def test_kisa3():
logger = getLogger('ostap.test_kisa3')
if 62400 <= ROOT.gROOT.GetVersionInt() < 62406:
logger.warning('Test can fail for %s' % ROOT.gROOT.GetVersion())
h1 = ROOT.TH1D('h1', '', 100, 0, 20)
h1 += lambda x: x
## from ostap.trees.funcs import H1DFunc
## xh1 = H1DFunc ( histo = h1 , xvar = 'pt' )
## from ostap.trees.funcs import FuncTH1
## xh1 = FuncTH1 ( histo = h1 , xvar = 'pt' )
from ostap.fitting.pyselectors import SelectorWithVars, Variable
variables = [
## Variable ( 'mass1' , 'mass(mu+mu-)' , 2 , 4 , lambda s : s.mass ) ,
Variable('mass', 'mass(mu+mu-)', 3.09, 3.11),
Variable('c2dtf', 'chi2(dtf)', -1, 10),
## Variable ( 'xpt' , 'xpt' , -1 , 30 , xh1 ) ,
Variable('mass2', 'mass(mu+mu-)', 1, 5, MASS()),
Variable('mass3', 'mass(mu+mu-)', 1, 5, 'mass')
]
with timing('fill it!'):
selector = SelectorWithVars(
variables=variables,
selection='2<=mass && mass<4 && 0<=c2dtf && c2dtf<5',
silence=True)
chain = data.chain
st = chain.pprocess(selector, silent=False, shortcut=True)
ds = selector.data
del selector
logger.info('Dataset (paralell):\n%s' % ds.table(prefix='# '))
def test_kisa2 () :
logger = getLogger ( 'ostap.test_kisa2' )
if 62400 <= ROOT.gROOT.GetVersionInt() < 62406 :
logger.warning ('Test can fail for %s' % ROOT.gROOT.GetVersion() )
from ostap.fitting.pyselectors import SelectorWithVars, Variable
variables = [
Variable ( 'mass' , 'mass(mu+mu-)' , 3.09 , 3.11 ) ,
Variable ( 'c2dtf' , 'chi2(dtf)' , -1 , 10 ) ,
Variable ( 'mass2' , 'mass(mu+mu-)' , 1 , 5 , MASS() ) ,
Variable ( 'mass3' , 'mass(mu+mu-)' , 1 , 5 , 'mass' )
]
from sys import version_info as python_version
if python_version.major < 3 :
variables.append ( Variable ( 'mass1' , 'mass(mu+mu-)' , 2 , 4 , lambda s : s.mass ) )
ppservers = () ## 'lxplus051' , )
## ppservers = 'auto'
nf = len ( data.files )
nf //= 40
nf += 1
nf = min ( nf , 25 )
with timing('%d files in sequence %s' % ( nf , len( data.chain ) ) ) :
selector = SelectorWithVars (
variables = variables ,
selection = '2<=mass && mass<4 && 0<=c2dtf && c2dtf<5' ,
silence = False
)
chain = data.chain[:nf]
st = chain.process ( selector , silent = False , shortcut = True )
ds = selector.data
del selector
logger.info ( 'Dataset (sequential):\n%s' % ds.table() )
with timing('%s files in parallel %s' % ( len ( data.files ) , len( data.chain ) ) ) :
selector = SelectorWithVars (
variables = variables ,
selection = '2<=mass && mass<4 && 0<=c2dtf && c2dtf<5' ,
silence = True
)
st = data.chain.parallel_fill ( selector ,
silent = False ,
chunk_size = -1 ,
max_files = 1 ,
ppservers = ppservers )
ds = selector.data
del selector
logger.info ( 'Dataset (paralell):\n%s' % ds.table ( prefix = '# ' ) )
## os.remove ( trainer.output_file )
# =============================================================================
## Use trained TMVA
# There are two alternatives
# - usage of TMVA Reader : it can be rather slow,
# but it is very flexible and powerful with respect to variable transformations
# - addTMVAResponse function : it is less flexible, but very CPU efficient
# =============================================================================
## prepare dataset with TMVA result
from ostap.fitting.pyselectors import SelectorWithVars, Variable
## 1) Book RooDataset
variables = [
Variable('var1', 'variable#1'),
Variable('var2', 'variable#2'),
Variable('var3', 'variable#3'),
]
## 2) create TMVA reader
from ostap.tools.tmva import Reader
reader = Reader('MyMLP',
variables=[('var1', lambda s: s.var1),
('var2', lambda s: s.var2),
('var3', lambda s: s.var3)],
weights_files=tar_file)
methods = reader.methods[:]
## # =============================================================================
from ostap.fitting.pyselectors import SelectorWithVars, Variable
import ostap.parallel.parallel_fill
