from modules import UtilityAnalysis
# from PyQt5.QtWidgets import QApplication, QVBoxLayout, QWidget
if __name__ == "__main__":
# ---------------------------Files reading---------------------------------
variables = Utility.read_inputFile("./inputFile.txt")
elementList = Utility.molToelemList(variables.molecule)
elementParameters = Utility.read_parameters(elementList,
variables.element_params_path)
path = Utility.path_xyz_file(variables.molecule)
numAtoms, element, x, y, z = Utility.read_xyz_file(path)
Q, I_Q = Utility.read_file(variables.data_file)
Qbkg, Ibkg_Q = Utility.read_file(variables.bkg_file)
# -------------------Preliminary calculation-------------------------------
fe_Q, Ztot = MainFunctions.calc_eeff(elementList, Q, elementParameters)
Iincoh_Q = MainFunctions.calc_Iincoh(elementList, Q, elementParameters)
J_Q = MainFunctions.calc_JQ(Iincoh_Q, Ztot, fe_Q)
Sinf = MainFunctions.calc_Sinf(elementList, fe_Q, Q, Ztot,
elementParameters)
dampingFunction = UtilityAnalysis.calc_dampingFunction(
Q, variables.dampingFactor, variables.QmaxIntegrate,
variables.typeFunction)
def Optimization(self):
"""Function to optimize and plot F(r)"""
#-------------------Intra-molecular components-----------------------------
# numAtoms, element, x, y, z = Utility.read_xyz_file(self.XYZFilePath)
numAtoms, element, x, y, z = Utility.read_xyz_file(
"/Users/ciccio/work/ID27/LASDiA/xyzFiles/Ar.xyz")
iintra_Q = Optimization.calc_iintra(self.Q, self.fe_Q, self.Ztot,
self.ui.QmaxIntegrate.value(),
self.ui.maxQ.value(),
self.elementList, element, x, y, z,
self.elementParameters)
iintradamp_Q = UtilityAnalysis.calc_iintradamp(iintra_Q,
self.dampingFunct)
Qiintradamp_Q = self.Q * iintradamp_Q
rintra, Fintra_r = MainFunctions.calc_Fr(
self.Q[self.Q <= self.ui.QmaxIntegrate.value()],
Qiintradamp_Q[self.Q <= self.ui.QmaxIntegrate.value()])
scaleFactor = self.ui.scaleFactorValue.value()
density0 = self.ui.densityValue.value()
# ----------------------First scale minimization---------------------------
scaleStep = 0.05
# sth = 0.008
# s0th = 0.006
sth = 0.0
s0th = 0.0
phi_matrix = 0.0
thickness_sampling = 0.0
scaleFactor = Minimization.OptimizeScale(
self.Q, self.I_Q, self.Ibkg_Q, self.J_Q, self.Iincoh_Q, self.fe_Q,
self.ui.maxQ.value(), self.ui.minQ.value(),
self.ui.QmaxIntegrate.value(), self.Ztot, density0,
scaleFactor, self.Sinf, self.ui.smoothingFactor.value(),
self.ui.rmin.value(), self.dampingFunct, Fintra_r,
self.ui.iterations.value(), scaleStep, sth, s0th,
thickness_sampling, phi_matrix, "n")
# ----------------------First density minimization-------------------------
densityStep = density0 / 50
densityStepEnd = density0 / 250
density = Minimization.OptimizeDensity(
self.Q, self.I_Q, self.Ibkg_Q, self.J_Q, self.Iincoh_Q, self.fe_Q,
self.ui.maxQ.value(), self.ui.minQ.value(),
self.ui.QmaxIntegrate.value(), self.Ztot, density0,
scaleFactor, self.Sinf, self.ui.smoothingFactor.value(),
self.ui.rmin.value(), self.dampingFunct, Fintra_r,
self.ui.iterations.value(), densityStep, densityStepEnd, sth, s0th,
thickness_sampling, phi_matrix, "n")
# print("density0, density", density0, density)
numLoopIteration = 0
while 1:
if np.abs(density - density0) > density / 25:
# print("First")
scaleStep = 0.006
densityStep = density / 10
WSamplestep = 0.0008
WRefstep = 0.0008
elif np.abs(density - density0) > density / 75:
# print("Second")
scaleStep = 0.0006
densityStep = density / 100
WSamplestep = 0.0002
WRefstep = 0.0002
else:
# print("Third")
scaleStep = 0.00006
densityStep = density / 1000
WSamplestep = 0.0001
WRefstep = 0.0001
scaleFactor = Minimization.OptimizeScale(
self.Q, self.I_Q, self.Ibkg_Q, self.J_Q, self.Iincoh_Q,
