data,showmeans=False,showmedians=False,showextrema=False,facecolor='#D43F3A',linecolor='black')forpcinparts['bodies']:pc.set_edgecolor('black')pc.set_linewidth(1)pc.set_alpha(1)quartile1,medians,quartile3=np.percentile(data,[25,50,75],axis=1)whiskers=np.array([adjacent_values(sorted_array,q1,q3)forsorted_array,q1,q3inzip(data,quartile1,quartile3)])whiskers_min,whiskers_max=whiskers[:,0],whiskers[:,1]inds=np.arange(1,len(medians)+1)ax3.scatter(inds,medians,marker='o',color='white',s=30,zorder=3)ax3.vlines(inds,quartile1,quartile3,color='k',linestyle='-',lw=5)ax3.vlines(inds,whiskers_min,whiskers_max,color='k',linestyle='-',lw=1)# set style for the axeslabels=['A','B','C','D']foraxin[ax1,ax2,ax3]:set_axis_style(ax,labels)plt.subplots_adjust(bottom=0.15,wspace=0.05)plt.show()

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