def test_reweighting():
my_obs = pe.Obs([np.random.rand(1000)], ['t'])
assert not my_obs.reweighted
r_obs = pe.reweight(my_obs, [my_obs])
assert r_obs[0].reweighted
r_obs2 = r_obs[0] * my_obs
assert r_obs2.reweighted
my_irregular_obs = pe.Obs([np.random.rand(500)], ['t'],
idl=[range(1, 1001, 2)])
assert not my_irregular_obs.reweighted
r_obs = pe.reweight(my_obs, [my_irregular_obs], all_configs=True)
r_obs = pe.reweight(my_obs, [my_irregular_obs], all_configs=False)
r_obs = pe.reweight(my_obs, [my_obs])
assert r_obs[0].reweighted
r_obs2 = r_obs[0] * my_obs
assert r_obs2.reweighted
my_covobs = pe.cov_Obs(1.0, 0.003, 'cov')
with pytest.raises(Exception):
pe.reweight(my_obs, [my_covobs])
my_obs2 = pe.Obs([np.random.rand(1000)], ['t2'])
with pytest.raises(Exception):
pe.reweight(my_obs, [my_obs + my_obs2])
with pytest.raises(Exception):
pe.reweight(my_irregular_obs, [my_obs])
def test_rwms():
path = './tests//data/openqcd_test/'
prefix = 'sfqcd'
postfix = '.rwms'
# sfqcd-1.6: Trajectories instead of confignumbers are printed to file.
rwfo = pe.input.openQCD.read_rwms(path, prefix, version='1.6', postfix=postfix)
repname = list(rwfo[0].idl.keys())[0]
assert(rwfo[0].idl[repname] == range(1, 13))
rwfo = pe.input.openQCD.read_rwms(path, prefix, version='1.6', postfix=postfix, r_start=[1], r_stop=[12])
assert(rwfo[0].idl[repname] == range(1, 13))
rwfo = pe.input.openQCD.read_rwms(path, prefix, version='1.6', postfix=postfix, r_start=[3], r_stop=[8])
assert(rwfo[0].idl[repname] == range(3, 9))
rwfo = pe.input.openQCD.read_rwms(path, prefix, version='1.6', postfix=postfix, r_start=[2], r_stop=[6])
assert(rwfo[0].idl[repname] == range(2, 7))
rwfs = pe.input.openQCD.read_rwms(path, prefix, version='1.6', postfix=postfix, r_start=[1], r_stop=[12], r_step=2)
assert(rwfs[0].idl[repname] == range(1, 12, 2))
rwfs = pe.input.openQCD.read_rwms(path, prefix, version='1.6', postfix=postfix, r_start=[2], r_stop=[12], r_step=2)
assert(rwfs[0].idl[repname] == range(2, 13, 2))
rwfo = pe.input.openQCD.read_rwms(path, prefix, version='1.6', postfix=postfix)
assert((rwfo[0].r_values[repname] + rwfo[0].deltas[repname][1]) == (rwfs[0].r_values[repname] + rwfs[0].deltas[repname][0]))
o = pe.pseudo_Obs(1., .01, repname, samples=12)
pe.reweight(rwfo[0], [o])
o = pe.pseudo_Obs(1., .01, repname, samples=6)
pe.reweight(rwfo[0], [o])
o.idl[repname] = range(2, 13, 2)
pe.reweight(rwfo[0], [o])
pe.reweight(rwfs[0], [o])
files = ['openqcd2r1.ms1.dat']
names = ['openqcd2|r1']
# TM with 2 Hasenbusch factors and 2 sources each + RHMC with one source, openQCD 2.0
rwfo = pe.input.openQCD.read_rwms(path, prefix, version='2.0', files=files, names=names)
assert(len(rwfo) == 2)
assert(rwfo[0].value == 0.9999974970236312)
assert(rwfo[1].value == 1.184681251089919)
repname = list(rwfo[0].idl.keys())[0]
assert(rwfo[0].idl[repname] == range(1, 10))
rwfo = pe.input.openQCD.read_rwms(path, prefix, version='2.0', files=files, names=names, r_start=[1], r_stop=[8], print_err=True)
