def test_discus(self):
"""check loading of discus file format
"""
f = datafile('Ni-discus.stru')
stru = loadStructure(f)
self.failUnless(type(stru) is PDFFitStructure)
return
def test_discus(self):
"""check loading of discus file format
"""
f = datafile('Ni-discus.stru')
stru = loadStructure(f)
self.failUnless(type(stru) is PDFFitStructure)
return
def loadStrufile(self, filename, stype='diffpy', periodic=None):
'''
read and parse a structure file
'''
self.filename = filename
ext = os.path.splitext(filename)[1]
if periodic != None:
self.periodic = periodic
else:
# detect periodicity using file type
if ext in ['.cif']:
periodic = True
else:
periodic = False
self.periodic = periodic
# read the file
if stype == 'diffpy':
self.rawstru = loadStructure(filename)
self.rawstype = stype
self.parseDiffpyStru(self.rawstru)
elif stype == 'objcryst':
if ext == '.cif':
self.rawstru = CreateCrystalFromCIF(file(filename))
self.rawstype = stype
else:
raise TypeError('Cannot read file!')
else:
raise TypeError('Cannot read file!')
return
def test_goodkwarg(self):
"""check loading of CIF file and passing of parser keyword argument.
"""
f = datafile('graphite.cif')
stru = loadStructure(f, eps=1e-10)
self.assertEqual(8, len(stru))
return
def setAdStru(self, adele, stru, dPDFmode='ad'):
'''
if dPDFmode == ad -> return the ad pdf
if dPDFmode == non_ad -> return the non_ad pdf
'''
self.adele = adele
self.dPDFmode = dPDFmode
self.periodic = stru.periodic
s = loadStructure(stru.parent.filename)
self.elements = list(set(s.element))
# init c
c = {}
for ele in self.elements:
c[ele] = 0.0
tc = 0.0
for ele, occ in zip(s.element, s.occupancy):
c[ele] = c[ele] + occ
tc = tc + occ
for ele in self.elements:
c[ele] = c[ele] / tc
self.c = c
# init f
self.f = {}
ftotal = 0
for ele in self.elements:
self.f[ele] = fxrayatq(ele, [0])
ftotal += fxrayatq(ele, [0]) * self.c[ele]
self.f['total'] = ftotal
self.adw = self.c[adele] * self.f[adele] / self.f['total']
return
def test_goodkwarg(self):
"""check loading of CIF file and passing of parser keyword argument.
"""
f = datafile('graphite.cif')
stru = loadStructure(f, eps=1e-10)
self.assertEqual(8, len(stru))
return
def test_cif(self):
"""check loading of CIF file format
"""
f = datafile('PbTe.cif')
stru = loadStructure(f)
self.failUnless(isinstance(stru, Structure))
self.failIf(isinstance(stru, PDFFitStructure))
return
def test_cif(self):
"""check loading of CIF file format
"""
f = datafile('PbTe.cif')
stru = loadStructure(f)
self.assertTrue(isinstance(stru, Structure))
self.assertFalse(isinstance(stru, PDFFitStructure))
return
def test_xcfg(self):
"""check loading of atomeye xcfg format
"""
f = datafile('BubbleRaftShort.xcfg')
stru = loadStructure(f)
self.failUnless(type(stru) is Structure)
self.assertRaises(StructureFormatError, loadStructure, f, 'xyz')
return
def test_cif(self):
"""check loading of CIF file format
"""
f = datafile('PbTe.cif')
stru = loadStructure(f)
self.assertTrue(isinstance(stru, Structure))
self.assertFalse(isinstance(stru, PDFFitStructure))
return
def test_cif(self):
"""check loading of CIF file format
"""
f = datafile('PbTe.cif')
stru = loadStructure(f)
self.failUnless(isinstance(stru, Structure))
self.failIf(isinstance(stru, PDFFitStructure))
return
def test_xcfg(self):
"""check loading of atomeye xcfg format
"""
f = datafile('BubbleRaftShort.xcfg')
stru = loadStructure(f)
self.failUnless(type(stru) is Structure)
self.assertRaises(StructureFormatError,
loadStructure, f, 'xyz')
return
def test(self):
path = os.path.dirname(os.path.abspath(__file__))
struc=loadStructure(find('MnO_cubic.cif',path))
msp=diffpy.mpdf.MagSpecies(struc=struc)
msp.magIdxs=[0,1,2,3]
msp.basisvecs=np.array([[1,-1,0]])
msp.kvecs=np.array([[0.5,0.5,0.5]])
msp.ffparamkey='Mn2'
mstr=diffpy.mpdf.MagStructure()
mstr.loadSpecies(msp)
mstr.makeAll()
mc=diffpy.mpdf.MPDFcalculator(magstruc=mstr)
r,fr,dr=mc.calc(both=True)
testval=np.round(dr[100],decimals=4)
self.assertEqual(testval,20.8841)
def dbc_iter(struc_f, iter_range):
'''change different range'''
import numpy as np
import matplotlib.pyplot as plt
from diffpy.srreal.pdfcalculator import DebyePDFCalculator
from diffpy.Structure import loadStructure
struc = loadStructure(struc_f)
