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main2.py
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import jax
import jax.numpy as jnp
from test import *
from reader import read_yaml
from params import init_params
from forces import init_forces
from grids import init_grids
from densities import init_densities
from meanfield import init_meanfield
from levels import init_levels
from static import init_static
from coulomb import init_coulomb
from moment import Moment
jax.config.update('jax_enable_x64', True)
# jax.config.update('jax_platform_name', 'cpu')
config = read_yaml('_config.yml')
# initialization
params = init_params(**config.get('params', {}))
forces = init_forces(params, **config.get('force', {}))
grids = init_grids(params, **config.get('grids', {}))
densities = init_densities(grids)
meanfield = init_meanfield(grids)
levels = init_levels(grids, **config.get('levels', {}))
static = init_static(levels, **config.get('static', {}))
coulomb = init_coulomb(grids)
moment = Moment(jnp.array([-1.4219041817327197E-016, -5.6374715900987012E-017, 3.9732369799358789E-016]))
def cdervx01(d, psin):
_, n, _, _ = psin.shape
kfac = (jnp.pi + jnp.pi) / (d * n)
half_n = n // 2
d1psout = jnp.fft.fft(psin, axis=1, norm="backward")
idx = jnp.arange(0, half_n)
idx_4d = idx[jnp.newaxis,:,jnp.newaxis,jnp.newaxis]
d2psout = jnp.copy(d1psout)
d2psout = d2psout.at[:,idx,:,:].multiply(-(idx_4d * kfac) ** 2 / n)
d2psout = d2psout.at[:,n-1-idx,:,:].multiply(-((idx_4d + 1) * kfac) ** 2 / n)
d1psout = d1psout.at[:,0,:,:].set(0.0)
d1psout = d1psout.at[:,idx,:,:].multiply((1j * idx_4d) * kfac / n)
d1psout = d1psout.at[:,n-idx,:,:].multiply(-((1j * idx_4d) * kfac) / n)
d1psout = d1psout.at[:,half_n,:,:].set(0.0)
d1psout = d1psout.at[...].set(
jnp.fft.ifft(d1psout, axis=1, norm="forward")
)
d2psout = d2psout.at[...].set(
jnp.fft.ifft(d2psout, axis=1, norm="forward")
)
# 5.2245375141434353e-17
# 1.36640756370672e-16
return d1psout, d2psout
def cdervy01(d, psin):
_, _, n, _ = psin.shape
kfac = (jnp.pi + jnp.pi) / (d * n)
half_n = n // 2
d1psout = jnp.fft.fft(psin, axis=2, norm="backward")
idx = jnp.arange(0, half_n)
idx_4d = idx[jnp.newaxis, jnp.newaxis, :, jnp.newaxis]
d2psout = jnp.copy(d1psout)
d2psout = d2psout.at[:,:,idx,:].multiply(-(idx_4d * kfac) ** 2 / n)
d2psout = d2psout.at[:,:,n-1-idx,:].multiply(-((idx_4d + 1) * kfac) ** 2 / n)
d1psout = d1psout.at[:,:,0,:].set(0.0)
d1psout = d1psout.at[:,:,idx,:].multiply((1j * idx_4d) * kfac / n)
d1psout = d1psout.at[:,:,n-idx,:].multiply(-((1j * idx_4d) * kfac) / n)
d1psout = d1psout.at[:,:,half_n,:].set(0.0)
d1psout = d1psout.at[...].set(
jnp.fft.ifft(d1psout, axis=2, norm="forward")
)
d2psout = d2psout.at[...].set(
jnp.fft.ifft(d2psout, axis=2, norm="forward")
)
# 3.966240216616929e-17
# 1.170194769447655e-16
return d1psout, d2psout
