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lines 5-97 of file: example/user/const_value.py
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# {xrst_begin user_const_value.py}
# {xrst_comment_ch #}
#
# Constrain Omega Using const_value
# #################################
#
# Node Table
# **********
# For this example the :ref:`node_table-name` is
# ::
#
#                 universe
#                     |
#                   world
#                 /      \
#            child_1   child_2
#
# Problem Parameters
# ******************
# The following values are used to simulate the data and set the priors
# for fitting the data:
# {xrst_spell_off}
# {xrst_code py}
iota_true    = { 'world':0.004, 'child_1':0.002,  'child_2':0.008 }
omega_true   = { 'world':0.01, 'child_1':0.005,  'child_2':0.002  }
n_data       = 51
# {xrst_code}
# {xrst_spell_on}
#
# Child Random Effects
# ********************
# The following code converts the child rates to child rate effects:
# {xrst_spell_off}
# {xrst_code py}
import math
for key in [ 'child_1', 'child_2' ] :
    iota_true[key]  = math.log( iota_true[key] / iota_true['world'] )
    omega_true[key] = math.log( omega_true[key] / omega_true['world'] )
# {xrst_code}
# {xrst_spell_on}
#
# Omega Priors
# ************
# The parent and child rates for omega are constrained to be their
# true value using the :ref:`smooth_grid_table@const_value`
# column in the smooth_grid table.
#
# nslist
# ======
# Note that the different children have different priors for the
# child random effects which requires using the
# :ref:`child_nslist<rate_table@child_nslist_id>` option in the
# rate table.
#
# Iota Priors
# ***********
# The iota priors are uniform.
#
# Parent
# ======
# For the parent, the lower (upper) limit is the true value
# divided by ten (multiplied by ten).
# The mean, which is two times the true value, is used for the
# :ref:`start_var_table-name` and :ref:`scale_var_table-name` ;
# see :ref:`init_command-name` .
#
# Data
# ****
# All of the data for this example is direct measurements of the
# :ref:`avg_integrand@Integrand, I_i(a,t)@susceptible`
# population (as a fraction of the initial population).
#
# random_seed
# ***********
# Use the clock to seed random number generator, but pass it into
# dismod_at using the :ref:`option table<option_table@random_seed>` :
# {xrst_spell_off}
# {xrst_code py}
import time
random_seed = int( time.time() )
# {xrst_code}
# {xrst_spell_on}
#
# Source Code
# ***********
# Given the problem parameters define above, below is the rest of the
# source code for this example:
# {xrst_literal
#       BEGIN PYTHON
#       END PYTHON
# }
#
# {xrst_end user_const_value.py}