def MakeFigures():
pops = populations.ReadData()
print len(pops)
cdf = Cdf.MakeCdfFromList(pops, 'populations')
myplot.Clf()
myplot.Cdf(cdf)
myplot.Save(root='populations',
title='City/Town Populations',
xlabel='population',
ylabel='CDF',
legend=False)
myplot.Clf()
myplot.Cdf(cdf)
myplot.Save(root='populations_logx',
title='City/Town Populations',
xlabel='population',
ylabel='CDF',
xscale='log',
legend=False)
myplot.Clf()
myplot.Cdf(cdf, complement=True)
myplot.Save(root='populations_loglog',
title='City/Town Populations',
xlabel='population',
ylabel='Complementary CDF',
yscale='log',
xscale='log',
legend=False)
t = [math.log(x) for x in pops]
t.sort()
rankit.MakeNormalPlot(t, 'populations_rankit')
import Cdf import populations import math import myplot import numpy import Pmf pops = populations.ReadData() bucketed_pops = map(lambda(x):50*math.floor(x/50.0),pops) pmf = Pmf.MakePmfFromList(bucketed_pops) cdf = Cdf.MakeCdfFromPmf(pmf) myplot.Pmf(pmf) myplot.Show(title="Pmf of populations", xscale='log') myplot.Cdf(cdf) myplot.Show(title="Cdf of populations", inverse=True, xscale='log') xs = sorted(numpy.random.normal(0, 1, len(pops))) ys = sorted(bucketed_pops) myplot.Plot(xs, ys) myplot.Show(title="Normal plot for populations") ys2 = sorted(map(lambda(y):math.log10(y+1),bucketed_pops)) myplot.Plot(xs, ys2) myplot.Show(title="LogNormal plot for populations") #it looks more like a lognormal, but with a hard lower bound (as expected)