def test_access_row():
nt = NTuple('A', 'B')
nt.fill('A', 5)
rw = nt.row(0)
assert rw.A == 5
nt.fill('B', 6)
assert rw.A == 5 and rw.B == 6
def test_get_with_cross_cut():
nt = NTuple('A', 'B')
for x in range(100):
nt.fill('A', x)
nt.fill('B', x * 100)
nt.write()
col = nt.column('B', lambda x: x.A > 50 and x.B < 8500)
assert col == [x * 100 for x in xrange(51, 85)]
def test_get_with_cut():
nt = NTuple('A', 'B')
for x in range(100):
nt.fill('A', x)
nt.fill('B', x * 100)
nt.write()
col = nt.column('A', lambda x: x.A > 50)
assert col == range(51, 100)
def reference_ntuple():
nt = NTuple('x', 'sin', 'cos')
import math
for x in xrange(-50, 51):
nt.fill('x', x)
nt.fill('sin', math.sin(x))
nt.fill('cos', math.cos(x))
nt.write()
return nt
def test_get_column():
nt = NTuple('A', 'B')
for x in range(100):
nt.fill('A', x)
nt.fill('B', x * 100)
nt.write()
A = nt.column('A')
assert A == range(100)
B = nt.column('B')
assert B == [x * 100 for x in range(100)]
def test_access_latest_row():
nt = NTuple('A', 'B')
nt.fill('A', 5)
rw = nt.row(0)
assert rw.A == 5
nt.fill('A', 7)
rw = nt.row(0)
assert rw.A == 7
nt.write()
nt.fill('A', 22)
rw = nt.row(1)
assert rw.A == 22
def test_fill_column_twice():
nt = NTuple('A', 'B')
nt.fill('A', 5)
nt.fill('A', 7)
def test_fill_column():
nt = NTuple('A', 'B')
nt.fill('A', 5)
import math
from random import gauss
from PyAna.pyntuple.ntuple import NTuple
from matplotlib import pyplot
from PyAna.pyhistoplots import ntuple_plot, histo_plot, ntuple_column_histo
mu_p = 15.
mu_pt = 5.
sigma_p = 10.
sigma_pt = 5.
nt = NTuple('x', 'p', 'pt')
for x in xrange(10000):
nt.fill('x', x)
nt.fill('p', gauss(mu_p, sigma_p))
nt.fill('pt', gauss(mu_pt, sigma_pt))
nt.write()
def test_ntuple_plot():
pt_plot = ntuple_plot(nt, 'pt', show=False)
p_plot = ntuple_plot(nt,
'p',
errorfunction=lambda x: x.height / 2.,
color='red',
linewidth='1.5',
show=False)