def _regular_step(heff, ovlp, xs, lindep, log):
try:
e, c = scipy.linalg.eigh(heff[1:, 1:], ovlp[1:, 1:])
except scipy.linalg.LinAlgError:
e, c = lib.safe_eigh(heff[1:, 1:], ovlp[1:, 1:], lindep)[:2]
if numpy.any(e < -1e-5):
log.debug('Negative hessians found %s', e[e < 0])
w, v, seig = lib.safe_eigh(heff, ovlp, lindep)
if log.verbose >= logger.DEBUG3:
numpy.set_printoptions(3, linewidth=1000)
log.debug3('v[0] %s', v[0])
log.debug3('AH eigs %s', w)
numpy.set_printoptions(8, linewidth=75)
#if e[0] < -.1:
# sel = 0
#else:
# There exists systems that the first eigenvalue of AH is -inf.
# Dynamically choosing the eigenvectors may be better.
idx = numpy.where(abs(v[0]) > 0.1)[0]
sel = idx[0]
log.debug1('CIAH eigen-sel %s', sel)
w_t = w[sel]
xtrial = _dgemv(v[1:, sel] / v[0, sel], xs)
return xtrial, w_t, v[:, sel], sel, seig
def _regular_step(heff, ovlp, xs, lindep, log):
try:
e, c = scipy.linalg.eigh(heff[1:, 1:], ovlp[1:, 1:])
except scipy.linalg.LinAlgError:
e, c = lib.safe_eigh(heff[1:, 1:], ovlp[1:, 1:], lindep)[:2]
if e[0] < -1e-5:
log.debug('Negative hessians found %s', e[e < 0])
log.debug('AH is shifted to avoid negative hessians')
heff = heff.copy()
sc = numpy.dot(ovlp[1:, 1:], c)
e[(-0.1 < e) & (e < 0)] = .1
e = abs(e)
heff[1:, 1:] = numpy.dot(sc * e, sc.T.conj())
w, v, seig = lib.safe_eigh(heff, ovlp, lindep)
if log.verbose >= logger.DEBUG3:
numpy.set_printoptions(3, linewidth=1000)
log.debug3('v[0] %s', v[0])
log.debug3('AH eigs %s', w)
numpy.set_printoptions(8, linewidth=75)
idx = numpy.where(abs(v[0]) > 0.1)[0]
sel = idx[0]
#sel = 0
w_t = w[sel]
xtrial = _dgemv(v[1:, sel] / v[0, sel], xs)
return xtrial, w_t, v[:, sel], sel, seig
def _regular_step(heff, ovlp, xs, lindep, log):
try:
e, c = scipy.linalg.eigh(heff[1:,1:], ovlp[1:,1:])
except scipy.linalg.LinAlgError:
e, c = lib.safe_eigh(heff[1:,1:], ovlp[1:,1:], lindep)[:2]
if numpy.any(e < -1e-5):
log.debug('Negative hessians found %s', e[e<0])
w, v, seig = lib.safe_eigh(heff, ovlp, lindep)
if log.verbose >= logger.DEBUG3:
numpy.set_printoptions(3, linewidth=1000)
log.debug3('v[0] %s', v[0])
log.debug3('AH eigs %s', w)
numpy.set_printoptions(8, linewidth=75)
#if e[0] < -.1:
# sel = 0
#else:
