def get_active_space(xyzfile, optionfile):
"""calculates the active space for a given molecule and excited state
(see http://www.dftbaby.chemie.uni-wuerzburg.de/DFTBaby/mdwiki.html#!WIKI/main_page.md, Active Space)
not implemented in CAST because no use for ground state calculations
for ground state calculations the active space can be set as small as desired"""
outputfile = open("output_dftb.txt", "a") # redirect output to file
sys.stdout = outputfile
try:
options = read_options(optionfile) # read options
atomlist = XYZ.read_xyz(xyzfile)[0] # read structure
init_options = extract_options(options, TD_INIT_OPTIONLIST)
td_options = extract_options(options, TD_OPTIONLIST)
kwds = XYZ.extract_keywords_xyz(xyzfile)
tddftb = LR_TDDFTB(atomlist, **init_options) # create object
tddftb.setGeometry(atomlist, charge=kwds.get("charge", 0.0))
tddftb.getEnergies(**td_options) # calculate energies
occ, virt = tddftb.determineActiveSpace()
return str((occ, virt))
except:
print sys.exc_info()
return "error"
def test_dftb_eigenvector_derivative():
"""compare analytical and numerical gradients of MO coefficients and orbital energies"""
from DFTB.XYZ import read_xyz, extract_keywords_xyz
from DFTB.DFTB2 import DFTB2
from DFTB.Analyse.Cube import CubeExporterEx
from DFTB.Molden import MoldenExporter
from DFTB import utils
from DFTB.LR_TDDFTB import LR_TDDFTB
from DFTB.ExcGradients import Gradients
import sys
import os
usage = "Usage: %s <xyz-file>\n" % sys.argv[0]
usage += " --help option will give more information\n"
parser = utils.OptionParserFuncWrapper([\
DFTB2.__init__, DFTB2.runSCC, \
LR_TDDFTB.getEnergies, LR_TDDFTB.saveAbsorptionSpectrum, LR_TDDFTB.analyseParticleHole, \
LR_TDDFTB.graphical_analysis, \
CubeExporterEx.exportCubes, MoldenExporter.export, \
Gradients.getGradients], \
usage)
(options, args) = parser.parse_args(DFTB2.__init__)
if len(args) < 1:
print(usage)
exit(-1)
xyz_file = args[0]
atomlist = read_xyz(xyz_file)[0]
kwds = extract_keywords_xyz(xyz_file)
tddftb = LR_TDDFTB(atomlist, **options)
(options, args) = parser.parse_args(tddftb.getEnergies)
(scf_options, args) = parser.parse_args(tddftb.dftb2.runSCC)
options.update(scf_options)
tddftb.setGeometry(atomlist, charge=kwds.get("charge", 0.0))
tddftb.getEnergies(**options)
grad = Gradients(tddftb)
grad.gradient(I=0, save_intermediates_CPKS=1)
dE_an, dX_an = grad.getMOgradients()
dftb2 = tddftb.dftb2
E = dftb2.getKSEnergies()
X = dftb2.getKSCoefficients()
dE_num, dX_num = dftb_numerical_mo_gradients(dftb2, atomlist)
print("eigenvalues")
print(E)
print("numerical eigenvalue gradients")
print(dE_num)
print("analytical eigenvalue gradients")
print(dE_an)
err_dE = la.norm(dE_num - dE_an)
err_dX = la.norm(dX_num - dX_an)
assert err_dE < 1.0e-3, "err(dE) = %s" % err_dE
def calc_gradients(xyzfile, optionfile):
"""calculates DFTB energies and gradients for a molecule in the xyz_file
with the options given in the optionfile"""
outputfile = open("output_dftb.txt", "a") # redirect output to file
sys.stdout = outputfile
try:
options = read_options(optionfile) # read options
atomlist = XYZ.read_xyz(xyzfile)[0] # read structure
init_options = extract_options(options, TD_INIT_OPTIONLIST)
td_options = extract_options(options, TD_OPTIONLIST)
grad_options = extract_options(options, GRAD_OPTIONS)
kwds = XYZ.extract_keywords_xyz(xyzfile)
tddftb = LR_TDDFTB(atomlist, **init_options) # create object
tddftb.setGeometry(atomlist, charge=kwds.get("charge", 0.0))
tddftb.getEnergies(**td_options) # calculate energies
grad = Gradients(tddftb) # calculate gradients
grad.getGradients(**grad_options)
energies = list(tddftb.dftb2.getEnergies()) # get partial energies
if tddftb.dftb2.long_range_correction == 1: # add long range correction to partial energies
energies.append(tddftb.dftb2.E_HF_x)
return str(energies)
except:
print sys.exc_info()
return "error"
def test_dipole_prepared_continuum():
"""
see
G. Fronzoni, M. Stener, S. Furlan, P. Decleva
Chemical Physics 273 (2001) 117-133
"""
from DFTB.LR_TDDFTB import LR_TDDFTB
from DFTB import XYZ
from DFTB.Scattering import slako_tables_scattering
# BOUND ORBITAL = H**O
atomlist = XYZ.read_xyz("./water.xyz")[0]
tddftb = LR_TDDFTB(atomlist)
tddftb.setGeometry(atomlist, charge=0)
options = {"nstates": 1}
tddftb.getEnergies(**options)
valorbs, radial_val = load_pseudo_atoms(atomlist)
H**O, LUMO = tddftb.dftb2.getFrontierOrbitals()
bound_orbs = tddftb.dftb2.getKSCoefficients()
# polarization direction of E-field
epol = np.array([0.0, 1.0, 0.0])
# according to Koopman's theorem the electron is ionized from the H**O
mo_indx = range(0, len(bound_orbs))
nmo = len(mo_indx)
for imo in range(0, nmo):
mo_bound = bound_orbs[:, mo_indx[imo]]
# CONTINUUM ORBITALS at energy E
for E in slako_tables_scattering.energies:
bs = AtomicScatteringBasisSet(atomlist, E)
SKT_bf, SKT_ff = load_slako_scattering(atomlist, E)
Dipole = ScatteringDipoleMatrix(atomlist, valorbs, SKT_bf)
# projection of dipoles onto polarization direction
Dipole_projected = np.zeros((Dipole.shape[0], Dipole.shape[1]))
for xyz in [0, 1, 2]:
Dipole_projected += Dipole[:, :, xyz] * epol[xyz]
# unnormalized coefficients of dipole-prepared continuum orbitals
mo_scatt = np.dot(mo_bound, Dipole_projected)
nrm2 = np.dot(mo_scatt, mo_scatt)
# normalized coefficients
mo_scatt /= np.sqrt(nrm2)
Cube.orbital2grid(atomlist, bs.bfs, mo_scatt, \
filename="/tmp/scattering_orbital_%d_to_%s.cube" % (imo, str(E).replace(".", "p")), dbuff=25.0)
delattr(Cube.orbital_amplitude, "cached_grid")
def test_averaged_asymptotic_density():
from DFTB.LR_TDDFTB import LR_TDDFTB
from DFTB import XYZ
from DFTB.Scattering import slako_tables_scattering
from DFTB.Scattering import PAD
# BOUND ORBITAL = H**O
atomlist = XYZ.read_xyz("./water.xyz")[0]
tddftb = LR_TDDFTB(atomlist)
tddftb.setGeometry(atomlist, charge=0)
options = {"nstates": 1}
tddftb.getEnergies(**options)
valorbs, radial_val = load_pseudo_atoms(atomlist)
H**O, LUMO = tddftb.dftb2.getFrontierOrbitals()
bound_orbs = tddftb.dftb2.getKSCoefficients()
# polarization direction of E-field
epol = np.array([0.0, 0.0, 1.0])
# according to Koopman's theorem the electron is ionized from the H**O
mo_indx = range(0, len(bound_orbs))
nmo = len(mo_indx)
for imo in range(0, nmo):
print "IMO = %s" % imo
import time
time.sleep(1)
mo_bound = bound_orbs[:, mo_indx[imo]]
# CONTINUUM ORBITALS at energy E
for E in slako_tables_scattering.energies[-2:-1]:
bs = AtomicScatteringBasisSet(atomlist, E)
SKT_bf, SKT_ff = load_slako_scattering(atomlist, E)
Dipole = ScatteringDipoleMatrix(atomlist, valorbs, SKT_bf)
PAD.averaged_asymptotic_density(mo_bound, Dipole, bs, 20.0, E)
def averaged_pad_scan(xyz_file, dyson_file,
