本文整理汇总了Python中diffpy.srfit.fitbase.FitContribution.registerCalculator方法的典型用法代码示例。如果您正苦于以下问题：Python FitContribution.registerCalculator方法的具体用法？Python FitContribution.registerCalculator怎么用？Python FitContribution.registerCalculator使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类diffpy.srfit.fitbase.FitContribution的用法示例。
在下文中一共展示了FitContribution.registerCalculator方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: makeRecipe
# 需要导入模块: from diffpy.srfit.fitbase import FitContribution [as 别名]
# 或者: from diffpy.srfit.fitbase.FitContribution import registerCalculator [as 别名]
def makeRecipe(ciffile, grdata, iqdata):
"""Make complex-modeling recipe where I(q) and G(r) are fit
simultaneously.
The fit I(q) is fed into the calculation of G(r), which provides feedback
for the fit parameters of both.
"""
# Create a PDF contribution as before
pdfprofile = Profile()
pdfparser = PDFParser()
pdfparser.parseFile(grdata)
pdfprofile.loadParsedData(pdfparser)
pdfprofile.setCalculationRange(xmin = 0.1, xmax = 20)
pdfcontribution = FitContribution("pdf")
pdfcontribution.setProfile(pdfprofile, xname = "r")
pdfgenerator = PDFGenerator("G")
pdfgenerator.setQmax(30.0)
stru = CreateCrystalFromCIF(file(ciffile))
pdfgenerator.setStructure(stru)
pdfcontribution.addProfileGenerator(pdfgenerator)
pdfcontribution.setResidualEquation("resv")
# Create a SAS contribution as well. We assume the nanoparticle is roughly
# elliptical.
sasprofile = Profile()
sasparser = SASParser()
sasparser.parseFile(iqdata)
sasprofile.loadParsedData(sasparser)
sascontribution = FitContribution("sas")
sascontribution.setProfile(sasprofile)
from sans.models.EllipsoidModel import EllipsoidModel
model = EllipsoidModel()
sasgenerator = SASGenerator("generator", model)
sascontribution.addProfileGenerator(sasgenerator)
sascontribution.setResidualEquation("resv")
# Now we set up a characteristic function calculator that depends on the
# sas model.
cfcalculator = SASCF("f", model)
# Register the calculator with the pdf contribution and define the fitting
# equation.
pdfcontribution.registerCalculator(cfcalculator)
# The PDF for a nanoscale crystalline is approximated by
# Gnano = f * Gcryst
pdfcontribution.setEquation("f * G")
# Moving on
recipe = FitRecipe()
recipe.addContribution(pdfcontribution)
recipe.addContribution(sascontribution)
# PDF
phase = pdfgenerator.phase
for par in phase.sgpars:
recipe.addVar(par)
recipe.addVar(pdfgenerator.scale, 1)
recipe.addVar(pdfgenerator.delta2, 0)
# SAS
recipe.addVar(sasgenerator.scale, 1, name = "iqscale")
recipe.addVar(sasgenerator.radius_a, 10)
recipe.addVar(sasgenerator.radius_b, 10)
# Even though the cfcalculator and sasgenerator depend on the same sas
# model, we must still constrain the cfcalculator Parameters so that it is
# informed of changes in the refined parameters.
recipe.constrain(cfcalculator.radius_a, "radius_a")
recipe.constrain(cfcalculator.radius_b, "radius_b")
return recipe