def test_aft_k1_high_cost(self):
kpts = cell.get_abs_kpts([[-.25, -.25, -.25], [-.25, -.25, .25],
[-.25, .25, -.25], [-.25, .25, .25],
[.25, -.25, -.25], [.25, -.25, .25],
[.25, .25, -.25], [.25, .25, .25]])
numpy.random.seed(1)
nao = cell.nao_nr()
dm = numpy.random.random((8, nao, nao))
mydf = aft.AFTDF(cell)
mydf.kpts = kpts
numpy.random.seed(1)
dm = numpy.random.random((8, nao, nao))
dm = dm + dm.transpose(0, 2, 1)
vk = aft_jk.get_k_kpts(mydf, dm, 1, mydf.kpts)
self.assertAlmostEqual(finger(vk[0]),
(8.7518173818250702 - 0.11793770445839372j) / 8,
9)
self.assertAlmostEqual(finger(
vk[1]), (5.7682393685317894 + 0.069482280306391239j) / 8, 9)
self.assertAlmostEqual(finger(
vk[2]), (7.1890462727492324 - 0.088727079644645671j) / 8, 9)
self.assertAlmostEqual(finger(vk[3]),
(10.08358152800003 + 0.1278144339422369j) / 8,
9)
self.assertAlmostEqual(finger(vk[4]),
(8.393281242945573 - 0.099410704957774876j) / 8,
9)
self.assertAlmostEqual(finger(vk[5]),
(7.9413682328898769 + 0.1015563120870652j) / 8,
9)
self.assertAlmostEqual(finger(
vk[6]), (7.3743790120272408 - 0.096290683129384574j) / 8, 9)
self.assertAlmostEqual(finger(vk[7]),
(6.8144379626901443 + 0.08071261392857812j) / 8,
9)
def test_aft_k(self):
kpts = cell.get_abs_kpts([[-.25, -.25, -.25], [-.25, -.25, .25],
[-.25, .25, -.25], [-.25, .25, .25],
[.25, -.25, -.25], [.25, -.25, .25],
[.25, .25, -.25], [.25, .25, .25]])
numpy.random.seed(1)
nao = cell.nao_nr()
dm = numpy.random.random((8, nao, nao))
mydf = aft.AFTDF(cell)
mydf.kpts = kpts
vk = aft_jk.get_k_kpts(mydf, dm, 0, mydf.kpts)
self.assertAlmostEqual(finger(
vk[0]), (4.3373802352168278 - 0.062977052131451577j) / 8, 9)
self.assertAlmostEqual(finger(vk[1]),
(2.878809181709983 + 0.028843869853690692j) / 8,
9)
self.assertAlmostEqual(finger(
vk[2]), (3.7027622609953061 - 0.052034330663180237j) / 8, 9)
self.assertAlmostEqual(finger(
vk[3]), (5.0939994842559422 + 0.060094478876149444j) / 8, 9)
self.assertAlmostEqual(finger(
vk[4]), (4.2942087551592651 - 0.061138484763336887j) / 8, 9)
self.assertAlmostEqual(finger(
vk[5]), (3.9689429688683679 + 0.048471952758750547j) / 8, 9)
self.assertAlmostEqual(finger(
vk[6]), (3.6342630872923456 - 0.054892635365850449j) / 8, 9)
self.assertAlmostEqual(finger(
vk[7]), (3.3483735224533548 + 0.040877095049528467j) / 8, 9)
def get_k_kpts(mydf, dm_kpts, hermi=1, kpts=numpy.zeros((1,3)), kpts_band=None,
exxdiv=None):
if mydf._cderi is None or mydf.auxcell is None or not mydf.has_kpts(kpts_band):
mydf.build(kpts_band=kpts_band)
vk_kpts = aft_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, exxdiv)
vk_kpts += df_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, None)
return vk_kpts
def get_jk(self,
dm,
hermi=1,
kpts=None,
kpts_band=None,
with_j=True,
with_k=True,
exxdiv=None):
if kpts is None:
if numpy.all(self.kpts == 0):
# Gamma-point calculation by default
kpts = numpy.zeros(3)
else:
kpts = self.kpts
if kpts.shape == (3, ):
return aft_jk.get_jk(self, dm, hermi, kpts, kpts_band, with_j,
with_k, exxdiv)
vj = vk = None
if with_k:
vk = aft_jk.get_k_kpts(self, dm, hermi, kpts, kpts_band, exxdiv)
if with_j:
vj = aft_jk.get_j_kpts(self, dm, hermi, kpts, kpts_band)
return vj, vk
def get_k_kpts(mydf, dm_kpts, hermi=1, kpts=numpy.zeros((1,3)), kpts_band=None,
exxdiv=None):
if rank != 0: # to apply df_jk._ewald_exxdiv_for_G0 function once
exxdiv = None
vk = aft_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, exxdiv)
vk = mpi.reduce(vk)
return vk
def get_jk(self,
dm,
hermi=1,
kpts=None,
kpts_band=None,
with_j=True,
with_k=True,
omega=None,
exxdiv=None):
if omega is not None: # J/K for RSH functionals
return _sub_df_jk_(self, dm, hermi, kpts, kpts_band, with_j,
with_k, omega, exxdiv)
if kpts is None:
if numpy.all(self.kpts == 0):
# Gamma-point calculation by default
kpts = numpy.zeros(3)
else:
kpts = self.kpts
kpts = numpy.asarray(kpts)
if kpts.shape == (3, ):
return aft_jk.get_jk(self, dm, hermi, kpts, kpts_band, with_j,
with_k, exxdiv)
vj = vk = None
if with_k:
vk = aft_jk.get_k_kpts(self, dm, hermi, kpts, kpts_band, exxdiv)
if with_j:
