def test_kisa():
logger = getLogger('ostap.test_kisa')
if 62400 <= ROOT.gROOT.GetVersionInt() < 62406:
logger.warning('Test can fail for %s' % ROOT.gROOT.GetVersion())
h1 = ROOT.TH1D('h1', '', 200, 3, 3.2)
h2 = h1.clone()
chain = data.chain
with timing('SEQUENTIAL(%s):' % len(chain), logger):
chain.project(h1, 'mass',
'3<=mass && mass<=3.2 && 0<=c2dtf && c2dtf<5')
logger.info(h1.dump(100, 30))
with timing('PARALLEL(%s):' % len(chain), logger):
chain.pproject(h2,
'mass',
'3<=mass && mass<=3.2 && 0<=c2dtf && c2dtf<5',
silent=False)
logger.info(h2.dump(100, 30))
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 = '# ' ) )
def test_kisa2 () :
from ostap.fitting.selectors 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:\n%s' % ds )
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.pprocess ( selector ,
silent = False ,
chunk_size = -1 ,
max_files = 1 ,
ppservers = ppservers )
ds = selector.data
del selector
logger.info ( 'Dataset:\n%s' % ds )
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_loop_with_cuts():
"""More advanced test
- loop over the good entries in the chain,
- fill dataset
"""
logger = getLogger("test_loop_with_cuts")
with timing("Loop with cuts", logger):
varset = ROOT.RooArgSet(mass, c2dtf, pt)
dataset = ROOT.RooDataSet(dsID(), 'Test Data set-1', varset)
for i in data.chain.withCuts(cuts):
v_mass = i.mass
v_c2dtf = i.c2dtf
v_pt = i.pt
## fill dataset
mass.value = v_mass
c2dtf.value = v_c2dtf
pt.value = v_pt
dataset.add(varset)
logger.info("Data set (loop-with-cuts):\n%s" % dataset.table(prefix="# "))
def test_simple_loop():
"""Simple test
- loop over the entries in the chain
- select good entries
- fill dataset
"""
logger = getLogger("test_simple_loop")
with timing("Simple loop", logger):
varset = ROOT.RooArgSet(mass, c2dtf, pt)
dataset = ROOT.RooDataSet(dsID(), 'Test Data set-1', varset)
for i in data.chain:
v_mass = float(i.mass)
v_c2dtf = float(i.c2dtf)
v_pt = float(i.pt)
## apply cuts
if not 3.015 < v_mass < 3.150: continue
if not 0.0 < v_c2dtf < 3.0: continue
if not 1.5 < v_pt < 10: continue
## fill dataset
mass.value = v_mass
c2dtf.value = v_c2dtf
pt.value = v_pt
dataset.add(varset)
logger.info("Data set (simple-loop):\n%s" % dataset.table(prefix="# "))
def derivative_testing ( der_type , func , der_exact , logger , **kwargs ) :
IMAX = der_type.IMAX
cnt1 = {}
for i in range ( IMAX ) : cnt1 [i] = SE()
ders = [ der_type ( func , I , **kwargs ) for I in range ( IMAX ) ]
with timing ( 'derivative test' , logger = logger ) :
for i in range(10000) :
x = random.uniform ( 0 , pi )
d_true = der_exact ( x )
for I , dd in enumerate ( ders ) :
delta = dd ( x ) - d_true
cnt1 [I] += delta
rows = [ ('I' , 'rms' , 'min' , 'max' ) ]
for i,c in cnt1.items() :
row = '%d' % i , '% .4g' % c.rms () , '% .4g' % c.min() , '% .4g' % c.max()
rows.append ( row )
table = T.table ( rows ,
title = 'Test numerical derivatives' ,
prefix = '# ' , alignment = 'clll' )
logger.info ( 'Test numerical derivatives\n%s' % table )
def test_db() :
logger.info('Saving all objects into DBASE')
import ostap.io.zipshelve as DBASE
from ostap.utils.timing import timing
with timing( name = 'Save everything to DBASE'), DBASE.tmpdb() as db :
db['models' ] = models
db.ls()
def test_kisa () :
h1 = ROOT.TH1D( 'h1' , '' , 200 , 3 , 3.2 )
h2 = h1.clone()
chain = data.chain
with timing('SEQUENTIAL(%s):' % len(chain) , logger ) :
chain. project ( h1 , 'mass' , '3<=mass && mass<=3.2 && 0<=c2dtf && c2dtf<5' )
logger.info ( h1.dump(100,30) )
with timing('PARALLEL(%s):' % len(chain) , logger ) :