dbc = DebyePDFCalculator()
dbc.setStructure(struc)
dbc.qmax = 20
dbc.qmin = 0.5
dbc.rmax = 20
#par = eval(para)
#print(dbc.par)
for step in iter_range:
(r,g) = dbc(delta2 = step)
plt.plot(r,g)
def simple_pdf_cal(input_f, Debye = True, DW_factor = glbl.DW_factor, qmin = glbl.q_min, qmax = glbl.q_max, rmax = glbl.r_max):
''' simple pdf calculator. Take input .cif/.xyz file to calculate PDF
(only use PDFCalculator now, can't calculate nano structrue at this stage)
argument:
input_f - str - strcuture file name
Dw_factor - float - value of Debye-Waller factor, which accounts for thermal motions. Default=1 means zero temperature
'''
## calculate theoretical pdf from given structure file
# create structure
struc = loadStructure(input_f)
struc.Bisoequiv = DW_factor
# calculate PDF
pdfc = PDFCalculator(qmax = qmax, rmax = rmax)
dbc = DebyePDFCalculator(qmax = qmax, rmax = rmax)
if Debye:
(r, g) = dbc(struc, qmin = qmin)
else:
(r, g) = pdfc(struc, qmin=qmin)
return (r, g)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
import matplotlib.pyplot as plt
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import PDFCalculator
from rectangleprofile import RectangleProfile
ni = loadStructure('ni.cif')
# The CIF file had no displacement data so we supply them here:
ni.Uisoequiv = 0.005
# Calculate PDF with default profile function
pc1 = PDFCalculator()
r1, g1 = pc1(ni)
print("standard peakprofile:\n " + repr(pc1.peakprofile))
# Create new calculator that uses the custom profile function
pc2 = PDFCalculator()
pc2.peakprofile = RectangleProfile()
# Note: pc2.peakprofile = 'rectangleprofile'
# would do the same, because RectangleProfile class was registered
# under its 'rectangleprofile' identifier.
print("custom peakprofile:\n " + repr(pc1.peakprofile))
r2, g2 = pc2(ni)
# compare both simulated curves
plt.plot(r1, g1, r2, g2)
plt.draw()
plt.show()
dataFile = "cdse.gr"
structureFile = "cdse.xyz"
# The first thing to construct is a contribution. Since this is a simple
# example, the contribution will simply contain our PDF data and an associated
# structure file. We'll give it the name "cdse"
cdsePDF = PDFContribution("CdSe")
# Load the data and set the r-range over which we'll fit
cdsePDF.loadData(dataFile)
cdsePDF.setCalculationRange(xmin=1, xmax=20, dx=0.01)
# Add the structure from our xyz file to the contribution, since the structure
# model is non-periodic, we need to specify the periodic=False here to get the
# right PDF
cdseStructure = loadStructure(structureFile)
cdsePDF.addStructure("CdSe", cdseStructure, periodic=False)
# The FitRecipe does the work of managing one or more contributions
# that are optimized together. In addition, FitRecipe configures
# fit variables that are tied to the model parameters and thus
# controls the calculated profiles.
cdseFit = FitRecipe()
# give the PDFContribution to the FitRecipe
cdseFit.addContribution(cdsePDF)
# Here we create variables for the overall scale of the PDF and a delta2
# parameter for correlated motion of neighboring atoms.
cdseFit.addVar(cdsePDF.scale, 1)
cdseFit.addVar(cdsePDF.CdSe.delta2, 5)
import pandas as pd
from time import strftime
from pprint import pprint
import matplotlib.pyplot as plt
from diffpy.Structure import loadStructure
from diffpy.Structure import StructureFormatError
from diffpy.srreal.structureadapter import nosymmetry
from diffpy.srreal.pdfcalculator import DebyePDFCalculator
from diffpy.srreal.pdfcalculator import PDFCalculator
from pdf_lib.glbl import pdfCal_cfg, Uiso, delta2
cal = PDFCalculator()
cal.delta2 = delta2
ni = loadStructure('ni.cif')
ni.Uisoequiv = Uiso
nacl = loadStructure('1000041.cif')
nacl.Uisoequiv = Uiso
print("Uiso = {}".format(Uiso))
def qdamp_test(struc, rmax_val, qdamp_array=None):
pdfCal_cfg['rmax'] = rmax_val
N = qdamp_array.size
fig, ax = plt.subplots(N, figsize=(20, 6),
sharex=True, sharey=True)
for _ax, qdamp_val in zip(ax, qdamp_array):
pdfCal_cfg['qdamp'] = qdamp_val
r, g = cal(struc, **pdfCal_cfg)
#cal.setStructure(struc)
import numpy as np
import matplotlib.pyplot as plt
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import PDFCalculator, DebyePDFCalculator
from diffpy.srfit.pdf import PDFContribution
