cumulative plot

import numpy as np
import seaborn as sns

def sns_color_ls():
    return sns.color_palette("Set1", n_colors=8, desat=.5)*2
    
def cumulate_dist_plot(ls_ls,ls_ls_label,bins=40,title=None,ax=None,savefn=None,xlabel=None,ylabel=None,add_vline=None,add_hline=None,log2transform=0,xlim=None,ylim=None):
    if ax is None:
        with sns.axes_style("ticks"):
            fig,ax = plt.subplots(figsize=(8,8))
            
    color_ls = sns_color_ls()
    
    ls_ls_label = [j+' ('+str(len(i))+')' for i,j in zip(ls_ls,ls_ls_label)]
    
    if log2transform:
        ls_ls = [np.log2(i) for i in ls_ls]
        
    for n,ls in enumerate(ls_ls):
        values,base = np.histogram(ls,bins=bins)
        cumulative = np.cumsum(values)
        cumulative_norm = [i/float(len(ls)) for i in cumulative]
        ax.plot(base[:-1],cumulative_norm,color=color_ls[n],label=ls_ls_label[n])
        print "plot line num: %s"%(n)
    
    if xlabel is not None:
        ax.set_xlabel(xlabel)
        
    if ylabel is not None:
        ax.set_ylabel(ylabel)
    else:
        ax.set_ylabel("Accumulate percent over total")
        
    if title is not None:
        ax.set_title(title)
        
    if add_vline is not None:
        for vline in add_vline:
            ax.axvline(vline,ls="--", color='lightgrey')
            
    if add_hline is not None:
        for hline in add_hline:
            ax.axhline(hline,ls="--", color='lightgrey')
            
    if xlim is not None:
        ax.set_xlim(xlim[0], xlim[1])
        
    if ylim is not None:
        ax.set_ylim(ylim[0], ylim[1])
        
    ax.legend(loc="best")
    
    if savefn is not None:
        plt.savefig(savefn)
        plt.close()

mu1, sigma1 = 0, 0.1
mu2, sigma2 = 0, 0.4
mu3, sigma3 = 0, 0.8

s1 = np.random.normal(mu1, sigma1, 1000)
s2 = np.random.normal(mu2, sigma2, 1000)
s3 = np.random.normal(mu3, sigma3, 1000)

cumulate_dist_plot(ls_ls=[s1,s2,s3],ls_ls_label=['S1','S2','S3'],bins=40)