# =============================================================================
## configuration of reweighting
weightings = (
## variable address in DB
Weight.Var('x', 'x-reweight'),
Weight.Var('y', 'y-reweight'),
Weight.Var(('x', 'y'), '2D-reweight'),
)
# =============================================================================
## variables to be used in MC-dataset
variables = [
Variable('x', 'x-var', 0, 20),
Variable('y', 'y-var', 0, 15),
]
selector = SelectorWithVars(variables,
'0<x && x<20 && 0<y && y<20',
silence=True)
mctree.process(selector, silent=True)
mcds_ = selector.data ## dataset
# =============================================================================
## start reweighting iterations:
for iter in range(1, maxIter + 1):
tag = 'Reweighting iteration #%d' % iter
logger.info(allright(tag))
with timing(tag + ': prepare MC-dataset:', logger=logger):
## Use trained TMVA/Chopping
# There are two alternatives
# - usage of TMVA/Chopper Reader : it can be rather slow,
# but it is very flexible and powerful with respect to variable transformations
# - addChoppingResponse function : it is less flexible, but very CPU efficient
# =============================================================================
## category function
category = lambda s: int(s.evt * 137 + 813 * s.run) % N
## prepare dataset with TMVA/Chopping result
from ostap.fitting.pyselectors import SelectorWithVars, Variable
## 1) Book RooDataset
variables = [
Variable('var1', 'variable#1'),
Variable('var2', 'variable#2'),
Variable('var3', 'variable#3'),
## extra: needed for addChoppingResponse
Variable('evt', 'event'),
Variable('run', 'run'),
## extra: needed for cross-checks
Variable('cat', 'category', accessor=category),
]
## 2) create TMVA/Chopping reader
from ostap.tools.chopping import Reader
reader = Reader(
N=N, ## number of categories
categoryfunc=category, ## category
else:
logger.info('Existing weights DBASE will be used')
#
## make reweighting iterations
#
from ostap.tools.reweight import Weight, makeWeights, WeightingPlot, W2Data
from ostap.fitting.pyselectors import SelectorWithVars, Variable
import ostap.parallel.parallel_fill
# =============================================================================
## weighting configuration: ## variable address in DB
weighting = (Weight.Var('x', address='x-reweight'), )
# ============================================================================
## variables to be used in MC-dataset
variables = [Variable('x', 'x-variable', 0, 100)]
# =============================================================================
## start iterations:
for iter in range(1, maxIter + 1):
tag = 'Reweighting iteration #%d' % iter
logger.info(allright(tag))
with timing(tag + ': prepare MC-dataset:', logger=logger):
# =============================================================================
## 0) The weighter object
weighter = Weight(dbname, weighting)
# ===============================================================================
def test_fitting_fill_1():
## if 1 < 2 :
logger = getLogger('test_fitting_fill_1')
## prepare data
with timing("Prepare test data", logger=logger):
files = prepare_data(4, 5000)
data = Data('S', files)
chain = data.chain
mJPsi = ROOT.RooRealVar('mJPsi', 'mass(J/Psi) [GeV]', 3.0 * GeV, 3.2 * GeV)
# =========================================================================
logger.info(attention('All trivial variables'))
# =========================================================================
variables = [
Variable(mJPsi, accessor='mass'),
Variable('massMeV', 'mass in MeV', 3000, 3200, 'mass*1000.0'),
Variable('vv102', 'vv10[2]', -1, 100, '1.0*vv10[2]'),
Variable('fevt', accessor='1.0*evt'), ('pt', ), ('eta', ),
('x', 'some variable', 0, 5000, '(mass+pt+eta)/eta')
]
config = {'variables': variables, 'selection': "pt>7 && eta<3"}
with timing("No SHORTCUT, no FRAME", logger=None) as t1:
