def get_systematic():
psqlpwd = pwd.passwd()
psql = sql.pysql('cchang5', 'cchang5', psqlpwd)
# get data
data_idx = select_data()
ens = data_idx.keys()[0]
l = []
for n in range(len(data_idx[ens].keys()) - 1):
# read gA and gV
sqlcmd = "SELECT (result->>'gA00')::double precision / (result->>'gV00')::double precision FROM callat_proj.ga_v1_bs g JOIN callat_corr.hisq_bootstrap b ON g.bs_id=b.id WHERE g.ga_v1_id=%s AND mbs=%s ORDER BY nbs;" % (
data_idx[ens]['gA%s' % n], data_idx[ens]['mbs'])
psql.cur.execute(sqlcmd)
gA = np.array(psql.cur.fetchall()).flatten()
l.append(gA)
l = np.array(l).T
lgv = gv.dataset.avg_data(l, spread=True, median=False)
#print lgv
print np.mean(lgv)
b0 = l[0, :]
b0mean = np.mean(b0)
#print b0mean
cov = np.cov(l, rowvar=False)
#print np.std(l,axis=0)
SA = np.einsum('ij,j->i', cov, np.ones(len(b0)))
#print SA
ASA = np.einsum('i,i->', np.ones(len(b0)), SA)
#print ASA
print b0mean, np.sqrt(ASA) / len(b0)
def get_bootstrap_list():
psqlpwd = pwd.passwd()
psql = sql.pysql('cchang5', 'cchang5', psqlpwd)
# get data
data_idx = select_data()
for ens in data_idx.keys():
sqlcmd = "SELECT draws FROM callat_corr.hisq_bootstrap bs JOIN callat_corr.hisq_ensembles e ON bs.hisq_ensembles_id=e.id WHERE e.tag='%s' ORDER BY nbs LIMIT 500;" % ens
psql.cur.execute(sqlcmd)
nbs = psql.cur.fetchall()
nbs = np.array(
[np.array(nbs[i][0])[:len(nbs[0][0])] for i in range(len(nbs))])
s = ''
for i in tqdm.tqdm(range(len(nbs))):
for j in range(len(nbs[0])):
if j == len(nbs[0]) - 1:
s += '%s' % nbs[i, j]
else:
s += '%s,' % nbs[i, j]
s += '\n'
with open('./nbslist/nbs_%s.csv' % ens, 'w+') as f:
f.write(s)
return
def get_bootstrap():
psqlpwd = pwd.passwd()
psql = sql.pysql('cchang5', 'cchang5', psqlpwd)
# get data
data_idx = select_data()
data = dict()
data['gA'] = {}
data['Fpi'] = {}
data['mpi'] = {}
data['mju'] = {}
data['epi'] = {}
data['eju'] = {}
data['ml'] = {}
data['Z0p'] = {}
data['mres'] = {}
data['aw0'] = {}
data['a2DI'] = {}
for e in data_idx.keys():
# read gA and gV
sqlcmd = "SELECT (result->>'gA00')::double precision / (result->>'gV00')::double precision FROM callat_proj.ga_v1_bs g JOIN callat_corr.hisq_bootstrap b ON g.bs_id=b.id WHERE g.ga_v1_id=%s AND mbs=%s ORDER BY nbs;" % (
data_idx[e]['gA'], data_idx[e]['mbs'])
psql.cur.execute(sqlcmd)
gA = np.array(psql.cur.fetchall()).flatten()
# read data from DB get E0 and Z0_p
sqlcmd = "SELECT (result->>'E0')::double precision FROM callat_proj.meson_v1_bs bn JOIN callat_corr.hisq_bootstrap bs ON bn.bs_id = bs.id WHERE bn.meson_v1_id=%s AND mbs=%s ORDER BY nbs;" % (
data_idx[e]['mpi'], data_idx[e]['mbs'])
psql.cur.execute(sqlcmd)
E = np.array(psql.cur.fetchall()).flatten()
sqlcmd = "SELECT (result->>'Z0_p')::double precision FROM callat_proj.meson_v1_bs bn JOIN callat_corr.hisq_bootstrap bs ON bn.bs_id = bs.id WHERE bn.meson_v1_id=%s AND mbs=%s ORDER BY nbs;" % (
data_idx[e]['mpi'], data_idx[e]['mbs'])
psql.cur.execute(sqlcmd)
Z = np.array(psql.cur.fetchall()).flatten()
# read mres from DB
sqlcmd = "SELECT (result->>'mres')::double precision FROM callat_proj.mres_v1_bs bn JOIN callat_corr.hisq_bootstrap bs ON bn.bs_id = bs.id WHERE bn.mres_v1_id=%s AND mbs=%s ORDER BY nbs;" % (
data_idx[e]['mres'], data_idx[e]['mbs'])