from scipy.integrate import simps
nkl_crystal = loadStructure("BaTiO3.cif")
nkl_crystal.Uisoequiv = 0.005
cfg_pc = {'rmin': 0, 'rmax': 20, 'rstep': 0.01}
cfg_dpc1 = {'qmax': 100, 'qmin': 0, 'rmin': 0, 'rmax': 100, 'rstep': 0.01}
#cfg_dpc2 = {'qmax' : 100,
# 'qmin' : 0,
# 'rmin' : 0,
# 'rmax' : 70,
# 'rstep': 0.01}
#
#cfg_dpc3 = {'qmax' : 100,
# 'qmin' : 0,
# 'rmin' : 0,
# 'rmax' : 100,
# 'rstep': 0.01}
# calculate PDF by real-space summation
pc0 = PDFCalculator(**cfg_pc)
r0, g0 = pc0(nkl_crystal)
# calcualte PDF by DPC
import numpy as np
import matplotlib.pyplot as plt
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import PDFCalculator
from diffpy.srfit.pdf import PDFContribution
from scipy.integrate import simps
##load structure files including single molecule, supercell in xyz format
mannitol_SM = loadStructure("Mannitol_Single_Molecule.xyz")
mannitol_supercell = loadStructure("Mannitol_5_5_5.xyz")
##assign them thermal factors
mannitol_SM.Uisoequiv = 0.005
mannitol_supercell.Uisoequiv = 0.005
cfg = { 'qmax' : 25,
'qmin' :0,
'rmin' : 0,
'rmax' : 20,
'rstep': 0.01,
'qdamp': 0.045,
'qbroad': 0.069}
# calculate PDF by real-space summation
pc0 = PDFCalculator(**cfg)
r0, g0 = pc0(mannitol_SM)
r1, g1 = pc0(mannitol_supercell)
###define a Gaussian function
def Gauss(r, r0, Gamma, scale):
return scale*(np.sqrt(np.log(2.)/np.pi))*(2./Gamma)*np.exp((-1)*(r-r0)**2*4.*np.log(2.)/Gamma**2)
import numpy as np
import matplotlib.pyplot as plt
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import PDFCalculator
from diffpy.srfit.pdf import PDFContribution
from scipy.integrate import simps
##load structure files including single molecule, in xyz format and crystal cif
mannitol_SM = loadStructure("Mannitol_Single_Molecule.xyz")
mannitol_crystal = loadStructure("DMANTL01_alpha_RT.cif")
##assign them thermal factors
mannitol_SM.Uisoequiv = 0.005
mannitol_crystal.Uisoequiv = 0.005
cfg = {
'qmax': 25,
'qmin': 0,
'rmin': 0,
'rmax': 20,
'rstep': 0.01,
'qdamp': 0.045,
'qbroad': 0.069
}
# calculate PDF by real-space summation
pc0 = PDFCalculator(**cfg)
r0, g0 = pc0(mannitol_SM)
r1, g1 = pc0(mannitol_crystal)
plt.plot(r0, g0, "b-")
plt.plot(r1, g1, "r-")
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import leastsq
from mcalculator import *
import diffpy as dp
from diffpy.Structure import loadStructure
# Create the structure from our cif file, update the lattice params
MnOrhomb = loadStructure("mPDF_exampleFiles/MnO_R-3m.cif")
MnOcubic = loadStructure("mPDF_exampleFiles/MnO_cubic.cif")
latCub = MnOcubic.lattice
latRhomb = MnOrhomb.lattice
latRhomb.a, latRhomb.b, latRhomb.c = latCub.a / np.sqrt(2), latCub.a / np.sqrt(
2), np.sqrt(6) * latCub.a / np.sqrt(2)
#MnOrhomb.lattice=latRhomb
# Set up the mPDF calculators
mcCub = mPDFcalculator(MnOcubic)
mcCub.magIdxs = [0, 1, 2, 3]
mcCub.makeAtoms()
mcRhomb = mPDFcalculator(MnOrhomb)
mcRhomb.magIdxs = [0, 1, 2]
mcRhomb.makeAtoms()
svec = 2.5 * np.array([1.0, -1.0, 0]) / np.sqrt(2)
mcCub.svec = svec
mcCub.kvec = np.array([0.5, 0.5, 0.5])
mcCub.spinOrigin = mcCub.atoms[0]
mcCub.makeSpins()
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import PDFCalculator
from matplotlib.pyplot import plot, show
cds = loadStructure('CdS_wurtzite.cif')
pc1 = PDFCalculator()
pc1.rmax = 20
pc1.scatteringfactortable.setCustomAs('S2-', 'S', 18)
pc1.scatteringfactortable.lookup('S2-')
r1, g1 = pc1(cds)
plot(r1, g1)
pc2 = pc1.copy()
cds2 = loadStructure('CdS_wurtzite.cif')
cds2.anisotropy = False
r2, g2 = pc2(cds2)
plot(r2, g2)
plot(r1, g1 - g2)
show()
# Files containing our experimental data and structure file
dataFile = "ni-q27r100-neutron.gr"
structureFile = "ni.cif"
spaceGroup = "Fm-3m"
# The first thing to construct is a contribution. Since this is a simple
# example, the contribution will simply contain our PDF data and an associated
# structure file. We'll give it the name "nickel"
niPDF = PDFContribution("nickel")
# Load the data and set the r-range over which we'll fit
niPDF.loadData(dataFile)
niPDF.setCalculationRange(xmin=1, xmax=20, dx=0.01)
# Add the structure from our cif file to the contribution
niStructure = loadStructure(structureFile)
niPDF.addStructure("nickel", niStructure)