def cdervz01(d, psin):
_, _, _, n = psin.shape
kfac = (jnp.pi + jnp.pi) / (d * n)
half_n = n // 2
d1psout = jnp.fft.fft(psin, axis=3, norm="backward")
idx = jnp.arange(0, half_n)
idx_4d = idx[jnp.newaxis,jnp.newaxis,jnp.newaxis,:]
d2psout = jnp.copy(d1psout)
d2psout = d2psout.at[:,:,:,idx].multiply(-(idx_4d * kfac) ** 2 / n)
d2psout = d2psout.at[:,:,:,n-1-idx].multiply(-((idx_4d + 1) * kfac) ** 2 / n)
d1psout = d1psout.at[:,:,:,0].set(0.0)
d1psout = d1psout.at[:,:,:,idx].multiply((1j * idx_4d) * kfac / n)
d1psout = d1psout.at[:,:,:,n-idx].multiply(-((1j * idx_4d) * kfac) / n)
d1psout = d1psout.at[:,:,:,half_n].set(0.0)
d1psout = d1psout.at[...].set(
jnp.fft.ifft(d1psout, axis=3, norm="forward")
)
d2psout = d2psout.at[...].set(
jnp.fft.ifft(d2psout, axis=3, norm="forward")
)
# 4.105394205386439e-17
# 1.258475307421716e-16
return d1psout, d2psout
def sp_properties_helper(pst, dx, dy, dz, xx, yy, zz):
psx, psw = cdervx01(dx, pst)
psy, ps2 = cdervy01(dy, pst)
psw = psw.at[...].add(ps2)
psz, ps3 = cdervz01(dz, pst)
psw = psw.at[...].add(ps3)
cc = jnp.array([
jnp.sum(
jnp.real(pst) * (yy * jnp.imag(psz) - zz * jnp.imag(psy)) +
jnp.imag(pst) * (zz * jnp.real(psy) - yy * jnp.real(psz))
),
jnp.sum(
jnp.real(pst) * (zz * jnp.imag(psx) - xx * jnp.imag(psz)) +
jnp.imag(pst) * (xx * jnp.real(psz) - zz * jnp.real(psx))
),
jnp.sum(
jnp.real(pst) * (xx * jnp.imag(psy) - yy * jnp.imag(psx)) +
jnp.imag(pst) * (yy * jnp.real(psx) - xx * jnp.real(psy))
)
])
kin = -jnp.sum(
jnp.real(pst) * jnp.real(psw) + jnp.imag(pst) * jnp.imag(psw)
)
xpar = jnp.sum(
jnp.real(pst) * jnp.real(pst[:, ::-1, ::-1, ::-1]) +
jnp.imag(pst) * jnp.imag(pst[:, ::-1, ::-1, ::-1])
)
ss = jnp.array([
jnp.sum(
jnp.real(jnp.conjugate(pst[0,...]) * pst[1,...]) +
jnp.real(jnp.conjugate(pst[1,...]) * pst[0,...])
),
jnp.sum(
jnp.real(jnp.conjugate(pst[0,...]) * pst[1,...] * (0.0 - 1.0j)) +
jnp.real(jnp.conjugate(pst[1,...]) * pst[0,...] * (0.0 + 1.0j))
),
jnp.sum(
jnp.real(jnp.conjugate(pst[0,...]) * pst[0,...]) -
jnp.real(jnp.conjugate(pst[1,...]) * pst[1,...])
)
])
return ss, cc, kin, xpar
sp_properties_helper_vmap = jax.vmap(
sp_properties_helper,
in_axes=(0, None, None, None, None, None, None)
)
@jax.jit
def sp_properties(forces, grids, levels, moment):
xx = (grids.x - moment.cmtot[0])[jnp.newaxis,:,jnp.newaxis,jnp.newaxis]
yy = (grids.y - moment.cmtot[1])[jnp.newaxis,jnp.newaxis,:,jnp.newaxis]
zz = (grids.z - moment.cmtot[2])[jnp.newaxis,jnp.newaxis,jnp.newaxis,:]
ss, cc, kin, xpar = sp_properties_helper_vmap(
levels.psi, grids.dx, grids.dy, grids.dz, xx, yy, zz
)
levels.sp_spin = levels.sp_spin.at[...].set(
0.5 * grids.wxyz * ss
)
levels.sp_orbital = levels.sp_orbital.at[...].set(
grids.wxyz * cc
)
levels.sp_kinetic = levels.sp_kinetic.at[...].set(
grids.wxyz * jnp.where(levels.isospin == 0, forces.h2m[0], forces.h2m[1]) * kin
)
