pdffit 0.1

Fit a Lognormal + Power law distribution to data

PDF_Fit

A code to fit the LN+PL or LN+2PL form to the density PDF of star forming regions. To use this:

pip install pdffit

Once you have installed, you can use the following sample script -

from fitter import *
import numpy as np


sample_data = np.load('./sample_data.npz')

#xdata and ydata are just two arrays. 
xdata = sample_data['arr_0']
ydata = sample_data['arr_1']
sink = float(sample_data['arr_2'])

params = Params(s_cut_off = sink)

p0 = [1.7, 1.6, 0.8, 7.1]
PLPLresult = PLPLFit(xdata, ydata, p0, params, use_K21=True)

p0 = [1.85, 1.57]
PLresult = PLFit(xdata, ydata, p0, params)

print (PLresult.sigma_err, PLresult.alpha_err, PLPLresult.sigma_err, PLPLresult.sb)
#To know more about how to access the result: help(Result)

In case you want to dig deeper or just use the function for plotting:

from LNPLPL_functions import *
from LNPL_functions import *

or whichever way you wish to import the modules and the functions within them.

To get help on any function:

help(function_name)

If you're on the pypi page, please checkout the github version to get the sample data if you need.