selected_orbitals, npts_euler, npts_theta, nskip, inter_atomic, sphere_radius):
molecule_name = os.path.basename(xyz_file).replace(".xyz", "")
atomlist = XYZ.read_xyz(xyz_file)[-1]
# shift molecule to center of mass
print "shift molecule to center of mass"
pos = XYZ.atomlist2vector(atomlist)
masses = AtomicData.atomlist2masses(atomlist)
pos_com = MolCo.shift_to_com(pos, masses)
atomlist = XYZ.vector2atomlist(pos_com, atomlist)
# compute molecular orbitals with DFTB
tddftb = LR_TDDFTB(atomlist)
tddftb.setGeometry(atomlist, charge=0)
options={"nstates": 1}
try:
tddftb.getEnergies(**options)
except DFTB.Solver.ExcitedStatesNotConverged:
pass
valorbs, radial_val = load_pseudo_atoms(atomlist)
if dyson_file == None:
print "tight-binding Kohn-Sham orbitals are taken as Dyson orbitals"
H**O, LUMO = tddftb.dftb2.getFrontierOrbitals()
bound_orbs = tddftb.dftb2.getKSCoefficients()
if selected_orbitals == None:
# all orbitals
selected_orbitals = range(0,bound_orbs.shape[1])
else:
selected_orbitals = eval(selected_orbitals, {}, {"H**O": H**O+1, "LUMO": LUMO+1})
print "Indeces of selected orbitals (counting from 1): %s" % selected_orbitals
orbital_names = ["orb_%s" % o for o in selected_orbitals]
selected_orbitals = np.array(selected_orbitals, dtype=int)-1 # counting from 0
dyson_orbs = bound_orbs[:,selected_orbitals]
ionization_energies = -tddftb.dftb2.getKSEnergies()[selected_orbitals]
else:
print "coeffients for Dyson orbitals are read from '%s'" % dyson_file
orbital_names, ionization_energies, dyson_orbs = load_dyson_orbitals(dyson_file)
ionization_energies = np.array(ionization_energies) / AtomicData.hartree_to_eV
print ""
print "*******************************************"
print "* PHOTOELECTRON ANGULAR DISTRIBUTIONS *"
print "*******************************************"
print ""
# determine the radius of the sphere where the angular distribution is calculated. It should be
# much larger than the extent of the molecule
(xmin,xmax),(ymin,ymax),(zmin,zmax) = Cube.get_bbox(atomlist, dbuff=0.0)
dx,dy,dz = xmax-xmin,ymax-ymin,zmax-zmin
Rmax = max([dx,dy,dz]) + sphere_radius
Npts = max(int(Rmax),1) * 50
print "Radius of sphere around molecule, Rmax = %s bohr" % Rmax
print "Points on radial grid, Npts = %d" % Npts
nr_dyson_orbs = len(orbital_names)
# compute PADs for all selected orbitals
for iorb in range(0, nr_dyson_orbs):
print "computing photoangular distribution for orbital %s" % orbital_names[iorb]
data_file = "betas_" + molecule_name + "_" + orbital_names[iorb] + ".dat"
pad_data = []
print " SCAN"
nskip = max(1, nskip)
# save table
fh = open(data_file, "w")
print " Writing table with betas to %s" % data_file
print>>fh, "# ionization from orbital %s IE = %6.3f eV" % (orbital_names[iorb], ionization_energies[iorb]*AtomicData.hartree_to_eV)
print>>fh, "# inter_atomic: %s npts_euler: %s npts_theta: %s rmax: %s" % (inter_atomic, npts_euler, npts_theta, Rmax)
print>>fh, "# PKE/eV sigma beta1 beta2 beta3 beta4"
for i,E in enumerate(slako_tables_scattering.energies):
if i % nskip != 0:
continue
print " PKE = %6.6f Hartree (%4.4f eV)" % (E, E*AtomicData.hartree_to_eV)
k = np.sqrt(2*E)
wavelength = 2.0 * np.pi/k
bs_free = AtomicScatteringBasisSet(atomlist, E, rmin=0.0, rmax=Rmax+2*wavelength, Npts=Npts)
SKT_bf, SKT_ff = load_slako_scattering(atomlist, E)
Dipole = ScatteringDipoleMatrix(atomlist, valorbs, SKT_bf, inter_atomic=inter_atomic).real
orientation_averaging = PAD.OrientationAveraging_small_memory(Dipole, bs_free, Rmax, E, npts_euler=npts_euler, npts_theta=npts_theta)
pad,betasE = orientation_averaging.averaged_pad(dyson_orbs[:,iorb])
pad_data.append( [E*AtomicData.hartree_to_eV] + list(betasE) )
# save PAD for this energy
print>>fh, "%10.6f %10.6e %+10.6e %+10.6f %+10.6e %+10.6e" % tuple(pad_data[-1])
fh.flush()
fh.close()
def test_photoangular_distribution():
from DFTB.LR_TDDFTB import LR_TDDFTB
from DFTB import XYZ
from DFTB.Scattering import slako_tables_scattering
# BOUND ORBITAL = H**O
atomlist = XYZ.read_xyz("./h2.xyz")[0]
tddftb = LR_TDDFTB(atomlist)
tddftb.setGeometry(atomlist, charge=0)
options = {"nstates": 1}
tddftb.getEnergies(**options)
valorbs, radial_val = load_pseudo_atoms(atomlist)
H**O, LUMO = tddftb.dftb2.getFrontierOrbitals()
bound_orbs = tddftb.dftb2.getKSCoefficients()
# according to Koopman's theorem the electron is ionized from the H**O
mo_indx = range(0, len(bound_orbs))
nmo = len(mo_indx)
energies = [[] for i in range(0, nmo)]
sigmas = [[] for i in range(0, nmo)]
betas = [[] for i in range(0, nmo)]
tdip2s = [[] for i in range(0, nmo)]
for imo in range(0, nmo):
mo_bound = bound_orbs[:, mo_indx[imo]]
# CONTINUUM ORBITALS at energy E
for E in slako_tables_scattering.energies:
SKT_bf, SKT_ff = load_slako_scattering(atomlist, E)
S_bb, H0_bb = tddftb.dftb2._constructH0andS()
S_bf, H0_bf = ScatteringHamiltonianMatrix(atomlist, valorbs,
SKT_bf)
#
invS_bb = la.inv(S_bb)
# (H-E*S)^t . Id . (H-E*S)
HmE2 = np.dot(H0_bf.conjugate().transpose(), np.dot(invS_bb, H0_bf)) \
- E * np.dot( S_bf.conjugate().transpose(), np.dot(invS_bb, H0_bf)) \
- E * np.dot(H0_bf.conjugate().transpose(), np.dot(invS_bb, S_bf)) \
+ E**2 * np.dot(S_bf.conjugate().transpose(), np.dot(invS_bb, S_bf))
#
scat_lambdas, scat_orbs = sla.eigh(HmE2)
print "PKE = %s" % E
print "lambdas = %s" % scat_lambdas
# photoangular distribution averaged over isotropically oriented ensemble of molecules
Dipole = ScatteringDipoleMatrix(atomlist, valorbs, SKT_bf)
sigma = 0.0
beta = 0.0
tdip2 = 0.0
olap = 0.0
for i in range(0, len(scat_lambdas)):
if abs(scat_lambdas[i]) > 1.0e-10:
print "%d lambda = %s" % (i, scat_lambdas[i])
mo_scatt = scat_orbs[:, i]
sigma_i, beta_i = angular_distribution(
atomlist, valorbs, mo_bound, mo_scatt, Dipole)
sigma += sigma_i
beta += sigma_i * beta_i
tdip_i = np.zeros(3, dtype=complex)
for xyz in range(0, 3):
tdip_i[xyz] += np.dot(
mo_bound, np.dot(Dipole[:, :, xyz], mo_scatt))
tdip2 += np.sum(abs(tdip_i)**2)
print "tdip2 = %s" % tdip2
beta /= sigma
####
#sigma_test, beta_test = angular_distribution_old2(atomlist, valorbs, mo_bound, mo_scatt, Dipole)
#assert abs(sigma-sigma_test) < 1.0e-10
#assert abs(beta-beta_test) < 1.0e-10
####
print "E= %s sigma=%s beta= %s" % (E, sigma, beta)
energies[imo].append(E)
sigmas[imo].append(sigma.real)
betas[imo].append(beta.real)
tdip2s[imo].append(tdip2)
energies = np.array(energies)
sigmas = np.array(sigmas)
betas = np.array(betas)
from matplotlib import pyplot as plt
# total cross section
plt.xlabel("PKE / eV")
plt.ylabel("total photoionization cross section $\sigma$")
for imo in range(0, nmo):
plt.plot(energies[imo] * 27.211, sigmas[imo], lw=2)
#plt.plot(energies[imo]*27.211, tdip2s[imo], lw=2, ls="-.")
