Esempio n. 1
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def objectiveFunction(proposalAllocation, totalBudget, costCoverageInfo,
                      optimise, numModelSteps, dataSpreadsheetName, data):
    import helper
    import costcov
    helper = helper.Helper()
    costCov = costcov.Costcov()
    model, derived, params = helper.setupModelConstantsParameters(data)
    if sum(proposalAllocation) == 0:
        scaledproposalAllocation = proposalAllocation
    else:
        scaledproposalAllocation = rescaleAllocation(totalBudget,
                                                     proposalAllocation)
    # run the model
    timestepsPre = 12
    for t in range(timestepsPre):
        model.moveOneTimeStep()
    # update coverages after 1 year
    targetPopSize = getTargetPopSizeFromModelInstance(dataSpreadsheetName,
                                                      helper.keyList, model)
    newCoverages = {}
    for i in range(0, len(data.interventionList)):
        intervention = data.interventionList[i]
        newCoverages[intervention] = costCov.function(
            scaledproposalAllocation[i], costCoverageInfo[intervention],
            targetPopSize[intervention]) / targetPopSize[intervention]
    model.updateCoverages(newCoverages)
    for t in range(numModelSteps - timestepsPre):
        model.moveOneTimeStep()
    if optimise == 'deaths':
        performanceMeasure = model.getTotalCumulativeDeaths()
    if optimise == 'stunting':
        performanceMeasure = model.getCumulativeAgingOutStunted()
    return performanceMeasure
Esempio n. 2
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 def oneModelRunWithOutput(self, allocationDictionary):
     import costcov
     import data
     from copy import deepcopy as dcp
     costCov = costcov.Costcov()
     spreadsheetData = data.readSpreadsheet(self.dataSpreadsheetName,
                                            self.helper.keyList)
     model, derived, params = self.helper.setupModelConstantsParameters(
         spreadsheetData)
     costCoverageInfo = self.getCostCoverageInfo()
     # run the model
     modelList = []
     timestepsPre = 12
     for t in range(timestepsPre):
         model.moveOneTimeStep()
         modelThisTimeStep = dcp(model)
         modelList.append(modelThisTimeStep)
     # update coverages after 1 year
     targetPopSize = getTargetPopSizeFromModelInstance(
         self.dataSpreadsheetName, self.helper.keyList, model)
     newCoverages = {}
     for i in range(0, len(spreadsheetData.interventionList)):
         intervention = spreadsheetData.interventionList[i]
         newCoverages[intervention] = costCov.function(
             allocationDictionary[intervention],
             costCoverageInfo[intervention],
             targetPopSize[intervention]) / targetPopSize[intervention]
     model.updateCoverages(newCoverages)
     for t in range(self.numModelSteps - timestepsPre):
         model.moveOneTimeStep()
         modelThisTimeStep = dcp(model)
         modelList.append(modelThisTimeStep)
     return modelList
Esempio n. 3
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def getTotalInitialAllocation(data, costCoverageInfo, targetPopSize):
    import costcov
    costCov = costcov.Costcov()
    allocation = []
    for intervention in data.interventionList:
        coverageFraction = array(
            [dcp(data.interventionCoveragesCurrent[intervention])])
        coverageNumber = coverageFraction * targetPopSize[intervention]
        if coverageNumber == 0:
            spending = array([0.])
        else:
            spending = costCov.inversefunction(coverageNumber,
                                               costCoverageInfo[intervention],
                                               targetPopSize[intervention])
        allocation.append(spending)
    return allocation
Esempio n. 4
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def getTotalInitialAllocation(data, costCoverageInfo, targetPopSize):
    import costcov
    from copy import deepcopy as dcp
    costCov = costcov.Costcov()
    allocation = []
    for intervention in data.interventionList:
        coverageFraction = dcp(data.coverage[intervention])
        coverageNumber = coverageFraction * targetPopSize[intervention]
        if coverageNumber == 0:
            spending = 0.
        else:
            spending = costCov.inversefunction(coverageNumber,
                                               costCoverageInfo[intervention],
                                               targetPopSize[intervention])
        allocation.append(spending)
    return allocation
@author: madhurakilledar
"""
from __future__ import division
from copy import deepcopy as dcp
from numpy import array

import os, sys
moduleDir = os.path.join(os.path.dirname(__file__), '..')
sys.path.append(moduleDir)
import data
import helper
import output
import costcov

helper = helper.Helper()
costCov = costcov.Costcov()

country = 'Bangladesh'
startYear = 2016
version = '1604'

dataFilename = '../input_spreadsheets/%s/InputForCode_%s.xlsx' % (country,
                                                                  country)
#dataFilename = '../input_spreadsheets/%s/Input_%s_%i_%s.xlsx'%(country, country, startYear, version)
inputData = data.readSpreadsheet(dataFilename, helper.keyList)
numAgeGroups = len(helper.keyList['ages'])

numsteps = 180

oldCoverages = {}
costCovParams = {}