chain.pproject ( h2 , 'mass' , '3<=mass && mass<=3.2 && 0<=c2dtf && c2dtf<5' , silent = False )
logger.info ( h2.dump(100,30) )
def test_db():
logger.info('Saving all objects into DBASE')
with timing(name='Save everything to DBASE'), DBASE.tmpdb() as db:
db['m_x'] = m_x
db['m_y'] = m_y
db['vars'] = varset
db['models'] = models
db['dataset'] = dataset
db.ls()
def test_positive_pdf():
logger = getLogger("test_positive_pdf")
with timing('Positive [4]', logger):
params = [h.pdf_positive(4, silent=True, draw=True) for h in histos]
for h, f in zip(histos, params):
f.plot.draw()
logger.info("%-25s : difference %s" % (h.title, diff1(f, h)))
time.sleep(1)
def test_convex_3():
with timing('Convex [4]', logger):
rB1 = h1.pdf_convex_decreasing(4, silent=True, draw=True)
rB2 = h2.pdf_convex_increasing(4, silent=True, draw=True)
rB3 = h3.pdf_concave_increasing(4, silent=True, draw=True)
rB4 = h4.pdf_concave_decreasing(4, silent=True, draw=True)
logger.info(
'Convex [4]: diff %s ' %
[diff1(*p) for p in [(rB1, h1), (rB2, h2), (rB3, h3), (rB4, h4)]])
def test_monotonic_3():
with timing('Monotonic[4]', logger):
rB1 = h1.pdf_decreasing(4, silent=True, draw=True)
rB2 = h2.pdf_increasing(4, silent=True, draw=True)
rB3 = h3.pdf_increasing(4, silent=True, draw=True)
rB4 = h4.pdf_decreasing(4, silent=True, draw=True)
logger.info(
'Monotonic[4]: diff %s ' %
[diff1(*p) for p in [(rB1, h1), (rB2, h2), (rB3, h3), (rB4, h4)]])
def test_convex():
with timing('Convex[4]', logger):
rL1 = h1.convex(4, increasing=False, convex=True)
rL2 = h2.convex(4, increasing=True, convex=True)
rL3 = h3.convex(4, increasing=True, convex=False)
rL4 = h4.convex(4, increasing=False, convex=False)
logger.info(
'Convex[4]: diff %s ' %
[diff2(*p) for p in [(rL1, h1), (rL2, h2), (rL3, h3), (rL4, h4)]])
def test_monotonic():
with timing('Monotonic[4]', logger):
rL1 = h1.monotonic(4, increasing=False)
rL2 = h2.monotonic(4, increasing=True)
rL3 = h3.monotonic(4, increasing=True)
rL4 = h4.monotonic(4, increasing=False)
logger.info(
'Monotonic[4]: diff %s ' %
[diff2(*p) for p in [(rL1, h1), (rL2, h2), (rL3, h3), (rL4, h4)]])
def test_db():
logger.info('Saving all objects into DBASE')
import ostap.io.zipshelve as DBASE
from ostap.utils.timing import timing
with timing('Save everything to DBASE', logger), DBASE.tmpdb() as db:
for i, m in enumerate(models):
db['model/%-2d: %s' % (i, m.name)] = m
db['models'] = models
db.ls()
def test_db() :
with timing ( 'Save everything to DBASE' , logger ), DBASE.tmpdb() as db :
db['m_x' ] = m_x
db['m_y' ] = m_y
db['vars' ] = varset
for m in models : db[ 'model:' + m.name ] = m
db['models' ] = models
db['dataset' ] = dataset
db.ls()
def test_positive_spline_pdf () :
logger = getLogger("test_positive_spline_pdf")
with timing ('P-spline [3,2]' , logger ) :
params = [ h.pdf_pSpline ( (5,2) , silent = True , draw = True ) for h in histos ]
for h , f in zip ( histos , params ) :
with wait ( 1 ) , use_canvas ( 'test_positive_spline_pdf: ' + h.GetTitle() ) :
f.plot.draw ()
logger.info ( "%-25s : difference %s" % ( h.title , diff1 ( f , h ) ) )
def test_db():
logger.info('Saving all objects into DBASE')
import ostap.io.zipshelve as DBASE
from ostap.utils.timing import timing
with timing(name='Save everything to DBASE'), DBASE.tmpdb() as db:
db['mass,vars'] = mass, varset0
db['dataset'] = dataset0
for m in models:
db['model:' + m.name] = m
db['models'] = models
db.ls()
def test_positive_spline():
logger = getLogger("test_positive_spline")
