Source code for pySAXS.models.PorodC

from model import Model
from pySAXS.LS.LSsca import Qlogspace
import numpy

[docs]class PorodC(Model): ''' Porod Curved for Spheres poly-Gauss Model by OT 10/06/2009 '''
[docs] def PorodCFunction(self,q,par): """ Porod model to fit q-4 part at high q par[0] : Scattering lenght density contrast in cm-2 par[1] : S/V cm-1 par[2] : principal curvature 1 cm-1 par[3] : Principal curvature 2 cm-1 """ return 2.0*numpy.pi*1.0e-32*par[0]*par[0]*par[1]*q**-4.0*(1.0+1e-16*q**-2.0*(((par[2]+par[3])**2.)/4.+((par[2]-par[3])**2.)/8.))
''' parameters definition class Model(7,Porod,/ Qlogspace(1e-4,1.,500.),( [1.0e10,1e6]), ("Scattering contrast (cm-2)", "S/V (cm-1)"),("%1.3e","%1.3e"), (True,True)), from LSsca ''' IntensityFunc=PorodCFunction #function N=0 q=Qlogspace(1e-4,1.,500.) #q range(x scale) Arg=[1.0e10,1e6,1e-2,1e-2] #list of defaults parameters Format=["%1.3e","%1.3e","%1.3e","%1.3e"] #list of c format istofit=[True,True,True,True] #list of boolean for fitting name="Porod with curvature correction" #name of the model Doc=["Scattering contrast (cm-2)","S/V (cm-1)","C1","C2"] #list of description for parameters
if __name__=="__main__": ''' test code ''' modl=PorodC() #plot the model import Gnuplot gp=Gnuplot.Gnuplot() gp("set logscale xy") c=Gnuplot.Data(modl.q,modl.getIntensity(),with_='points') gp.plot(c) raw_input("enter") #plot and fit the noisy model yn=modl.getNoisy(0.4) cn=Gnuplot.Data(modl.q,yn,with_='points') res=modl.fit(yn) cf=Gnuplot.Data(modl.q,modl.IntensityFunc(modl.q,res),with_='lines') gp.plot(c,cn,cf) raw_input("enter") #plot and fit the noisy model with fitBounds bounds=modl.getBoundsFromParam() #[250.0,2e11,1e10,1.5e15] res2=modl.fitBounds(yn,bounds) print res2 raw_input("enter")