# The FitRecipe does the work of calculating the PDF with the fit variable
# that we give it.
niFit = FitRecipe()
# give the PDFContribution to the FitRecipe
niFit.addContribution(niPDF)
# Configure the fit variables and give them to the recipe. We can use the
# srfit function constrainAsSpaceGroup to constrain the lattice and ADP
# parameters according to the Fm-3m space group.
from diffpy.srfit.structure import constrainAsSpaceGroup
spaceGroupParams = constrainAsSpaceGroup(niPDF.nickel.phase, spaceGroup)
print "Space group parameters are:",
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from matplotlib.pyplot import *
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import PDFCalculator
from rectangleprofile import RectangleProfile
ni = loadStructure('ni.cif')
# The CIF file had no displacement data so we supply them here:
ni.Uisoequiv = 0.005
# Calculate PDF with default profile function
pc1 = PDFCalculator()
r1, g1 = pc1(ni)
print "standard peakprofile:\n " + repr(pc1.peakprofile)
# Create new calculator that uses the custom profile function
pc2 = PDFCalculator()
pc2.peakprofile = RectangleProfile()
# Note: pc2.peakprofile = 'rectangleprofile'
# would do the same, because RectangleProfile class was registered
# under its 'rectangleprofile' identifier.
print "custom peakprofile:\n " + repr(pc1.peakprofile)
r2, g2 = pc2(ni)
# compare both simulated curves
plot(r1, g1, r2, g2)
draw()
show()
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import PDFCalculator
from matplotlib.pyplot import plot, show
cds = loadStructure('CdS_wurtzite.cif')
pc1 = PDFCalculator()
pc1.rmax = 20
pc1.scatteringfactortable.setCustomAs('S2-', 'S', 18)
pc1.scatteringfactortable.lookup('S2-')
r1, g1 = pc1(cds)
plot(r1, g1)
pc2 = pc1.copy()
cds2 = loadStructure('CdS_wurtzite.cif')
cds2.anisotropy = False
r2, g2 = pc2(cds2)
plot(r2, g2)
plot(r1, g1-g2)
show()
def learninglib_build(self, output_dir=None, pdfcal_cfg=None,
rdf=True, xrd=False, Bisoequiv=0.1,
rstep=None, DebyeCal=False, nosymmetry=False,
tth_range=None, wavelength=0.5):
""" method to build learning lib with diffpy based on path
of cif library. Paramters of G(r) calculation are set
via glbl.<attribute>. "PDFCal_config.txt" file with PDFCalculator
configuration will also be output
Parameters
----------
pdfcal_cfg : dict, optional
configuration of PDF calculator, default is the one defined
inside glbl class.
rdf : bool, optional
option to compute RDF or not. default to True, if not,
compute pdf
xrd : bool, optional
option to compute XRD (which is slow). default to False.
Bisoequiv : float, optional
value of isotropic thermal parameter. default is 0.1.
scientific equation: Biso = 8 (pi**2) Uiso
rstep : float, optioanl
space of PDF. default is pi/qmax.
DebyeCal : bool, optional
option to use Debye calculator. default is False.
nosymmetry : bool, optional
DEPRECATED for now. option to apply no symmetry.
default is False.
tth_range : ndarray, optional
range of 2theta. default is [0:0.1:90]
wavelength : float, optional
wavelength in angstroms, default to 0.5 A which corresponds
to Qmax ~= 17
"""
# setup output dir
timestr = _timestampstr(time.time())
if output_dir is None:
tail = "LearningLib_{}".format(timestr)
output_dir = os.path.join(os.getcwd(), tail)
print('=== output dir would be {} ==='.format(output_dir))
self.output_dir = output_dir
if tth_range is None:
self.tth_range = np.arange(0, 90, 0.1)
self.wavelength = wavelength
self.std_q = theta2q(self.tth_range, self.wavelength)
####### configure pymatgen XRD calculator #####
# instantiate calculators
xrd_cal = XRDCalculator()
xrd_cal.wavelength = self.wavelength
xrd_cal.TWO_THETA_TOL = 10**-2
self.calculate_params.update({'xrd_wavelength':
xrd_cal.wavelength})
xrd_list = []
sg_list = []
# (a,b,c, alpha, beta, gamma, volume)
structure_list_1 = [] # primative cell
structure_list_2 = [] # ordinary cell
# chemical element
composition_list_1 = [] # primative cell
composition_list_2 = [] # ordinary cell
fail_list = []
####### configure diffpy PDF calculator ######
if DebyeCal:
cal = DebyePDFCalculator()
self.calculator_type = 'Debye'
