def generate(argv=None):
from optparse import OptionParser
parser = OptionParser(usage='%prog [options] element',
version='%prog 0.1')
parser.add_option('-f', '--xc-functional', type='string', default='LDA',
help='Exchange-Correlation functional ' +
'(default value LDA)',
metavar='<XC>')
parser.add_option('-P', '--projectors',
help='Projector functions - use comma-separated - ' +
'nl values, where n can be pricipal quantum number ' +
'(integer) or energy (floating point number). ' +
'Example: 2s,0.5s,2p,0.5p,0.0d.')
parser.add_option('-r', '--radius',
help='1.2 or 1.2,1.1,1.1')
parser.add_option('-0', '--zero-potential',
metavar='type,nderivs,radius,e0',
help='Parameters for zero potential.')
parser.add_option('-c', '--pseudo-core-density-radius', type=float,
metavar='radius',
help='Radius for pseudizing core density.')
parser.add_option('-z', '--pseudize',
metavar='type,nderivs',
help='Parameters for pseudizing wave functions.')
parser.add_option('-p', '--plot', action='store_true')
parser.add_option('-l', '--logarithmic-derivatives',
metavar='spdfg,e1:e2:de,radius',
help='Plot logarithmic derivatives. ' +
'Example: -l spdf,-1:1:0.05,1.3. ' +
'Energy range and/or radius can be left out.')
parser.add_option('-w', '--write', action='store_true')
parser.add_option('-s', '--scalar-relativistic', action='store_true')
parser.add_option('--no-check', action='store_true')
parser.add_option('-t', '--tag', type='string')
parser.add_option('-a', '--alpha', type=float)
opt, args = parser.parse_args(argv)
if len(args) == 0:
symbols = [symbol for symbol in chemical_symbols
if symbol in parameters]
elif len(args) == 1 and '-' in args[0]:
Z1, Z2 = args[0].split('-')
Z1 = str2z(Z1)
if Z2:
Z2 = str2z(Z2)
else:
Z2 = 86
symbols = range(Z1, Z2 + 1)
else:
symbols = args
for symbol in symbols:
Z = str2z(symbol)
symbol = chemical_symbols[Z]
kwargs = get_parameters(symbol, opt)
print kwargs
gen = _generate(**kwargs)
if opt.no_check:
ok = True
else:
ok = gen.check_all()
#gen.test_convergence()
if opt.write or opt.tag:
gen.make_paw_setup(opt.tag).write_xml()
if opt.logarithmic_derivatives or opt.plot:
import matplotlib.pyplot as plt
if opt.logarithmic_derivatives:
r = 1.1 * gen.rcmax
emin = min(min(wave.e_n) for wave in gen.waves_l) - 0.8
emax = max(max(wave.e_n) for wave in gen.waves_l) + 0.8
lvalues, energies, r = parse_ld_str(opt.logarithmic_derivatives,
(emin, emax, 0.05), r)
ldmax = 0.0
for l in lvalues:
ld = gen.aea.logarithmic_derivative(l, energies, r)
plt.plot(energies, ld, colors[l], label='spdfg'[l])
ld = gen.logarithmic_derivative(l, energies, r)
plt.plot(energies, ld, '--' + colors[l])
# Fixed points:
if l < len(gen.waves_l):
efix = gen.waves_l[l].e_n
ldfix = gen.logarithmic_derivative(l, efix, r)
plt.plot(efix, ldfix, 'x' + colors[l])
ldmax = max(ldmax, max(abs(ld) for ld in ldfix))
if l == gen.l0:
efix = [gen.e0]
ldfix = gen.logarithmic_derivative(l, efix, r)
plt.plot(efix, ldfix, 'x' + colors[l])
ldmax = max(ldmax, max(abs(ld) for ld in ldfix))
if ldmax != 0.0:
plt.axis(ymin=-3 * ldmax, ymax=3 * ldmax)
plt.xlabel('energy [Ha]')
plt.ylabel(r'$d\phi_{\ell\epsilon}(r)/dr/\phi_{\ell\epsilon}' +
r'(r)|_{r=r_c}$')
plt.legend(loc='best')
if opt.plot:
gen.plot()
try:
plt.show()
except KeyboardInterrupt:
pass
return gen
def main(argv=None):
from optparse import OptionParser
parser = OptionParser(usage='gwap dataset [options] element')
add = parser.add_option
add('-f',
'--xc-functional',
type='string',
default='LDA',
help='Exchange-Correlation functional (default value LDA)',
metavar='<XC>')
add('-C',
'--configuration',
help='e.g. for Li: "[(1, 0, 2, -1.878564), (2, 0, 1, -0.10554),'
' (2, 1, 0, 0.0)]"')
add('-P',
'--projectors',
help='Projector functions - use comma-separated - ' +
'nl values, where n can be principal quantum number ' +
'(integer) or energy (floating point number). ' +
'Example: 2s,0.5s,2p,0.5p,0.0d.')