assert(rwfo[0].idl[repname] == range(1, 9))
# t0
prefix = 'openqcd'
t0 = pe.input.openQCD.extract_t0(path, prefix, dtr_read=3, xmin=0, spatial_extent=4)
files = ['openqcd2r1.ms.dat']
names = ['openqcd2|r1']
t0 = pe.input.openQCD.extract_t0(path, '', dtr_read=3, xmin=0, spatial_extent=4, files=files, names=names, fit_range=2)
t0 = pe.input.openQCD.extract_t0(path, prefix, dtr_read=3, xmin=0, spatial_extent=4, r_start=[1])
repname = list(rwfo[0].idl.keys())[0]
assert(t0.idl[repname] == range(1, 10))
t0 = pe.input.openQCD.extract_t0(path, prefix, dtr_read=3, xmin=0, spatial_extent=4, r_start=[2], r_stop=[8])
repname = list(rwfo[0].idl.keys())[0]
assert(t0.idl[repname] == range(2, 9))
t0 = pe.input.openQCD.extract_t0(path, prefix, dtr_read=3, xmin=0, spatial_extent=4, fit_range=2, plaquette=True, assume_thermalization=True)
pe.input.openQCD.extract_t0(path, '', dtr_read=3, xmin=0, spatial_extent=4, files=files, names=names, fit_range=2, plot_fit=True)
def test_correlate():
my_obs1 = pe.Obs([np.random.rand(100)], ['t'])
my_obs2 = pe.Obs([np.random.rand(100)], ['t'])
corr1 = pe.correlate(my_obs1, my_obs2)
corr2 = pe.correlate(my_obs2, my_obs1)
assert corr1 == corr2
my_obs3 = pe.Obs([np.random.rand(100)], ['t'], idl=[range(2, 102)])
with pytest.raises(Exception):
pe.correlate(my_obs1, my_obs3)
my_obs4 = pe.Obs([np.random.rand(99)], ['t'])
with pytest.raises(Exception):
pe.correlate(my_obs1, my_obs4)
my_obs5 = pe.Obs([np.random.rand(100)], ['t'], idl=[range(5, 505, 5)])
my_obs6 = pe.Obs([np.random.rand(100)], ['t'], idl=[range(5, 505, 5)])
corr3 = pe.correlate(my_obs5, my_obs6)
assert my_obs5.idl == corr3.idl
my_new_obs = pe.Obs([np.random.rand(100)], ['q3'])
with pytest.raises(Exception):
pe.correlate(my_obs1, my_new_obs)
my_covobs = pe.cov_Obs(1.0, 0.003, 'cov')
with pytest.raises(Exception):
pe.correlate(my_covobs, my_covobs)
r_obs = pe.reweight(my_obs1, [my_obs1])[0]
with pytest.warns(RuntimeWarning):
pe.correlate(r_obs, r_obs)
def test_json_corr_io():
my_list = [
pe.Obs([np.random.normal(1.0, 0.1, 100)], ['ens1']) for o in range(8)
]
rw_list = pe.reweight(pe.Obs([np.random.normal(1.0, 0.1, 100)], ['ens1']),
my_list)
for obs_list in [my_list, rw_list]:
for tag in [None, "test"]:
obs_list[3].tag = tag
for pad in [0, 2]:
for corr_tag in [None, 'my_Corr_tag']:
for prange in [None, [3, 6]]:
for gap in [False, True]:
my_corr = pe.Corr(obs_list,
padding=[pad, pad],
prange=prange)
my_corr.tag = corr_tag
if gap:
my_corr.content[4] = None
pe.input.json.dump_to_json(my_corr, 'corr')
recover = pe.input.json.load_json('corr')
os.remove('corr.json.gz')
assert np.all([
o.is_zero() for o in [
x for x in (my_corr - recover)
if x is not None
]
])
for index, entry in enumerate(my_corr):
if entry is None:
assert recover[index] is None
assert my_corr.tag == recover.tag
assert my_corr.prange == recover.prange
assert my_corr.reweighted == recover.reweighted