def main():
results = relay.ReadResults()
speeds = relay.GetSpeeds(results)
speeds = relay.BinData(speeds, 3, 12, 100)
# plot the distribution of actual speeds
pmf = thinkstats2.Pmf(speeds, 'actual speeds')
# plot the biased distribution seen by the observer
biased = ObservedPmf(pmf, 7.5, label='observed speeds')
thinkplot.Pmf(biased)
thinkplot.Save(root='observed_speeds',
title='PMF of running speed',
xlabel='speed (mph)',
ylabel='PMF')
cdf = thinkstats2.Cdf(pmf)
cdf_biased = thinkstats2.Cdf(biased)
thinkplot.PrePlot(2)
thinkplot.Cdfs([cdf, cdf_biased])
thinkplot.Save(root='observed_speeds_cdf',
title='CDF of running speed',
xlabel='speed (mph)',
ylabel='CDF')
def main():
#cdf, place = total_percentile_rank(results)
speeds = relay.GetSpeeds(results)
speed = relay.ConvertPaceToSpeed('6:53')
cdf = Cdf.MakeCdfFromList(speeds)
print cdf.Prob(speed),'speed'
print convert_speeds_to_time(speed),'time'
myplot.Cdf(cdf)
myplot.Show()
speeds_old = GetSpeeds_M4049(results)
cdf_old = Cdf.MakeCdfFromList(speeds_old)
rank = cdf_old.Prob(speed)
print rank,'rank', speed,'speed'
print convert_speeds_to_time(speed),'time'
myplot.Cdf(cdf_old)
myplot.Show()
speeds_5059 = GetSpeeds_M5059(results)
cdf_5059 = Cdf.MakeCdfFromList(speeds_5059)
future_speed = cdf_5059.Value(rank)
print future_speed,'speed'
print convert_speeds_to_time(future_speed),'time'
myplot.Cdf(cdf_5059)
myplot.Show()
fspeeds = GetSpeeds_F2039(results)
cdf_female = Cdf.MakeCdfFromList(fspeeds)
fspeed = cdf_female.Value(rank)
print fspeed,'speed'
print convert_speeds_to_time(fspeed),'time'
myplot.Cdf(cdf_female)
myplot.Show()
def main():
results = relay.ReadResults()
speeds = relay.GetSpeeds(results)
# plot the distribution of actual speeds
pmf = Pmf.MakePmfFromList(speeds, 'actual speeds')
# myplot.Clf()
# myplot.Hist(pmf)
# myplot.Save(root='observed_speeds',
# title='PMF of running speed',
# xlabel='speed (mph)',
# ylabel='probability')
# plot the biased distribution seen by the observer
biased = BiasPmf(pmf, 7.5, name='observed speeds')
myplot.Clf()
myplot.Hist(biased)
myplot.Save(root='observed_speeds',
title='PMF of running speed',
xlabel='speed (mph)',
ylabel='probability')
cdf = Cdf.MakeCdfFromPmf(biased)
myplot.Clf()
myplot.Cdf(cdf)
myplot.show(root='observed_speeds_cdf',
title='CDF of running speed',
xlabel='speed (mph)',
ylabel='cumulative probability')
def main():
#Exercise 3.5
results = relay.ReadResults()
speeds = relay.GetSpeeds(results)
speedsCdf = Cdf.MakeCdfFromList(speeds, "race speeds")
mplt.Cdf(speedsCdf)
mplt.show(title="Race Speed CDF",
xlabel="speed in mph",
ylabel="probability")
def main():
results = relay.ReadResults()
speeds = relay.GetSpeeds(results)
# plot the distribution of actual speeds
cdf = Cdf.MakeCdfFromList(speeds, 'speeds')
myplot.Cdf(cdf,
title='CDF of running speed',
xlabel='speed (mph)',
ylabel='probability',
show=True)
def main():
results = relay.ReadResults()
speeds = relay.GetSpeeds(results)
pmf = Pmf.MakePmfFromList(speeds, 'actual speeds')
observed = BiasPmf(pmf, 7.5, 'observed speeds')
myplot.Clf()
myplot.Hist(observed)
myplot.Show(title='observed speeds',
xlabel='speed (mph)',
ylabel='probability')
def main():
results = relay.ReadResults()
speeds = relay.GetSpeeds(results)
pmf = Pmf.MakePmfFromList(speeds, 'speeds')
pmf = BiasPmf(7,pmf)
myplot.Hist(pmf)
#myplot.Show(title='PMF of observed speed',
# xlabel='speed (mph)',
# ylabel='probability')
myplot.Save(
formats=['png'],
root='runner',
title='PMF of observed speed',
xlabel='speed (mph)',
ylabel='probability')
def main():
# Exercise 3.1
d = {
7: 8,
12: 8,
17: 14,
22: 4,
27: 6,
32: 12,
37: 8,
42: 3,
47: 2
}
classSizeDean = Pmf.MakePmfFromDict(d, name='Actual')
print(classSizeDean.Mean())
classSizeStudent = classSizeDean.Copy(name='Student Perspective')
for x, _ in classSizeStudent.Items():
classSizeStudent.Mult(x, x)
classSizeStudent.Normalize()
print(classSizeStudent.Mean())
classSizeUnbaised = UnbiasPmf(classSizeStudent, 'Student Unbiased')
print(classSizeUnbaised.Mean())
getValue = itemgetter(0)
deanPlot = sorted(classSizeDean.Items(), key=getValue)
studentPlot = sorted(classSizeStudent.Items(), key=getValue)
plt.plot(zip(*deanPlot)[0], zip(*deanPlot)[1], 'g-', label='Actual')
plt.plot(zip(*studentPlot)[0], zip(*studentPlot)[1], 'r-', label='Student Perspective')
plt.legend(loc=4)
plt.xlabel('Class Size')
plt.ylabel('Probability')
plt.show()
#Exercise 3.2
results = relay.ReadResults()
speeds = relay.GetSpeeds(results)
unbaisedSpeedsPmf = Pmf.MakePmfFromList(speeds, 'speeds')
biasedSpeedsPmf = BiasPmf(unbaisedSpeedsPmf, 7.5, '7.5 mph biased speeds')
biasedPlot = sorted(biasedSpeedsPmf.Items(), key=getValue)
myplot.Pmf(biasedSpeedsPmf)
myplot.Show(title='7.5mph biased speeds',
xlabel='speeds (mph)',
ylabel='probability')
def main():
results = relay.ReadResults()
speeds = relay.GetSpeeds(results)
rankit.MakeNormalPlot(speeds, root='relay_normal', ylabel='Speed (MPH)')
def __init__(self):
results = relay.ReadResults()
speeds = relay.GetSpeeds(results)
self.speeds = speeds
self.pmf = Pmf.MakePmfFromList(speeds)
import relay
import Cdf
import Pmf
import myplot
speeds = relay.GetSpeeds(relay.ReadResults())
pmf = Pmf.MakePmfFromList(speeds)
cdf = Cdf.MakeCdfFromList(speeds)
myplot.Pmf(pmf)
myplot.Cdf(cdf)
myplot.Show(title='PMF vs CDF of running speeds',
xlabel='speed (mph)',
ylabel='probability')
import math import myplot import numpy import relay results = relay.ReadResults() speeds = relay.GetSpeeds(results) xs = sorted(numpy.random.normal(0, 1, len(speeds))) ys = sorted(speeds) myplot.Plot(xs, ys) myplot.Show(title="Normal Plot for Running Speeds")