cal = PDFCalculator()
self.calculator = cal
self.calculator_type = 'PDF'
self.calculate_params.update({'calculator_type':
self.calculator_type})
# setup calculator parameters
if rstep is None:
rstep = glbl.rstep
self.rstep = rstep
self.calculator.rstep = rstep # annoying fact
self.calculate_params.update({'rstep':rstep})
if pdfcal_cfg is None:
self.pdfcal_cfg = glbl.cfg
self.calculate_params.update(self.pdfcal_cfg)
# configure calculator
for k,v in self.pdfcal_cfg.items():
setattr(self.calculator, k, v)
# empty list to store results
gr_list = []
rdf_list = []
print("====== INFO: calculation parameters:====\n{}"
.format(self.calculate_params))
struc_df = pd.DataFrame()
############# loop through cifs #################
for cif in sorted(self.cif_list):
_cif = os.path.join(self.input_dir, cif)
try:
# diffpy structure
struc = loadStructure(_cif)
struc.Bisoequiv = Bisoequiv
## calculate PDF/RDF with diffpy ##
if nosymmetry:
struc = nosymmetry(struc)
cal.setStructure(struc)
cal.eval()
# pymatge structure
struc_meta = CifParser(_cif)
## calculate XRD with pymatgen ##
if xrd:
xrd = xrd_cal.get_xrd_data(struc_meta\
.get_structures(False).pop())
_xrd = np.asarray(xrd)[:,:2]
q, iq = _xrd.T
interp_q = assign_nearest(self.std_q, q, iq)
xrd_list.append(interp_q)
else:
pass
## test space group info ##
_sg = struc_meta.get_structures(False).pop()\
.get_space_group_info()
except:
print("{} fail".format(_cif))
fail_list.append(cif)
else:
# no error for both pymatgen and diffpy
gr_list.append(cal.pdf)
rdf_list.append(cal.rdf)
self.density_list.append(cal.slope)
print('=== Finished evaluating PDF from structure {} ==='
.format(cif))
## update features ##
flag = ['primitive', 'ordinary']
option = [True, False]
compo_list = [composition_list_1, composition_list_2]
struc_fields = ['a','b','c','alpha','beta','gamma', 'volume']
for f, op, compo in zip(flag, option, compo_list):
rv_dict = {}
struc = struc_meta.get_structures(op).pop()
a, b, c = struc.lattice.abc
aa, bb, cc = struc.lattice.angles
volume = struc.volume
for k, v in zip(struc_fields,
[a, b, c, aa, bb, cc, volume]):
rv_dict.update({"{}_{}".format(f, k) : v})
compo.append(struc.composition.as_dict())
struc_df = struc_df.append(rv_dict,
ignore_index=True)
# sg info, use the ordinary setup
sg_list.append(struc.get_space_group_info())
print('=== Finished evaluating XRD from structure {} ==='
.format(cif))
# finally, store crucial calculation results as attributes
self.r_grid = cal.rgrid
#4*pi * r^2 * rho(r) = R(r) -> RDF to density
self.gr_array = np.asarray(gr_list)/4/np.pi/self.r_grid**2
self.rdf_array = np.asarray(gr_list)
self.density_list = np.asarray(self.density_list)
self.xrd_info = np.asarray(xrd_list)
self.sg_list = sg_list
# 1 -> primitive , 2 -> ordinary
self.composition_list_1 = composition_list_1
self.composition_list_2 = composition_list_2
self.struc_df = struc_df
self.fail_list = fail_list
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import DebyePDFCalculator
from matplotlib.pyplot import plot, show
c60 = loadStructure('c60.stru')
dpc = DebyePDFCalculator()
dpc.qmax = 20
dpc.rmax = 20
r3, g3 = dpc(c60, qmin=0)
r4, g4 = dpc(c60, qmin=1)
plot(r3, g3, r4, g4)
show()
import numpy as np
import matplotlib.pyplot as plt
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import PDFCalculator
from diffpy.srfit.pdf import PDFContribution
from scipy.integrate import simps
bto_cluster_1 = loadStructure("BaTiO3.xyz")
bto_cluster_2 = loadStructure("BaTiO3_4_4_4.xyz")
bto_cluster_3 = loadStructure("BaTiO3_8_8_8.xyz")
bto_cluster_1.Uisoequiv = 0.005
bto_cluster_2.Uisoequiv = 0.005
bto_cluster_3.Uisoequiv = 0.005
cfg = {
'qmax': 25,
'qmin': 0,
'rmin': 0,
'rmax': 20,
'rstep': 0.01,
'qdamp': 0.045,
'qbroad': 0.069
}
# calculate PDF by real-space summation
pc0 = PDFCalculator(**cfg)
r1, g1 = pc0(bto_cluster_1)
r2, g2 = pc0(bto_cluster_2)
r3, g3 = pc0(bto_cluster_3)
def gr_lib_build(self, cif_lib_path):
''' method to calculate G(r) based on path of cif library located at.
Paramters of G(r) calculation are set via glbl.<attribute>, one can tune it based on purpose of building library.