# There exists systems that the first eigenvalue of AH is -inf.
# Dynamically choosing the eigenvectors may be better.
idx = numpy.where(abs(v[0]) > 0.1)[0]
sel = idx[0]
log.debug1('CIAH eigen-sel %s', sel)
w_t = w[sel]
xtrial = _dgemv(v[1:,sel]/v[0,sel], xs)
return xtrial, w_t, v[:,sel], sel, seig
def _regular_step(heff, ovlp, xs, lindep, log):
try:
e, c = scipy.linalg.eigh(heff[1:,1:], ovlp[1:,1:])
except scipy.linalg.LinAlgError:
e, c = lib.safe_eigh(heff[1:,1:], ovlp[1:,1:], lindep)[:2]
if e[0] < -1e-5:
log.debug('Negative hessians found %s', e[e<0])
w, v, seig = lib.safe_eigh(heff, ovlp, lindep)
if log.verbose >= logger.DEBUG3:
numpy.set_printoptions(3, linewidth=1000)
log.debug3('v[0] %s', v[0])
log.debug3('AH eigs %s', w)
numpy.set_printoptions(8, linewidth=75)
if e[0] < -.1:
sel = 0
else:
idx = numpy.where(abs(v[0]) > 0.1)[0]
sel = idx[0]
w_t = w[sel]
xtrial = _dgemv(v[1:,sel]/v[0,sel], xs)
return xtrial, w_t, v[:,sel], sel, seig
def solve_approx_ci(self, h1, h2, ci0, ecore, e_ci, envs):
''' Solve CI eigenvalue/response problem approximately
'''
ncas = self.ncas
nelecas = self.nelecas
ncore = self.ncore
nocc = ncore + ncas
if 'norm_gorb' in envs:
tol = max(self.conv_tol, envs['norm_gorb']**2*.1)
else:
tol = None
if hasattr(self.fcisolver, 'approx_kernel'):
ci1 = self.fcisolver.approx_kernel(h1, h2, ncas, nelecas, ci0=ci0,
tol=tol, max_memory=self.max_memory)[1]
return ci1, None
h2eff = self.fcisolver.absorb_h1e(h1, h2, ncas, nelecas, .5)
hc = self.fcisolver.contract_2e(h2eff, ci0, ncas, nelecas).ravel()
g = hc - (e_ci-ecore) * ci0.ravel()
if self.ci_response_space > 7:
logger.debug(self, 'CI step by full response')
# full response
max_memory = max(400, self.max_memory-lib.current_memory()[0])
e, ci1 = self.fcisolver.kernel(h1, h2, ncas, nelecas, ci0=ci0,
tol=tol, max_memory=max_memory)
else:
nd = min(max(self.ci_response_space, 2), ci0.size)
logger.debug(self, 'CI step by %dD subspace response', nd)
xs = [ci0.ravel()]
ax = [hc]
heff = numpy.empty((nd,nd))
seff = numpy.empty((nd,nd))
heff[0,0] = numpy.dot(xs[0], ax[0])
seff[0,0] = 1
for i in range(1, nd):
xs.append(ax[i-1] - xs[i-1] * e_ci)
ax.append(self.fcisolver.contract_2e(h2eff, xs[i], ncas,
nelecas).ravel())
for j in range(i+1):
heff[i,j] = heff[j,i] = numpy.dot(xs[i], ax[j])
seff[i,j] = seff[j,i] = numpy.dot(xs[i], xs[j])
e, v = lib.safe_eigh(heff, seff)[:2]
ci1 = xs[0] * v[0,0]
for i in range(1,nd):
ci1 += xs[i] * v[i,0]
return ci1, g
def _regular_step(heff, ovlp, xs, lindep, log):
w, v, seig = lib.safe_eigh(heff, ovlp, lindep)
if log.verbose >= logger.DEBUG3:
numpy.set_printoptions(3, linewidth=1000)
log.debug3('v[0] %s', v[0])
log.debug3('AH eigs %s', w)
log.debug3('H eigs %s', scipy.linalg.eigh(heff[1:, 1:])[0])
numpy.set_printoptions(8, linewidth=75)
idx = numpy.where(abs(v[0]) > 0.1)[0]
sel = idx[0]
if w[sel] < -1e-5:
log.debug1('AH might follow negative hessians %s', w[:sel])
w_t = w[sel]
xtrial = _dgemv(v[1:, sel] / v[0, sel], xs)
return xtrial, w_t, v[:, sel], sel, seig
def _regular_step(heff, ovlp, xs, lindep, log):
w, v, seig = lib.safe_eigh(heff, ovlp, lindep)
if log.verbose >= logger.DEBUG3:
numpy.set_printoptions(3, linewidth=1000)
log.debug3('v[0] %s', v[0])
log.debug3('AH eigs %s', w)
log.debug3('H eigs %s', scipy.linalg.eigh(heff[1:,1:])[0])
numpy.set_printoptions(8, linewidth=75)
idx = numpy.where(abs(v[0]) > 0.1)[0]
sel = idx[0]
if w[sel] < -1e-5:
log.debug1('AH might follow negative hessians %s', w[:sel])
w_t = w[sel]
xtrial = _dgemv(v[1:,sel]/v[0,sel], xs)
return xtrial, w_t, v[:,sel], sel, seig
def solve_approx_ci(self, h1, h2, ci0, ecore, e_ci):
''' Solve CI eigenvalue/response problem approximately
'''
ncas = self.ncas
nelecas = self.nelecas
ncore = self.ncore
nocc = ncore + ncas