plt.show()
# anisotropy
plt.cla()
plt.ylim((-1.0, 2.0))
plt.xlabel("PKE / eV")
plt.ylabel("anisotropy $\\beta_2$")
for imo in range(0, nmo):
plt.plot(energies[imo] * 27.211, betas[imo], lw=2, label="%d" % imo)
plt.legend()
plt.show()
return energies, sigmas, betas
def test_scattering_orbitals():
from DFTB.LR_TDDFTB import LR_TDDFTB
from DFTB import XYZ
atomlist = XYZ.read_xyz("h2.xyz")[0]
tddftb = LR_TDDFTB(atomlist)
tddftb.setGeometry(atomlist, charge=0)
options = {"nstates": 1}
tddftb.getEnergies(**options)
valorbs, radial_val = load_pseudo_atoms(atomlist)
E = 5.0 / 27.211
bs = AtomicScatteringBasisSet(atomlist, E)
print bs.bfs
SKT_bf, SKT_ff = load_slako_scattering(atomlist, E)
S_bb, H0_bb = tddftb.dftb2._constructH0andS()
S_bf, H0_bf = ScatteringHamiltonianMatrix(atomlist, valorbs, SKT_bf)
#
invS_bb = la.inv(S_bb)
# (H-E*S)^t . Id . (H-E*S)
HmE2 = np.dot(H0_bf.conjugate().transpose(), np.dot(invS_bb, H0_bf)) \
- E * np.dot( S_bf.conjugate().transpose(), np.dot(invS_bb, H0_bf)) \
- E * np.dot(H0_bf.conjugate().transpose(), np.dot(invS_bb, S_bf)) \
+ E**2 * np.dot(S_bf.conjugate().transpose(), np.dot(invS_bb, S_bf))
Scont = continuum_flux(atomlist, SKT_bf)
S2 = np.dot(S_bf.conjugate().transpose(), np.dot(la.inv(S_bb), S_bf))
"""
#
H2 = np.dot(H0_bf.transpose(), np.dot(la.inv(S_bb), H0_bf))
S2 = np.dot( S_bf.transpose(), np.dot(la.inv(S_bb), S_bf))
print "H2"
print H2
print "S2"
print S2
scat_orbe2, scat_orbs = sla.eig(H2) #, S2)
print "PKE = %s" % E
print "Energies^2 = %s" % scat_orbe2
scat_orbe = np.sqrt(scat_orbe2)
sort_indx = np.argsort(scat_orbe)
scat_orbe = scat_orbe[sort_indx]
scat_orbs = scat_orbs[:,sort_indx]
print "Energies of scattering orbitals: %s" % scat_orbe
orbE = np.argmin(abs(scat_orbe-E))
"""
assert np.sum(abs(HmE2.conjugate().transpose() - HmE2)) < 1.0e-10
assert np.sum(abs(S2.conjugate().transpose() - S2)) < 1.0e-10
lambdas, scat_orbs = sla.eigh(HmE2)
print "lambdas = %s" % lambdas
from DFTB.Scattering import PAD
for i in range(0, len(lambdas)):
if abs(lambdas[i]) > 1.0e-8:
print "%d lambda = %s" % (i, lambdas[i])
###
def wavefunction(grid, dV):
# evaluate orbital
amp = Cube.orbital_amplitude(grid,
bs.bfs,
scat_orbs[:, i],
cache=False)
return amp
PAD.asymptotic_density(wavefunction, 20, E)
###
for (flm, l, m) in classify_lm(bs, scat_orbs[:, i]):
if abs(flm).max() > 1.0e-4:
print " %s %s %s" % (l, m, abs(flm))
Cube.orbital2grid(atomlist, bs.bfs, scat_orbs[:,i], \
filename="/tmp/scattering_orbital_%d.cube" % i, dbuff=25.0)
delattr(Cube.orbital_amplitude, "cached_grid")
def atomic_pz_orbital(Z, data_file):
atomlist = [(Z, (0.0, 0.0, 0.0))]
# compute molecular orbitals with DFTB
print "compute molecular orbitals with tight-binding DFT"
tddftb = LR_TDDFTB(atomlist)
tddftb.setGeometry(atomlist, charge=0)
options = {"nstates": 1}
try:
tddftb.getEnergies(**options)
except DFTB.Solver.ExcitedStatesNotConverged:
pass
valorbs, radial_val = load_pseudo_atoms(atomlist)
bound_orbs = tddftb.dftb2.getKSCoefficients()
# order of orbitals s, py,pz,px, dxy,dyz,dz2,dzx,dx2y2, so the pz-orbital has index 2
mo_bound = bound_orbs[:, 2]
tdipole_data = []
for iE, E in enumerate(slako_tables_scattering.energies):
print "PKE = %s" % E
try:
SKT_bf, SKT_ff = load_slako_scattering(atomlist, E)
except ImportError:
break
Dipole = ScatteringDipoleMatrix(atomlist, valorbs, SKT_bf).real
# dipole between bound orbital and the continuum AO basis orbitals
dipole_bf = np.tensordot(mo_bound, Dipole, axes=(0, 0))
tdip_pz_to_s = dipole_bf[0, 2] # points along z-axis
tdip_pz_to_dyz = dipole_bf[5, 1] # points along y-axis
tdip_pz_to_dz2 = dipole_bf[6, 2] # points along z-axis
tdip_pz_to_dzx = dipole_bf[7, 0] # points along x-axis
tdipole_data.append(
[E * AtomicData.hartree_to_eV] +
[tdip_pz_to_s, tdip_pz_to_dyz, tdip_pz_to_dz2, tdip_pz_to_dzx])
####
# determine the radius of the sphere where the angular distribution is calculated. It should be
# much larger than the extent of the molecule
(xmin, xmax), (ymin, ymax), (zmin, zmax) = Cube.get_bbox(atomlist,
dbuff=0.0)
dx, dy, dz = xmax - xmin, ymax - ymin, zmax - zmin
Rmax = max([dx, dy, dz]) + 500.0
print "Radius of sphere around molecule, Rmax = %s bohr" % Rmax
k = np.sqrt(2 * E)
wavelength = 2.0 * np.pi / k
print "wavelength = %s" % wavelength
valorbsE, radial_valE = load_pseudo_atoms_scattering(atomlist,
E,
rmin=0.0,
rmax=Rmax +
2 * wavelength,
Npts=90000)
# Plot radial wavefunctions
import matplotlib.pyplot as plt
plt.ion()
r = np.linspace(0.0, Rmax + 2 * wavelength, 5000)
for i, (Zi, posi) in enumerate(atomlist):
for indx, (ni, li, mi) in enumerate(valorbsE[Zi]):
# only plot the dz2 continuum orbital
if li == 2 and mi == 0 and (iE % 10 == 0):
R_spl = radial_valE[Zi][indx]
radial_orbital_wfn = R_spl(r)
plt.plot(r,
radial_orbital_wfn,
label="Z=%s n=%s l=%s m=%s E=%s" %
(Zi, ni, li, mi, E))
plt.plot(r, np.sin(k * r) / r, ls="-.")
#plt.plot(r, np.sin(k*r + 1.0/k * np.log(2*k*r))/r, ls="--", lw=2)
plt.plot(r,
np.array([
float(mpmath.coulombf(li, -1.0 / k, k * rx)) /
rx for rx in r
]),
ls="--",
lw=2,
label="CoulombF l=%s E=%s" % (li, E))
plt.draw()
####
# save table
fh = open(data_file, "w")
print >> fh, "# PKE/eV pz->s pz->dyz pz->dz2 pz->dzx"
np.savetxt(fh, tdipole_data)
fh.close()
print "Wrote table with transition dipoles to %s" % data_file
# show radial wavefunctions
plt.ioff()
plt.show()
def test_dftb_charge_derivative():
"""compare analytical and numerical gradients of Mulliken charges"""
from DFTB.XYZ import read_xyz, extract_keywords_xyz
from DFTB.DFTB2 import DFTB2
from DFTB.Analyse.Cube import CubeExporterEx
from DFTB.Molden import MoldenExporter
from DFTB import utils
from DFTB.LR_TDDFTB import LR_TDDFTB
from DFTB.ExcGradients import Gradients
import sys
import os
usage = "Usage: %s <xyz-file>\n" % sys.argv[0]
usage += " --help option will give more information\n"
parser = utils.OptionParserFuncWrapper([\
DFTB2.__init__, DFTB2.runSCC, \
LR_TDDFTB.getEnergies, LR_TDDFTB.saveAbsorptionSpectrum, LR_TDDFTB.analyseParticleHole, \
LR_TDDFTB.graphical_analysis, \
CubeExporterEx.exportCubes, MoldenExporter.export, \
Gradients.getGradients], \
usage)
(options, args) = parser.parse_args(DFTB2.__init__)
if len(args) < 1:
print usage
exit(-1)
xyz_file = args[0]
atomlist = read_xyz(xyz_file)[0]
kwds = extract_keywords_xyz(xyz_file)
tddftb = LR_TDDFTB(atomlist, **options)
(options, args) = parser.parse_args(tddftb.getEnergies)
(scf_options, args) = parser.parse_args(tddftb.dftb2.runSCC)
options.update(scf_options)
tddftb.setGeometry(atomlist, charge=kwds.get("charge", 0.0))
tddftb.getEnergies(**options)
grad = Gradients(tddftb)
grad.gradient(I=0, save_intermediates_CPKS=1)
dQdp_ana = grad.getChargeGradients()
dftb2 = tddftb.dftb2
dQdp_num = dftb_numerical_charge_gradients(dftb2, atomlist)
print "partial Mulliken charges"
print dftb2.getPartialCharges()
print "numerical charge gradients"
print dQdp_num
print "analytical charge gradients"
print dQdp_ana
print "difference"
print dQdp_num - dQdp_ana
err_dQ = la.norm(dQdp_num - dQdp_ana)
print "err(dQdp) = %s" % err_dQ
#assert err_dQ < 1.0e-4, "err(dQdp) = %s" % err_dQ
# show timings
print T
class PotentialEnergySurfaces(object):
def __init__(self, atomlist, Nst=2, **kwds):
"""
The DFTB module has many parameters which can be set from the command
line using options, e.g. --scf_conv=1.0e-10.
