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_energy_df(self):
las = LASSCF(mf_df, (4, ), (4, ),
spin_sub=(1, )).set(conv_tol_grad=1e-5)
las.state_average_(weights=[0.5, 0.5],
charges=[0, 0],
spins=[0, 2],
smults=[1, 3]).run()
self.assertAlmostEqual(las.e_tot, mc_df.e_tot, 8)
self.assertAlmostEqual(las.e_states[0], mc_df.e_states[0], 7)
self.assertAlmostEqual(las.e_states[1], mc_df.e_states[1], 7)
from pyscf import scf, lib, tools, mcscf
from pyscf.mcscf.addons import state_average_mix
from mrh.my_pyscf.mcscf.lasscf_testing import LASSCF
from pyscf.mcscf.newton_casscf import gen_g_hop, _pack_ci_get_H
from c2h6n4_struct import structure as struct
from mrh.my_pyscf.fci import csf_solver
from itertools import product
import os
mol = struct(2.0, 2.0, '6-31g', symmetry=False)
mol.output = 'sa_lasscf_testing.log'
mol.verbose = lib.logger.DEBUG
mol.build()
mf = scf.RHF(mol).run()
mo_coeff = mf.mo_coeff.copy()
las = LASSCF(mf, (4, 4), (4, 4), spin_sub=(1, 1))
mo_loc = las.localize_init_guess((list(range(3)), list(range(9, 12))),
mo_coeff=mo_coeff)
las.state_average_(weights=[0.5, 0.5], spins=[[0, 0], [2, -2]])
las.set(max_cycle_macro=1, max_cycle_micro=1, ah_level_shift=0).kernel()
np.random.seed(1)
ugg = las.get_ugg()
ci0 = [np.random.rand(ncsf) for ncsf in ugg.ncsf_sub.ravel()]
ci0 = [c / linalg.norm(c) for c in ci0]
x0 = np.concatenate([
np.zeros(ugg.nvar_orb),
] + ci0)
_, ci0_sa = ugg.unpack(x0)
las.mo_coeff = mo_loc
las.ci = ci0_sa
import numpy as np
from pyscf import gto, scf, tools
from c2h6n4_struct import structure as struct
from mrh.my_pyscf.mcscf.lasscf_testing import LASSCF
rnn0 = 1.23681571
mol = struct(3.0, 3.0, '6-31g', symmetry=False)
mf = scf.RHF(mol).run()
las = LASSCF(mf, (4, 4), (4, 4), spin_sub=(1, 1))
frag_atom_list = (list(range(3)), list(range(9, 12)))
mo0 = las.localize_init_guess(frag_atom_list)
las.kernel(mo0)
las_scanner = las.as_scanner()
pes = np.loadtxt('c2h6n4_pes_old.dat')[:34, :]
pes = np.hstack((pes, np.zeros((34, 1))))