psql.cur.execute(sqlcmd)
mres = np.array(psql.cur.fetchall()).flatten()
# read ml
sqlcmd = "SELECT p.mval::double precision FROM callat_proj.mres_v1 m JOIN callat_corr.dwhisq_corr_jmu j ON m.mp_id = j.id JOIN callat_corr.dwhisq_props p ON j.dwhisq_prop_id = p.id WHERE m.id = '%s';" % data_idx[
e]['mres']
psql.cur.execute(sqlcmd)
ml = psql.cur.fetchone()[0]
# read mju
sqlcmd = "SELECT (result->>'E0')::double precision FROM callat_proj.mixed_v1_bs bn JOIN callat_corr.hisq_bootstrap bs ON bn.bs_id = bs.id WHERE bn.mixed_v1_id=%s AND mbs=%s ORDER BY nbs;" % (
data_idx[e]['mju'], data_idx[e]['mbs'])
psql.cur.execute(sqlcmd)
Eju = np.array(psql.cur.fetchall()).flatten()
# read aw0 and a2DI
sqlcmd = "SELECT id FROM callat_corr.hisq_ensembles WHERE tag='%s';" % e
psql.cur.execute(sqlcmd)
hisq_id = psql.cur.fetchone()[0]
sqlcmd = "SELECT aw0 FROM callat_corr.hisq_params_bootstrap WHERE hisq_ensembles_id=%s ORDER BY nbs;" % hisq_id
psql.cur.execute(sqlcmd)
aw0 = np.array(psql.cur.fetchall()).flatten()
sql.cmd = "SELECT a2di FROM callat_corr.hisq_params_bootstrap WHERE hisq_ensembles_id=%s ORDER BY nbs;" % hisq_id
psql.cur.execute(sqlcmd)
a2di = np.array(psql.cur.fetchall()).flatten()
# make data
data['gA'][e] = gA
data['Fpi'][e] = fpi(ml, E, Z, mres)
data['epi'][e] = E / (4. * np.pi * data['Fpi'][e])
data['eju'][e] = Eju / (4. * np.pi * data['Fpi'][e])
data['mpi'][e] = E
data['mju'][e] = Eju
data['mres'][e] = mres
data['ml'][e] = ml
data['Z0p'][e] = Z
data['aw0'][e] = aw0
data['a2DI'][e] = a2di
return data
tbl_print['A1'] = [boot0fit['pmean'][t]['A1'] for t in range(len(boot0fit['pmean']))]
tbl_print['dA1'] = [boot0fit['psdev'][t]['A1'] for t in range(len(boot0fit['pmean']))]
tbl_print['chi2/dof'] = np.array(boot0fit['chi2'])/np.array(boot0fit['dof'])
tbl_print['logGBF'] = boot0fit['logGBF']
print tabulate(tbl_print, headers='keys')
return {'mixed_meson_fit': boot0fit['rawoutput'][0]}
if __name__=='__main__':
# read master
f = open('./mixed.yml','r')
params = yaml.load(f)
f.close()
# yaml entires
fitmeta = params['mixed_fit']
# log in sql
psqlpwd = pwd.passwd()
psql = sql.pysql('cchang5','cchang5',psqlpwd)
## bootstrap decay constant
# phi_ju
dataju = read_mixed_meson(psql,params,'phi_ju')
gvdataju = c51.make_gvars(dataju)
resp = fit_mixed_meson(psql,params,'phi_ju', gvdataju)
print resp['mixed_meson_fit']
### phi_js
#data = read_mixed_meson(psql,params,'phi_js')
#data = data[:200]
#datagv = c51.make_gvars(data)
#resp = fit_mixed_meson(psql,params,'phi_js', datagv)
### phi_ru
#data = read_mixed_meson(psql,params,'phi_ru')
ncfg = len(data)
databs = []
for n in range(nbs):
a = []
for m in range(ncfg):
a.append(np.random.randint(ncfg))
databs.append(np.mean(data[a,:],axis=0))
return np.array(databs)
if __name__=='__main__':
# options
t = 10 # time slice plotted
nbs = 10000 # bootstrap sampling for mean
# read master
f = open('./fh.yml','r')
params = yaml.load(f)
f.close()
# log in sql
psqlpwd = pwd.passwd()
psql = sql.pysql('cchang5','cchang5',psqlpwd)
# read gA
SS, PS, fhSS, fhPS = read_gA_bs(psql,params)
# pick
corr = SS
filename = 'SS'
# bootstrap this
corrbs = bootstrap(corr,nbs)
# plot histogram
plot_histogram(corr[:,t], corrbs[:,t], t, 't=%s' %str(t), filename)
plt.show()
