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

        normalized_pdf = self.lognormal_dist.pdf(self.data)/self.lognormal_dist.pdf(self.data).max()
        minY,maxY = pylab.gca().get_ylim()
        pylab.plot(self.data,normalized_pdf*maxY,'.',**kwargs)
def plot_lognormal_pdf(self,**kwargs):
        """
        Plot the fitted lognormal distribution
        """
        if not hasattr(self,'lognormal_dist'):
            return

        normalized_pdf = self.lognormal_dist.pdf(self.data)/self.lognormal_dist.pdf(self.data).max()
        minY,maxY = pylab.gca().get_ylim()
        pylab.plot(self.data,normalized_pdf*maxY,'.',**kwargs)
def plot_lognormal_pdf ( self , * * kwargs ) : if not hasattr ( self , 'lognormal_dist' ) : return normalized_pdf = self . lognormal_dist . pdf ( self . data ) / self . lognormal_dist . pdf ( self . data ) . max ( ) minY , maxY = pylab . gca ( ) . get_ylim ( ) pylab . plot ( self . data , normalized_pdf * maxY , '.' , * * kwargs )
Plot the fitted lognormal distribution
Plot the fitted lognormal distribution