During the initialization
- the command line arguments are parsed for options
- Slater-Koster tables and repulsive potentials
are loaded for the atom pair present in the molecule
Parameters:
===========
atomlist: list of tuples (Zi,[xi,yi,zi]) for each atom in the molecule
Nst: number of electronic states (including ground state)
"""
usage = "Type --help to show all options for DFTB"
parser = optparse.OptionParserFuncWrapper([
DFTB2.__init__, DFTB2.runSCC, SolventCavity.__init__,
LR_TDDFTB.getEnergies
],
usage,
section_headers=["DFTBaby"],
unknown_options="ignore")
options, args = parser.parse_args(DFTB2.__init__)
self.atomlist = atomlist
self.tddftb = LR_TDDFTB(atomlist, **options)
solvent_options, args = parser.parse_args(SolventCavity.__init__)
solvent_cavity = SolventCavity(**solvent_options)
self.tddftb.dftb2.setSolventCavity(solvent_cavity)
self.grads = Gradients(self.tddftb)
self.tddftb.setGeometry(atomlist, charge=kwds.get("charge", 0.0))
self.options, args = parser.parse_args(self.tddftb.getEnergies)
self.scf_options, args = parser.parse_args(self.tddftb.dftb2.runSCC)
self.options.update(self.scf_options)
self.Nst = Nst
# # always use iterative diagonalizer for lowest Nst-1 excited states
self.options["nstates"] = Nst - 1
# save geometry, orbitals and TD-DFT coefficients from
# last calculation
self.last_calculation = None
# save transition dipoles from last calculation
self.tdip_old = None
def getEnergies(self, x):
"""
This functions computes the adiabatic energies ONLY. It should
not be used during a dynamics simulation
"""
self.atomlist = XYZ.vector2atomlist(x, self.atomlist)
self.tddftb.setGeometry(self.atomlist,
keep_charge=True,
update_symmetry=False)
self.tddftb.getEnergies(**self.options)
# total ground state energy
E0 = self.tddftb.dftb2.E_tot
# excitation energies
Exc = self.tddftb.getExcEnergies()
# total energies of ground and excited states
energies = np.hstack(([E0], E0 + Exc))
return energies[:self.Nst]
def getEnergy_S0(self, x):
"""
This function compute the ground state energy ONLY.
"""
self.atomlist = XYZ.vector2atomlist(x, self.atomlist)
self.tddftb.setGeometry(self.atomlist,
keep_charge=True,
update_symmetry=False)
E0 = self.tddftb.dftb2.getEnergy(**self.scf_options)
energies = np.array([E0]) # only ground state energy
return energies
@T.timer
def getEnergiesAndGradient(self, x, gradient_state):
"""
This function computes the adiabatic electronic energies
for the nuclear geometry contained in 'x' and the gradient
of the total energy of state 'gradient_state'.
Parameters:
===========
x: a numpy array with the nuclear coordinates,
x[3*i:3*(i+1)] should contain the cartesian coordinates of atom i
gradient_state: index of the electronic state, whose gradient should
be calculated. 0 stands for the ground state, 1 for the 1st excited
state, etc.
Returns:
========
energies: numpy array with total energies (in Hartree) for all electronic
states
gradTot: total gradient of the selected state,
gradTot[3*i:3*(i+1)] contains the energy derivative w/r/t the 3 cartesian
coordinates of atom i.
"""
self.atomlist = XYZ.vector2atomlist(x, self.atomlist)
self.tddftb.setGeometry(self.atomlist,
keep_charge=True,
update_symmetry=False)
self.tddftb.getEnergies(**self.options)
# total ground state energy
E0 = self.tddftb.dftb2.E_tot
# excitation energies
Exc = self.tddftb.getExcEnergies()
# total energies of ground and excited states
energies = np.hstack(([E0], E0 + Exc))
gradVrep, gradE0, gradExc = self.grads.gradient(
I=gradient_state, save_intermediates_CPKS=1)
gradTot = gradVrep + gradE0 + gradExc
# QM/MM
if self.tddftb.dftb2.qmmm != None:
# expand gradient to the full system
gradTot = self.tddftb.dftb2.qmmm.getGradientFull(gradTot)
# confining cavity
if self.tddftb.dftb2.cavity != None:
if self.tddftb.dftb2.qmmm != None:
atomlist = self.tddftb.dftb2.qmmm.getGeometryFull()
else:
atomlist = self.atomlist
gradTot += self.tddftb.dftb2.cavity.getGradient(atomlist)
return energies, gradTot
def getEnergyAndGradient_S0(self, x, has_scf=False):
"""
obtain the ground state energy and gradient while skipping an excited state calculation.
This function should be called with has_scf=True directly after a failed TD-DFTB calculation. Then the scf calculation is skipped as well, assuming that the converged ground state orbitals are available.
Returns:
========
E0: ground state energy
gradTot: gradient on ground state
"""
# ground state energy
if has_scf == True:
# SCF calculation has been done already
E0 = self.tddftb.dftb2.E_tot
else:
self.atomlist = XYZ.vector2atomlist(x, self.atomlist)
self.tddftb.setGeometry(self.atomlist,
keep_charge=True,
update_symmetry=False)
# SCF calculation
E0 = self.tddftb.dftb2.getEnergy(**self.scf_options)
# try to compute gradient on ground state
gradVrep, gradE0, gradExc = self.grads.gradient(
I=0, save_intermediates_CPKS=1)
gradTot = gradVrep + gradE0 + gradExc
# QM/MM
if self.tddftb.dftb2.qmmm != None:
# expand gradient to the full system
gradTot = self.tddftb.dftb2.qmmm.getGradientFull(gradTot)
# confining cavity
if self.tddftb.dftb2.cavity != None:
if self.tddftb.dftb2.qmmm != None:
atomlist = self.tddftb.dftb2.qmmm.getGeometryFull()
else:
atomlist = self.atomlist
gradTot += self.tddftb.dftb2.cavity.getGradient(atomlist)
return E0, gradTot
def resetXY(self):
# reset excitation vectors, so that in the next iteration
# we start with a clean guess
self.tddftb.XmY = None
self.tddftb.XpY = None
def resetSCF(self):
# set Mulliken partial charges to zero and density matrix P to
# reference density matrix P0, so that in the next iteration
# we start with a clean guess
self.tddftb.dftb2.dq *= 0.0
self.tddftb.dftb2.P = self.tddftb.dftb2.density_matrix_ref()
def getScalarCouplings(self, threshold=0.01):
"""
Parameters:
===========
threshold: smaller excitation coefficients are neglected in the calculation
of overlaps
Returns:
========
coupl: antisymmetric matrix with scalar non-adiabatic coupling
coupl[A,B] ~ <Psi_A|d/dt Psi_B>*dt
The coupling matrix has to be divided by the nuclear time step dt
It is important that this function is called
exactly once after calling 'getEnergiesAndGradient'
"""
atomlist2 = self.atomlist
orbs2 = self.tddftb.dftb2.orbs
C2 = self.tddftb.Cij[:self.Nst -
1, :, :] # only save the states of interest
# off-diagonal elements of electronic hamiltonian
SC = ScalarCoupling(self.tddftb)
# retrieve last calculation
if self.last_calculation == None:
# This is the first calculation, so use the same data
atomlist1, orbs1, C1 = atomlist2, orbs2, C2
else:
atomlist1, orbs1, C1 = self.last_calculation
Sci = SC.ci_overlap(atomlist1,
orbs1,
C1,
atomlist2,
orbs2,
C2,
self.Nst,
threshold=threshold)
# align phases
# The eigenvalue solver produces vectors with arbitrary global phases
# (+1 or -1). The orbitals of the ground state can also change their signs.
# Eigen states from neighbouring geometries should change continuously.
signs = np.sign(np.diag(Sci))
self.P = np.diag(signs)
# align C2 with C1
C2 = np.tensordot(self.P[1:, :][:, 1:], C2, axes=(0, 0))
# align overlap matrix
Sci = np.dot(Sci, self.P)
# The relative signs for the overlap between the ground and excited states at different geometries
# cannot be deduced from the diagonal elements of Sci. The phases are chosen such that the coupling
# between S0 and S1-SN changes smoothly for most of the states.
if hasattr(self, "last_coupl"):
s = np.sign(self.last_coupl[0, 1:] / Sci[0, 1:])
w = np.abs(Sci[0, 1:] - self.last_coupl[0, 1:])
mean_sign = np.sign(np.sum(w * s) / np.sum(w))
sign0I = mean_sign
for I in range(1, self.Nst):
Sci[0, I] *= sign0I
Sci[I, 0] *= sign0I
#
state_labels = [("S%d" % I) for I in range(0, self.Nst)]
if self.tddftb.dftb2.verbose > 0:
print "Overlap <Psi(t)|Psi(t+dt)>"
print "=========================="
print utils.annotated_matrix(Sci, state_labels, state_labels)
# overlap between wavefunctions at different time steps
olap = np.copy(Sci)
coupl = Sci
# coupl[A,B] = <Psi_A(t)|Psi_B(t+dt)> - delta_AB
# ~ <Psi_A(t)|d/dR Psi_B(t)>*dR/dt dt
# TEST
# The scalar coupling matrix should be more or less anti-symmetric
# provided the time-step is small enough
# set diagonal elements of coupl to zero
coupl[np.diag_indices_from(coupl)] = 0.0
err = np.sum(abs(coupl + coupl.transpose()))
if err > 1.0e-1:
print "WARNING: Scalar coupling matrix is not antisymmetric, error = %s" % err
#
# Because of the finite time-step it will not be completely antisymmetric,
# so antisymmetrize it
coupl = 0.5 * (coupl - coupl.transpose())
# save coupling for establishing relative phases
self.last_coupl = coupl
state_labels = [("S%d" % I) for I in range(0, self.Nst)]
if self.tddftb.dftb2.verbose > 0:
print "Scalar Coupling"
print "==============="
print utils.annotated_matrix(coupl, state_labels, state_labels)
# save last calculation
self.last_calculation = (atomlist2, orbs2, C2)
return coupl, olap
def saveLastCalculation(self):
"""
save geometry, MO coefficients and TD-DFTB coefficients of last calculation.
