def apply_unary_operator(self, opcode, o, i):
assert len(i.v_obj) == len(o.v_obj)
assert len(i.v_obj) == (len(self.obj)) ** 0.5
tmp = gpt.lattice(o)
o[:] = 0.0
for m in range(len(i.v_obj)):
tmp[:] = 0.0
for n in range(len(i.v_obj)):
cgpt.apply_fermion_operator(
self.obj[n * len(i.v_obj) + m], opcode, i.v_obj[n], tmp.v_obj[m]
)
o += tmp
def apply_unary_operator(self, opcode, o, i):
assert len(i.v_obj) == len(o.v_obj)
assert len(i.v_obj) == (len(self.obj))**0.5
if len(i.v_obj) == 1:
cgpt.apply_fermion_operator(self.obj[0], opcode, i.v_obj[0],
o.v_obj[0])
else:
tmp = self.tmp if o.checkerboard() is gpt.none else self.tmp_eo
for n in range(len(i.v_obj)):
for m in range(len(i.v_obj)):
cgpt.apply_fermion_operator(
self.obj[n * len(i.v_obj) + m],
opcode,
i.v_obj[n],
o.v_obj[m] if n == 0 else tmp.v_obj[m],
)
if n != 0:
o += tmp
def apply_unary_operator(self, opcode, o, i):
assert len(i.v_obj) == 1
assert len(o.v_obj) == 1
# Grid has different calling conventions which we adopt in cgpt:
return cgpt.apply_fermion_operator(self.obj, opcode, i.v_obj[0],
o.v_obj[0])
def unary(self, opcode, i, o):
assert (len(i.v_obj) == 1)
assert (len(o.v_obj) == 1)
return cgpt.apply_fermion_operator(self.obj, opcode, i.v_obj[0],
o.v_obj[0])