def mk_src(geo):
src = q.mk_point_src(geo, [0, 0, 0, 0])
grid = qg.mk_grid(geo)
g_src = g.mspincolor(grid)
g.create.point(g_src, [0, 0, 0, 0])
src1 = qg.qlat_from_gpt(g_src)
src1 -= src
assert src1.qnorm() == 0.0
return src
def test_src(xg):
q.displayln_info(f"test_src: xg={xg}")
#
src_q = q.mk_point_src(geo, xg)
#
grid = qg.mk_grid(geo)
g_src_gpt = g.mspincolor(grid)
g.create.point(g_src_gpt, xg)
src_g = qg.qlat_from_gpt(g_src_gpt)
#
src_diff = src_q.copy()
src_diff -= src_g
#
q.displayln_info(src_q.qnorm(), src_g.qnorm(), src_diff.qnorm())
assert src_diff.qnorm() == 0
"b": 1.0,
"c": 0.0,
"Ls": 32,
"boundary_phases": [1.0, 1.0, 1.0, 1.0],
}
gpt_gf = qg.gpt_from_qlat(gf)
qm = g.qcd.fermion.mobius(gpt_gf, mobius_params)
pc = g.qcd.fermion.preconditioner
inv = g.algorithms.inverter
cg = inv.cg({"eps": 1e-11, "maxiter": 10000})
slv_5d = inv.preconditioned(pc.eo2_ne(), cg)
slv_qm = qm.propagator(slv_5d)
ginv = qg.InverterGPT(inverter=slv_qm, timer=q.Timer("py:InverterGPT"))
src_p = q.mk_point_src(geo, [0, 0, 0, 0])
src_r = q.Prop(geo)
src_r.set_rand(rs.split("src_r"))
for src in [src_p, src_r]:
sol = qinv * src
sol1 = ginv * src
sol_diff = sol1.copy()
sol_diff -= sol
q.displayln_info(sol.qnorm(), sol1.qnorm(), sol_diff.qnorm())
q.timer_display()