def init_ao_log_ion(self, sp2ion, **kw):
"""
Reads data from a previous SIESTA calculation,
interpolates the orbitals on a single log mesh.
"""
from pyscf.nao.m_log_interp import log_interp_c
from pyscf.nao.m_siesta_ion_interp import siesta_ion_interp
from pyscf.nao.m_siesta_ion_add_sp2 import _siesta_ion_add_sp2
from pyscf.nao.m_spline_diff2 import spline_diff2
from pyscf.nao.m_spline_interp import spline_interp
import numpy as np
self.init_log_mesh_ion(sp2ion, **kw)
#print(__name__, self.nr)
#print(__name__, self.rr)
#print(__name__, self.rmax)
#print(__name__, self.rmin)
#print(__name__, self.kmax)
self.interp_rr,self.interp_pp = log_interp_c(self.rr), log_interp_c(self.pp)
_siesta_ion_add_sp2(self, sp2ion) # adds the fields for counting, .nspecies etc.
self.jmx = max([mu2j.max() for mu2j in self.sp_mu2j])
self.sp2norbs = np.array([mu2s[self.sp2nmult[sp]] for sp,mu2s in enumerate(self.sp_mu2s)], dtype='int64')
self.sp2ion = sp2ion
rr = self.rr
nr = len(rr)
#print(__name__, 'self.jmx', self.jmx)
#print(__name__, 'self.sp2norbs', self.sp2norbs)
#print(__name__, 'self.sp2norbs', dir(self))
#print(__name__, 'self.sp_mu2j', self.sp_mu2j)
#print(__name__, 'self.sp_mu2rcut', self.sp_mu2rcut)
#print(__name__, 'self.sp_mu2s', self.sp_mu2s)
self.psi_log = siesta_ion_interp(rr, sp2ion, 1)
self.psi_log_rl = siesta_ion_interp(rr, sp2ion, 0)
self.sp2vna = [] # Interpolate a Neutral-atom potential V_NA(r) for each specie
for ion in sp2ion:
vna = np.zeros(nr)
if ion["vna"] is not None:
h,dat = ion["vna"]["delta"], ion["vna"]["data"][0][:, 1]
yy_diff2 = spline_diff2(h, dat, 0.0, 1.0e301)
for ir,r in enumerate(rr):
vna[ir] = spline_interp(h, dat, yy_diff2, r)
self.sp2vna.append(vna*0.5) # given in Rydberg?
self.sp_mu2rcut = [ np.array(ion["paos"]["cutoff"]) for ion in sp2ion]
self.sp2rcut = np.array([np.amax(rcuts) for rcuts in self.sp_mu2rcut])
self.sp2charge = [int(ion['z']) for ion in self.sp2ion]
self.sp2valence = [int(ion['valence']) for ion in self.sp2ion]
#call sp2ion_to_psi_log(sv%sp2ion, sv%rr, sv%psi_log)
#call init_psi_log_rl(sv%psi_log, sv%rr, sv%uc%mu_sp2j, sv%uc%sp2nmult, sv%psi_log_rl)
#call sp2ion_to_core(sv%sp2ion, sv%rr, sv%core_log, sv%sp2has_core, sv%sp2rcut_core)
return self
def init_ao_log_ion(self, **kw):
"""
Reads data from a previous SIESTA calculation,
interpolates the Pseudo-Atomic Orbitals on a single log mesh.
