# histograms are unified!
from rootpy.plotting import Hist
hist = Hist(10, -3, 3) # <== notice that the name or title is not needed
hist.name # the name is automatically a unique ID

# Hist is really a subclass of the appropriate ROOT TH1X class
hist.__class__.__bases__

# the base class is determined dynamically at runtime
hist = Hist(10, -3, 3, type='D', title="asd", linecolor="#ccddee")
hist.__class__.__bases__

print hist.GetLineColor()

# rootpy has ipython notebook support so things can be drawn inline
hist.FillRandom('gaus')
hist

from rootpy.plotting import Hist2D, Hist3D
# variable-width bins
h1d = Hist([-10, -3.2, 5.2, 6])

# 2D histogram with fixed-width bins; 10 along x and 5 along y
h2d = Hist2D(10, 0, 1, 5, -2, 4, drawstyle='E')
# 3 variable-width bins along x and 4 fixed-width bins along y
h2d = Hist2D([10, 30, 100, 1000], 4, 10, 33.5)

# 3D histogram with fixed-width bins
h3d = Hist3D(100, 0, 1, 20, 5.8, 7.2, 1000, -10, 1)
# fixed-width bins along x and z and variable-width bins along y
h3d = Hist3D(5, 0, 1, [-20, 5, 50, 1e3], 10, 0, 1)

from rootpy.plotting import set_style
set_style('ATLAS')
hist = Hist(50, -3, 3)
hist.FillRandom('gaus')
hist.xaxis.title = 'Variable [Units]'
hist.yaxis.title = 'Entries'
hist.linewidth = 3
hist.linestyle = 'dashed'
hist.linecolor = 'forestgreen' # SVG
hist.markercolor = '#334455' # hex
hist.fillstyle = '/'
hist.fillcolor = 'red'
hist.drawstyle = 'HIST'
hist

# access bin contents and errors
hist[1] = (3, 1.2)
hist[1].value

hist[1].error

# reverse bin contents (and errors)
hist[:] = hist.Clone(shallow=True)[::-1]

hist

# rebin by 2 along x
hist.rebinned(5, axis=0)

Hist(hist[::10]) # you can construct histograms from "views" of other histograms. The step value in the slice creates a rebinning.

# merge specific bins
hist.merge_bins([(0, 5), (40, -1)])

# same functionality in 2D and 3D...
from rootpy.plotting import F2
h2 = Hist2D(20, 0, 1, 20, 0, 1)
h2.FillRandom(F2('x*y'))
h2.drawstyle = 'LEGO2'
h2

h2_merged = h2.merge_bins([(6, 12)], axis=1)
h2_merged.drawstyle = 'LEGO2'
h2_merged

h2_merged = h2_merged.merge_bins([(6, 12)], axis=0)
h2_merged.drawstyle = 'LEGO2'
h2_merged

Hist2D(h2[5:10,::5], drawstyle='LEGO2') # crop along x and rebin along y

h2[:,2:8] = (0, 0) # set specific ranges of bins (value, error)
h2

# flatten a histogram by rebinning according to the quantiles
h = Hist(1000, -3, 3)
h.FillRandom('gaus', 100000)
print h.quantiles(5, strict=True)
h_flat = h.rebinned(h.quantiles(5, strict=True))
h_flat.SetMinimum(0)
h_flat

from rootpy.io import root_open
from rootpy.testdata import get_filepath
# objects are automatically cast to the rootpy subclasses if they exist

# support for the with-statement
with root_open(get_filepath()) as f:
    print f
    for path, dirs, objects in f.walk():
        print path, objects

f = root_open(get_filepath())
list(f.find('hist1'))

# only loop over objects of a given class
for path, dirs, objects in f.walk(class_pattern='TH1F'):
    print objects

f.scales.hist1 # easy acess

# does something exist in a file?
'scales' in f

'blah' in f

'scales/hist1' in f

# create a new file
g = root_open('test.root', 'recreate')
hist = Hist(10, -3, 3)
hist.FillRandom('gaus')
# write to this file
g.myhist = hist
list(g)

g.Get('myhist')

# ROOT errors become real Python exceptions
root_open('does_not_exist.root')

g['asasd']

from rootpy.tree import Tree, TreeModel, IntCol, FloatCol
from rootpy.vector import LorentzVector
from random import gauss, uniform, expovariate
from math import pi

class Event(TreeModel):
    number = IntCol()
    MET_phi = FloatCol()
    MET = FloatCol(default=-1)
    jet = LorentzVector
    
output = root_open('test.root', 'recreate')
    
tree = Tree('data', model=Event)

for i in xrange(1000):
    tree.number = i
    tree.MET_phi = uniform(-pi, pi)
    if i % 2 == 1:
        tree.MET = expovariate(10)
    tree.jet.SetPtEtaPhiM(expovariate(10), gauss(0, 2), uniform(-pi, pi), 0)
    tree.Fill(reset=True)

len(tree)

tree.Draw('MET_phi')

tree.Draw('jet.Pt()', drawstyle='hist', linewidth=3, linestyle='dotted')

# a more complicated model...

class Particle(TreeModel):
    charge = IntCol()
    fourvector = LorentzVector
    
class Jet(TreeModel):
    num_tracks = IntCol()
    vertex_fraction = FloatCol()
    fourvector = LorentzVector
    
class Event(Particle.prefix('mu1_'), Particle.prefix('mu2_'),
            Jet.prefix('jet1_'), Jet.prefix('jet2_')):
    number = IntCol()
    MET_phi = FloatCol()
    MET = FloatCol(default=-1)

tree2 = Tree('events', model=Event)
tree2._buffer

from rootpy.tree import Cut
a = Cut()
a.__class__.__bases__

cut1 = Cut('a < 10')
cut2 = Cut('b % 2 == 0')

cut1 & cut2

# expansion of ternary conditions
cut3 = Cut('10 < a < 20')
cut3

# easily combine cuts arbitrarily
((cut1 & cut2) | - cut3)