sthist.setBinWidth ( 'x', 1. )
canvas.addDisplay ( sthist )
# Create second static histogram and add it to canvas
sthists = Display ( "Static Histogram" )
sthists.setTitle ( "Gaussian Distribution (low statistics)" )
sthists.setLabel ( 'x', 'X' )
sthists.setRange ( 'x', 0, 100)
sthists.setBinWidth ( 'x', 1. )
canvas.addDisplay ( sthists )
# Create empty NTuple and set the column label.
# Setting the column labels sets the number of columns
ntuple = NTuple ( )
ntuple.setTitle ( 'Gaussian Distribution' )
ntuple.setLabels ( ('X value', ) )
# Register the NTuple so the Inspector can see it.
NTupleController.instance().registerNTuple ( ntuple )
# Create dynamic histogram and attach it to NTuple.
# It will automatically adjust its range, title, and labels
dyhist = Display ( "Histogram", ntuple, ('X value', ) )
canvas.addDisplay ( dyhist )
mean = 45
sigma = 10
gauss = random.gauss
# Generate some data, fill the static histograms and NTuple.
for i in range(10000):
""" -*- mode: python -*-
Create an NTuple with power-law distribution and histogram it on log log scale
@author J. Chiang <*****@*****.**>
"""
from load_hippo import app, canvas
import random, math
shoot = random.uniform
# Create empty NTuple of 4 columns that we can fill by row.
from hippo import NTuple, NTupleController
nt = NTuple()
nt.setLabels(['x'])
xmin = 1.
xmax = 100.
gamma = 2.1
xpmax = math.pow(xmax, 1. - gamma)
xpmin = math.pow(xmin, 1. - gamma)
nsamp = 10000
for i in range(nsamp):
x = shoot(0, 1)
xx = math.pow(x * (xpmax - xpmin) + xpmin, 1. / (1. - gamma))
nt.addRow((xx, ))
from hippo import Display
""" -*- mode: python -*-
Create an NTuple with power-law distribution and histogram it on log log scale
@author J. Chiang <*****@*****.**>
"""
from load_hippo import app, canvas
import random, math
shoot = random.uniform
# Create empty NTuple of 4 columns that we can fill by row.
from hippo import NTuple, NTupleController
nt = NTuple ()
nt.setLabels ( [ 'x' ] )
xmin = 1.
xmax = 100.
gamma = 2.1
xpmax = math.pow ( xmax, 1. - gamma )
xpmin = math.pow ( xmin, 1. - gamma )
nsamp = 10000
for i in range(nsamp):
x = shoot(0, 1)
xx = math.pow ( x*( xpmax - xpmin ) + xpmin, 1./ (1. - gamma) )
nt.addRow ( (xx, ) )
from hippo import Display