if hasattr(self.fcisolver, 'approx_kernel'):
ci1 = self.fcisolver.approx_kernel(h1, h2, ncas, nelecas,
ci0=ci0)[1]
return ci1, None
h2eff = self.fcisolver.absorb_h1e(h1, h2, ncas, nelecas, .5)
hc = self.fcisolver.contract_2e(h2eff, ci0, ncas, nelecas).ravel()
g = hc - (e_ci - ecore) * ci0.ravel()
if self.ci_response_space > 7:
logger.debug(self, 'CI step by full response')
# full response
e, ci1 = self.fcisolver.kernel(h1, h2, ncas, nelecas, ci0=ci0)
else:
nd = min(max(self.ci_response_space, 2), ci0.size)
logger.debug(self, 'CI step by %dD subspace response', nd)
xs = [ci0.ravel()]
ax = [hc]
heff = numpy.empty((nd, nd))
seff = numpy.empty((nd, nd))
heff[0, 0] = numpy.dot(xs[0], ax[0])
seff[0, 0] = 1
for i in range(1, nd):
xs.append(ax[i - 1] - xs[i - 1] * e_ci)
ax.append(
self.fcisolver.contract_2e(h2eff, xs[i], ncas,
nelecas).ravel())
for j in range(i + 1):
heff[i, j] = heff[j, i] = numpy.dot(xs[i], ax[j])
seff[i, j] = seff[j, i] = numpy.dot(xs[i], xs[j])
e, v = lib.safe_eigh(heff, seff)[:2]
ci1 = xs[0] * v[0, 0]
for i in range(1, nd):
ci1 += xs[i] * v[i, 0]
return ci1, g
def solve_approx_ci(self, h1, h2, ci0, ecore, e_ci, envs):
''' Solve CI eigenvalue/response problem approximately
'''
ncas = self.ncas
nelecas = self.nelecas
ncore = self.ncore
nocc = ncore + ncas
if 'norm_gorb' in envs:
tol = max(self.conv_tol, envs['norm_gorb']**2 * .1)
else:
tol = None
if hasattr(self.fcisolver, 'approx_kernel'):
fn = self.fcisolver.approx_kernel
ci1 = fn(h1,
h2,
ncas,
nelecas,
ci0=ci0,
tol=tol,
max_memory=self.max_memory)[1]
return ci1, None
elif not (hasattr(self.fcisolver, 'contract_2e')
and hasattr(self.fcisolver, 'absorb_h1e')):
fn = self.fcisolver.kernel
ci1 = fn(h1,
h2,
ncas,
nelecas,
ci0=ci0,
tol=tol,
max_memory=self.max_memory,
max_cycle=self.ci_response_space)[1]
return ci1, None
h2eff = self.fcisolver.absorb_h1e(h1, h2, ncas, nelecas, .5)
hc = self.fcisolver.contract_2e(h2eff, ci0, ncas, nelecas).ravel()
g = hc - (e_ci - ecore) * ci0.ravel()
if self.ci_response_space > 7:
logger.debug(self, 'CI step by full response')
# full response
max_memory = max(400, self.max_memory - lib.current_memory()[0])
e, ci1 = self.fcisolver.kernel(h1,
h2,
ncas,
nelecas,
ci0=ci0,
tol=tol,
max_memory=max_memory)
else:
nd = min(max(self.ci_response_space, 2), ci0.size)
logger.debug(self, 'CI step by %dD subspace response', nd)
xs = [ci0.ravel()]
ax = [hc]
heff = numpy.empty((nd, nd))
seff = numpy.empty((nd, nd))
heff[0, 0] = numpy.dot(xs[0], ax[0])
seff[0, 0] = 1
for i in range(1, nd):
xs.append(ax[i - 1] - xs[i - 1] * e_ci)
ax.append(
self.fcisolver.contract_2e(h2eff, xs[i], ncas,
nelecas).ravel())
for j in range(i + 1):
heff[i, j] = heff[j, i] = numpy.dot(xs[i], ax[j])
seff[i, j] = seff[j, i] = numpy.dot(xs[i], xs[j])
e, v = lib.safe_eigh(heff, seff)[:2]
ci1 = xs[0] * v[0, 0]
for i in range(1, nd):
ci1 += xs[i] * v[i, 0]
return ci1, g
def solve_approx_ci_csf(mc, h1, h2, ci0, ecore, e_cas, envs):
''' This is identical to pyscf.mcscf.mc1step.CASSCF.solve_approx_ci
(with %s/self/mc/g) as of 03/24/2019 for the first 48 lines '''
ncas = mc.ncas
nelecas = mc.nelecas
ncore = mc.ncore
nocc = ncore + ncas
if 'norm_gorb' in envs:
tol = max(mc.conv_tol, envs['norm_gorb']**2 * .1)
else:
tol = None
if getattr(mc.fcisolver, 'approx_kernel', None):
fn = mc.fcisolver.approx_kernel
e, ci1 = fn(h1,
h2,
ncas,
nelecas,
ecore=ecore,
ci0=ci0,
tol=tol,
max_memory=mc.max_memory)
return ci1, None
elif not (getattr(mc.fcisolver, 'contract_2e', None)
and getattr(mc.fcisolver, 'absorb_h1e', None)):
fn = mc.fcisolver.kernel
e, ci1 = fn(h1,
h2,
ncas,
nelecas,
ecore=ecore,
ci0=ci0,
tol=tol,
max_memory=mc.max_memory,
max_cycle=mc.ci_response_space)
return ci1, None
h2eff = mc.fcisolver.absorb_h1e(h1, h2, ncas, nelecas, .5)