logger.info(attention(t1.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=False, use_frame=False)
ds1_1 = selector.data
with timing(" SHORTCUT, no FRAME", logger=None) as t2:
logger.info(attention(t2.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=True, use_frame=False)
ds1_2 = selector.data
with timing("No SHORTCUT, FRAME", logger=None) as t3:
logger.info(attention(t3.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=False, use_frame=True)
ds1_3 = selector.data
with timing(" SHORTCUT, FRAME", logger=None) as t4:
logger.info(attention(t4.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=True, use_frame=True)
ds1_4 = selector.data
if DataSet_NEW_FILL:
with timing(" pure-FRAME (new) ", logger=None) as t5:
logger.info(attention(t5.name))
ds1_5, _ = chain.make_dataset(silent=False, **config)
table = [('Configuration', 'CPU')]
table.append((t1.name, '%.3fs' % t1.delta))
table.append((t2.name, '%.3fs' % t2.delta))
table.append((t3.name, '%.3fs' % t3.delta))
table.append((t4.name, '%.3fs' % t4.delta))
if DataSet_NEW_FILL:
table.append((t5.name, '%.3fs' % t5.delta))
title1 = "All trivial variables"
table1 = T.table(table, title=title1, prefix='# ', alignment='rr')
logger.info('%s\n%s' % (title1, table1))
if ds1_1 != ds1_2:
logger.error('Datasets ds1_1 and ds1_2 are different!')
if ds1_1 != ds1_3:
logger.error('Datasets ds1_1 and ds1_3 are different!')
if ds1_1 != ds1_4:
logger.error('Datasets ds1_1 and ds1_4 are different!')
if DataSet_NEW_FILL:
if ds1_1 != ds1_5:
logger.error('Datasets ds1_1 and ds1_5 are different!')
with timing("No SHORTCUT, no FRAME", logger=None) as t1:
logger.info(attention(t1.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=False,
use_frame=False,
max_files=1)
ds1p_1 = selector.data
with timing(" SHORTCUT, no FRAME", logger=None) as t2:
logger.info(attention(t2.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=True,
use_frame=False,
max_files=1)
ds1p_2 = selector.data
with timing("No SHORTCUT, FRAME", logger=None) as t3:
logger.info(attention(t3.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=False,
use_frame=True,
max_files=1)
ds1p_3 = selector.data
with timing(" SHORTCUT, FRAME", logger=None) as t4:
logger.info(attention(t4.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=True,
use_frame=True,
max_files=1)
ds1p_4 = selector.data
table = [('Configuration', 'CPU')]
table.append((t1.name, '%.3fs' % t1.delta))
table.append((t2.name, '%.3fs' % t2.delta))
table.append((t3.name, '%.3fs' % t3.delta))
table.append((t4.name, '%.3fs' % t4.delta))
title1p = "All trivial variables (parallel)"
table1p = T.table(table, title=title1p, prefix='# ', alignment='rr')
logger.info('%s\n%s' % (title1p, table1p))
if ds1_1 != ds1p_1:
logger.error('Datasets ds1_1 and ds1p_1 are different!')
if ds1_2 != ds1p_2:
logger.error('Datasets ds1_2 and ds1p_2 are different!')
if ds1_3 != ds1p_3:
logger.error('Datasets ds1_3 and ds1p_3 are different!')
if ds1_4 != ds1p_4:
logger.error('Datasets ds1_4 and ds1p_4 are different!')
# =========================================================================
logger.info(attention('Trivial variables + CUT'))
# =========================================================================
variables = [
Variable(mJPsi, accessor='mass'),
Variable('massMeV', 'mass in MeV', 3000, 3200, 'mass*1000'),
Variable('vv102', 'vv10[2]', -1, 100, '1.0*vv10[2]'),
Variable('fevt', accessor='1.0*evt'), ('pt', ), ('eta', ),
('x', 'some variable', 0, 5000, '(mass+pt+eta)/eta')
]
if not DILL_PY3_issue:
config = {
'variables': variables,
'selection': "pt>7 && eta<3",
'cuts': lambda s: s.pt > 3
} ## ATTENTION: no trivial cuts!
else:
logger.warning('There is an issue with dill+python3: avoid lambda!')
config = {
'variables': variables,
'selection': "pt>7 && eta<3",
'cuts': ptcut
} ## ATTENTION: no trivial cuts!