After entire method, text file contains all G(r), space_group_symbol and material name will be saved respectively
Parameters
----------
cif_lib_path : str
path to lib of cif files
'''
el_list = [] # data column
space_group_symbol_list = [] # reference for search have been done in the past
# set up calculation environment
#dbc = DebyePDFCalculator()
pdf = PDFCalculator()
pdf.rstep = glbl.rstep
cfg = {'qmin': glbl.q_min, 'qmax':glbl.q_max, 'rmin':glbl.r_min, 'rmax': glbl.r_max}
Bisoequiv = glbl.Bisoequiv #FIXME: current value = 0.5, need to figure out the most suitable value
print('====Parameter used in this PDF calculator is: {}===='.format(cfg))
print('====Bisoequiv used in this PDF calculator is: {}===='.format(Bisoequiv))
# step 1: list cif dir
output_dir = os.path.join(self.data_dir, 'lib_data')
self._makedirs(output_dir)
self.output_dir = output_dir
cif_f_list = [ f for f in os.listdir(self.cif_dir)]
# hidden step as numpy can't take an empty array and stack
struc = loadStructure(os.path.join(self.cif_dir, cif_f_list[0]))
struc.Bisoequiv = Bisoequiv
(r,g) = pdf(nosymmetry(struc), **cfg)
r_grid = np.array(r) # data x-axis
gr_list = np.empty_like(np.array(g)) # data y-axis
for cif in cif_f_list:
# part 2: calculate PDF with diffpy
struc = loadStructure(os.path.join(self.cif_dir, cif))
struc.Bisoequiv = Bisoequiv
#(r,g) = pdf(nosymmetry(struc), **cfg)
(r,g) = pdf(struc, **cfg)
print('Finished calculation of G(r) on {}'.format(cif))
sep = cif.index('_')
space_group_symbol = cif[:sep]
m_name = cif[sep+1:]
# part 3: save data
#if not gr_list.any():
#gr_list = np.append(gr_list, g)
gr_list = np.vstack((gr_list,g))
space_group_symbol_list.append(space_group_symbol)
el_list.append(m_name)
#print('size of gr_list = {}'.format(np.shape(gr_list)))
#space_group_symbol_list = np.concatenate([space_group_symbol_list, space_group_symbol], axis=0)
#el_list = np.concatenate([el_list, m_name], axis=0)
time_info = time.strftime('%Y-%m-%d')
gr_list_name = '{}_{}_Gr'.format(self.crystal_system, time_info)
gr_list_w_name = os.path.join(output_dir, gr_list_name)
print('Saving {}'.format(gr_list_w_name))
np.save(gr_list_w_name, gr_list)
r_grid_name = '{}_{}_rgrid'.format(self.crystal_system, time_info)
r_grid_w_name = os.path.join(output_dir, r_grid_name)
np.save(r_grid_w_name, r)
space_group_symbol_list_name = '{}_{}_SpaceGroupSymbol'.format(self.crystal_system, time_info)
space_group_symbol_list_w_name= os.path.join(output_dir, space_group_symbol_list_name)
np.save(space_group_symbol_list_w_name, space_group_symbol_list) #fmt="%s")
el_list_name = '{}_{}_Element'.format(self.crystal_system, time_info)
el_list_w_name = os.path.join(output_dir, el_list_name)
np.save(el_list_w_name, el_list) #fmt="%s")
print('''====SUMMARY====:
for {} cystsal sytem,
Number of cif pulled out and G(r) calculated is {}'''.format(self.crystal_system, np.shape(gr_list)))
return gr_list
shuffle(urls)
num_cifs0 = num_downloaded
temp_filename = f"{save_loc}tmp.cif"
for i, url in enumerate(urls):
try:
#Download file
download = urlopen(url).read()
#Create temporary copy to load structure from
with open(temp_filename, "wb") as w:
w.write(download)
atom_list = loadStructure(temp_filename).tolist()
#Make sure it doesn't contain hydrogen
contains_H = False
for atom in atom_list:
elem_num = atom_enums[process_elem_string(atom.element)]
if elem_num == 1:
contains_H = True
break
if contains_H:
continue
num_downloaded += 1
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import leastsq
from mcalculator import *
import diffpy as dp
from diffpy.Structure import loadStructure
# Create the structure from our cif file, update the lattice params
MnOrhomb = loadStructure("mPDF_exampleFiles/MnO_R-3m.cif")
MnOcubic = loadStructure("mPDF_exampleFiles/MnO_cubic.cif")
latCub=MnOcubic.lattice
latRhomb=MnOrhomb.lattice
latRhomb.a,latRhomb.b,latRhomb.c=latCub.a/np.sqrt(2),latCub.a/np.sqrt(2),np.sqrt(6)*latCub.a/np.sqrt(2)
#MnOrhomb.lattice=latRhomb
# Set up the mPDF calculators
mcCub=mPDFcalculator(MnOcubic)
mcCub.magIdxs=[0,1,2,3]
mcCub.makeAtoms()
mcRhomb=mPDFcalculator(MnOrhomb)
mcRhomb.magIdxs=[0,1,2]
mcRhomb.makeAtoms()
svec=2.5*np.array([1.0,-1.0,0])/np.sqrt(2)
mcCub.svec=svec
mcCub.kvec=np.array([0.5,0.5,0.5])
