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Lorentz.py
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Lorentz.py
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# Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2007 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
# pylint: disable=no-init,invalid-name
'''
@author Mathieu Doucet, ORNL
@date Oct 13, 2014
'''
import math
import numpy as np
from mantid.api import IFunction1D, FunctionFactory
class Lorentz(IFunction1D):
"""
Provide a Lorentz model for SANS
I(q) = scale / ( 1 + q^2 L^2 ) + background
"""
def category(self):
return "SANS"
def init(self):
# Active fitting parameters
self.declareParameter("Scale", 1.0, 'Scale')
self.declareParameter("Length", 50.0, 'Length')
self.declareParameter("Background", 0.0, 'Background')
def function1D(self, xvals):
"""
Evaluate the model
@param xvals: numpy array of q-values
"""
return self.getParameterValue("Scale") / (1.0 + np.power(xvals*self.getParameterValue('Length'), 2)) +\
self.getParameterValue('Background')
def functionDeriv1D(self, xvals, jacobian):
"""
Evaluate the first derivatives
@param xvals: numpy array of q-values
@param jacobian: Jacobian object
"""
i = 0
for x in xvals:
jacobian.set(
i, 0, 1.0 / (1.0 + np.power(x*self.getParameterValue('Length'), 2)))
denom = math.pow(
1.0 + math.pow(x*self.getParameterValue('Length'), 2), -2)
jacobian.set(i, 1, -2.0 * self.getParameterValue("Scale")
* x * x * self.getParameterValue('Length') * denom)
jacobian.set(i, 2, 1.0)
i += 1
# Required to have Mantid recognise the new function
FunctionFactory.subscribe(Lorentz)