with timing("No SHORTCUT, no FRAME", logger=None) as t1:
logger.info(attention(t1.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=False, use_frame=False)
ds2_1 = selector.data
with timing(" SHORTCUT, no FRAME", logger=None) as t2:
logger.info(attention(t2.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=True, use_frame=False)
ds2_2 = selector.data
with timing("No SHORTCUT, FRAME", logger=None) as t3:
logger.info(attention(t3.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=False, use_frame=True)
ds2_3 = selector.data
with timing(" SHORTCUT, FRAME", logger=None) as t4:
logger.info(attention(t4.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=True, use_frame=True)
ds2_4 = selector.data
table = [('Configuration', 'CPU')]
table.append((t1.name, '%.3fs' % t1.delta))
table.append((t2.name, '%.3fs' % t2.delta))
table.append((t3.name, '%.3fs' % t3.delta))
table.append((t4.name, '%.3fs' % t4.delta))
title2 = "Trivial variables + CUT"
table2 = T.table(table, title=title2, prefix='# ', alignment='rr')
logger.info('%s\n%s' % (title2, table2))
if ds2_1 != ds2_2:
logger.error('Datasets ds2_1 and ds2_2 are different!')
if ds2_1 != ds2_3:
logger.error('Datasets ds2_1 and ds2_3 are different!')
if ds2_1 != ds2_4:
logger.error('Datasets ds2_1 and ds2_4 are different!')
with timing("No SHORTCUT, no FRAME", logger=None) as t1:
logger.info(attention(t1.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=False,
use_frame=False,
maX_files=1)
ds2p_1 = selector.data
with timing(" SHORTCUT, no FRAME", logger=None) as t2:
logger.info(attention(t2.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=True,
use_frame=False,
maX_files=1)
ds2p_2 = selector.data
with timing("No SHORTCUT, FRAME", logger=None) as t3:
logger.info(attention(t3.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=False,
use_frame=True,
max_files=1)
ds2p_3 = selector.data
with timing(" SHORTCUT, FRAME", logger=None) as t4:
logger.info(attention(t4.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=True,
use_frame=True,
max_files=1)
ds2p_4 = selector.data
table = [('Configuration', 'CPU')]
table.append((t1.name, '%.3fs' % t1.delta))
table.append((t2.name, '%.3fs' % t2.delta))
table.append((t3.name, '%.3fs' % t3.delta))
table.append((t4.name, '%.3fs' % t4.delta))
title2p = "Trivial variables + CUT (parallel)"
table2p = T.table(table, title=title2p, prefix='# ', alignment='rr')
logger.info('%s\n%s' % (title2p, table2p))
if ds1_1 != ds2_1:
logger.error('Datasets ds1_1 and ds2_1 are different!')
if ds2_1 != ds2p_1:
logger.error('Datasets ds2_1 and ds2p_1 are different!')
if ds2_2 != ds2p_2:
logger.error('Datasets ds2_2 and ds2p_2 are different!')
if ds2_3 != ds2p_3:
logger.error('Datasets ds2_3 and ds2p_3 are different!')
if ds2_4 != ds2p_4:
logger.error('Datasets ds2_4 and ds2p_4 are different!')
# =========================================================================
logger.info(attention('Non-trivial variables'))
# =========================================================================
if not DILL_PY3_issue:
variables = [
Variable(mJPsi, accessor='mass'),
Variable('massMeV', 'mass in MeV', 3000, 3200, 'mass*1000'),
Variable('vv102', 'vv10[2]', -1, 100, '1.0*vv10[2]'),
Variable('fevt', accessor='1.0*evt'), ('pt', ), ('eta', ),
('x', 'some variable', 0, 5000, lambda s:
(s.mass + s.pt + s.eta) / s.eta)
]
else:
logger.warning('There is an issue with dill+python3: avoid lambda!')
