Updating for PyCon 2015

dice.py

@@ -5,6 +5,8 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
 from thinkbayes import Suite
 
 
@@ -25,13 +27,13 @@ def main():
     suite = Dice([4, 6, 8, 12, 20])
 
     suite.Update(6)
-    print 'After one 6'
+    print('After one 6')
     suite.Print()
 
     for roll in [8, 7, 7, 5, 4]:
         suite.Update(roll)
 
-    print 'After more rolls'
+    print('After more rolls')
     suite.Print()
 
 

dice_soln.py

@@ -5,6 +5,8 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
 from thinkbayes import Suite
 
 
@@ -27,13 +29,13 @@ def main():
     suite = Dice([4, 6, 8, 12, 20])
 
     suite.Update(6)
-    print 'After one 6'
+    print('After one 6')
     suite.Print()
 
     for roll in [8, 7, 7, 5, 4]:
         suite.Update(roll)
 
-    print 'After more rolls'
+    print('After more rolls')
     suite.Print()
 
 

euro.py

@@ -5,6 +5,12 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
+import thinkbayes
+import thinkplot
+
+
 """This file contains a partial solution to a problem from
 MacKay, "Information Theory, Inference, and Learning Algorithms."
 
@@ -22,10 +28,6 @@
 
 """
 
-import thinkbayes
-import thinkplot
-
-
 class Euro(thinkbayes.Suite):
 
     def Likelihood(self, data, hypo):
@@ -43,9 +45,10 @@ def main():
 
     suite.Update('H')
 
-    thinkplot.Pmf(suite)
+    thinkplot.Pdf(suite)
     thinkplot.Show(xlabel='x',
-                ylabel='Probability')
+                   ylabel='Probability',
+                   legend=False)
 
 
 if __name__ == '__main__':

euro2.py

@@ -5,6 +5,11 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
+import thinkbayes
+
+
 """This file contains a partial solution to a problem from
 MacKay, "Information Theory, Inference, and Learning Algorithms."
 
@@ -22,16 +27,14 @@
 
 """
 
-import thinkbayes
-
 
 class Euro(thinkbayes.Suite):
 
     def Likelihood(self, data, hypo):
         """Computes the likelihood of the data under the hypothesis.
 
-        hypo: integer value of x, the probability of heads (0-100)
         data: tuple (#heads, #tails)
+        hypo: integer value of x, the probability of heads (0-100)
         """
         x = hypo / 100.0
         heads, tails = data
@@ -72,13 +75,13 @@ def main():
     data = 140, 110
 
     like_bias = AverageLikelihood(bias, data)
-    print 'like_bias', like_bias
+    print('like_bias', like_bias)
 
     like_fair = AverageLikelihood(fair, data)
-    print 'like_fair', like_fair
+    print('like_fair', like_fair)
 
     ratio = like_bias / like_fair
-    print 'Bayes factor', ratio
+    print('Bayes factor', ratio)
 
 
 if __name__ == '__main__':

euro2_soln.py

@@ -5,6 +5,12 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
+import thinkbayes
+import thinkplot
+
+
 """This file contains a partial solution to a problem from
 MacKay, "Information Theory, Inference, and Learning Algorithms."
 
@@ -22,17 +28,13 @@
 
 """
 
-import thinkbayes
-import thinkplot
-
-
 class Euro(thinkbayes.Suite):
 
-    def Likelihood(self, hypo, data):
+    def Likelihood(self, data, hypo):
         """Computes the likelihood of the data under the hypothesis.
 
-        hypo: integer value of x, the probability of heads (0-100)
         data: tuple (#heads, #tails)
+        hypo: integer value of x, the probability of heads (0-100)
         """
         x = hypo / 100.0
         heads, tails = data
@@ -53,7 +55,7 @@ def AverageLikelihood(suite, data):
     total = 0
 
     for hypo, prob in suite.Items():
-        like = suite.Likelihood(hypo, data)
+        like = suite.Likelihood(data, hypo)
         total += prob * like
 
     return total
@@ -70,20 +72,20 @@ def main():
         bias.Set(x, 100-x)
     bias.Normalize()
 
-    thinkplot.Pmf(bias)
+    thinkplot.Pdf(bias)
     thinkplot.Show()
 
     # notice that we've changed the representation of the data
     data = 140, 110
 
     like_bias = AverageLikelihood(bias, data)
-    print 'like_bias', like_bias
+    print('like_bias', like_bias)
 
     like_fair = AverageLikelihood(fair, data)
-    print 'like_fair', like_fair
+    print('like_fair', like_fair)
 
     ratio = like_bias / like_fair
-    print 'Bayes factor', ratio
+    print('Bayes factor', ratio)
 
 
 if __name__ == '__main__':

euro_soln.py

@@ -5,6 +5,12 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
+import thinkbayes
+import thinkplot
+
+
 """This file contains a partial solution to a problem from
 MacKay, "Information Theory, Inference, and Learning Algorithms."
 