pes[33, 3] = las.e_tot
# ISN'T THIS SO MUCH BETTER RIDDHISH?????
for ix, dr_nn in enumerate(np.arange(2.9, -0.301, -0.1)):
mol1 = struct(dr_nn, dr_nn, '6-31g', symmetry=False)
pes[32 - ix, 3] = las_scanner(mol1)
print(" r_NN {:>11s} {:>13s} {:>13s}".format("CASSCF", "vLASSCF(v1)",
"vLASSCF(test)"))
for row in pes:
print(" {:5.3f} {:11.6f} {:13.8f} {:13.8f}".format(*row))
weights = [
1.0,
] + [
0.0,
] * 56
nroots = 57
# End building crazy state list
dr_nn = 2.0
mol = struct(dr_nn, dr_nn, '6-31g', symmetry='Cs')
mol.verbose = lib.logger.INFO
mol.output = 'test_lassi_op.log'
mol.spin = 0
mol.build()
mf = scf.RHF(mol).run()
las = LASSCF(mf, (4, 2, 4), (4, 2, 4))
las.state_average_(weights=weights, **states)
las.mo_coeff = las.localize_init_guess(
(list(range(3)), list(range(3, 7)), list(range(7, 10))), mf.mo_coeff)
las.ci = get_init_guess_ci(las, las.mo_coeff, las.get_h2eff(las.mo_coeff))
np.random.seed(1)
for c in las.ci:
for iroot in range(len(c)):
c[iroot] = np.random.rand(*c[iroot].shape)
c[iroot] /= linalg.norm(c[iroot])
orbsym = getattr(las.mo_coeff, 'orbsym', None)
if orbsym is None and callable(getattr(las, 'label_symmetry_', None)):
orbsym = las.label_symmetry_(las.mo_coeff).orbsym
if orbsym is not None:
orbsym = orbsym[las.ncore:las.ncore + las.ncas]
wfnsym = 0
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)
from mrh.my_pyscf.mcscf.lasscf_testing import LASSCF
mol = struct(3.0, 3.0, '6-31g', symmetry=False)
mol.verbose = lib.logger.INFO
mol.output = 'c2h4n4_spin.log'
mol.build()
mf = scf.RHF(mol).run()
# 1. Diamagnetic singlet
''' The constructor arguments are
1) SCF object
2) List or tuple of ncas for each fragment
3) List or tuple of nelec for each fragment
A list or tuple of total-spin multiplicity is supplied
in "spin_sub".'''
las = LASSCF(mf, (4, 4), (4, 4), spin_sub=(1, 1))
''' The class doesn't know anything about "fragments" at all.
The active space is only "localized" provided one offers an
initial guess for the active orbitals that is localized.
That is the purpose of the localize_init_guess function.
It requires a sequence of sequence of atom numbers, and it
projects the orbitals in the ncore:nocc columns into the
space of those atoms' AOs. The orbitals in the range
ncore:ncore+ncas_sub[0] are the first active subspace,
those in the range ncore+ncas_sub[0]:ncore+sum(ncas_sub[:2])
are the second active subspace, and so on.'''
frag_atom_list = (list(range(3)), list(range(7, 10)))
mo_coeff = las.localize_init_guess(frag_atom_list, mf.mo_coeff)
''' Right now, this function can only (roughly) reproduce the
"force_imp=False, confine_guess=True" behavior of the old
orbital guess builder. I might add the complement later,
def test_af_df (self):
las = LASSCF (mf_hs_df, (4,4), ((4,0),(0,4)), spin_sub=(5,5))
mo_coeff = las.localize_init_guess (frags)
las.kernel (mo_coeff)
self.assertAlmostEqual (las.e_tot, -295.4466638852035, 7)
def test_energy_hs_df(self):
las = LASSCF(mf_hs_df, (4, ), ((4, 0), ),
spin_sub=(5, )).set(conv_tol_grad=1e-5).run()
self.assertAlmostEqual(las.e_tot, mf_hs_df.e_tot, 8)
def test_energy(self):