variables = [
Variable(mJPsi, accessor='mass'),
Variable('massMeV', 'mass in MeV', 3000, 3200, 'mass*1000'),
Variable('vv102', 'vv10[2]', -1, 100, '1.0*vv10[2]'),
Variable('fevt', accessor='1.0*evt'), ('pt', ), ('eta', ),
('x', 'some variable', 0, 5000, xvar)
]
config = {'variables': variables, 'selection': "pt>7 && eta<3"}
with timing("No SHORTCUT, no FRAME", logger=None) as t1:
logger.info(attention(t1.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=False, use_frame=False)
ds3_1 = selector.data
with timing(" SHORTCUT, no FRAME", logger=None) as t2:
logger.info(attention(t2.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=True, use_frame=False)
ds3_2 = selector.data
with timing("No SHORTCUT, FRAME", logger=None) as t3:
logger.info(attention(t3.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=False, use_frame=True)
ds3_3 = selector.data
with timing(" SHORTCUT, FRAME", logger=None) as t4:
logger.info(attention(t4.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=True, use_frame=True)
ds3_4 = selector.data
table = [('Configuration', 'CPU')]
table.append((t1.name, '%.3fs' % t1.delta))
table.append((t2.name, '%.3fs' % t2.delta))
table.append((t3.name, '%.3fs' % t3.delta))
table.append((t4.name, '%.3fs' % t4.delta))
title3 = "Non-trivial variables"
table3 = T.table(table, title=title3, prefix='# ', alignment='rr')
logger.info('%s\n%s' % (title3, table3))
if ds1_1 != ds3_1:
logger.error('Datasets ds1_1 and ds3_1 are different!')
if ds3_1 != ds3_2:
logger.error('Datasets ds3_1 and ds2_2 are different!')
if ds3_1 != ds3_3:
logger.error('Datasets ds3_1 and ds2_3 are different!')
if ds3_1 != ds3_4:
logger.error('Datasets ds3_1 and ds2_4 are different!')
with timing("No SHORTCUT, no FRAME", logger=None) as t1:
logger.info(attention(t1.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=False,
use_frame=False,
max_files=1)
ds3p_1 = selector.data
with timing(" SHORTCUT, no FRAME", logger=None) as t2:
logger.info(attention(t2.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=True,
use_frame=False,
max_files=1)
ds3p_2 = selector.data
with timing("No SHORTCUT, FRAME", logger=None) as t3:
logger.info(attention(t3.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=False,
use_frame=True,
max_files=1)
ds3p_3 = selector.data
with timing(" SHORTCUT, FRAME", logger=None) as t4:
logger.info(attention(t4.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=True,
use_frame=True,
max_files=1)
ds3p_4 = selector.data
table = [('Configuration', 'CPU')]
table.append((t1.name, '%.3fs' % t1.delta))
table.append((t2.name, '%.3fs' % t2.delta))
table.append((t3.name, '%.3fs' % t3.delta))
table.append((t4.name, '%.3fs' % t4.delta))
title3p = "Non-trivial variables (parallel)"
table3p = T.table(table, title=title3p, prefix='# ', alignment='rr')
logger.info('%s\n%s' % (title3p, table3p))
if ds3_1 != ds3p_1:
logger.error('Datasets ds3_1 and ds3p_1 are different!')
if ds3_2 != ds3p_2:
logger.error('Datasets ds3_2 and ds3p_2 are different!')
if ds3_3 != ds3p_3:
logger.error('Datasets ds3_3 and ds3p_3 are different!')
if ds3_4 != ds3p_4:
logger.error('Datasets ds3_4 and ds3p_4 are different!')
# =========================================================================
logger.info(attention('Non-trivial variables + CUT'))
# =========================================================================
if not DILL_PY3_issue:
variables = [
Variable(mJPsi, accessor='mass'),
Variable('massMeV', 'mass in MeV', 3000, 3200, 'mass*1000'),
Variable('vv102', 'vv10[2]', -1, 100, '1.0*vv10[2]'),
Variable('fevt', accessor='1.0*evt'), ('pt', ), ('eta', ),
('x', 'some variable', 0, 5000, lambda s:
(s.mass + s.pt + s.eta) / s.eta)
]
else:
logger.warning('There is an issue with dill+python3: avoid lambda!')
variables = [
Variable(mJPsi, accessor='mass'),
Variable('massMeV', 'mass in MeV', 3000, 3200, 'mass*1000'),
Variable('vv102', 'vv10[2]', -1, 100, '1.0*vv10[2]'),
Variable('fevt', accessor='1.0*evt'), ('pt', ), ('eta', ),
('x', 'some variable', 0, 5000, xvar)
]
if not DILL_PY3_issue:
config = {
'variables': variables,
'selection': "pt>7 && eta<3",
'cuts': lambda s: s.pt > 3
} ## ATTENTION: no trivial cuts!
