Demonstraton of static versus dynamic histograms.  Also demonstrates
taking difference between two histograms and plotting it.

 @author Paul F. Kunz <*****@*****.**>

"""
import random
from time import sleep

from load_hippo import app, canvas

from hippo import Display, NTuple, NTupleController

# Create static histogram and add it to canvas.
sthist = Display ( "Static Histogram" )
sthist.setTitle ( "Gaussian Distribution (static hist)" )
sthist.setLabel ( 'x', 'X' )
sthist.setRange ( 'x', 0, 100)
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
Beispiel #2
0
"""
   Demonstrates making simple XY plot.  

   author Paul F. Kunz <*****@*****.**>
"""
#
# load the HippoDraw module
#
from load_hippo import app, canvas

from hippo import Display

# Create list of data
energy = [90.74, 91.06, 91.43, 91.50, 92.16, 92.22, 92.96, 89.24, 89.98, 90.35]
sigma = [29.0, 30.0, 28.40, 28.80, 21.95, 22.90, 13.50, 4.50, 10.80, 24.20]
errors = [5.9, 3.15, 3.0, 5.8, 7.9, 3.1, 4.6, 3.5, 4.6, 3.6]

# make a plot to test it.
xy = Display("XY Plot", [energy, sigma, errors],
             ['Energy', 'Sigma', 'nil', 'error'])

canvas.addDisplay(xy)

xy.setTitle('Mark II Z0 scan')

print "An XY plot is now displayed.   You can use the Inspector dialog"
print "to modify the appearance or fit a function to it."
Beispiel #3
0
"""
   Demonstrates making simple XY plot.  

   author Paul F. Kunz <*****@*****.**>
"""
#
# load the HippoDraw module
#
from load_hippo import app, canvas

from hippo import Display

# Create list of data
energy = [90.74, 91.06, 91.43, 91.50, 92.16, 92.22, 92.96, 89.24, 89.98, 90.35]
sigma  = [ 29.0, 30.0,  28.40, 28.80, 21.95, 22.90, 13.50,  4.50, 10.80, 24.20]
errors = [  5.9,  3.15,  3.0,   5.8,  7.9,   3.1,   4.6,    3.5,   4.6,   3.6]

# make a plot to test it.
xy = Display ( "XY Plot", [ energy, sigma, errors ],
               ['Energy', 'Sigma', 'nil', 'error' ] )

canvas.addDisplay ( xy )

xy.setTitle ( 'Mark II Z0 scan' )

print "An XY plot is now displayed.   You can use the Inspector dialog"
print "to modify the appearance or fit a function to it."