vj = aft_jk.get_j_kpts(self, dm, hermi, kpts, kpts_band)
return vj, vk
def test_aft_k1_high_cost(self):
kpts = cell.get_abs_kpts([[-.25,-.25,-.25],
[-.25,-.25, .25],
[-.25, .25,-.25],
[-.25, .25, .25],
[ .25,-.25,-.25],
[ .25,-.25, .25],
[ .25, .25,-.25],
[ .25, .25, .25]])
numpy.random.seed(1)
nao = cell.nao_nr()
dm = numpy.random.random((8,nao,nao))
mydf = aft.AFTDF(cell)
mydf.kpts = kpts
numpy.random.seed(1)
dm = numpy.random.random((8,nao,nao))
dm = dm + dm.transpose(0,2,1)
vk = aft_jk.get_k_kpts(mydf, dm, 1, mydf.kpts)
self.assertAlmostEqual(finger(vk[0]), (8.7518173818250702-0.11793770445839372j) /8, 9)
self.assertAlmostEqual(finger(vk[1]), (5.7682393685317894+0.069482280306391239j)/8, 9)
self.assertAlmostEqual(finger(vk[2]), (7.1890462727492324-0.088727079644645671j)/8, 9)
self.assertAlmostEqual(finger(vk[3]), (10.08358152800003+0.1278144339422369j )/8, 9)
self.assertAlmostEqual(finger(vk[4]), (8.393281242945573-0.099410704957774876j) /8, 9)
self.assertAlmostEqual(finger(vk[5]), (7.9413682328898769+0.1015563120870652j) /8, 9)
self.assertAlmostEqual(finger(vk[6]), (7.3743790120272408-0.096290683129384574j)/8, 9)
self.assertAlmostEqual(finger(vk[7]), (6.8144379626901443+0.08071261392857812j) /8, 9)
def get_k_kpts(mydf,
dm_kpts,
hermi=1,
kpts=numpy.zeros((1, 3)),
kpts_band=None,
exxdiv=None):
vk_kpts = aft_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, exxdiv)
vk_kpts += df_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, None)
return vk_kpts
def get_k_kpts(mydf,
dm_kpts,
hermi=1,
kpts=numpy.zeros((1, 3)),
kpts_band=None,
exxdiv=None):
if rank != 0: # to apply df_jk._ewald_exxdiv_for_G0 function once
exxdiv = None
vk = aft_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, exxdiv)
vk = mpi.reduce(vk)
return vk
def get_k_kpts(mydf,
dm_kpts,
hermi=1,
kpts=numpy.zeros((1, 3)),
kpts_band=None,
exxdiv=None):
if exxdiv is not None and exxdiv != 'ewald':
logger.warn(
mydf, 'MDF does not support exxdiv %s. '
'exxdiv needs to be "ewald" or None', exxdiv)
raise RuntimeError('GDF does not support exxdiv %s' % exxdiv)
vk_kpts = aft_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, exxdiv)
vk_kpts += df_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, None)
return vk_kpts
def get_jk(self, dm, hermi=1, kpts=None, kpts_band=None,
with_j=True, with_k=True, exxdiv=None):
if kpts is None:
if numpy.all(self.kpts == 0):
# Gamma-point calculation by default
kpts = numpy.zeros(3)
else:
kpts = self.kpts
if kpts.shape == (3,):
return aft_jk.get_jk(self, dm, hermi, kpts, kpts_band, with_j,
with_k, exxdiv)
vj = vk = None
if with_k:
vk = aft_jk.get_k_kpts(self, dm, hermi, kpts, kpts_band, exxdiv)
if with_j:
vj = aft_jk.get_j_kpts(self, dm, hermi, kpts, kpts_band)
return vj, vk
def test_aft_k(self):
kpts = cell.get_abs_kpts([[-.25,-.25,-.25],
[-.25,-.25, .25],
[-.25, .25,-.25],
[-.25, .25, .25],
[ .25,-.25,-.25],
[ .25,-.25, .25],
[ .25, .25,-.25],
[ .25, .25, .25]])
numpy.random.seed(1)
nao = cell.nao_nr()
dm = numpy.random.random((8,nao,nao))
mydf = aft.AFTDF(cell)
mydf.kpts = kpts
vk = aft_jk.get_k_kpts(mydf, dm, 0, mydf.kpts)
self.assertAlmostEqual(finger(vk[0]), (4.3373802352168278-0.062977052131451577j)/8, 9)
self.assertAlmostEqual(finger(vk[1]), (2.878809181709983+0.028843869853690692j) /8, 9)
self.assertAlmostEqual(finger(vk[2]), (3.7027622609953061-0.052034330663180237j)/8, 9)
self.assertAlmostEqual(finger(vk[3]), (5.0939994842559422+0.060094478876149444j)/8, 9)
self.assertAlmostEqual(finger(vk[4]), (4.2942087551592651-0.061138484763336887j)/8, 9)
self.assertAlmostEqual(finger(vk[5]), (3.9689429688683679+0.048471952758750547j)/8, 9)
self.assertAlmostEqual(finger(vk[6]), (3.6342630872923456-0.054892635365850449j)/8, 9)
self.assertAlmostEqual(finger(vk[7]), (3.3483735224533548+0.040877095049528467j)/8, 9)
def get_k_kpts(mydf, dm_kpts, hermi=1, kpts=numpy.zeros((1,3)), kpts_band=None,
exxdiv=None):
vk_kpts = aft_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, exxdiv)
vk_kpts += df_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpts_band, None)
return vk_kpts