add('-r', '--radius', help='1.2 or 1.2,1.1,1.1')
add('-0',
'--zero-potential',
metavar='nderivs,radius',
help='Parameters for zero potential.')
add('-c',
'--pseudo-core-density-radius',
type=float,
metavar='radius',
help='Radius for pseudizing core density.')
add('-z',
'--pseudize',
metavar='type,nderivs',
help='Parameters for pseudizing wave functions.')
add('-p', '--plot', action='store_true')
add('-l',
'--logarithmic-derivatives',
metavar='spdfg,e1:e2:de,radius',
help='Plot logarithmic derivatives. ' +
'Example: -l spdf,-1:1:0.05,1.3. ' +
'Energy range and/or radius can be left out.')
add('-w', '--write', action='store_true')
add('-s', '--scalar-relativistic', action='store_true')
add('-n', '--no-check', action='store_true')
add('-t', '--tag', type='string')
add('-a', '--alpha', type=float)
add('-b', '--create-basis-set', action='store_true')
add('--nlcc',
action='store_true',
help='Use NLCC-style pseudo core density (for vdW-DF functionals).')
add('--core-hole')
add('-e', '--electrons', type=int)
add('-o', '--output')
opt, symbols = parser.parse_args(argv)
for symbol in symbols:
kwargs = get_parameters(symbol, opt)
gen = _generate(**kwargs)
if not opt.no_check:
if not gen.check_all():
raise DatasetGenerationError
if opt.create_basis_set or opt.write:
basis = gen.create_basis_set()
if opt.create_basis_set:
basis.write_xml()
if opt.write:
setup = gen.make_paw_setup(opt.tag)
parameters = []
for key, value in kwargs.items():
if value is not None:
parameters.append('{0}={1!r}'.format(key, value))
setup.generatordata = ',\n '.join(parameters)
setup.write_xml()
if opt.logarithmic_derivatives or opt.plot:
if opt.plot:
import matplotlib.pyplot as plt
if opt.logarithmic_derivatives:
r = 1.1 * gen.rcmax
emin = min(min(wave.e_n) for wave in gen.waves_l) - 0.8
emax = max(max(wave.e_n) for wave in gen.waves_l) + 0.8
lvalues, energies, r = parse_ld_str(
opt.logarithmic_derivatives, (emin, emax, 0.05), r)
emin = energies[0]
de = energies[1] - emin
error = 0.0
for l in lvalues:
efix = []
# Fixed points:
if l < len(gen.waves_l):
efix.extend(gen.waves_l[l].e_n)
if l == gen.l0:
efix.append(0.0)
ld1 = gen.aea.logarithmic_derivative(l, energies, r)
ld2 = gen.logarithmic_derivative(l, energies, r)
for e in efix:
i = int((e - emin) / de)
if 0 <= i < len(energies):
ld1 -= round(ld1[i] - ld2[i])
if opt.plot:
ldfix = ld1[i]
plt.plot([energies[i]], [ldfix],
'x' + colors[l])
if opt.plot:
plt.plot(energies, ld1, colors[l], label='spdfg'[l])
plt.plot(energies, ld2, '--' + colors[l])
error = abs(ld1 - ld2).sum() * de
print('Logarithmic derivative error:', l, error)
if opt.plot:
plt.xlabel('energy [Ha]')
plt.ylabel(r'$\arctan(d\log\phi_{\ell\epsilon}(r)/dr)/\pi'
r'|_{r=r_c}$')
plt.legend(loc='best')
if opt.plot:
gen.plot()
if opt.create_basis_set:
gen.basis.generatordata = '' # we already printed this
BasisPlotter(show=True).plot(gen.basis)
if opt.plot:
try:
plt.show()
except KeyboardInterrupt:
pass
world.barrier()
return gen
def main(argv=None):
from optparse import OptionParser
parser = OptionParser(usage='gwap dataset [options] element')
add = parser.add_option
add('-f', '--xc-functional', type='string', default='LDA',
help='Exchange-Correlation functional (default value LDA)',
metavar='<XC>')
add('-C', '--configuration',
help='e.g. for Li: "[(1, 0, 2, -1.878564), (2, 0, 1, -0.10554),'
'(2, 1, 0, 0.0)]"')
add('-P', '--projectors',
help='Projector functions - use comma-separated - ' +
'nl values, where n can be pricipal quantum number ' +
'(integer) or energy (floating point number). ' +
'Example: 2s,0.5s,2p,0.5p,0.0d.')