This data is needed to align the phases between neighbouring steps.
"""
atomlist = self.atomlist
orbs = self.tddftb.dftb2.orbs
# only save the states of interest
C = self.tddftb.Cij[:self.Nst - 1, :, :]
# save last calculation
self.last_calculation = (atomlist, orbs, C)
def alignCoefficients(self, c):
"""
align phases of coefficients of adiabatic states
"""
if hasattr(self, "P"):
c = np.dot(self.P[1:, :][:, 1:], c)
return c
def getTransitionDipoles(self):
"""
computes and aligns transition dipoles between all Nst states
This function should be called only once directly after getScalarCouplings!
"""
tdip = self.tddftb.getTransitionDipolesExc(self.Nst)
# eigenvectors can have arbitrary phases
# align transition dipoles with old ones
tdip_old = self.tdip_old
if type(tdip_old) == type(None):
tdip_old = tdip
for A in range(0, self.Nst):
for B in range(0, self.Nst):
sign = np.dot(tdip_old[A, B, :], tdip[A, B, :])
if sign < 0.0:
tdip[A, B, :] *= -1.0
self.tdip_old = tdip
if self.tddftb.dftb2.verbose > 0:
state_labels = [("S%d" % I) for I in range(0, self.Nst)]
print "Transition Dipoles"
print "=================="
print "X-Component"
print utils.annotated_matrix(tdip[:, :, 0], state_labels,
state_labels)
print "Y-Component"
print utils.annotated_matrix(tdip[:, :, 1], state_labels,
state_labels)
print "Z-Component"
print utils.annotated_matrix(tdip[:, :, 2], state_labels,
state_labels)
#
return tdip
def calculate_charge_derivative():
"""compute analytical gradients of Mulliken charges"""
#
# This long prologue serves for reading all options
# from the command line or the dftbaby.cfg file.
# The command-line option
#
# --cpks_solver='direct' or 'iterative'
#
# determines whether the full CPKS matrix should be constructed ('direct')
# or whether the system of linear equations should be solved iteratively using the Krylov
# subspace method.
#
from DFTB.XYZ import read_xyz, extract_keywords_xyz
from DFTB.DFTB2 import DFTB2
from DFTB import utils
from DFTB.LR_TDDFTB import LR_TDDFTB
from DFTB.ExcGradients import Gradients
import sys
import os
usage = "Usage: %s <xyz-file>\n" % sys.argv[0]
usage += " --help option will give more information\n"
parser = utils.OptionParserFuncWrapper([\
DFTB2.__init__, DFTB2.runSCC, \
LR_TDDFTB.getEnergies, LR_TDDFTB.saveAbsorptionSpectrum, LR_TDDFTB.analyseParticleHole, \
Gradients.getGradients], \
usage)
(options, args) = parser.parse_args(DFTB2.__init__)
if len(args) < 1:
print usage
exit(-1)
xyz_file = args[0]
atomlist = read_xyz(xyz_file)[0]
# number of atoms
Nat = len(atomlist)
kwds = extract_keywords_xyz(xyz_file)
tddftb = LR_TDDFTB(atomlist, **options)
(options, args) = parser.parse_args(tddftb.getEnergies)
(scf_options, args) = parser.parse_args(tddftb.dftb2.runSCC)
options.update(scf_options)
tddftb.setGeometry(atomlist, charge=kwds.get("charge", 0.0))
tddftb.getEnergies(**options)
#
# The important part starts here.
#
grad = Gradients(tddftb)
# A CPKS calculation has to be preceeded by a gradient calculation.
# The option `save_intermediates_CPKS=1` tells the program to save intermediate
# variables that are needed later during the CPKS calculation.
grad.gradient(I=0, save_intermediates_CPKS=1)
# This runs a CPKS calculation and computes the gradients of the charges
dQdp = grad.getChargeGradients()
# The gradient of the charge on atom B w/r/t the position of atom A is
# d(Q_B)/dR_A = dQdp[3*A:3*(A+1), B]
A = 0 # first atom
B = Nat - 1 # last atom
print "Gradient of Mulliken charge on atom A=%d w/r/t nucleus B=%d d(Q_B)/dR_A = %s" \
% (A, B, dQdp[3*A:3*(A+1), B])
class Main(QtGui.QMainWindow):
def __init__(self, xyz_file, dyson_file=None):
super(Main, self).__init__()
self.settings = Settings({
"Continuum Orbital": {
"Ionization transitions":
[0, ["only intra-atomic", "inter-atomic"]]
},
"Averaging": {
"Euler angle grid points": 5,
"polar angle grid points": 1000,
"sphere radius Rmax": 300.0,
},
"Scan": {
"nr. points": 20
},
"Cube": {
"extra space / bohr": 15.0,
"points per bohr": 3.0
}
})
# perform DFTB calculation
# BOUND ORBITAL = H**O
self.atomlist = XYZ.read_xyz(xyz_file)[0]
# shift molecule to center of mass
print "shift molecule to center of mass"
pos = XYZ.atomlist2vector(self.atomlist)
masses = AtomicData.atomlist2masses(self.atomlist)
pos_com = MolCo.shift_to_com(pos, masses)
self.atomlist = XYZ.vector2atomlist(pos_com, self.atomlist)
self.tddftb = LR_TDDFTB(self.atomlist)
self.tddftb.setGeometry(self.atomlist, charge=0)
options = {"nstates": 1}
try:
self.tddftb.getEnergies(**options)
except DFTB.Solver.ExcitedStatesNotConverged:
pass
self.valorbs, radial_val = load_pseudo_atoms(self.atomlist)
if dyson_file == None:
# Kohn-Sham orbitals are taken as Dyson orbitals
self.H**O, self.LUMO = self.tddftb.dftb2.getFrontierOrbitals()
self.bound_orbs = self.tddftb.dftb2.getKSCoefficients()
self.orbe = self.tddftb.dftb2.getKSEnergies()
orbital_names = []
norb = len(self.orbe)
for o in range(0, norb):
if o < self.H**O:
name = "occup."