mcCub.spinOrigin=mcCub.atoms[0]
mcCub.makeSpins()
mcRhomb.svec=svec
def learninglib_build(cif_list, xrd=False):
"""function designed for parallel computation
Parameters
----------
cif_list : list
List of cif filenames
xrd : bool, optional
Wether to calculate xrd pattern. Default to False
"""
gr_list = []
density_list = []
xrd_list = []
struc_df = pd.DataFrame()
fail_list = []
composition_list_1 = []
composition_list_2 = []
# database fields
flag = ['primitive', 'ordinary']
option = [True, False]
compo_list = [composition_list_1, composition_list_2]
struc_fields = ['a','b','c','alpha','beta','gamma',
'volume', 'sg_label', 'sg_order']
# looping
for _cif in sorted(cif_list):
try:
# diffpy structure
struc = loadStructure(_cif)
struc.Uisoequiv = Uiso
## calculate PDF/RDF with diffpy ##
r_grid, gr = cal(struc, **pdfCal_cfg)
density = cal.slope
# pymatgen structure
struc_meta = CifParser(_cif)
## calculate XRD with pymatgen ##
if xrd:
xrd = xrd_cal.get_xrd_data(struc_meta\
.get_structures(False).pop())
_xrd = np.asarray(xrd)[:,:2]
q, iq = _xrd.T
q = theta2q(q, wavelength)
interp_q = assign_nearest(std_q, q, iq)
xrd_list.append(interp_q)
else:
pass
## test if space group info can be parsed##
dummy_struc = struc_meta.get_structures(False).pop()
_sg = dummy_struc.get_space_group_info()
#except RuntimeError: # allow exception to debug
except:
print("{} fail".format(_cif))
fail_list.append(_cif)
else:
# no error for both pymatgen and diffpy
print('=== Finished evaluating PDF from structure {} ==='
.format(_cif))
## update features ##
rv_dict = {}
for f, op, compo in zip(flag, option, compo_list):
struc = struc_meta.get_structures(op).pop()
a, b, c = struc.lattice.abc
aa, bb, cc = struc.lattice.angles
volume = struc.volume
sg, sg_order = struc.get_space_group_info()
for k, v in zip(struc_fields,
[a, b, c, aa, bb, cc, volume,
sg, sg_order]):
rv_dict.update({"{}_{}".format(f, k) : v})
compo.append(struc.composition.as_dict())
struc_df = struc_df.append(rv_dict, ignore_index=True)
# storing results
gr_list.append(gr)
density_list.append(density)
# end of loop, storing turn result into ndarray
r_grid = cal.rgrid
gr_array = np.asarray(gr_list)
density_array = np.asarray(density_list)
xrd_info = np.asarray(xrd_list)
q_grid = std_q
# talktive statement
rv_name_list = ['gr_array', 'density_array', 'r_grid',
'xrd_info', 'q_grid',
'primitive_composition_list',
'ordinary_composition_list',
'struc_df', 'fail_list']
print('{:=^80}'.format(' Return '))
print('\n'.join(rv_name_list))
rv = gr_array, density_array, r_grid, xrd_info, q_grid,\
composition_list_1, composition_list_2, struc_df, fail_list
return rv
def map_learninglib(cif_fp, mode='bond_dst'):
"""function designed to build atomic distance list with
parallel computation
Parameters
----------
cif_list : str
full filepath to cif files.
mode : str, optional
String to specify quantities being calculated.
Allowed strings are: ``pdf`` or ``bond_dst``.
Default to ``pdf``
"""
## container for md ##
rv_dict = {}
struc_df = pd.DataFrame()
composition_list_1 = []
composition_list_2 = []
## fields for features ##
flag = ['primitive', 'ordinary']
option = [True, False]
compo_list = [composition_list_1, composition_list_2]
struc_fields = ['a','b','c','alpha','beta','gamma',
'volume', 'sg_label', 'sg_order']
if mode not in ('pdf', 'bond_dst'):
raise RuntimeError("Mode must be either 'pdf' or 'bond_dst'")
try:
# diffpy structure
if mode == 'pdf':
## calculate PDF/RDF with diffpy ##
struc = loadStructure(cif_fp)
struc.Uisoequiv = Uiso
r_grid, gr = cal(struc, **pdfCal_cfg)
density = cal.slope
elif mode == 'bond_dst':
struc = loadStructure(cif_fp, eps=eps)
dst = bc(struc)
uniq_ind = (np.diff(np.r_[-1.0, bc.distances]) > 1e-8)
uniq_dst = dst[uniq_ind]
uniq_direction = bc.directions[uniq_ind]
# pymatgen structure
struc_meta = CifParser(cif_fp)
## test if space group info can be parsed##
dummy_struc = struc_meta.get_structures(False).pop()
_sg = dummy_struc.get_space_group_info()
except:
# parallelized so direct return
return os.path.basename(cif_fp)
else:
# insert uid
rv_dict.update({"COD_uid": strip_fn(cif_fp)})
for f, op, compo in zip(flag, option, compo_list):
struc = struc_meta.get_structures(op).pop()
