def test_hmc(total_site, ga):
#
q.qmkdir_info("results")
q.qmkdir_info("results/gf_info")
q.qmkdir_info("results/wilson_flow_energy_info")
q.qmkdir_info("results/gm_force_info")
#
geo = q.Geometry(total_site, 1)
rs = q.RngState("test_hmc-{}x{}x{}x{}".format(total_site[0], total_site[1],
total_site[2],
total_site[3]))
gf = q.GaugeField(geo)
q.set_unit(gf)
traj = 0
for i in range(4):
traj += 1
run_hmc(gf, ga, traj, rs.split("hmc-{}".format(traj)))
plaq_avg = q.gf_avg_plaq(gf)
plaq_sum = np.prod(total_site) * 6.0 * (1.0 - plaq_avg)
q.displayln_info("test_hmc: traj={} ; plaq_avg={}".format(
traj, plaq_avg))
if traj % 2 == 0:
q.display_gauge_field_info_table_with_wilson_flow(
"results/gf_info/traj={}.lat".format(traj),
"results/wilson_flow_energy_info/traj={}.lat".format(traj), gf,
0.1, 5, 2)
q.save_gm_force_magnitudes_list(
"results/gm_force_info/traj={}.lat".format(traj))
def run(job_tag, traj):
q.qmkdir_info(f"locks")
q.qmkdir_info(get_save_path(f""))
q.qmkdir_info(get_save_path(f"eig"))
q.qmkdir_info(get_save_path(f"eig/{job_tag}"))
q.qmkdir_info(get_save_path(f"configs"))
q.qmkdir_info(get_save_path(f"configs/{job_tag}"))
#
total_site = ru.get_total_site(job_tag)
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
#
path_gf = get_load_path(f"configs/{job_tag}/ckpoint_lat.{traj}")
if path_gf is None:
gf = mk_sample_gauge_field(job_tag, traj)
gf.show_info()
gf.save(get_save_path(f"configs/{job_tag}/ckpoint_lat.{traj}"))
else:
gf = q.GaugeField()
gf.load(path_gf)
#
if q.obtain_lock(f"locks/{job_tag}-{traj}-compute-eig"):
get_eig = compute_eig(gf,
job_tag,
inv_type=0,
path=f"eig/{job_tag}/traj={traj}")
test_eig(gf, get_eig(), job_tag, inv_type=0)
q.release_lock()
def get_fgrid(total_site, fermion_params):
geo = q.Geometry(total_site, 1)
gf = q.GaugeField(geo)
gf.set_unit()
gpt_gf = g.convert(gpt_from_qlat(gf), g.single)
if "omega" in fermion_params:
qm = g.qcd.fermion.zmobius(gpt_gf, fermion_params)
else:
qm = g.qcd.fermion.mobius(gpt_gf, fermion_params)
return qm.F_grid_eo
def qlat_from_gpt_ff4d(gpt_ff):
ctype = "WilsonVector"
total_site = gpt_ff.grid.fdimensions
multiplicity = 1
tag = "qlat_from_gpt"
plan = get_qlat_gpt_copy_plan(ctype, total_site, multiplicity, tag)
geo = q.Geometry(total_site, 1)
ff = q.FermionField4d(geo)
plan(ff.mview(), gpt_ff)
return ff
def mk_sample_gauge_field(job_tag, traj):
rs = q.RngState(f"seed {job_tag} {traj}").split("mk_sample_gauge_field")
total_site = ru.get_total_site(job_tag)
geo = q.Geometry(total_site, 1)
gf = q.GaugeField(geo)
gf.set_rand(rs, sigma=0.25, n_step=4)
for i in range(4):
q.gf_wilson_flow_step(gf, 0.05)
gf.unitarize()
return gf
def qlat_from_gpt_prop(gpt_prop):
ctype = "WilsonMatrix"
total_site = gpt_prop.grid.fdimensions
multiplicity = 1
tag = "qlat_from_gpt"
plan = get_qlat_gpt_copy_plan(ctype, total_site, multiplicity, tag)
geo = q.Geometry(total_site, 1)
prop_msc = q.Prop(geo)
plan(prop_msc.mview(), gpt_prop)
prop_wm = q.Prop(geo)
q.convert_wm_from_mspincolor_prop(prop_wm, prop_msc)
return prop_wm
def qlat_from_gpt_gauge_field(gpt_gf):
assert len(gpt_gf) == 4
ctype = "ColorMatrix"
total_site = gpt_gf[0].grid.fdimensions
multiplicity = 1
tag = "qlat_from_gpt"
plan = get_qlat_gpt_copy_plan(ctype, total_site, multiplicity, tag)
geo = q.Geometry(total_site, 1)
fs = [q.Field(ctype, geo) for i in range(4)]
assert len(fs) == 4
for i in range(4):
plan(fs[i].mview(), gpt_gf[i])
gf = q.GaugeField()
q.merge_fields(gf, fs)
return gf
def mk_qlat_gpt_copy_plan(ctype, total_site, multiplicity, tag):
geo = q.Geometry(total_site, multiplicity)
f_gpt = mk_gpt_field(ctype, geo)
f_qlat = q.Field(ctype, geo)
lexicographic_coordinates = g.coordinates(f_gpt)
buf = f_qlat.mview()
if tag == "qlat_from_gpt":
qlat_from_gpt = g.copy_plan(buf, f_gpt)
qlat_from_gpt.destination += g.global_memory_view(
f_gpt.grid, [[f_gpt.grid.processor, buf, 0, buf.nbytes]])
qlat_from_gpt.source += f_gpt.view[lexicographic_coordinates]
qlat_from_gpt = qlat_from_gpt(local_only=True)
return qlat_from_gpt
elif tag == "gpt_from_qlat":
gpt_from_qlat = g.copy_plan(f_gpt, buf)
gpt_from_qlat.source += g.global_memory_view(
f_gpt.grid, [[f_gpt.grid.processor, buf, 0, buf.nbytes]])
gpt_from_qlat.destination += f_gpt.view[lexicographic_coordinates]
gpt_from_qlat = gpt_from_qlat(local_only=True)
return gpt_from_qlat
else:
q.displayln_info(tag)
raise Exception("mk_qlat_gpt_copy_plan")
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
qg.begin_with_gpt()
rs = q.RngState("seed")
total_site = [4, 4, 4, 8]
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
gf = q.GaugeField(geo)
gf.set_rand(rs, 0.2, 2)
gf.show_info()
test_gf(gf)
for i in range(16):
xg = [
rs.rand_gen() % total_site[0],
rs.rand_gen() % total_site[1],
rs.rand_gen() % total_site[2],
rs.rand_gen() % total_site[3]
]
#!/usr/bin/env python3
import qlat_gpt as qg
import qlat as q
import gpt as g
qg.begin_with_gpt()
q.qremove_all_info("results")
q.qmkdir_info("results")
rs = q.RngState("seed")
geo = q.Geometry([4, 4, 4, 8], 1)
q.displayln_info("geo.show() =", geo.show())
gf = q.GaugeField(geo)
gf.set_rand(rs.split("gf-init"), 0.05, 2)
gf.show_info()
mobius_params = {
"mass": 0.1,
"M5": 1.0,
"b": 1.0,
"c": 0.0,
"Ls": 8,
"boundary_phases": [1.0, 1.0, 1.0, 1.0],
}
gpt_gf = qg.gpt_from_qlat(gf)