from wavefunction import Wavefunction
from hamiltonian import Hamiltonian
from pbasis import PBasis
from vmfpropagate import vmfpropagate
if __name__ == "__main__":
nel = 2
nmodes = 1
nspfs = np.array([[10],
[10]], dtype=int)
npbfs = [[24, 151]]
# TODO need to be able to combine modes with different pbfs
pbfs = list()
pbfs.append( PBasis(['ho', 24, 1.0, 1.0]) )
pbfs.append( PBasis(['plane wave', 151, 1.0],sparse=True) )
wf = Wavefunction(nel, nmodes, nspfs, npbfs)
wf.generate_ic(1)
# reshpae y into A tensor and spfs
A = np.zeros(2, dtype=np.ndarray)
spfs = np.zeros(2, dtype=np.ndarray)
for alpha in range(wf.nel):
shaper = ()
for mode in range(wf.nmodes):
shaper += (wf.nspfs[alpha,mode],)
# set A
ind0 = wf.psistart[0,alpha]
indf = wf.psiend[0,alpha]
np.set_printoptions(precision=20)
import units
from wavefunction import Wavefunction
from hamiltonian import Hamiltonian
from pbasis import PBasis
from optools import precompute_ops
from eom import eom_coeffs
nel = 2
nmodes = 4
nspfs = np.array([[8, 13, 7, 6],
[7, 12, 6, 5]], dtype=int)
npbfs = np.array([22, 32, 21, 12], dtype=int)
pbfs = list()
pbfs.append( PBasis(['ho', 22, 1.0, 1.0]) )
pbfs.append( PBasis(['ho', 32, 1.0, 1.0]) )
pbfs.append( PBasis(['ho', 21, 1.0, 1.0]) )
pbfs.append( PBasis(['ho', 12, 1.0, 1.0]) )
wf = Wavefunction(nel, nmodes, nspfs, npbfs)
wf.generate_ic(1)
w10a = 0.09357
w6a = 0.0740
w1 = 0.1273
w9a = 0.1568
delta = 0.46165
lamda = 0.1825
k6a1 = -0.0964
k6a2 = 0.1194