@@ -22,10 +28,6 @@
 
 """
 
-import thinkbayes
-import thinkplot
-
-
 class Euro(thinkbayes.Suite):
 
     def Likelihood(self, data, hypo):
@@ -46,9 +48,10 @@ def main():
 
     suite.Update('H')
 
-    thinkplot.Pmf(suite)
+    thinkplot.Pdf(suite)
     thinkplot.Show(xlabel='x',
-                ylabel='Probability')
+                   ylabel='Probability',
+                   legend=False)
 
 
 if __name__ == '__main__':

install_test.py

@@ -5,6 +5,8 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
 import math
 import numpy
 
@@ -20,7 +22,7 @@ def RenderPdf(mu, sigma, n=101):
     n: number of places to evaluate the PDF
     """
     xs = numpy.linspace(mu-4*sigma, mu+4*sigma, n)
-    ys = [thinkbayes.EvalGaussianPdf(x, mu, sigma) for x in xs]
+    ys = [thinkbayes.EvalNormalPdf(x, mu, sigma) for x in xs]
     return xs, ys
 
 

lincoln.py

@@ -5,6 +5,8 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
 import thinkbayes
 import thinkplot
 
@@ -24,13 +26,13 @@
 there are at least 20 bugs, and if you have supreme confidence in your
 tester, you may suppose there are around 20 bugs. But maybe your
 tester isn't very good. Maybe there are hundreds of bugs. How can you
-have any idea how many bugs there are? There’s no way to know with one
+have any idea how many bugs there are? There's no way to know with one
 tester. But if you have two testers, you can get a good idea, even if
-you don’t know how skilled the testers are."
+you don't know how skilled the testers are."
 
-Then he presents the Lincoln index, an estimator "described by
+Then he presents the Lincoln index, an estimator "described by
 Frederick Charles Lincoln in 1930," where Wikpedia's use of
-"described" is a hint that the index is another example of Stigler's
+"described" is a hint that the index is another example of Stigler's
 law of eponymy.
 
     "Suppose two testers independently search for bugs. Let k1 be the
@@ -98,9 +100,7 @@ def Likelihood(self, data, hypo):
         return part1 * part2
 
 
-
 def main():
-
     data = 20, 15, 3
     probs = numpy.linspace(0, 1, 101)
     hypos = []
@@ -120,8 +120,8 @@ def main():
                    ylabel='PMF',
                    formats=['pdf', 'png'])
 
-    print n_marginal.Mean()
-    print n_marginal.MaximumLikelihood()
+    print(n_marginal.Mean())
+    print(n_marginal.MaximumLikelihood())
 
 
 if __name__ == '__main__':

sat.py

@@ -5,6 +5,8 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
 import csv
 
 import thinkbayes
@@ -168,23 +170,25 @@ def PmfProbGreater(pmf1, pmf2):
 
 
 def main():
-
     exam = Exam()
 
     alice = Sat(exam)
-    alice.name = 'alice'
+    alice.label = 'alice'
     alice.Update(780)
 
     bob = Sat(exam)
-    bob.name = 'bob'
+    bob.label = 'bob'
     bob.Update(760)
 
-    print 'Prob Alice is "smarter":', PmfProbGreater(alice, bob)
-    print 'Prob Bob is "smarter":', PmfProbGreater(bob, alice)
+    print('Prob Alice is "smarter":', PmfProbGreater(alice, bob))
+    print('Prob Bob is "smarter":', PmfProbGreater(bob, alice))
 
-    thinkplot.Pmfs([alice, bob])
+    thinkplot.PrePlot(2)
+    thinkplot.Pdfs([alice, bob])
     thinkplot.Show(xlabel='x',
-                   ylabel='Probability')
+                   ylabel='Probability',
+                   loc='upper left',
+                   xlim=[0.7, 1.02])
 
 
 if __name__ == '__main__':

sat_soln.py

@@ -5,6 +5,8 @@
 License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
 """
 
+from __future__ import print_function, division
+
 import csv
 
 import thinkbayes
@@ -168,23 +170,25 @@ def PmfProbGreater(pmf1, pmf2):
 
 
 def main():
-
     exam = Exam()
 
     alice = Sat(exam)
-    alice.name = 'alice'
+    alice.label = 'alice'
     alice.Update(780)
 
     bob = Sat(exam)
-    bob.name = 'bob'
+    bob.label = 'bob'
     bob.Update(760)
 
-    print 'Prob Alice is "smarter":', PmfProbGreater(alice, bob)
-    print 'Prob Bob is "smarter":', PmfProbGreater(bob, alice)
+    print('Prob Alice is "smarter":', PmfProbGreater(alice, bob))
+    print('Prob Bob is "smarter":', PmfProbGreater(bob, alice))
 
-    thinkplot.Pmfs([alice, bob])
+    thinkplot.PrePlot(2)
+    thinkplot.Pdfs([alice, bob])
     thinkplot.Show(xlabel='x',
-                   ylabel='Probability')
+                   ylabel='Probability',
+                   loc='upper left',
+                   xlim=[0.7, 1.02])
 
 
 if __name__ == '__main__':