levels.sp_parity = levels.sp_parity.at[...].set(
grids.wxyz * xpar
)
return levels
levels.psi = levels.psi.at[...].set(load5d('psi'))
# sp_spin = load2d_real('sp_spin', 3, 132)
# sp_orbital = load2d_real('sp_orbital', 3, 132)
# sp_kinetic = load1d_real('sp_kinetic', 132)
# sp_parity = load1d_real('sp_parity', 132)
sp_spin = jnp.ones((132, 3))
sp_orbital = jnp.ones((132, 3))
sp_kinetic = jnp.ones((132))
sp_parity = jnp.ones((132))
res = sp_properties(forces, grids, levels, moment)
print("sp_spin")
print(jnp.max(jnp.abs(res.sp_spin - sp_spin)))
print("sp_orbital")
print(jnp.max(jnp.abs(res.sp_orbital - sp_orbital)))
print("sp_kinetic")
print(jnp.max(jnp.abs(res.sp_kinetic - sp_kinetic)))
print("sp_parity")
print(jnp.max(jnp.abs(res.sp_parity - sp_parity)))
#relative_error = jnp.abs(res.sp_spin.flatten() - sp_spin.flatten()) / jnp.abs(sp_spin.flatten())
#print(jnp.max(relative_error))
#print(sp_spin[5,:])
#print(res.sp_spin[5,:])
import timeit
start_time = timeit.default_timer()
for _ in range(100):
res = sp_properties(forces, grids, levels, moment)
jax.block_until_ready(res)
end_time = timeit.default_timer()
total_time = end_time - start_time
average_time = total_time / 100
print(average_time)
'''
pst = load4d('pst')
psx = load4d('psx')
psy = load4d('psy')
psz = load4d('psz')
psw = load4d('psw')
ps2 = load4d('ps2')
xx = load1d_real('xx')[jnp.newaxis, :, np.newaxis, np.newaxis]
yy = load1d_real('yy')[jnp.newaxis, np.newaxis, :, np.newaxis]
zz = load1d_real('zz')[jnp.newaxis, np.newaxis, np.newaxis, :]
sp_spin = load1d_real('sp_spin', 3)
sp_orbital = load1d_real('sp_orbital', 3)
sp_kinetic = load1d_real('sp_kinetic', 1)
sp_parity = load1d_real('sp_parity', 1)
wxyz = 0.8 * 0.8 * 0.8
kin = 0.0
xpar = 0.0
cc = jnp.array([
jnp.sum(
jnp.real(pst) * (yy * jnp.imag(psz) - zz * jnp.imag(psy)) +
jnp.imag(pst) * (zz * jnp.real(psy) - yy * jnp.real(psz))
),
jnp.sum(
jnp.real(pst) * (zz * jnp.imag(psx) - xx * jnp.imag(psz)) +
jnp.imag(pst) * (xx * jnp.real(psz) - zz * jnp.real(psx))
),
jnp.sum(
jnp.real(pst) * (xx * jnp.imag(psy) - yy * jnp.imag(psx)) +
jnp.imag(pst) * (yy * jnp.real(psx) - xx * jnp.real(psy))
)
])
kin = - jnp.sum(
jnp.real(pst) * jnp.real(psw) + jnp.imag(pst) * jnp.imag(psw)
)
xpar = jnp.sum(
jnp.real(pst) * jnp.real(pst[:, ::-1, ::-1, ::-1]) +
jnp.imag(pst) * jnp.imag(pst[:, ::-1, ::-1, ::-1])
)
ss = jnp.array([
jnp.sum(
jnp.real(jnp.conjugate(pst[0,...]) * pst[1,...]) +
jnp.real(jnp.conjugate(pst[1,...]) * pst[0,...])
),
jnp.sum(
jnp.real(jnp.conjugate(pst[0,...]) * pst[1,...] * (0.0 - 1.0j)) +
jnp.real(jnp.conjugate(pst[1,...]) * pst[0,...] * (0.0 + 1.0j))
),
jnp.sum(
jnp.real(jnp.conjugate(pst[0,...]) * pst[0,...]) -
jnp.real(jnp.conjugate(pst[1,...]) * pst[1,...])
)
])
print(kin)
print(xpar)
print(cc)
print(sp_spin)
print(sp_orbital)
print(sp_kinetic)
print(sp_parity)
'''