add('-r', '--radius',
help='1.2 or 1.2,1.1,1.1')
add('-0', '--zero-potential',
metavar='nderivs,radius',
help='Parameters for zero potential.')
add('-c', '--pseudo-core-density-radius', type=float,
metavar='radius',
help='Radius for pseudizing core density.')
add('-z', '--pseudize',
metavar='type,nderivs',
help='Parameters for pseudizing wave functions.')
add('-p', '--plot', action='store_true')
add('-l', '--logarithmic-derivatives',
metavar='spdfg,e1:e2:de,radius',
help='Plot logarithmic derivatives. ' +
'Example: -l spdf,-1:1:0.05,1.3. ' +
'Energy range and/or radius can be left out.')
add('-w', '--write', action='store_true')
add('-s', '--scalar-relativistic', action='store_true')
add('--no-check', action='store_true')
add('-t', '--tag', type='string')
add('-a', '--alpha', type=float)
add('-b', '--create-basis-set', action='store_true')
add('--core-hole')
add('-e', '--electrons', type=int)
add('-o', '--output')
opt, symbols = parser.parse_args(argv)
for symbol in symbols:
kwargs = get_parameters(symbol, opt)
gen = _generate(**kwargs)
if not opt.no_check:
gen.check_all()
if opt.create_basis_set or opt.write:
basis = None # gen.create_basis_set()
if opt.create_basis_set:
basis.write_xml()
if opt.write:
gen.make_paw_setup(opt.tag).write_xml()
if opt.logarithmic_derivatives or opt.plot:
import matplotlib.pyplot as plt
if opt.logarithmic_derivatives:
r = 1.1 * gen.rcmax
emin = min(min(wave.e_n) for wave in gen.waves_l) - 0.8
emax = max(max(wave.e_n) for wave in gen.waves_l) + 0.8
lvalues, energies, r = parse_ld_str(
opt.logarithmic_derivatives, (emin, emax, 0.05), r)
ldmax = 0.0
for l in lvalues:
ld = gen.aea.logarithmic_derivative(l, energies, r)
plt.plot(energies, ld, colors[l], label='spdfg'[l])
ld = gen.logarithmic_derivative(l, energies, r)
plt.plot(energies, ld, '--' + colors[l])
# Fixed points:
if l < len(gen.waves_l):
efix = gen.waves_l[l].e_n
ldfix = gen.logarithmic_derivative(l, efix, r)
plt.plot(efix, ldfix, 'x' + colors[l])
ldmax = max(ldmax, max(abs(ld) for ld in ldfix))
if l == gen.l0:
efix = [0.0]
ldfix = gen.logarithmic_derivative(l, efix, r)
plt.plot(efix, ldfix, 'x' + colors[l])
ldmax = max(ldmax, max(abs(ld) for ld in ldfix))
if ldmax != 0.0:
plt.axis(ymin=-3 * ldmax, ymax=3 * ldmax)
plt.xlabel('energy [Ha]')
plt.ylabel(r'$d\phi_{\ell\epsilon}(r)/dr/\phi_{\ell\epsilon}' +
r'(r)|_{r=r_c}$')
plt.legend(loc='best')
if opt.plot:
gen.plot()
if opt.create_basis_set:
gen.basis.generatordata = '' # we already printed this
BasisPlotter(show=True).plot(gen.basis)
try:
plt.show()
except KeyboardInterrupt:
pass
world.barrier()
return gen
def generate(argv=None):
from optparse import OptionParser
parser = OptionParser(usage="%prog [options] element", version="%prog 0.1")
parser.add_option(
"-f",
"--xc-functional",
type="string",
default="LDA",
help="Exchange-Correlation functional " + "(default value LDA)",
metavar="<XC>",
)
parser.add_option(
"-P",
"--projectors",
help="Projector functions - use comma-separated - "
+ "nl values, where n can be pricipal quantum number "
+ "(integer) or energy (floating point number). "
+ "Example: 2s,0.5s,2p,0.5p,0.0d.",
)
parser.add_option("-r", "--radius", help="1.2 or 1.2,1.1,1.1")
parser.add_option("-0", "--zero-potential", metavar="type,nderivs,radius,e0", help="Parameters for zero potential.")
