def test_select_strs1(self):
myci = select_ci.SelectCI()
myci.select_cutoff = .1
myci.ci_coeff_cutoff = .01
eri1 = ao2mo.restore(1, eri, norb)
eri_pq_max = abs(eri1.reshape(norb**2,-1)).max(axis=1).reshape(norb,norb)
civec_a_max = abs(ci_coeff).max(axis=1)
civec_b_max = abs(ci_coeff).max(axis=0)
strs_add0 = select_strs(myci, eri1, eri_pq_max, civec_a_max, ci_strs[0],
norb, nelec//2)
strs_add1 = select_ci.select_strs(myci, eri1, eri_pq_max, civec_a_max,
ci_strs[0], norb, nelec//2)
self.assertTrue(numpy.all(strs_add0 == strs_add1))
strs_add0 = select_strs(myci, eri1, eri_pq_max, civec_b_max, ci_strs[1],
norb, nelec//2)
strs_add1 = select_ci.select_strs(myci, eri1, eri_pq_max, civec_b_max,
ci_strs[1], norb, nelec//2)
self.assertTrue(numpy.all(strs_add0 == strs_add1))
def test_select_strs1(self):
myci = select_ci.SCI()
myci.select_cutoff = .1
myci.ci_coeff_cutoff = .01
eri1 = ao2mo.restore(1, eri, norb)
eri_pq_max = abs(eri1.reshape(norb**2,
-1)).max(axis=1).reshape(norb, norb)
civec_a_max = abs(ci_coeff).max(axis=1)
civec_b_max = abs(ci_coeff).max(axis=0)
strs_add0 = select_strs(myci, eri1, eri_pq_max, civec_a_max,
ci_strs[0], norb, nelec // 2)
strs_add1 = select_ci.select_strs(myci, eri1, eri_pq_max, civec_a_max,
ci_strs[0], norb, nelec // 2)
self.assertTrue(numpy.all(strs_add0 == strs_add1))
strs_add0 = select_strs(myci, eri1, eri_pq_max, civec_b_max,
ci_strs[1], norb, nelec // 2)
strs_add1 = select_ci.select_strs(myci, eri1, eri_pq_max, civec_b_max,
ci_strs[1], norb, nelec // 2)
self.assertTrue(numpy.all(strs_add0 == strs_add1))
def test_select_strs(self):
myci = select_ci.SelectCI()
myci.select_cutoff = 1e-3
norb, nelec = 10, 4
strs = cistring.gen_strings4orblist(range(norb), nelec)
numpy.random.seed(11)
mask = numpy.random.random(len(strs)) > .8
strs = strs[mask]
nn = norb*(norb+1)//2
eri = (numpy.random.random(nn*(nn+1)//2)-.2)**3
eri[eri<.1] *= 3e-3
eri = ao2mo.restore(1, eri, norb)
eri_pq_max = abs(eri.reshape(norb**2,-1)).max(axis=1).reshape(norb,norb)
civec_max = numpy.random.random(len(strs))
strs_add0 = select_strs(myci, eri, eri_pq_max, civec_max, strs, norb, nelec)
strs_add1 = select_ci.select_strs(myci, eri, eri_pq_max, civec_max,
strs, norb, nelec)
self.assertTrue(numpy.all(strs_add0 == strs_add1))
def enlarge_space(myci, civec_strs, eri, norb, nelec):
if isinstance(civec_strs, (tuple, list)):
nelec, (strsa, strsb) = select_ci._unpack(civec_strs[0], nelec)[1:]
ci_coeff = lib.asarray(civec_strs)
else:
ci_coeff, nelec, (strsa, strsb) = select_ci._unpack(civec_strs, nelec)
na = nb = len(strsa)
ci0 = ci_coeff.reshape(-1, na, nb)
abs_ci = abs(ci0).max(axis=0)
eri = ao2mo.restore(1, eri, norb)
eri_pq_max = abs(eri.reshape(norb**2, -1)).max(axis=1).reshape(norb, norb)
civec_a_max = abs_ci.max(axis=1)
ci_aidx = numpy.where(civec_a_max > myci.ci_coeff_cutoff)[0]
