def test_derivatives(self):
np.random.seed(1)
las = LASSCF(mf, (4, ),
(4, ), spin_sub=(1, )).set(max_cycle_macro=1,
ah_level_shift=0).run()
ugg = las.get_ugg()
ci0_csf = np.random.rand(ugg.ncsf_sub[0][0])
ci0_csf /= np.linalg.norm(ci0_csf)
ci0 = ugg.ci_transformers[0][0].vec_csf2det(ci0_csf)
las_gorb, las_gci = las.get_grad(mo_coeff=mf.mo_coeff, ci=[[ci0]])[:2]
las_grad = np.append(las_gorb, las_gci)
las_hess = las.get_hop(ugg=ugg, mo_coeff=mf.mo_coeff, ci=[[ci0]])
self.assertAlmostEqual(lib.fp(las_grad), lib.fp(las_hess.get_grad()),
8)
cas_grad, _, cas_hess, _ = newton_casscf.gen_g_hop(
mc, mf.mo_coeff, ci0, mc.ao2mo(mf.mo_coeff))
_pack_ci, _unpack_ci = newton_casscf._pack_ci_get_H(
mc, mf.mo_coeff, ci0)[-2:]
def pack_cas(kappa, ci1):
return np.append(mc.pack_uniq_var(kappa), _pack_ci(ci1))
def unpack_cas(x):
return mc.unpack_uniq_var(x[:ugg.nvar_orb]), _unpack_ci(
x[ugg.nvar_orb:])
def cas2las(y, mode='hx'):
yorb, yci = unpack_cas(y)
yc = yci[0].ravel().dot(ci0.ravel())
yci[0] -= yc * ci0
yorb *= (0.5 if mode == 'hx' else 1)
return ugg.pack(yorb, [yci])
def las2cas(y, mode='x'):
yorb, yci = ugg.unpack(y)
yc = yci[0][0].ravel().dot(ci0.ravel())
yci[0][0] -= yc * ci0
yorb *= (0.5 if mode == 'x' else 1)
return pack_cas(yorb, yci[0])
cas_grad = cas2las(cas_grad)
self.assertAlmostEqual(lib.fp(las_grad), lib.fp(cas_grad), 8)
x = np.random.rand(ugg.nvar_tot)
# orb on input
x_las = x.copy()
x_las[ugg.nvar_orb:] = 0.0
x_cas = las2cas(x_las, mode='x')
hx_las = las_hess._matvec(x_las)
hx_cas = cas2las(cas_hess(x_cas), mode='x')
self.assertAlmostEqual(lib.fp(hx_las), lib.fp(hx_cas), 8)
# CI on input
x_las = x.copy()
x_las[:ugg.nvar_orb] = 0.0
x_cas = las2cas(x_las, mode='hx')
hx_las = las_hess._matvec(x_las)
hx_cas = cas2las(cas_hess(x_cas), mode='hx')
self.assertAlmostEqual(lib.fp(hx_las), lib.fp(hx_cas), 8)
def test_derivatives(self):
np.random.seed(1)
las = LASSCF(mf, (4, ), (4, ), spin_sub=(1, )).set(max_cycle_macro=1,
ah_level_shift=0)
las.state_average_(weights=[0.5, 0.5],
charges=[0, 0],
spins=[0, 2],
smults=[1, 3]).run()
ugg = las.get_ugg()
ci0_csf = [np.random.rand(ncsf) for ncsf in ugg.ncsf_sub[0]]
ci0_csf = [c / np.linalg.norm(c) for c in ci0_csf]
ci0 = [
t.vec_csf2det(c) for t, c in zip(ugg.ci_transformers[0], ci0_csf)
]
las_gorb, las_gci = las.get_grad(mo_coeff=mf.mo_coeff, ci=[ci0])[:2]
las_grad = np.append(las_gorb, las_gci)
las_hess = las.get_hop(ugg=ugg, mo_coeff=mf.mo_coeff, ci=[ci0])
self.assertAlmostEqual(lib.fp(las_grad), lib.fp(las_hess.get_grad()),
8)
cas_grad, _, cas_hess, _ = newton_casscf.gen_g_hop(
mc, mf.mo_coeff, ci0, mc.ao2mo(mf.mo_coeff))
_pack_ci, _unpack_ci = newton_casscf._pack_ci_get_H(
mc, mf.mo_coeff, ci0)[-2:]
def pack_cas(kappa, ci1):
return np.append(mc.pack_uniq_var(kappa), _pack_ci(ci1))
def unpack_cas(x):
return mc.unpack_uniq_var(x[:ugg.nvar_orb]), _unpack_ci(
x[ugg.nvar_orb:])
def cas2las(y, mode='hx'):
yorb, yci = unpack_cas(y)
yci = [
2 * (yc - c * c.ravel().dot(yc.ravel()))
for c, yc in zip(ci0, yci)
]
yorb *= (0.5 if mode == 'hx' else 1)
return ugg.pack(yorb, [yci])
def las2cas(y, mode='x'):
yorb, yci = ugg.unpack(y)
yci = [
yc - c * c.ravel().dot(yc.ravel())
for c, yc in zip(ci0, yci[0])
]
yorb *= (0.5 if mode == 'x' else 1)
return pack_cas(yorb, yci)
cas_grad = cas2las(cas_grad)
self.assertAlmostEqual(lib.fp(las_grad), lib.fp(cas_grad), 8)
x = np.random.rand(ugg.nvar_tot)
# orb on input
x_las = x.copy()
x_las[ugg.nvar_orb:] = 0.0
x_cas = las2cas(x_las, mode='x')
hx_las = las_hess._matvec(x_las)
hx_cas = cas2las(cas_hess(x_cas), mode='x')
self.assertAlmostEqual(lib.fp(hx_las), lib.fp(hx_cas), 8)
# CI on input
x_las = x.copy()
x_las[:ugg.nvar_orb] = 0.0
x_cas = las2cas(x_las, mode='hx')
hx_las = las_hess._matvec(x_las)
hx_cas = cas2las(cas_hess(x_cas), mode='hx')
self.assertAlmostEqual(lib.fp(hx_las), lib.fp(hx_cas), 8)