# Be careful with the symmetry adapted contract_2e function. When the
# symmetry adapted FCI solver is used, the symmetry of ci0 may be
# different to fcisolver.wfnsym. This function may output 0.
if getattr(mc.fcisolver, 'guess_wfnsym', None):
wfnsym = mc.fcisolver.guess_wfnsym(mc.ncas, mc.nelecas, ci0)
else:
wfnsym = None
def contract_2e(c):
if wfnsym is None:
hc = mc.fcisolver.contract_2e(h2eff, c, ncas, nelecas)
else:
with lib.temporary_env(mc.fcisolver, wfnsym=wfnsym):
hc = mc.fcisolver.contract_2e(h2eff, c, ncas, nelecas)
return hc.ravel()
hc = contract_2e(ci0)
g = hc - (e_cas - ecore) * ci0.ravel()
if mc.ci_response_space > 7:
logger.debug(mc, 'CI step by full response')
# full response
max_memory = max(400, mc.max_memory - lib.current_memory()[0])
e, ci1 = mc.fcisolver.kernel(h1,
h2,
ncas,
nelecas,
ecore=ecore,
ci0=ci0,
tol=tol,
max_memory=max_memory)
else:
# MRH 03/24/2019: this is where I intervene to enforce CSFs
fci = mc.fcisolver
smult = fci.smult
neleca, nelecb = _unpack_nelec(nelecas)
norb = np.asarray(h1).shape[-1]
if hasattr(fci, 'wfnsym') and hasattr(fci, 'confsym'):
idx_sym = fci.confsym[fci.econf_csf_mask] == fci.wfnsym
else:
idx_sym = None
xs = [
csf.pack_sym_ci(
transform_civec_det2csf(ci0,
norb,
neleca,
nelecb,
smult,
csd_mask=fci.csd_mask,
do_normalize=True)[0], idx_sym)
]
nd = min(max(mc.ci_response_space, 2), xs[0].size)
logger.debug(mc, 'CI step by %dD subspace response', nd)
def contract_2e_csf(x):
x_det = transform_civec_csf2det(csf.unpack_sym_ci(x, idx_sym),
norb,
neleca,
nelecb,
smult,
csd_mask=fci.csd_mask)[0]
hx = contract_2e(x_det)
hx = transform_civec_det2csf(hx,
norb,
neleca,
nelecb,
smult,
csd_mask=fci.csd_mask,
do_normalize=False)[0]
return csf.pack_sym_ci(hx, idx_sym).ravel()
ax = [contract_2e_csf(xs[0])]
heff = np.empty((nd, nd))
seff = np.empty((nd, nd))
heff[0, 0] = np.dot(xs[0], ax[0])
seff[0, 0] = 1
for i in range(1, nd):
xs.append(ax[i - 1] - xs[i - 1] * e_cas)
ax.append(contract_2e_csf(xs[i]))
for j in range(i + 1):
heff[i, j] = heff[j, i] = (xs[i] * ax[j]).sum()
seff[i, j] = seff[j, i] = (xs[i] * xs[j]).sum()
e, v = lib.safe_eigh(heff, seff)[:2]
ci1 = xs[0] * v[0, 0]
for i in range(1, nd):
ci1 += xs[i] * v[i, 0]
ci1 = transform_civec_csf2det(csf.unpack_sym_ci(ci1, idx_sym),
norb,
neleca,
nelecb,
smult,
csd_mask=fci.csd_mask,
do_normalize=True)[0]
return ci1, g
