def plotLattice():
p.figure()
p.hold('on')
sd = np.where(I==-1) #spin down
su = np.where(I==1) #spin up
l = str(L)
p.scatter(sd[0],sd[1],color='black',title='2D Ising Model Size: '+l+'x'+l)
p.scatter(su[0],su[1],color='blue')
from webplot import p
import pandas
df = pandas.read_csv('auto-mpg.csv')
p.use_doc('cars')
source = p.model('PandasDataSource', df=df)
source.update()
p.pandastable(source)
p.figure()
p.scatter('mpg', 'weight', data_source=source)
p.figure()
p.scatter('mpg', 'yr', data_source=source)
from webplot import p
p.use_doc('webplot example')
import numpy as np
import datetime
import time
x = np.arange(100) / 6.0
y = np.sin(x)
z = np.cos(x)
data_source = p.make_source(idx=range(100), x=x, y=y, z=z)
p.plot(x, y, 'orange')
p.figure()
p.plot('x', 'y', color='blue', data_source=data_source, title='sincos')
p.plot('x', 'z', color='green')
p.figure()
p.plot('x', 'y', data_source=data_source)
p.figure()
p.plot('x', 'z', data_source=data_source)
p.figure()
p.table(data_source, ['x', 'y', 'z'])
p.scatter('x', 'y', data_source=data_source)
p.figure()
p.scatter('x', 'z', data_source=data_source)
p.figure()
p.hold(False)
p.scatter('x', 'y', 'orange', data_source=data_source)
p.scatter('x', 'z', 'red', data_source=data_source)
p.plot('x', 'z', 'yellow', data_source=data_source)
p.plot('x', 'y', 'black', data_source=data_source)
print "click on the plots tab to see results"