elif o == self.H**O:
name = "H**O"
elif o == self.LUMO:
name = "LUMO "
else:
name = "virtual"
name = name + " " + str(o).rjust(4) + (
" %+10.3f eV" % (self.orbe[o] * 27.211))
orbital_names.append(name)
initially_selected = self.H**O
else:
# load coefficients of Dyson orbitals from file
names, ionization_energies, self.bound_orbs = load_dyson_orbitals(
dyson_file)
self.orbe = np.array(ionization_energies) / 27.211
orbital_names = []
norb = len(self.orbe)
for o in range(0, norb):
name = names[o] + " " + str(o).rjust(4) + (
" %4.2f eV" % (self.orbe[o] * 27.211))
orbital_names.append(name)
initially_selected = 0
self.photo_kinetic_energy = slako_tables_scattering.energies[0]
self.epol = np.array([15.0, 0.0, 0.0])
# Build Graphical User Interface
main = QtGui.QWidget()
mainLayout = QtGui.QHBoxLayout(main)
#
selectionFrame = QtGui.QFrame()
selectionFrame.setSizePolicy(QtGui.QSizePolicy.Fixed,
QtGui.QSizePolicy.Preferred)
mainLayout.addWidget(selectionFrame)
selectionLayout = QtGui.QVBoxLayout(selectionFrame)
#
label = QtGui.QLabel(selectionFrame)
label.setText("Select bound MO:")
selectionLayout.addWidget(label)
# bound orbitals
self.orbitalSelection = QtGui.QListWidget(selectionFrame)
self.orbitalSelection.itemSelectionChanged.connect(
self.selectBoundOrbital)
norb = len(self.orbe)
self.orbital_dict = {}
for o in range(0, norb):
name = orbital_names[o]
self.orbital_dict[name] = o
item = QtGui.QListWidgetItem(name, self.orbitalSelection)
if o == initially_selected:
selected_orbital_item = item
selectionLayout.addWidget(self.orbitalSelection)
### VIEWS
center = QtGui.QWidget()
mainLayout.addWidget(center)
centerLayout = QtGui.QGridLayout(center)
#
boundFrame = QtGui.QFrame()
centerLayout.addWidget(boundFrame, 1, 1)
boundLayout = QtGui.QVBoxLayout(boundFrame)
# "Bound Orbital"
label = QtGui.QLabel(boundFrame)
label.setText("Bound Orbital")
boundLayout.addWidget(label)
#
self.boundOrbitalViewer = QCubeViewerWidget(boundFrame)
boundLayout.addWidget(self.boundOrbitalViewer)
# continuum orbital
continuumFrame = QtGui.QFrame()
centerLayout.addWidget(continuumFrame, 1, 2)
continuumLayout = QtGui.QVBoxLayout(continuumFrame)
# "Dipole-Prepared Continuum Orbital"
label = QtGui.QLabel(continuumFrame)
label.setText("Dipole-Prepared Continuum Orbital")
continuumLayout.addWidget(label)
self.continuumOrbitalViewer = QCubeViewerWidget(continuumFrame)
continuumLayout.addWidget(self.continuumOrbitalViewer)
self.efield_objects = []
self.efield_actors = []
self.selected = None
# picker
self.picker = self.continuumOrbitalViewer.visualization.scene.mayavi_scene.on_mouse_pick(
self.picker_callback)
self.picker.tolerance = 0.01
# PHOTO KINETIC ENERGY
sliderFrame = QtGui.QFrame(continuumFrame)
continuumLayout.addWidget(sliderFrame)
sliderLayout = QtGui.QHBoxLayout(sliderFrame)
# label
self.pke_label = QtGui.QLabel()
self.pke_label.setText("PKE: %6.4f eV" %
(self.photo_kinetic_energy * 27.211))
sliderLayout.addWidget(self.pke_label)
# Slider for changing the PKE
self.pke_slider = QtGui.QSlider(QtCore.Qt.Horizontal)
self.pke_slider.setMinimum(0)
self.pke_slider.setMaximum(len(slako_tables_scattering.energies) - 1)
self.pke_slider.setValue(0)
self.pke_slider.sliderReleased.connect(self.changePKE)
self.pke_slider.valueChanged.connect(self.searchPKE)
sliderLayout.addWidget(self.pke_slider)
#
# molecular frame photoangular distribution
mfpadFrame = QtGui.QFrame()
centerLayout.addWidget(mfpadFrame, 2, 1)
mfpadLayout = QtGui.QVBoxLayout(mfpadFrame)
mfpadLayout.addWidget(QtGui.QLabel("Molecular Frame PAD"))
mfpadTabs = QtGui.QTabWidget()
mfpadLayout.addWidget(mfpadTabs)
# 2D map
mfpadFrame2D = QtGui.QFrame()
mfpadTabs.addTab(mfpadFrame2D, "2D")
mfpadLayout2D = QtGui.QVBoxLayout(mfpadFrame2D)
self.MFPADfig2D = Figure()
self.MFPADCanvas2D = FigureCanvas(self.MFPADfig2D)
mfpadLayout2D.addWidget(self.MFPADCanvas2D)
self.MFPADCanvas2D.draw()
NavigationToolbar(self.MFPADCanvas2D, mfpadFrame2D, coordinates=True)
# 3D
mfpadFrame3D = QtGui.QFrame()
mfpadTabs.addTab(mfpadFrame3D, "3D")
mfpadLayout3D = QtGui.QVBoxLayout(mfpadFrame3D)
self.MFPADfig3D = Figure()
self.MFPADCanvas3D = FigureCanvas(self.MFPADfig3D)
mfpadLayout3D.addWidget(self.MFPADCanvas3D)
self.MFPADCanvas3D.draw()
NavigationToolbar(self.MFPADCanvas3D, mfpadFrame3D, coordinates=True)
# orientation averaged photoangular distribution
avgpadFrame = QtGui.QFrame()
centerLayout.addWidget(avgpadFrame, 2, 2)
avgpadLayout = QtGui.QVBoxLayout(avgpadFrame)
self.activate_average = QtGui.QCheckBox("Orientation Averaged PAD")
self.activate_average.setToolTip(
"Check this box to start averaging of the molecular frame PADs over all orientations. This can take a while."
)
self.activate_average.setCheckState(QtCore.Qt.Unchecked)
self.activate_average.stateChanged.connect(self.activateAveragedPAD)
avgpadLayout.addWidget(self.activate_average)
avgpadTabs = QtGui.QTabWidget()
avgpadLayout.addWidget(avgpadTabs)
# 1D map
avgpadFrame1D = QtGui.QFrame()
avgpadTabs.addTab(avgpadFrame1D, "1D")
avgpadLayout1D = QtGui.QVBoxLayout(avgpadFrame1D)
self.AvgPADfig1D = Figure()
self.AvgPADCanvas1D = FigureCanvas(self.AvgPADfig1D)
avgpadLayout1D.addWidget(self.AvgPADCanvas1D)
self.AvgPADCanvas1D.draw()
NavigationToolbar(self.AvgPADCanvas1D, avgpadFrame1D, coordinates=True)
# 2D map
avgpadFrame2D = QtGui.QFrame()
avgpadFrame2D.setToolTip(
"The averaged PAD should have no phi-dependence anymore. A phi-dependence is a sign of incomplete averaging."
)
avgpadTabs.addTab(avgpadFrame2D, "2D")
avgpadLayout2D = QtGui.QVBoxLayout(avgpadFrame2D)
self.AvgPADfig2D = Figure()
self.AvgPADCanvas2D = FigureCanvas(self.AvgPADfig2D)
avgpadLayout2D.addWidget(self.AvgPADCanvas2D)
self.AvgPADCanvas2D.draw()
NavigationToolbar(self.AvgPADCanvas2D, avgpadFrame2D, coordinates=True)
# Table
avgpadFrameTable = QtGui.QFrame()
avgpadTabs.addTab(avgpadFrameTable, "Table")
avgpadLayoutTable = QtGui.QVBoxLayout(avgpadFrameTable)
self.avgpadTable = QtGui.QTableWidget(0, 6)
self.avgpadTable.setToolTip(
"Activate averaging and move the PKE slider above to add a new row with beta values. After collecting betas for different energies you can save the table or plot a curve beta(PKE) for the selected orbital."
