plfit/plfit.py
def plot_lognormal_cdf(self,**kwargs):
        """
        Plot the fitted lognormal distribution
        """
        if not hasattr(self,'lognormal_dist'):
            return

        x=np.sort(self.data)
        n=len(x)
        xcdf = np.arange(n,0,-1,dtype='float')/float(n)
        lcdf = self.lognormal_dist.sf(x)

        D_location = argmax(xcdf-lcdf)
        pylab.vlines(x[D_location],xcdf[D_location],lcdf[D_location],color='m',linewidth=2)

        pylab.plot(x, lcdf,',',**kwargs)
def plot_lognormal_cdf(self,**kwargs):
        """
        Plot the fitted lognormal distribution
        """
        if not hasattr(self,'lognormal_dist'):
            return

        x=np.sort(self.data)
        n=len(x)
        xcdf = np.arange(n,0,-1,dtype='float')/float(n)
        lcdf = self.lognormal_dist.sf(x)

        D_location = argmax(xcdf-lcdf)
        pylab.vlines(x[D_location],xcdf[D_location],lcdf[D_location],color='m',linewidth=2)

        pylab.plot(x, lcdf,',',**kwargs)
Plot the fitted lognormal distribution