def main():
pmf = Pmf()
pmf.Set('Bowl 1', 0.5)
pmf.Set('Bowl 2', 0.5)
pmf.Mult('Bowl 1', 0.75)
pmf.Mult('Bowl 2', 0.5)
pmf.Normalize()
print(pmf.Prob('Bowl 1'))
print(pmf.Prob('Bowl 2'))
"""This file contains code for use with "Think Bayes",
by Allen B. Downey, available from greenteapress.com
Copyright 2012 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function, division
from thinkbayes2 import Pmf
pmf = Pmf()
pmf.Set('Bowl 1', 0.5)
pmf.Set('Bowl 2', 0.5)
pmf.Mult('Bowl 1', 0.75)
pmf.Mult('Bowl 2', 0.5)
pmf.Normalize()
print(pmf.Prob('Bowl 1'))
import sys
sys.path.insert(0, '/Users/carol/python/ThinkBayes2/thinkbayes2/')
import numpy as np
import matplotlib.pyplot as plt
from thinkbayes2 import Pmf, Suite, CredibleInterval, Beta
# PMF for 6-sided die
pmf = Pmf()
for x in [1, 2, 3, 4, 5, 6]:
pmf.Set(x, 1 / 6)
print(pmf)
# How to build up a pmf from a list of strings
pmf2 = Pmf()
for word in ['a', 'in', 'or', 'to', 'a', 'me', 'in']:
pmf2.Incr(word, 1)
pmf2.Normalize()
print(pmf2)
print("Probability of letter a:", pmf2.Prob(
'a')) # Typo p12 print pmf.Prob('the') should read print(pmf.Prob('the'))
# PMF for the Cookie problem
pmf = Pmf()
# Prior:
pmf.Set("Bowl 1", 0.5)
pmf.Set("Bowl 2", 0.5)
# Posterior:
# First multiply prior by likelihood
pmf.Mult("Bowl 1", 0.75)
# http://www.greenteapress.com/thinkbayes/thinkbayes.pdf
# http://thinkbayes.com/thinkbayes.py
# python -m pip install scipy numpy matplotlib pandas
from thinkbayes2 import Pmf
pmf = Pmf()
pmf.Set('tazon1', 0.5)
pmf.Set('tazon2', 0.5)
pmf.Mult('tazon1', 0.75)
pmf.Mult('tazon2', 0.5)
pmf.Normalize()
print(pmf.Prob('tazon1'))
from __future__ import print_function, division
import sys
sys.path.append("../lib/ThinkBayes2/code/")
from thinkbayes2 import Suite, Pmf, SampleSum, MakeMixture
import thinkplot
from simulationDD02 import Die
pmf_dice = Pmf()
pmf_dice.Set(Die(4), 2)
pmf_dice.Set(Die(6), 3)
pmf_dice.Set(Die(8), 2)
pmf_dice.Set(Die(12), 1)
pmf_dice.Set(Die(20), 1)
pmf_dice.Normalize()
print(pmf_dice)
print("#################################################")
mix = Pmf()
for die, weight in pmf_dice.Items():
for outcome, prob in die.Items():
mix.Incr(outcome, weight * prob)
#Shorthand for above
#mix = MakeMixture(pmf_dice)
print(mix)
thinkplot.Hist(mix)
thinkplot.Save(root='bar',
xlabel='Mixture over a set of dice',
ylabel='Probability',
formats=['pdf'])
from thinkbayes2 import Pmf
if __name__ == '__main__':
pmf = Pmf()
for x in range(1, 7):
pmf.Set(x, 1 / 6.0)
pmf.Print()
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 17 12:08:20 2018
@author: QJ
"""
###Think Bayes
from thinkbayes2 import Pmf
pmf = Pmf()
for x in [1, 2, 3, 4, 5, 6]:
pmf.Set(x, 1 / 6.0)
pmf.Set('Bowl1', 0.5)
pmf.Set('Bowl2', 0.5)
pmf.Mult('Bowl1', 0.75)
pmf.Mult('Bowl2', 0.5)
print pmf.Prob('Bowl 1')
print(pmf)