else:
logger.warning('There is an issue with dill+python3: avoid lambda!')
config = {
'variables': variables,
'selection': "pt>7 && eta<3",
'cuts': ptcut
} ## ATTENTION: no trivial cuts!
with timing("No SHORTCUT, no FRAME", logger=None) as t1:
logger.info(attention(t1.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=False, use_frame=False)
ds4_1 = selector.data
with timing(" SHORTCUT, no FRAME", logger=None) as t2:
logger.info(attention(t2.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=True, use_frame=False)
ds4_2 = selector.data
with timing("No SHORTCUT, FRAME", logger=None) as t3:
logger.info(attention(t3.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=False, use_frame=True)
ds4_3 = selector.data
with timing(" SHORTCUT, FRAME", logger=None) as t4:
logger.info(attention(t4.name))
selector = SelectorWithVars(**config)
chain.fill_dataset(selector, shortcut=True, use_frame=True)
ds4_4 = selector.data
table = [('Configuration', 'CPU')]
table.append((t1.name, '%.3fs' % t1.delta))
table.append((t2.name, '%.3fs' % t2.delta))
table.append((t3.name, '%.3fs' % t3.delta))
table.append((t4.name, '%.3fs' % t4.delta))
title4 = "Non-trivial variables + CUT"
table4 = T.table(table, title=title4, prefix='# ', alignment='rr')
logger.info('%s\n%s' % (title4, table4))
if ds1_1 != ds4_1:
logger.error('Datasets ds1_1 and ds4_1 are different!')
if ds4_1 != ds4_2:
logger.error('Datasets ds4_1 and ds4_2 are different!')
if ds4_1 != ds4_3:
logger.error('Datasets ds4_1 and ds4_3 are different!')
if ds4_1 != ds4_4:
logger.error('Datasets ds4_1 and ds4_4 are different!')
with timing("No SHORTCUT, no FRAME", logger=None) as t1:
logger.info(attention(t1.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=False,
use_frame=False,
max_files=1)
ds4p_1 = selector.data
with timing(" SHORTCUT, no FRAME", logger=None) as t2:
logger.info(attention(t2.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=True,
use_frame=False,
max_files=1)
ds4p_2 = selector.data
with timing("No SHORTCUT, FRAME", logger=None) as t3:
logger.info(attention(t3.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=False,
use_frame=True,
max_files=1)
ds4p_3 = selector.data
with timing(" SHORTCUT, FRAME", logger=None) as t4:
logger.info(attention(t4.name))
selector = SelectorWithVars(**config)
chain.parallel_fill(selector,
shortcut=True,
use_frame=True,
max_files=1)
ds4p_4 = selector.data
table = [('Configuration', 'CPU')]
table.append((t1.name, '%.3fs' % t1.delta))
table.append((t2.name, '%.3fs' % t2.delta))
table.append((t3.name, '%.3fs' % t3.delta))
table.append((t4.name, '%.3fs' % t4.delta))
title4p = "Non-trivial variables + CUT (parallel)"
table4p = T.table(table, title=title4p, prefix='# ', alignment='rr')
logger.info('%s\n%s' % (title4p, table4p))
if ds4_1 != ds4p_1:
logger.error('Datasets ds4_1 and ds4p_1 are different!')
if ds4_2 != ds4p_2:
logger.error('Datasets ds4_2 and ds4p_2 are different!')
if ds4_3 != ds4p_3:
logger.error('Datasets ds4_3 and ds4p_3 are different!')
if ds4_4 != ds4p_4:
logger.error('Datasets ds4_4 and ds4p_4 are different!')
logger.info('%s\n%s' % (title1, table1))
logger.info('%s\n%s' % (title1p, table1p))
logger.info('%s\n%s' % (title2, table2))
logger.info('%s\n%s' % (title2p, table2p))
logger.info('%s\n%s' % (title3, table3))
logger.info('%s\n%s' % (title3p, table3p))
logger.info('%s\n%s' % (title4, table4))
logger.info('%s\n%s' % (title4p, table4p))