"""
from pyscf.nao.m_log_interp import log_interp_c
from pyscf.nao.m_spline_diff2 import spline_diff2
from pyscf.nao.m_spline_interp import spline_interp
self.interp_rr,self.interp_pp = log_interp_c(self.rr), log_interp_c(self.pp)
sp2ion = self.sp2ion = kw['sp2ion']
fname = kw['fname'] if 'fname' in kw else 'paos'
if fname in sp2ion[0]:
self.siesta_ion_interp(sp2ion, fname=fname)
self.sp2vna = [None]*len(sp2ion) # Interpolate a Neutral-Atom potential V_NA(r) for each specie
self.sp2rcut_vna = np.zeros(len(sp2ion))
for isp, ion in enumerate(sp2ion):
if "vna" not in ion.keys(): continue
if ion["vna"] is None: continue
self.sp2rcut_vna[isp] = ion["vna"]["cutoff"]
h,dat = ion["vna"]["delta"][0], ion["vna"]["data"][0][:,1]
d2 = spline_diff2(h, dat, 0.0, 1.0e301)
self.sp2vna[isp] = np.array([0.5*spline_interp(h, dat, d2, r) for r in self.rr]) # given in Rydberg in sp2ion
self.sp2chlocal = [None]*len(sp2ion) # Interpolate the atomic charges for each specie
self.sp2rcut_chlocal = np.zeros(len(sp2ion))
for isp, ion in enumerate(sp2ion):
if "chlocal" not in ion.keys(): continue
if ion["chlocal"] is None: continue
self.sp2rcut_chlocal[isp] = ion["chlocal"]["cutoff"]
h,dat = ion["chlocal"]["delta"][0], ion["chlocal"]["data"][0][:,1]
d2 = spline_diff2(h, dat, 0.0, 1.0e301)
self.sp2chlocal[isp] = np.array([spline_interp(h, dat, d2, r) for r in self.rr])
return self
def siesta_ion_interp(rr, sp2ion, fj=1):
""" Interpolation of orbitals given on linear grid in the ion dictionary """
nr = len(rr)
assert(nr>2)
nsp = len(sp2ion)
nmultmax = max([len(sp2ion[sp]["paos"]["orbital"]) for sp in range(nsp)])
smr2ro_log = [] #numpy.zeros((nsp,nmultmax,nr), dtype='float64', order='F')
for sp,ion in enumerate(sp2ion):
nmu = len(sp2ion[sp]["paos"]["orbital"])
smr2ro_log.append(np.zeros((nmu,nr)))
for mu,dat in enumerate(ion["paos"]["data"]):
#print(__name__, 'dat.shape', dat.shape, dat[0:4,0], dat[0:4,1])
j, h = ion["paos"]['orbital'][mu]['l'], ion["paos"]["delta"][mu]
yy_diff2 = spline_diff2(h, dat[:, 1], 0.0, 1.0e301)
for ir in range(nr):
smr2ro_log[sp][mu,ir] = spline_interp(h,dat[:, 1],yy_diff2,rr[ir])*(rr[ir]**(fj*j))
return smr2ro_log
def siesta_ion_interp(rr, sp2ion, fj=1):
""" Interpolation of orbitals given on linear grid in the ion dictionary """
nr = len(rr)
assert (nr > 2)
nsp = len(sp2ion)
nmultmax = max([len(sp2ion[sp]["paos"]["orbital"]) for sp in range(nsp)])
smr2ro_log = [
] #numpy.zeros((nsp,nmultmax,nr), dtype='float64', order='F')
for sp, ion in enumerate(sp2ion):
nmu = len(sp2ion[sp]["paos"]["orbital"])
smr2ro_log.append(np.zeros((nmu, nr)))
for mu, dat in enumerate(ion["paos"]["data"]):
#print(__name__, 'dat.shape', dat.shape, dat[0:4,0], dat[0:4,1])
j, h = ion["paos"]['orbital'][mu]['l'], ion["paos"]["delta"][mu]
yy_diff2 = spline_diff2(h, dat[:, 1], 0.0, 1.0e301)
for ir in range(nr):
smr2ro_log[sp][mu, ir] = spline_interp(
h, dat[:, 1], yy_diff2, rr[ir]) * (rr[ir]**(fj * j))
return smr2ro_log
def siesta_ion_interp(self, sp2ion, fname='paos'):
from pyscf.nao.m_get_sp_mu2s import get_sp_mu2s
from pyscf.nao.m_spline_diff2 import spline_diff2
from pyscf.nao.m_spline_interp import spline_interp
"""
Interpolation of orbitals or projectors given on linear grid in the ion dictionary
rr : is the grid on which we want the function
sp2ion : list of dictionaries
fname : function name, can be 'paos' or 'kbs'
"""
rr, nr, nsp = self.rr, len(self.rr), len(sp2ion)
pname = {'paos': 'orbital', 'kbs': 'projector'}[fname]
self.nspecies = len(sp2ion)
self.sp2nmult = np.zeros(self.nspecies, dtype='int64')
self.sp_mu2rcut = [None]*self.nspecies
self.sp_mu2j = [None]*self.nspecies
self.sp_mu2s = [None]*self.nspecies
self.sp2norbs = np.zeros(self.nspecies, dtype='int64')
self.sp2rcut = np.zeros(self.nspecies)
self.sp2charge = np.zeros(self.nspecies, dtype='int64')
