e@0: # -*- coding: utf-8 -*-
e@0: """
e@0: Created on Thu May 28 13:02:25 2015
e@0: 
e@0: @author: mmxgn
e@0: """
e@0: 
e@0: from pymc import DiscreteUniform, Exponential, deterministic, Poisson, Uniform
e@0: 
e@0: import numpy as np
e@0: 
e@0: disasters_array =   \
e@0:      np.array([ 4, 5, 4, 0, 1, 4, 3, 4, 0, 6, 3, 3, 4, 0, 2, 6,
e@0:                    3, 3, 5, 4, 5, 3, 1, 4, 4, 1, 5, 5, 3, 4, 2, 5,
e@0:                    2, 2, 3, 4, 2, 1, 3, 2, 2, 1, 1, 1, 1, 3, 0, 0,
e@0:                    1, 0, 1, 1, 0, 0, 3, 1, 0, 3, 2, 2, 0, 1, 1, 1,
e@0:                    0, 1, 0, 1, 0, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 2,
e@0:                    3, 3, 1, 1, 2, 1, 1, 1, 1, 2, 4, 2, 0, 0, 1, 4,
e@0:                    0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1])
e@0:                    
e@0: switchpoint = DiscreteUniform('switchpoint', lower=0, upper=110, doc='Switchpoint[year]')                   
e@0: 
e@0: early_mean = Exponential('early_mean', beta=1.)
e@0: late_mean = Exponential('late_mean', beta=1.)
e@0: 
e@0: 
e@0: @deterministic(plot=False)
e@0: def rate(s=switchpoint, e=early_mean, l=late_mean):
e@0:     ''' Concatenate Poisson means '''
e@0:     out = np.empty(len(disasters_array))
e@0:     out[:s] = e
e@0:     out[s:] = l
e@0:     return out
e@0: 
e@0: 
e@0: disasters = Poisson('disasters', mu=rate, value=disasters_array, observed=True)