with timing('P-spline [2,2]', logger):
params = [h.pSpline(degree=2, knots=2) for h in histos]
for h, f in zip(histos, params):
h.draw()
f.tf1.draw('same')
logger.info("%-25s : difference %s" % (h.title, diff2(f, h)))
time.sleep(1)
def test_generic_spline():
logger = getLogger("test_generic_spline")
with timing('B-spline [1,4]', logger):
params = [h.bSpline(degree=1, knots=4) for h in histos]
for h, f in zip(histos, params):
h.draw()
f.tf1.draw('same')
logger.info("%-25s : difference %s" % (h.title, diff2(f, h)))
time.sleep(1)
def test_fourier():
logger = getLogger("test_fourier")
with timing('Fourier [4]', logger):
params = [h5.fourier(4), h6.fourier(6)]
for h, f in zip((h5, h6), params):
h.draw()
f.tf1.draw('same')
logger.info("%-25s : difference %s" % (h.title, diff2(f, h)))
time.sleep(1)
def test_positive():
logger = getLogger("test_positive")
with timing('Positive [4]', logger):
params = [h.positive(4) for h in histos]
for h, f in zip(histos, params):
h.draw()
f.tf1.draw('same')
logger.info("%-25s : difference %s" % (h.title, diff2(f, h)))
time.sleep(1)
def test_positive() :
logger = getLogger("test_positive")
with timing ( 'Positive [4]' , logger ) :
params = [ h.positive ( 4 ) for h in histos ]
for h , f in zip ( histos , params ) :
with wait ( 2 ) , use_canvas ( 'test_positive %s' % h.GetTitle() ) :
h .draw()
f.tf1.draw('same')
logger.info ( "%-25s : difference %s" % ( h.title , diff2 ( f , h ) ) )
def test_positive_spline () :
logger = getLogger("test_positive_spline")
with timing ('P-spline [2,3]' , logger ) :
params = [ h.pSpline ( degree = 2 , knots = 3 ) for h in histos ]
for h , f in zip ( histos , params ) :
with wait ( 2 ) , use_canvas ( 'test_positive_spline: %s' % h.GetTitle() ) :
h .draw()
f.tf1.draw('same')
logger.info ( "%-25s : difference %s" % ( h.title , diff2 ( f , h ) ) )
def test_db():
logger = getLogger('test_db')
logger.info('Saving all objects into DBASE')
import ostap.io.zipshelve as DBASE
from ostap.utils.timing import timing
with timing('Save everything to DBASE', logger), DBASE.tmpdb() as db:
for i, f in enumerate(functions, start=1):
db['%03d:%s' % (i, f.__class__.__name__)] = f
db['functions'] = functions
db.ls()
def test_db():
logger = getLogger('test_db')
logger.info('Saving all objects into DBASE')
with timing('Save everything to DBASE', logger), DBASE.tmpdb() as db:
db['m_x'] = m_x
db['m_y'] = m_y
for m in models:
db['model:' + m.name] = m
db['models'] = models
db.ls()
def test_frame1():
c = 0
for mt in (False, True, False, True):
with implicitMT(mt):
logger.info('MT enabled? %s/%s' %
(ROOT.ROOT.IsImplicitMTEnabled(),
ROOT.ROOT.GetImplicitMTPoolSize()))
for obj in ((tree, 'Tree'), (frame, 'Frame'), (tree, 'Tree')):
with timing(obj[1], logger):
##logger.info ('Kurtosis: %s ' % obj[0].kurtosis ( 'b1' , 'b1/(b2+1)' ) )
c += obj[0].kurtosis('b1', 'b1/(b2+1)')
def test_chebyshev_sum() :
logger = getLogger("test_chebyshev_sum")
with timing ( 'Chebyshev-sum[6]' , logger ) :
params = [ h.chebyshev_sum ( 8 ) for h in histos ]
for h , f in zip ( histos , params ) :
with wait ( 1 ) , use_canvas ( 'test_chebyshev_sum: ' + h.GetTitle() ) :
h.draw()
f.draw('same')
logger.info ( "%-25s : difference %s" % ( h.title , diff1 ( f , h ) ) )
def test_fourier():
with timing('Fourier[8]', logger):
rF1 = h1.fourier(8)
rF2 = h2.fourier(8)
rF3 = h3.fourier(8)
rF4 = h4.fourier(8)
rF5 = h5.fourier(8)
rF6 = h6.fourier(8)
logger.info('Fourier[8] : diff %s ' % [
diff2(*p) for p in [(rF1, h1), (rF2, h2), (rF3, h3), (rF4, h4),
(rF5, h5), (rF6, h6)]
])