a, b, c = struc.lattice.abc
aa, bb, cc = struc.lattice.angles
volume = struc.volume
sg, sg_order = struc.get_space_group_info()
for k, v in zip(struc_fields,
[a, b, c, aa, bb, cc, volume,
sg, sg_order]):
rv_dict.update({"{}_{}".format(f, k) : v})
compo_info =dict(struc.composition.as_dict())
compo.append(compo_info)
rv_dict.update({"{}_composition".format(f): compo})
struc_df = struc_df.append(rv_dict, ignore_index=True)
if mode=='pdf':
rv_name_list = ['gr', 'density', 'r_grid', 'struc_df']
print('{:=^80}'.format(' Return '))
print('\n'.join(rv_name_list))
return (gr, density, r_grid, struc_df)
elif mode=='bond_dst':
rv_name_list = ['uniq_dst', 'uniq_direction', 'struc_df']
print('{:=^80}'.format(' Return '))
print('\n'.join(rv_name_list))
return (uniq_dst, uniq_direction, struc_df)
import numpy as np
import matplotlib.pyplot as plt
from diffpy.Structure import loadStructure
from diffpy.srreal.pdfcalculator import PDFCalculator, DebyePDFCalculator
from diffpy.srfit.pdf import PDFContribution
from scipy.integrate import simps
nkl_crystal = loadStructure("Nickel.cif")
nkl_crystal.Uisoequiv = 0.005
cfg_pc = {'rmin': 0, 'rmax': 20, 'rstep': 0.01}
cfg_dpc1 = {'qmax': 100, 'qmin': 0, 'rmin': 0, 'rmax': 40, 'rstep': 0.01}
#cfg_dpc2 = {'qmax' : 100,
# 'qmin' : 0,
# 'rmin' : 0,
# 'rmax' : 70,
# 'rstep': 0.01}
#
#cfg_dpc3 = {'qmax' : 100,
# 'qmin' : 0,
# 'rmin' : 0,
# 'rmax' : 100,
# 'rstep': 0.01}
# calculate PDF by real-space summation
pc0 = PDFCalculator(**cfg_pc)
r0, g0 = pc0(nkl_crystal)
# calcualte PDF by DPC
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''Calculation of bond valence sums using diffpy.srreal module included in
DiffPy-CMI.
'''
from __future__ import print_function
from diffpy.Structure import loadStructure
from diffpy.srreal.bvscalculator import BVSCalculator
# load crystal structure data from a CIF file
nacl = loadStructure('NaCl.cif')
# create bond valence sum calculator object
bvsc = BVSCalculator()
# calculate BVS and print the expected and actual valences
vsim = bvsc(nacl)
print('Calculate bond valence sums for NaCl "bvsc(nacl)"')
print('expected "bvsc.valences":\n ', bvsc.valences)
print('calculated "bvsc.value":\n ' , vsim)
print('difference "bvsc.bvdiff":\n ', bvsc.bvdiff)
print('root mean square difference "bvsc.bvrmsdiff":', bvsc.bvrmsdiff)
print()
# create new BVS calculator with a custom bond valence parameters
bvsc2 = BVSCalculator()
# Use alternate value for the Na+ Cl- bond valence parameters from
# http://www.iucr.org/__data/assets/file/0018/59004/bvparm2011.cif
# Import necessary functions
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import leastsq
from diffpy.mpdf import *
from diffpy.Structure import loadStructure
from diffpy.srfit.pdf import PDFContribution
from diffpy.srfit.fitbase import FitRecipe, FitResults
# Files containing our experimental data and structure file
dataFile = "npdf_07334.gr"
structureFile = "MnO_R-3m.cif"
spaceGroup = "H-3m"
mnostructure = loadStructure(structureFile)
# Create the Mn2+ magnetic species
mn2p = MagSpecies(struc=mnostructure,
label='Mn2+',
magIdxs=[0, 1, 2],
basisvecs=2.5 * np.array([[1, 0, 0]]),
kvecs=np.array([[0, 0, 1.5]]),
ffparamkey='Mn2')
# Create and prep the magnetic structure
mstr = MagStructure()
mstr.loadSpecies(mn2p)
mstr.makeAll()
# Set up the mPDF calculator
Instituion:-----University of Colorado Boulder
--------------------Raman Spectroscopy and Neutron Scattering Laboratory
--------------------Professor Dmitry Reznik
Description: You have to go down to where 'masses' is introduced and enter the
masses of the atoms corresponding to the atoms in 'types'
"""
import numpy as np
from diffpy.Structure import loadStructure
from diffpy.Structure.expansion import supercell
infile = 'C_mp-667273_conventional_standard.cif'
outfile = 'c60'
c60 = loadStructure(infile)
c60_2x2x2 = supercell(c60, [12, 2, 2])
c60.write(outfile + '.xyz', 'xyz')
c60_2x2x2.write(outfile + '_2x2x2.xyz', 'xyz')
struct = c60_2x2x2
with open(outfile + '_2x2x2.xyz', 'r') as fid:
nat = int(fid.readline()) # number of atoms
fid.readline() # skip comment line
pos = np.zeros((nat, 4))
types = []
for i in range(nat):
tmp = fid.readline().strip().split()
if tmp[0] not in types:
types.append(tmp[0])