)
self.avgpadTable.setHorizontalHeaderLabels(
["PKE / eV", "sigma", "beta1", "beta2", "beta3", "beta4"])
avgpadLayoutTable.addWidget(self.avgpadTable)
# Buttons
buttonFrame = QtGui.QFrame()
avgpadLayoutTable.addWidget(buttonFrame)
buttonLayout = QtGui.QHBoxLayout(buttonFrame)
deleteButton = QtGui.QPushButton("Delete")
deleteButton.setToolTip("clear table")
deleteButton.clicked.connect(self.deletePADTable)
buttonLayout.addWidget(deleteButton)
buttonLayout.addSpacing(3)
scanButton = QtGui.QPushButton("Scan")
scanButton.setToolTip(
"fill table by scanning automatically through all PKE values")
scanButton.clicked.connect(self.scanPADTable)
buttonLayout.addWidget(scanButton)
saveButton = QtGui.QPushButton("Save")
saveButton.setToolTip("save table as a text file")
saveButton.clicked.connect(self.savePADTable)
buttonLayout.addWidget(saveButton)
plotButton = QtGui.QPushButton("Plot")
plotButton.setToolTip("plot beta2 column as a function of PKE")
plotButton.clicked.connect(self.plotPADTable)
buttonLayout.addWidget(plotButton)
"""
# DOCKS
self.setDockOptions(QtGui.QMainWindow.AnimatedDocks | QtGui.QMainWindow.AllowNestedDocks)
#
selectionDock = QtGui.QDockWidget(self)
selectionDock.setWidget(selectionFrame)
selectionDock.setFeatures(QtGui.QDockWidget.DockWidgetFloatable | QtGui.QDockWidget.DockWidgetMovable)
self.addDockWidget(QtCore.Qt.DockWidgetArea(1), selectionDock)
#
boundDock = QtGui.QDockWidget(self)
boundDock.setWidget(boundFrame)
boundDock.setFeatures(QtGui.QDockWidget.DockWidgetFloatable | QtGui.QDockWidget.DockWidgetMovable)
boundDock.setSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Preferred)
self.addDockWidget(QtCore.Qt.DockWidgetArea(2), boundDock)
#
continuumDock = QtGui.QDockWidget(self)
continuumDock.setWidget(continuumFrame)
continuumDock.setFeatures(QtGui.QDockWidget.DockWidgetFloatable | QtGui.QDockWidget.DockWidgetMovable)
continuumDock.setSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Preferred)
self.addDockWidget(QtCore.Qt.DockWidgetArea(2), continuumDock)
"""
self.setCentralWidget(main)
self.status_bar = QtGui.QStatusBar(main)
self.setStatusBar(self.status_bar)
self.default_message = "Click on the tip of the green arrow in the top right figure to change the orientation of the E-field"
self.statusBar().showMessage(self.default_message)
# Menu bar
menubar = self.menuBar()
exitAction = QtGui.QAction('&Exit', self)
exitAction.setShortcut('Ctrl+Q')
exitAction.setStatusTip('Exit program')
exitAction.triggered.connect(exit)
fileMenu = menubar.addMenu('&File')
fileMenu.addAction(exitAction)
settingsMenu = menubar.addMenu('&Edit')
settingsAction = QtGui.QAction('&Settings...', self)
settingsAction.setStatusTip('Edit settings')
settingsAction.triggered.connect(self.editSettings)
settingsMenu.addAction(settingsAction)
self.loadContinuum()
# select H**O
selected_orbital_item.setSelected(True)
def loadContinuum(self):
E = self.photo_kinetic_energy
k = np.sqrt(2 * E)
wavelength = 2.0 * np.pi / k
# determine the radius of the sphere where the angular distribution is calculated. It should be
# much larger than the extent of the molecule
(xmin, xmax), (ymin, ymax), (zmin, zmax) = Cube.get_bbox(self.atomlist,
dbuff=0.0)
dx, dy, dz = xmax - xmin, ymax - ymin, zmax - zmin
Rmax0 = self.settings.getOption("Averaging", "sphere radius Rmax")
Rmax = max([dx, dy, dz]) + Rmax0
Npts = max(int(Rmax), 1) * 50
print "Radius of sphere around molecule, Rmax = %s bohr" % Rmax
print "Points on radial grid, Npts = %d" % Npts
self.bs_free = AtomicScatteringBasisSet(self.atomlist,
E,
rmin=0.0,
rmax=Rmax + 2 * wavelength,
Npts=Npts)
self.SKT_bf, SKT_ff = load_slako_scattering(self.atomlist, E)
if self.settings.getOption("Continuum Orbital",
"Ionization transitions") == "inter-atomic":
inter_atomic = True
else:
inter_atomic = False
print "inter-atomic transitions: %s" % inter_atomic
self.Dipole = ScatteringDipoleMatrix(self.atomlist,
self.valorbs,
self.SKT_bf,
inter_atomic=inter_atomic).real
#
if self.activate_average.isChecked():
print "ORIENTATION AVERAGING"
npts_euler = self.settings.getOption("Averaging",
"Euler angle grid points")
npts_theta = self.settings.getOption("Averaging",
"polar angle grid points")
self.orientation_averaging = PAD.OrientationAveraging_small_memory(
self.Dipole,
self.bs_free,
Rmax,
E,
npts_euler=npts_euler,
npts_theta=npts_theta)
else:
print "NO AVERAGING"
def searchPKE(self):
self.photo_kinetic_energy = slako_tables_scattering.energies[
self.pke_slider.value()]
self.pke_label.setText("PKE: %6.4f eV" %
(self.photo_kinetic_energy * 27.211))
#self.pke_label.update()
@busy
def changePKE(self):
self.photo_kinetic_energy = slako_tables_scattering.energies[
self.pke_slider.value()]
self.pke_label.setText("PKE: %6.4f eV" %
(self.photo_kinetic_energy * 27.211))
self.loadContinuum()
self.plotContinuumOrbital()
self.plotMFPAD()
self.plotAveragedPAD()
@busy
def selectBoundOrbital(self):
self.plotBoundOrbital()
self.plotContinuumOrbital()
self.plotMFPAD()
self.deletePADTable()
self.plotAveragedPAD()
def plotBoundOrbital(self):
selected = self.orbitalSelection.selectedItems()
assert len(selected) == 1
selected_orbital = self.orbital_dict[str(selected[0].text())]
self.mo_bound = self.bound_orbs[:, selected_orbital]
# shift geometry so that the expectation value of the dipole operator vanishes
# dipole matrix
dipole = np.tensordot(self.mo_bound,
np.tensordot(self.tddftb.dftb2.D,
self.mo_bound,
axes=(1, 0)),
axes=(0, 0))
print "expectation value of dipole: %s" % dipole
# shift molecule R -> R - dipole
self.atomlist = MolCo.transform_molecule(
self.tddftb.dftb2.getGeometry(), (0, 0, 0), -dipole)
# load bound basis functions
self.bs_bound = AtomicBasisSet(self.atomlist)
# plot selected orbital
(xmin, xmax), (ymin, ymax), (zmin, zmax) = Cube.get_bbox(self.atomlist,
dbuff=5.0)
dx, dy, dz = xmax - xmin, ymax - ymin, zmax - zmin
ppb = 3.0 # Points per bohr
nx, ny, nz = int(dx * ppb), int(dy * ppb), int(dz * ppb)
x, y, z = np.mgrid[xmin:xmax:nx * 1j, ymin:ymax:ny * 1j,
zmin:zmax:nz * 1j]
grid = (x, y, z)
amplitude_bound = Cube.orbital_amplitude(grid,
self.bs_bound.bfs,
self.mo_bound,
cache=False)
bound_cube = CubeData()
bound_cube.data = amplitude_bound.real
bound_cube.grid = grid
bound_cube.atomlist = self.atomlist
self.boundOrbitalViewer.setCubes([bound_cube])
def plotContinuumOrbital(self):
dbuff = self.settings["Cube"]["extra space / bohr"]
ppb = self.settings["Cube"]["points per bohr"]
(xmin, xmax), (ymin, ymax), (zmin, zmax) = Cube.get_bbox(self.atomlist,
dbuff=dbuff)
dx, dy, dz = xmax - xmin, ymax - ymin, zmax - zmin
nx, ny, nz = int(dx * ppb), int(dy * ppb), int(dz * ppb)
x, y, z = np.mgrid[xmin:xmax:nx * 1j, ymin:ymax:ny * 1j,
zmin:zmax:nz * 1j]
grid = (x, y, z)
# plot continuum orbital
# projection of dipoles onto polarization direction
Dipole_projected = np.zeros(
(self.Dipole.shape[0], self.Dipole.shape[1]))
# normalize polarization
epol_unit = self.epol / np.sqrt(np.dot(self.epol, self.epol))
print "Polarization direction of E-field:"
print "E (normalized) = %s" % epol_unit
for xyz in [0, 1, 2]:
Dipole_projected += self.Dipole[:, :, xyz] * epol_unit[xyz]
#print "Dipole projected"
#print Dipole_projected
# unnormalized coefficients of dipole-prepared continuum orbitals
self.mo_free = np.dot(self.mo_bound, Dipole_projected)
nrm2 = np.dot(self.mo_free.conjugate(), self.mo_free)
#print "nrm2 = %s" % nrm2
# normalized coefficients
self.mo_free /= np.sqrt(nrm2)
amplitude_continuum = Cube.orbital_amplitude(grid,
self.bs_free.bfs,
self.mo_free,
cache=False)
continuum_cube = CubeData()
continuum_cube.data = amplitude_continuum.real
continuum_cube.grid = grid
continuum_cube.atomlist = self.atomlist
self.continuumOrbitalViewer.setCubes([continuum_cube])
# plot E-field
for o in self.efield_objects:
o.remove()
mlab = self.continuumOrbitalViewer.visualization.scene.mlab
# self.efield_arrow = mlab.quiver3d(0,0,0, self.epol[0], self.epol[1], self.epol[2],
self.efield_arrow = mlab.quiver3d(0,
0,
0,
float(self.epol[0]),
float(self.epol[1]),
float(self.epol[2]),
color=(0.0, 1.0, 0.0),
scale_factor=1.0,
mode='arrow',
resolution=20,
figure=self.continuumOrbitalViewer.
visualization.scene.mayavi_scene)
self.efield_text = mlab.text(self.epol[0],
self.epol[1],
"E-field",
z=self.epol[2],
figure=self.continuumOrbitalViewer.
visualization.scene.mayavi_scene)
self.efield_text.actor.set(text_scale_mode='none',
width=0.05,
height=0.1)
self.efield_text.property.set(justification='centered',
vertical_justification='centered')
self.efield_head = mlab.points3d([self.epol[0]], [self.epol[1]],
[self.epol[2]],
scale_factor=0.5,
mode='cube',
resolution=20,
color=(0.0, 1.0, 0.0),
figure=self.continuumOrbitalViewer.
visualization.scene.mayavi_scene)
self.efield_head.glyph.glyph_source.glyph_source.center = [0, 0, 0]
self.efield_outline = mlab.outline(line_width=3,
figure=self.continuumOrbitalViewer.
