#!/usr/bin/env python
# -*- coding: utf-8 -*-
# This file is part of the Cortix toolkit environment.
# https://cortix.org
import numpy as np
import scipy.constants as const
from scipy.integrate import odeint
from cortix import Module
from cortix import Phase
from cortix import Quantity
[docs]class Probation(Module):
'''
Probation Cortix module used to model criminal group population in a probation.
Notes
-----
These are the `port` names available in this module to connect to respective
modules: `adjudication`, `jail`, `arrested`, and `community`.
See instance attribute `port_names_expected`.
'''
[docs] def __init__(self, n_groups=1, pool_size=0.0):
'''
Parameters
----------
n_groups: int
Number of groups in the population.
pool_size: float
Upperbound on the range of the existing population groups. A random value
from 0 to the upperbound value will be assigned to each group.
'''
super().__init__()
self.port_names_expected = ['adjudication','jail','arrested','community']
quantities = list()
self.ode_params = dict()
self.initial_time = 0.0 * const.day
self.end_time = 100 * const.day
self.time_step = 0.5 * const.day
# Population groups
self.n_groups = n_groups
# Probation population groups
fbg_0 = np.random.random(self.n_groups) * pool_size
fbg = Quantity(name='fbg', formalName='probation-pop-grps',
unit='individual', value=fbg_0)
quantities.append(fbg)
# Model parameters: commitment coefficients and their modifiers
# Probation to community
cb0g_0 = np.random.random(self.n_groups) / const.day
cb0g = Quantity(name='cb0g', formalName='commit-community-coeff-grps',
unit='individual', value=cb0g_0)
self.ode_params['commit-to-community-coeff-grps'] = cb0g_0
quantities.append(cb0g)
mb0g_0 = np.random.random(self.n_groups)
mb0g = Quantity(name='mb0g', formalName='commit-community-coeff-mod-grps',
unit='individual', value=mb0g_0)
self.ode_params['commit-to-community-coeff-mod-grps'] = mb0g_0
quantities.append(mb0g)
# Probation to jail
cbjg_0 = np.random.random(self.n_groups) / const.day
cbjg = Quantity(name='cbjg', formalName='commit-jail-coeff-grps',
unit='individual', value=cbjg_0)
self.ode_params['commit-to-jail-coeff-grps'] = cbjg_0
quantities.append(cbjg)
mbjg_0 = np.random.random(self.n_groups)
mbjg = Quantity(name='mbjg', formalName='commit-jail-coeff-mod-grps',
unit='individual', value=mbjg_0)
self.ode_params['commit-to-jail-coeff-mod-grps'] = mbjg_0
quantities.append(mbjg)
# Death term
self.ode_params['probation-death-rates'] = np.zeros(self.n_groups)
# Initialize inflows to zero
self.ode_params['arrested-inflow-rates'] = np.zeros(self.n_groups)
self.ode_params['adjudication-inflow-rates'] = np.zeros(self.n_groups)
# Phase state
self.population_phase = Phase(self.initial_time, time_unit='s',
quantities=quantities)
self.population_phase.SetValue('fbg', fbg_0, self.initial_time)
return
[docs] def run(self, *args):
self.__zero_ode_parameters()
time = self.initial_time
while time < self.end_time:
# Interactions in the jail port
#------------------------------
# one way "to" jail
message_time = self.recv('jail')
outflow_rates = self.__compute_outflow_rates( message_time, 'jail' )
self.send( (message_time, outflow_rates), 'jail' )
# Interactions in the adjudication port
#------------------------------------
# one way "from" adjudication
self.send( time, 'adjudication' )
(check_time, inflow_rates) = self.recv('adjudication')
assert abs(check_time-time) <= 1e-6
self.ode_params['adjudication-inflow-rates'] = inflow_rates
# Interactions in the arrested port
#----------------------------------
# one way "from" arrested
self.send( time, 'arrested' )
(check_time, inflow_rates) = self.recv('arrested')
assert abs(check_time-time) <= 1e-6
self.ode_params['arrested-inflow-rates'] = inflow_rates
# Interactions in the community port
#------------------------------
# one way "to" community
message_time = self.recv('community')
outflow_rates = self.__compute_outflow_rates( message_time, 'community' )
self.send( (message_time, outflow_rates), 'community' )
# Evolve probation group population to the next time stamp
#---------------------------------------------------------
time = self.__step( time )
def __rhs_fn(self, u_vec, t, params):
fbg = u_vec # probation population groups
arrested_inflow_rates = params['arrested-inflow-rates']
adjudication_inflow_rates = params['adjudication-inflow-rates']
inflow_rates = arrested_inflow_rates + adjudication_inflow_rates
cb0g = self.ode_params['commit-to-community-coeff-grps']
mb0g = self.ode_params['commit-to-community-coeff-mod-grps']
cbjg = self.ode_params['commit-to-jail-coeff-grps']
mbjg = self.ode_params['commit-to-jail-coeff-mod-grps']
outflow_rates = ( cb0g * mb0g + cbjg * mbjg ) * fbg
death_rates = params['probation-death-rates']
dt_fbg = inflow_rates - outflow_rates - death_rates
return dt_fbg
def __step(self, time=0.0):
r'''
ODE IVP problem:
Given the initial data at :math:`t=0`,
:math:`u = (u_1(0),u_2(0),\ldots)`
solve :math:`\frac{\text{d}u}{\text{d}t} = f(u)` in the interval
:math:`0\le t \le t_f`.
Parameters
----------
time: float
Time in the droplet unit of time (seconds).
Returns
-------
None
'''
u_vec_0 = self.population_phase.GetValue('fbg', time)
t_interval_sec = np.linspace(0.0, self.time_step, num=2)
(u_vec_hist, info_dict) = odeint(self.__rhs_fn,
u_vec_0, t_interval_sec,
args=( self.ode_params, ),
rtol=1e-4, atol=1e-8, mxstep=200,
full_output=True)
assert info_dict['message'] =='Integration successful.', info_dict['message']
u_vec = u_vec_hist[1,:] # solution vector at final time step
values = self.population_phase.GetRow(time) # values at previous time
time += self.time_step
self.population_phase.AddRow(time, values)
# Update current values
self.population_phase.SetValue('fbg', u_vec, time)
return time
def __compute_outflow_rates(self, time, name):
fbg = self.population_phase.GetValue('fbg',time)
assert np.all(fbg>=0.0), 'values: %r'%fbg
if name == 'jail':
cbjg = self.ode_params['commit-to-jail-coeff-grps']
mbjg = self.ode_params['commit-to-jail-coeff-mod-grps']
outflow_rates = cbjg * mbjg * fbg
if name == 'community':
cb0g = self.ode_params['commit-to-community-coeff-grps']
mb0g = self.ode_params['commit-to-community-coeff-mod-grps']
outflow_rates = cb0g * mb0g * fbg
return outflow_rates
def __zero_ode_parameters(self):
'''
If ports are not connected the corresponding outflows must be zero.
'''
zeros = np.zeros(self.n_groups)
p_names = [p.name for p in self.ports]
if 'community' not in p_names:
self.ode_params['commit-to-community-coeff-grps'] = zeros
self.ode_params['commit-to-community-coeff-mod-grps'] = zeros
if 'jail' not in p_names:
self.ode_params['commit-to-jail-coeff-grps'] = zeros
self.ode_params['commit-to-jail-coeff-mod-grps'] = zeros
return