self.fe_Q, self.ui.maxQ.value(), self.ui.minQ.value(),
self.ui.QmaxIntegrate.value(), self.Ztot, density,
scaleFactor, self.Sinf, self.ui.smoothingFactor.value(),
self.ui.rmin.value(), self.dampingFunct, Fintra_r,
self.ui.iterations.value(), scaleStep, sth, s0th,
thickness_sampling, phi_matrix, "n")
density0 = density
density = Minimization.OptimizeDensity(
self.Q, self.I_Q, self.Ibkg_Q, self.J_Q, self.Iincoh_Q,
self.fe_Q, self.ui.maxQ.value(), self.ui.minQ.value(),
self.ui.QmaxIntegrate.value(), self.Ztot, density0,
scaleFactor, self.Sinf, self.ui.smoothingFactor.value(),
self.ui.rmin.value(), self.dampingFunct, Fintra_r,
self.ui.iterations.value(), densityStep, density / 250, sth,
s0th, thickness_sampling, phi_matrix, "n")
numLoopIteration += 1
# print("numLoopIteration", numLoopIteration, scaleFactor, density)
if (np.abs(density - density0) > np.abs(
density / 2500)) and (numLoopIteration <= 30):
continue
else:
break
# print("final scale", scaleFactor, "final density", density)
self.ui.scaleFactorValue.setValue(scaleFactor)
self.ui.densityValue.setValue(density)
Isample_Q = MainFunctions.calc_IsampleQ(self.I_Q, scaleFactor,
self.Ibkg_Q)
alpha = MainFunctions.calc_alpha(
self.J_Q[self.Q <= self.ui.QmaxIntegrate.value()], self.Sinf,
self.Q[self.Q <= self.ui.QmaxIntegrate.value()],
Isample_Q[self.Q <= self.ui.QmaxIntegrate.value()],
self.fe_Q[self.Q <= self.ui.QmaxIntegrate.value()], self.Ztot,
density)
Icoh_Q = MainFunctions.calc_Icoh(alpha, Isample_Q, self.Iincoh_Q)
S_Q = MainFunctions.calc_SQ(Icoh_Q, self.Ztot, self.fe_Q, self.Sinf,
self.Q, self.ui.minQ.value(),
self.ui.QmaxIntegrate.value(),
self.ui.maxQ.value())
Ssmooth_Q = UtilityAnalysis.calc_SQsmoothing(
self.Q, S_Q, self.Sinf, self.ui.smoothingFactor.value(),
self.ui.minQ.value(), self.ui.QmaxIntegrate.value(),
self.ui.maxQ.value())
SsmoothDamp_Q = UtilityAnalysis.calc_SQdamp(Ssmooth_Q, self.Sinf,
self.dampingFunct)
i_Q = MainFunctions.calc_iQ(SsmoothDamp_Q, self.Sinf)
Qi_Q = self.Q * i_Q
r, F_r = MainFunctions.calc_Fr(
self.Q[self.Q <= self.ui.QmaxIntegrate.value()],
Qi_Q[self.Q <= self.ui.QmaxIntegrate.value()])
Fopt_r, deltaFopt_r = Optimization.calc_optimize_Fr(
self.ui.iterations.value(), F_r, Fintra_r, density,
i_Q[self.Q <= self.ui.QmaxIntegrate.value()],
self.Q[self.Q <= self.ui.QmaxIntegrate.value()], self.Sinf,
self.J_Q[self.Q <= self.ui.QmaxIntegrate.value()], r,
self.ui.rmin.value(), "n")
Scorr_Q = MainFunctions.calc_SQCorr(Fopt_r, r, self.Q, self.Sinf)
self.ui.distfuncPlot.canvas.ax.plot(r,
Fopt_r,
"g",
label=r"$F_{opt}(r)$")
self.ui.distfuncPlot.canvas.ax.legend()
self.ui.distfuncPlot.canvas.draw()
self.ui.factorPlot.canvas.ax.plot(self.Q,
Scorr_Q,
"g",
label=r"$S_{opt}(Q)$")
self.ui.factorPlot.canvas.ax.legend()
self.ui.factorPlot.canvas.draw()
app.exit()
return filename
if __name__ == "__main__":
#---------------------------Files reading----------------------------------
# inputFile_path = open_file("./")
inputVariables = Utility.read_inputFile("./inputFile.txt")
elementList = Utility.molToElemList(inputVariables["molecule"])
elementParameters = Utility.read_parameters(
elementList, inputVariables["elementParamsPath"])
elementPosition = Utility.read_xyz_file(inputVariables["xyzPath"])
Q, I_Q = Utility.read_file(inputVariables["dataFile"])
Qbkg, Ibkg_Q = Utility.read_file(inputVariables["bkgFile"])
# plt.plot(Q, I_Q)
# plt.plot(Qbkg, Ibkg_Q)
# plt.show
#--------------------Preliminary calculation-------------------------------
Q, I_Q = UtilityAnalysis.data_interpolation(Q, I_Q, inputVariables["minQ"],
inputVariables["maxQ"],
inputVariables["numPoints"])
Qbkg, Ibkg_Q = UtilityAnalysis.data_interpolation(
Qbkg, Ibkg_Q, inputVariables["minQ"], inputVariables["maxQ"],