visualization.scene.mayavi_scene)
self.efield_outline.outline_mode = 'cornered'
w = 0.1
self.efield_outline.bounds = (self.epol[0] - w, self.epol[0] + w,
self.epol[1] - w, self.epol[1] + w,
self.epol[2] - w, self.epol[2] + w)
self.efield_objects = [
self.efield_arrow, self.efield_text, self.efield_head,
self.efield_outline
]
self.efield_actors = [self.efield_head.actor.actors]
def picker_callback(self, picker):
for actors in self.efield_actors:
if picker.actor in actors:
mlab = self.continuumOrbitalViewer.visualization.scene.mlab
self.selected = "arrow"
w = 1.0
self.efield_outline.bounds = (self.epol[0] - w, self.epol[0] +
w, self.epol[1] - w,
self.epol[1] + w, self.epol[2] -
w, self.epol[2] + w)
break
else:
#
if self.selected != None:
w = 0.1
self.efield_outline.bounds = (self.epol[0] - w, self.epol[0] +
w, self.epol[1] - w,
self.epol[1] + w, self.epol[2] -
w, self.epol[2] + w)
self.epol = np.array(picker.pick_position)
self.plotContinuumOrbital()
self.plotMFPAD()
self.selected = None
def plotMFPAD(self):
Rmax = 80.0
npts = 30
E = self.photo_kinetic_energy
k = np.sqrt(2 * E)
wavelength = 2.0 * np.pi / k
# spherical grid
rs, thetas, phis = np.mgrid[Rmax:(Rmax + wavelength):30j,
0.0:np.pi:npts * 1j,
0.0:2 * np.pi:npts * 1j]
# transformed into cartesian coordinates
xs = rs * np.sin(thetas) * np.cos(phis)
ys = rs * np.sin(thetas) * np.sin(phis)
zs = rs * np.cos(thetas)
grid = (xs, ys, zs)
amplitude_continuum = Cube.orbital_amplitude(grid,
self.bs_free.bfs,
self.mo_free,
cache=False)
# integrate continuum orbital along radial-direction for 1 wavelength
wfn2 = abs(amplitude_continuum)**2
#
dr = wavelength / 30.0
wfn2_angular = np.sum(wfn2 * dr, axis=0)
# SPHERICAL PLOT
self.MFPADfig3D.clf()
xs = wfn2_angular * np.sin(thetas[0, :, :]) * np.cos(phis[0, :, :])
ys = wfn2_angular * np.sin(thetas[0, :, :]) * np.sin(phis[0, :, :])
zs = wfn2_angular * np.cos(thetas[0, :, :])
ax = self.MFPADfig3D.add_subplot(111, projection='3d')
rmax = wfn2_angular.max() * 1.5
ax.set_xlim((-rmax, rmax))
ax.set_ylim((-rmax, rmax))
ax.set_zlim((-rmax, rmax))
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_zlabel("z")
# draw efield
arrow_vec = wfn2_angular.max() * 1.2 * self.epol / la.norm(self.epol)
arrow = Arrow3D([0.0, arrow_vec[0]], [0.0, arrow_vec[1]],
[0.0, arrow_vec[2]],
color=(0.0, 1.0, 0.0),
mutation_scale=20,
lw=2,
arrowstyle="-|>")
ax.add_artist(arrow)
ax.text(arrow_vec[0],
arrow_vec[1],
arrow_vec[2],
"E-field",
color=(0.0, 1.0, 0.0))
ax.plot_surface(xs, ys, zs, rstride=1, cstride=1)
ax.scatter(xs, ys, zs, color="k", s=20)
ax.get_xaxis().set_ticks([])
ax.get_yaxis().set_ticks([])
ax.w_zaxis.set_ticks([])
self.MFPADCanvas3D.draw()
# 2D PLOT
self.MFPADfig2D.clf()
ax = self.MFPADfig2D.add_subplot(111)
image = ax.imshow(np.fliplr(wfn2_angular.transpose()),
extent=[0.0, np.pi, 0.0, 2 * np.pi],
aspect=0.5,
origin='lower')
ax.set_xlim((0.0, np.pi))
ax.set_ylim((0.0, 2 * np.pi))
ax.set_xlabel("$\\theta$")
ax.set_ylabel("$\phi$")
self.MFPADfig2D.colorbar(image)
# show piercing points of E-field vector
# ... coming out of the plane
r = la.norm(self.epol)
th_efield = np.arccos(self.epol[2] / r)
phi_efield = np.arctan2(self.epol[1], self.epol[0]) + np.pi
print "th, phi = %s %s" % (th_efield, phi_efield)
ax.plot([th_efield], [phi_efield],
"o",
markersize=10,
color=(0.0, 1.0, 0.0))
ax.text(th_efield,
phi_efield,
"E-field",
color=(0.0, 1.0, 0.0),
ha="center",
va="top")
# ... going into the plane
th_efield = np.arccos(-self.epol[2] / r)
phi_efield = np.arctan2(-self.epol[1], -self.epol[0]) + np.pi
print "- th, phi = %s %s" % (th_efield, phi_efield)
ax.plot([th_efield], [phi_efield],
"x",
markersize=10,
color=(0.0, 1.0, 0.0))
self.MFPADCanvas2D.draw()
@busy
def activateAveragedPAD(self, s):
print "s = %s" % s
self.loadContinuum()
self.plotAveragedPAD()
@busy
def plotAveragedPAD(self):
if self.activate_average.isChecked() == False:
for fig in [self.AvgPADfig1D, self.AvgPADfig2D]:
fig.clf()
ax = fig.add_subplot(111)
ax.set_xlim((0.0, 1.0))
ax.set_ylim((0.0, 1.0))
ax.text(0.2, 0.6, "click checkbox to", fontsize=20)
ax.text(0.2, 0.3, "activate averaging", fontsize=20)
#self.AvgPADfig1D.draw()
else:
pad, betas = self.orientation_averaging.averaged_pad(self.mo_bound)
# 1D plot
# cut along any phi
self.AvgPADfig1D.clf()
ax1d = self.AvgPADfig1D.add_subplot(111, projection='polar')
nx, ny = pad.shape
thetas = np.linspace(0.0, np.pi, nx)
for i in range(0, ny):
ax1d.plot(thetas, pad[:, i], color="black")
ax1d.plot(thetas + np.pi, pad[::-1, i], color="black")
# plot PAD = sigma/4pi * (1 + beta2 * P2(cos(theta))) in read
pad2 = betas[0] / (4.0 * np.pi) * (1.0 + betas[2] * 0.5 *
(3 * np.cos(thetas)**2 - 1.0))
print "max(pad) / max(pad2) = %s" % (pad.max() / pad2.max())
ax1d.plot(thetas, pad2, color="red", ls="-.")
ax1d.plot(thetas + np.pi, pad2[::-1], color="red", ls="-.")
self.AvgPADCanvas1D.draw()
# 2D plot
self.AvgPADfig2D.clf()
ax2d = self.AvgPADfig2D.add_subplot(111)
image = ax2d.imshow(np.fliplr(pad.transpose()),
extent=[0.0, np.pi, 0.0, 2 * np.pi],
aspect=0.5,
origin='lower')
ax2d.set_xlim((0.0, np.pi))
ax2d.set_ylim((0.0, 2 * np.pi))
ax2d.set_xlabel("$\\theta$")
ax2d.set_ylabel("$\phi$")
self.AvgPADfig2D.colorbar(image)
self.AvgPADCanvas2D.draw()
# Table
n = self.avgpadTable.rowCount()
self.avgpadTable.insertRow(n)
self.avgpadTable.setItem(
n, 0,
QtGui.QTableWidgetItem("%6.4f" %
(self.photo_kinetic_energy * 27.211)))
for i, b in enumerate(betas):
if i == 0:
# sigma
self.avgpadTable.setItem(
n, i + 1, QtGui.QTableWidgetItem("%e" % betas[i]))
else:
self.avgpadTable.setItem(
n, i + 1, QtGui.QTableWidgetItem("%6.4f" % betas[i]))
def deletePADTable(self):
n = self.avgpadTable.rowCount()
for i in range(0, n):
self.avgpadTable.removeRow(0)
def scanPADTable(self):
if self.activate_average.isChecked() == False:
self.statusBar().showMessage(
"You have to activate averaging first before performing a scan!"
)
return
self.deletePADTable()
# scan through all PKE's and fill table
print "SCAN"
nskip = len(slako_tables_scattering.energies) / int(
self.settings.getOption("Scan", "nr. points"))
nskip = max(1, nskip)
print "nskip = %s" % nskip
for i, pke in enumerate(slako_tables_scattering.energies):
if i % nskip != 0:
continue
print "*** PKE = %s Hartree ***" % pke
self.pke_slider.setValue(i)
self.changePKE()
def getPADTable(self):
m, n = self.avgpadTable.rowCount(), self.avgpadTable.columnCount()
pad_data = np.zeros((m, n))
for i in range(0, m):
for j in range(0, n):
item = self.avgpadTable.item(i, j)
if item is not None:
pad_data[i, j] = float(item.text())
return pad_data
def savePADTable(self):
data_file = QtGui.QFileDialog.getSaveFileName(self, 'Save Table', '',
'*')[0]
pad_data = self.getPADTable()
if str(data_file) != "":
fh = open(data_file, "w")
print >> fh, "# PKE/eV sigma beta1 beta2 beta3 beta4"
np.savetxt(fh, pad_data)
fh.close()
print "Wrote table with betas to %s" % data_file
def plotPADTable(self):
pad_data = self.getPADTable()
self.plot_window = FigurePopup(pad_data[:, 0], pad_data[:, 1],
pad_data[:, 3])
def editSettings(self):
self.settings_window = SettingsPopup(self.settings)