def plot_lognormal_cdf(self,**kwargs):
if not hasattr(self,'<STR_LIT>'):<EOL><INDENT>return<EOL><DEDENT>x=np.sort(self.data)<EOL>n=len(x)<EOL>xcdf = np.arange(n,<NUM_LIT:0>,-<NUM_LIT:1>,dtype='<STR_LIT:float>')/float(n)<EOL>lcdf = self.lognormal_dist.sf(x)<EOL>D_location = argmax(xcdf-lcdf)<EOL>pylab.vlines(x[D_location],xcdf[D_location],lcdf[D_location],color='<STR_LIT:m>',linewidth=<NUM_LIT:2>)<EOL>pylab.plot(x, lcdf,'<STR_LIT:U+002C>',**kwargs)<EOL>
Plot the fitted lognormal distribution