las = LASSCF(mf, (4, ), (4, ),
spin_sub=(1, )).set(conv_tol_grad=1e-5).run()
self.assertAlmostEqual(las.e_tot, mc.e_tot, 8)
import numpy as np
from scipy import linalg
from pyscf import lib, gto, scf, dft, fci, mcscf, df
from pyscf.tools import molden
from c2h4n4_struct import structure as struct
from mrh.my_pyscf.mcscf.lasscf_testing import LASSCF
from mrh.my_pyscf.mcscf.lassi import roots_make_rdm12s, make_stdm12s, ham_2q
dr_nn = 2.0
mol = struct(dr_nn, dr_nn, '6-31g', symmetry=False)
mol.verbose = lib.logger.DEBUG
mol.output = 'test_lassi.log'
mol.spin = 0
mol.build()
mf = scf.RHF(mol).run()
las = LASSCF(mf, (4, 4), (4, 4), spin_sub=(1, 1))
las.state_average_(weights=[
1.0 / 5.0,
] * 5,
spins=[[0, 0], [0, 0], [2, -2], [-2, 2], [2, 2]],
smults=[[1, 1], [3, 3], [3, 3], [3, 3], [3, 3]])
las.frozen = list(range(las.mo_coeff.shape[-1]))
ugg = las.get_ugg()
las.mo_coeff = np.loadtxt('test_lassi_mo.dat')
las.ci = ugg.unpack(np.loadtxt('test_lassi_ci.dat'))[1]
#las.set (conv_tol_grad=1e-8).run ()
#np.savetxt ('test_lassi_mo.dat', las.mo_coeff)
#np.savetxt ('test_lassi_ci.dat', ugg.pack (las.mo_coeff, las.ci))
las.e_states = las.energy_nuc() + las.states_energy_elec()
e_roots, si = las.lassi()
rdm1s, rdm2s = roots_make_rdm12s(las, las.ci, si)
def test_symm_df (self):
las = LASSCF (mf_df, (4,4), (4,4), spin_sub=(1,1))
mo_coeff = las.localize_init_guess (frags)
las.kernel (mo_coeff)
self.assertAlmostEqual (las.e_tot, -295.44716017803967, 7)
def test_symm (self):
las = LASSCF (mf, (4,4), (4,4), spin_sub=(1,1))
mo_coeff = las.localize_init_guess (frags)
las.kernel (mo_coeff)
self.assertAlmostEqual (las.e_tot, -295.44779578419946, 7)
mol = struct(3.0, 3.0, '6-31g')
mol.symmetry = 'Cs'
mol.output = 'c2h4n4_631g.log'
mol.verbose = lib.logger.INFO
mol.build()
mf = scf.RHF(mol).run()
# SA-LASSCF object
# The first positional argument of "state_average" is the orbital weighting function
# Note that there are four states and two fragments and the weights sum to 1
# "Spins" is neleca - nelecb (= 2m for the sake of being an integer)
# "Smults" is the desired local spin quantum *MULTIPLICITY* (2s+1)
# "Wfnsyms" can also be the names of the irreps but I got lazy
# "Charges" should be self-explanatory
# If your molecule doesn't have point-group symmetry turned on then don't pass "wfnsyms"
las = LASSCF(mf, (5, 5), ((3, 2), (2, 3)))
las = las.state_average([0.5, 0.5, 0.0, 0.0],
spins=[[1, -1], [-1, 1], [0, 0], [0, 0]],
smults=[[2, 2], [2, 2], [1, 1], [1, 1]],
charges=[[0, 0], [0, 0], [-1, 1], [1, -1]],
wfnsyms=[[1, 1], [1, 1], [0, 0], [0, 0]])
mo_loc = las.localize_init_guess((list(range(5)), list(range(5, 10))),
mf.mo_coeff)
las.kernel(mo_loc)
print("\n---SA-LASSCF---")
print("Energy:", las.e_states)
# For now, the LASSI diagonalizer is just a post-hoc function call
# It returns eigenvalues (energies) in the first position and
# eigenvectors (here, a 4-by-4 vector)
e_roots, si = las.lassi()
from scipy import linalg
from pyscf import lib, gto, scf, dft, fci, mcscf, df
from pyscf.tools import molden
from c2h4n4_struct import structure as struct
from mrh.my_pyscf.mcscf.lasscf_testing import LASSCF