self.sp2valence = np.zeros(self.nspecies, dtype='int64')
for isp, ion in enumerate(sp2ion):
if ion[fname] is None:
continue
self.sp2nmult[isp] = len(ion[fname]['data'])
self.sp_mu2rcut[isp] = np.array(ion[fname]["cutoff"])
self.sp_mu2j[isp] = np.array([o["l"] for o in ion[fname][pname]], dtype='int64')
mu2s = np.zeros(self.sp2nmult[isp]+1, dtype='int64')
for mu in range(self.sp2nmult[isp]):
mu2s[mu+1] = sum(2*self.sp_mu2j[isp][0:mu+1]+1)
self.sp_mu2s[isp] = mu2s
self.sp2norbs[isp] = self.sp_mu2s[isp][self.sp2nmult[isp]]
self.sp2rcut[isp] = np.amax(self.sp_mu2rcut[isp])
self.sp2charge[isp] = int(self.sp2ion[isp]['z'])
self.sp2valence[isp] = int(self.sp2ion[isp]['valence'])
self.jmx = max([mu2j.max() for mu2j in self.sp_mu2j if mu2j is not None])
if fname=='kbs':
self.sp_mu2vkb = [None]*self.nspecies
for isp, ion in enumerate(sp2ion):
if ion[fname] is None:
continue
self.sp_mu2vkb[isp] = np.array([0.5*p['ref_energy'] for p in ion['kbs']['projector'] ])
self.psi_log_rl = [None]*self.nspecies
for isp, ion in enumerate(sp2ion):
if ion[fname] is None:
continue
ff = np.zeros((len(ion[fname][pname]), nr))
for mu,(h,dat) in enumerate(zip(ion[fname]["delta"],ion[fname]["data"])):
diff2 = spline_diff2(h, dat[:,1], 0.0, 1.0e301)
for i, r in enumerate(rr):
ff[mu,i] = spline_interp(h, dat[:,1], diff2, r)
self.psi_log_rl[isp] = ff
self.psi_log = [None]*self.nspecies
for isp, (mu2ff, mu2j) in enumerate(zip(self.psi_log_rl, self.sp_mu2j)):
if mu2ff is None:
continue
gg = np.zeros((len(mu2j), nr))
for mu,(ff,j) in enumerate(zip(mu2ff,mu2j)):
gg[mu] = ff*(rr**j)
self.psi_log[isp] = gg
def init_ao_log_ion(self, sp2ion, **kw):
"""
Reads data from a previous SIESTA calculation,
interpolates the orbitals on a single log mesh.
"""
from pyscf.nao.m_log_interp import log_interp_c
from pyscf.nao.m_siesta_ion_interp import siesta_ion_interp
from pyscf.nao.m_siesta_ion_add_sp2 import _siesta_ion_add_sp2
from pyscf.nao.m_spline_diff2 import spline_diff2
from pyscf.nao.m_spline_interp import spline_interp
import numpy as np
self.init_log_mesh_ion(sp2ion, **kw)
#print(__name__, self.nr)
#print(__name__, self.rr)
#print(__name__, self.rmax)
#print(__name__, self.rmin)
#print(__name__, self.kmax)
self.interp_rr, self.interp_pp = log_interp_c(self.rr), log_interp_c(
self.pp)
_siesta_ion_add_sp2(
self, sp2ion) # adds the fields for counting, .nspecies etc.
self.jmx = max([mu2j.max() for mu2j in self.sp_mu2j])
self.sp2norbs = np.array(
[mu2s[self.sp2nmult[sp]] for sp, mu2s in enumerate(self.sp_mu2s)],
dtype='int64')
self.sp2ion = sp2ion
rr = self.rr
nr = len(rr)
#print(__name__, 'self.jmx', self.jmx)
#print(__name__, 'self.sp2norbs', self.sp2norbs)
#print(__name__, 'self.sp2norbs', dir(self))
#print(__name__, 'self.sp_mu2j', self.sp_mu2j)
#print(__name__, 'self.sp_mu2rcut', self.sp_mu2rcut)
#print(__name__, 'self.sp_mu2s', self.sp_mu2s)
self.psi_log = siesta_ion_interp(rr, sp2ion, 1)
self.psi_log_rl = siesta_ion_interp(rr, sp2ion, 0)
self.sp2vna = [
] # Interpolate a Neutral-atom potential V_NA(r) for each specie
for ion in sp2ion:
vna = np.zeros(nr)
if ion["vna"] is not None:
h, dat = ion["vna"]["delta"], ion["vna"]["data"][0][:, 1]
yy_diff2 = spline_diff2(h, dat, 0.0, 1.0e301)
for ir, r in enumerate(rr):
vna[ir] = spline_interp(h, dat, yy_diff2, r)
self.sp2vna.append(vna * 0.5) # given in Rydberg?
self.sp_mu2rcut = [np.array(ion["paos"]["cutoff"]) for ion in sp2ion]
self.sp2rcut = np.array([np.amax(rcuts) for rcuts in self.sp_mu2rcut])
self.sp2charge = [int(ion['z']) for ion in self.sp2ion]
self.sp2valence = [int(ion['valence']) for ion in self.sp2ion]
#call sp2ion_to_psi_log(sv%sp2ion, sv%rr, sv%psi_log)
#call init_psi_log_rl(sv%psi_log, sv%rr, sv%uc%mu_sp2j, sv%uc%sp2nmult, sv%psi_log_rl)
#call sp2ion_to_core(sv%sp2ion, sv%rr, sv%core_log, sv%sp2has_core, sv%sp2rcut_core)
return self