parser.add_option(
"-c", "--pseudo-core-density-radius", type=float, metavar="radius", help="Radius for pseudizing core density."
)
parser.add_option("-z", "--pseudize", metavar="type,nderivs", help="Parameters for pseudizing wave functions.")
parser.add_option("-p", "--plot", action="store_true")
parser.add_option(
"-l",
"--logarithmic-derivatives",
metavar="spdfg,e1:e2:de,radius",
help="Plot logarithmic derivatives. "
+ "Example: -l spdf,-1:1:0.05,1.3. "
+ "Energy range and/or radius can be left out.",
)
parser.add_option("-w", "--write", action="store_true")
parser.add_option("-s", "--scalar-relativistic", action="store_true")
parser.add_option("--no-check", action="store_true")
parser.add_option("-t", "--tag", type="string")
parser.add_option("-a", "--alpha", type=float)
opt, args = parser.parse_args(argv)
if len(args) == 0:
symbols = [symbol for symbol in chemical_symbols if symbol in parameters]
elif len(args) == 1 and "-" in args[0]:
Z1, Z2 = args[0].split("-")
Z1 = str2z(Z1)
if Z2:
Z2 = str2z(Z2)
else:
Z2 = 86
symbols = range(Z1, Z2 + 1)
else:
symbols = args
for symbol in symbols:
Z = str2z(symbol)
symbol = chemical_symbols[Z]
kwargs = get_parameters(symbol, opt)
print kwargs
gen = _generate(**kwargs)
if opt.no_check:
ok = True
else:
ok = gen.check_all()
# gen.test_convergence()
if opt.write or opt.tag:
gen.make_paw_setup(opt.tag).write_xml()
if opt.logarithmic_derivatives or opt.plot:
import matplotlib.pyplot as plt
if opt.logarithmic_derivatives:
r = 1.1 * gen.rcmax
emin = min(min(wave.e_n) for wave in gen.waves_l) - 0.8
emax = max(max(wave.e_n) for wave in gen.waves_l) + 0.8
lvalues, energies, r = parse_ld_str(opt.logarithmic_derivatives, (emin, emax, 0.05), r)
ldmax = 0.0
for l in lvalues:
ld = gen.aea.logarithmic_derivative(l, energies, r)
plt.plot(energies, ld, colors[l], label="spdfg"[l])
ld = gen.logarithmic_derivative(l, energies, r)
plt.plot(energies, ld, "--" + colors[l])
# Fixed points:
if l < len(gen.waves_l):
efix = gen.waves_l[l].e_n
ldfix = gen.logarithmic_derivative(l, efix, r)
plt.plot(efix, ldfix, "x" + colors[l])
ldmax = max(ldmax, max(abs(ld) for ld in ldfix))
if l == gen.l0:
efix = [gen.e0]
ldfix = gen.logarithmic_derivative(l, efix, r)
plt.plot(efix, ldfix, "x" + colors[l])
ldmax = max(ldmax, max(abs(ld) for ld in ldfix))
if ldmax != 0.0:
plt.axis(ymin=-3 * ldmax, ymax=3 * ldmax)
plt.xlabel("energy [Ha]")
plt.ylabel(r"$d\phi_{\ell\epsilon}(r)/dr/\phi_{\ell\epsilon}" + r"(r)|_{r=r_c}$")
plt.legend(loc="best")
if opt.plot:
gen.plot()
try:
plt.show()
except KeyboardInterrupt:
pass
return gen
def main(argv=None):
from optparse import OptionParser
parser = OptionParser(usage='gwap dataset [options] element')
add = parser.add_option
add('-f',
'--xc-functional',
type='string',
default='LDA',
help='Exchange-Correlation functional (default value LDA)',
metavar='<XC>')
add('-C',
'--configuration',
help='e.g. for Li: "[(1, 0, 2, -1.878564), (2, 0, 1, -0.10554),'
'(2, 1, 0, 0.0)]"')
add('-P',
'--projectors',
help='Projector functions - use comma-separated - ' +
'nl values, where n can be pricipal quantum number ' +
'(integer) or energy (floating point number). ' +
'Example: 2s,0.5s,2p,0.5p,0.0d.')
