# Set all temperature factors isotropic and equal to @4
for idx in range(1, 5):
pf.constrain(pf.u11(idx), '@4')
pf.constrain(pf.u22(idx), '@4')
pf.constrain(pf.u33(idx), '@4')
pf.setpar(4, pf.u11(1))
# Refine ---------------------------------------------------------------------
pf.pdfrange(1, 1.5, 19.99)
pf.refine()
# Save results ---------------------------------------------------------------
pf.save_pdf(1, "Ni_refinement.fgr")
pf.save_struct(1, "Ni_refinement.rstr")
pf.save_res("Ni_refinement.res")
# Plot results ---------------------------------------------------------------
# pylab is matplotlib interface with MATLAB-like plotting commands
import pylab
# obtain data from PdfFit calculator object
r = pf.getR()
Gobs = pf.getpdf_obs()
Gfit = pf.getpdf_fit()
# calculate difference curve, with pylab arrays it can be done
# without for loop
Gdiff = pylab.array(Gobs) - pylab.array(Gfit)
# Set all temperature factors isotropic and equal to @4
for idx in range(1, 5):
pf.constrain(pf.u11(idx), '@4')
pf.constrain(pf.u22(idx), '@4')
pf.constrain(pf.u33(idx), '@4')
pf.setpar(4, pf.u11(1))
# Refine ---------------------------------------------------------------------
pf.pdfrange(1, 1.5, 19.99)
pf.refine()
# Save results ---------------------------------------------------------------
pf.save_pdf(1, "Ni_refinement.fgr")
pf.save_struct(1, "Ni_refinement.rstr")
pf.save_res("Ni_refinement.res")
# Plot results ---------------------------------------------------------------
# pylab is matplotlib interface with MATLAB-like plotting commands
import pylab
# obtain data from PdfFit calculator object
r = pf.getR()
Gobs = pf.getpdf_obs()
Gfit = pf.getpdf_fit()
# calculate difference curve, with pylab arrays it can be done
# without for loop
Gdiff = pylab.array(Gobs) - pylab.array(Gfit)
