plfit/plfit_v1.py
def plotpdf(x,xmin,alpha,nbins=30,dolog=False):
    """
    Plots PDF and powerlaw....
    """

    x=sort(x)
    n=len(x)

    if dolog:
        hb = hist(x,bins=logspace(log10(min(x)),log10(max(x)),nbins),log=True)
        alpha += 1
    else:
        hb = hist(x,bins=linspace((min(x)),(max(x)),nbins))
    h,b=hb[0],hb[1]
    b = b[1:]

    q = x[x>=xmin]
    px = (alpha-1)/xmin * (q/xmin)**(-alpha)

    arg = argmin(abs(b-xmin))
    norm = mean( h[b>xmin] / ((alpha-1)/xmin * (b[b>xmin]/xmin)**(-alpha))  )
    px = px*norm

    loglog(q,px)

    gca().set_xlim(min(x),max(x))
def plotpdf(x,xmin,alpha,nbins=30,dolog=False):
    """
    Plots PDF and powerlaw....
    """

    x=sort(x)
    n=len(x)

    if dolog:
        hb = hist(x,bins=logspace(log10(min(x)),log10(max(x)),nbins),log=True)
        alpha += 1
    else:
        hb = hist(x,bins=linspace((min(x)),(max(x)),nbins))
    h,b=hb[0],hb[1]
    b = b[1:]

    q = x[x>=xmin]
    px = (alpha-1)/xmin * (q/xmin)**(-alpha)

    arg = argmin(abs(b-xmin))
    norm = mean( h[b>xmin] / ((alpha-1)/xmin * (b[b>xmin]/xmin)**(-alpha))  )
    px = px*norm

    loglog(q,px)

    gca().set_xlim(min(x),max(x))
def plotpdf ( x , xmin , alpha , nbins = 30 , dolog = False ) : x = sort ( x ) n = len ( x ) if dolog : hb = hist ( x , bins = logspace ( log10 ( min ( x ) ) , log10 ( max ( x ) ) , nbins ) , log = True ) alpha += 1 else : hb = hist ( x , bins = linspace ( ( min ( x ) ) , ( max ( x ) ) , nbins ) ) h , b = hb [ 0 ] , hb [ 1 ] b = b [ 1 : ] q = x [ x >= xmin ] px = ( alpha - 1 ) / xmin * ( q / xmin ) ** ( - alpha ) arg = argmin ( abs ( b - xmin ) ) norm = mean ( h [ b > xmin ] / ( ( alpha - 1 ) / xmin * ( b [ b > xmin ] / xmin ) ** ( - alpha ) ) ) px = px * norm loglog ( q , px ) gca ( ) . set_xlim ( min ( x ) , max ( x ) )
Plots PDF and powerlaw....
Plots PDF and powerlaw ....