from mrh.my_pyscf.mcscf.lassi import roots_make_rdm12s, make_stdm12s, ham_2q
dr_nn = 2.0
mol = struct(dr_nn, dr_nn, '6-31g', symmetry='Cs')
mol.verbose = lib.logger.DEBUG
mol.output = 'test_lassi_symm.log'
mol.spin = 0
mol.symmetry = 'Cs'
mol.build()
mf = scf.RHF(mol).run()
las = LASSCF(mf, (4, 4), (4, 4), spin_sub=(1, 1))
las.state_average_(weights=[
1.0 / 7.0,
] * 7,
spins=[[0, 0], [0, 0], [2, -2], [-2, 2], [0, 0], [0, 0],
[2, 2]],
smults=[[1, 1], [3, 3], [3, 3], [3, 3], [1, 1], [1, 1],
[3, 3]],
wfnsyms=[
['A\'', 'A\''],
] * 4 + [['A"', 'A\''], ['A\'', 'A"'], ['A\'', 'A\'']])
las.frozen = list(range(las.mo_coeff.shape[-1]))
ugg = las.get_ugg()
las.mo_coeff = las.label_symmetry_(np.loadtxt('test_lassi_symm_mo.dat'))
las.ci = ugg.unpack(np.loadtxt('test_lassi_symm_ci.dat'))[1]
#las.set (conv_tol_grad=1e-8).run ()
def __enter__(self):
self.savedPath = os.getcwd()
os.chdir(self.newPath)
def __exit__(self, etype, value, traceback):
os.chdir(self.savedPath)
from mrh.examples.lasscf.c2h6n4.c2h6n4_struct import structure as struct
with cd("/home/herme068/gits/mrh/examples/lasscf/c2h6n4"):
mol = struct(2.0, 2.0, '6-31g', symmetry=False)
mol.verbose = lib.logger.DEBUG
mol.output = 'sa_lasscf_slow_ham.log'
mol.build()
mf = scf.RHF(mol).run()
tol = 1e-6 if len(sys.argv) < 2 else float(sys.argv[1])
las = LASSCF(mf, (4, 4), (4, 4)).set(conv_tol_grad=tol)
mo = las.localize_init_guess((list(range(3)), list(range(9, 12))),
mo_coeff=mf.mo_coeff)
las.state_average_(weights=[0.5, 0.5], spins=[[0, 0], [2, -2]])
h2eff_sub, veff = las.kernel(mo)[-2:]
e_states = las.e_states
ncore, ncas, nocc = las.ncore, las.ncas, las.ncore + las.ncas
mo_coeff = las.mo_coeff
mo_core = mo_coeff[:, :ncore]
mo_cas = mo_coeff[:, ncore:nocc]
e0 = las._scf.energy_nuc() + 2 * ((
(las._scf.get_hcore() + veff.c / 2) @ mo_core) * mo_core).sum()
h1 = mo_cas.conj().T @ (las._scf.get_hcore() + veff.c) @ mo_cas
h2 = h2eff_sub[ncore:nocc].reshape(ncas * ncas, ncas * (ncas + 1) // 2)
h2 = lib.numpy_helper.unpack_tril(h2).reshape(ncas, ncas, ncas, ncas)
import unittest
import numpy as np
from scipy import linalg
from pyscf import lib, gto, scf, dft, fci, mcscf, df
from pyscf.tools import molden
from c2h4n4_struct import structure as struct
from mrh.my_pyscf.mcscf.lasscf_testing import LASSCF
dr_nn = 2.0
mol = struct(dr_nn, dr_nn, '6-31g', symmetry=False)
mol.verbose = lib.logger.DEBUG
mol.output = '/dev/null'
mol.spin = 0
mol.build()
mf = scf.RHF(mol).run()
las = LASSCF(mf, (4, 4), ((3, 1), (1, 3)), spin_sub=(3, 3))
las.max_cycle_macro = 1
las.kernel()
las.mo_coeff = np.loadtxt('test_lasci_mo.dat')
las.ci = [[np.loadtxt('test_lasci_ci0.dat')],
[-np.loadtxt('test_lasci_ci1.dat').T]]
ugg = las.get_ugg()
h_op = las.get_hop(ugg=ugg)
np.random.seed(0)
x = np.random.rand(ugg.nvar_tot)
def tearDownModule():
global mol, mf, las, ugg, h_op, x
mol.stdout.close()
del mol, mf, las, ugg, h_op, x
def test_ferro_df (self):
las = LASSCF (mf_hs_df, (4,4), ((4,0),(4,0)), spin_sub=(5,5))
mo_coeff = las.localize_init_guess (frags)
las.kernel (mo_coeff)
self.assertAlmostEqual (las.e_tot, mf_hs_df.e_tot, 7)