civec_a_max = civec_a_max[ci_aidx]
strsa = strsa[ci_aidx]
strsa_add = select_ci.select_strs(myci, eri, eri_pq_max, civec_a_max,
strsa, norb, nelec[0])
strsa = numpy.append(strsa, strsa_add)
aidx = numpy.argsort(strsa)
strsa = strsa[aidx]
aidx = numpy.where(aidx < len(ci_aidx))[0]
ci_bidx = ci_aidx
strsb = strsa
bidx = aidx
ma = mb = len(strsa)
cs = []
for i in range(ci0.shape[0]):
ci1 = numpy.zeros((ma, mb))
tmp = lib.take_2d(ci0[i], ci_aidx, ci_bidx)
lib.takebak_2d(ci1, tmp, aidx, bidx)
cs.append(select_ci._as_SCIvector(ci1, (strsa, strsb)))
if ci_coeff[0].ndim == 0 or ci_coeff[0].shape[-1] != nb:
cs = [c.ravel() for c in cs]
if (isinstance(ci_coeff, numpy.ndarray) and ci_coeff.shape[0] == na
or ci_coeff.shape[0] == na * nb):
cs = cs[0]
return cs
def enlarge_space(myci, civec_strs, eri, norb, nelec):
if isinstance(civec_strs, (tuple, list)):
nelec, (strsa, strsb) = select_ci._unpack(civec_strs[0], nelec)[1:]
ci_coeff = lib.asarray(civec_strs)
else:
ci_coeff, nelec, (strsa, strsb) = select_ci._unpack(civec_strs, nelec)
na = nb = len(strsa)
ci0 = ci_coeff.reshape(-1,na,nb)
abs_ci = abs(ci0).max(axis=0)
eri = ao2mo.restore(1, eri, norb)
eri_pq_max = abs(eri.reshape(norb**2,-1)).max(axis=1).reshape(norb,norb)
civec_a_max = abs_ci.max(axis=1)
ci_aidx = numpy.where(civec_a_max > myci.ci_coeff_cutoff)[0]
civec_a_max = civec_a_max[ci_aidx]
strsa = strsa[ci_aidx]
strsa_add = select_ci.select_strs(myci, eri, eri_pq_max, civec_a_max, strsa, norb, nelec[0])
strsa = numpy.append(strsa, strsa_add)
aidx = numpy.argsort(strsa)
strsa = strsa[aidx]
aidx = numpy.where(aidx < len(ci_aidx))[0]
ci_bidx = ci_aidx
strsb = strsa
bidx = aidx
ma = mb = len(strsa)
cs = []
for i in range(ci0.shape[0]):
ci1 = numpy.zeros((ma,mb))
tmp = lib.take_2d(ci0[i], ci_aidx, ci_bidx)
lib.takebak_2d(ci1, tmp, aidx, bidx)
cs.append(select_ci._as_SCIvector(ci1, (strsa,strsb)))
if ci_coeff[0].ndim == 0 or ci_coeff[0].shape[-1] != nb:
cs = [c.ravel() for c in cs]
if (isinstance(ci_coeff, numpy.ndarray) and
ci_coeff.shape[0] == na or ci_coeff.shape[0] == na*nb):
cs = cs[0]
return cs
def test_select_strs(self):
myci = select_ci.SCI()
myci.select_cutoff = 1e-3
norb, nelec = 10, 4
strs = cistring.gen_strings4orblist(range(norb), nelec)
numpy.random.seed(11)
mask = numpy.random.random(len(strs)) > .8
strs = strs[mask]
nn = norb * (norb + 1) // 2
eri = (numpy.random.random(nn * (nn + 1) // 2) - .2)**3
eri[eri < .1] *= 3e-3
eri = ao2mo.restore(1, eri, norb)
eri_pq_max = abs(eri.reshape(norb**2,
-1)).max(axis=1).reshape(norb, norb)
civec_max = numpy.random.random(len(strs))
strs_add0 = select_strs(myci, eri, eri_pq_max, civec_max, strs, norb,
nelec)
strs_add1 = select_ci.select_strs(myci, eri, eri_pq_max, civec_max,
strs, norb, nelec)
self.assertTrue(numpy.all(strs_add0 == strs_add1))