add('-r', '--radius', help='1.2 or 1.2,1.1,1.1')
add('-0',
'--zero-potential',
metavar='nderivs,radius',
help='Parameters for zero potential.')
add('-c',
'--pseudo-core-density-radius',
type=float,
metavar='radius',
help='Radius for pseudizing core density.')
add('-z',
'--pseudize',
metavar='type,nderivs',
help='Parameters for pseudizing wave functions.')
add('-p', '--plot', action='store_true')
add('-l',
'--logarithmic-derivatives',
metavar='spdfg,e1:e2:de,radius',
help='Plot logarithmic derivatives. ' +
'Example: -l spdf,-1:1:0.05,1.3. ' +
'Energy range and/or radius can be left out.')
add('-w', '--write', action='store_true')
add('-s', '--scalar-relativistic', action='store_true')
add('--no-check', action='store_true')
add('-t', '--tag', type='string')
add('-a', '--alpha', type=float)
add('-b', '--create-basis-set', action='store_true')
add('--core-hole')
add('-e', '--electrons', type=int)
add('-o', '--output')
opt, symbols = parser.parse_args(argv)
for symbol in symbols:
kwargs = get_parameters(symbol, opt)
gen = _generate(**kwargs)
if not opt.no_check:
gen.check_all()
if opt.create_basis_set or opt.write:
basis = None # gen.create_basis_set()
if opt.create_basis_set:
basis.write_xml()
if opt.write:
gen.make_paw_setup(opt.tag).write_xml()
if opt.logarithmic_derivatives or opt.plot:
import matplotlib.pyplot as plt
if opt.logarithmic_derivatives:
r = 1.1 * gen.rcmax
emin = min(min(wave.e_n) for wave in gen.waves_l) - 0.8
emax = max(max(wave.e_n) for wave in gen.waves_l) + 0.8
lvalues, energies, r = parse_ld_str(
opt.logarithmic_derivatives, (emin, emax, 0.05), r)
ldmax = 0.0
for l in lvalues:
ld = gen.aea.logarithmic_derivative(l, energies, r)
plt.plot(energies, ld, colors[l], label='spdfg'[l])
ld = gen.logarithmic_derivative(l, energies, r)
plt.plot(energies, ld, '--' + colors[l])
# Fixed points:
if l < len(gen.waves_l):
efix = gen.waves_l[l].e_n
ldfix = gen.logarithmic_derivative(l, efix, r)
plt.plot(efix, ldfix, 'x' + colors[l])
ldmax = max(ldmax, max(abs(ld) for ld in ldfix))
if l == gen.l0:
efix = [0.0]
ldfix = gen.logarithmic_derivative(l, efix, r)
plt.plot(efix, ldfix, 'x' + colors[l])
ldmax = max(ldmax, max(abs(ld) for ld in ldfix))
if ldmax != 0.0:
plt.axis(ymin=-3 * ldmax, ymax=3 * ldmax)
plt.xlabel('energy [Ha]')
plt.ylabel(r'$d\phi_{\ell\epsilon}(r)/dr/\phi_{\ell\epsilon}' +
r'(r)|_{r=r_c}$')
plt.legend(loc='best')
if opt.plot:
gen.plot()
if opt.create_basis_set:
gen.basis.generatordata = '' # we already printed this
BasisPlotter(show=True).plot(gen.basis)
try:
plt.show()
except KeyboardInterrupt:
pass
world.barrier()
return gen
