import asd as asd
import numpy as np
helper = helper.Helper()
costCov = costcov.Costcov()
dataSpreadsheetName = 'InputForCode_Bangladesh.xlsx'
timestep = 1. / 12.
numsteps = 180
ages = [
"<1 month", "1-5 months", "6-11 months", "12-23 months", "24-59 months"
]
birthOutcomes = ["Pre-term SGA", "Pre-term AGA", "Term SGA", "Term AGA"]
wastingList = ["normal", "mild", "moderate", "high"]
stuntingList = ["normal", "mild", "moderate", "high"]
breastfeedingList = ["exclusive", "predominant", "partial", "none"]
keyList = [ages, birthOutcomes, wastingList, stuntingList, breastfeedingList]
spreadsheetData = dataCode.getDataFromSpreadsheet(dataSpreadsheetName, keyList)
mothers = helper.makePregnantWomen(spreadsheetData)
mothers['annualPercentPopGrowth'] = -0.01
ageGroupSpans = [1., 5., 6., 12., 36.] # number of months in each age group
agingRateList = [
1. / 1., 1. / 5., 1. / 6., 1. / 12., 1. / 36.
] # fraction of people aging out per MONTH (WARNING use ageSpans to define this)
numAgeGroups = len(ages)
agePopSizes = helper.makeAgePopSizes(numAgeGroups, ageGroupSpans,
spreadsheetData)
targetPopSize = {}
costCoverageInfo = {}
for intervention in spreadsheetData.interventionList:
targetPopSize[intervention] = 0.
costCoverageInfo[intervention] = {}
for iAge in range(numAgeGroups):
import pickle as pickle
import os, sys
moduleDir = os.path.join(os.path.dirname(__file__), '..')
sys.path.append(moduleDir)
import data
import helper
import output
country = 'Bangladesh'
helper = helper.Helper()
dataFilename = '../input_spreadsheets/%s/InputForCode_%s.xlsx'%(country, country)
inputData = data.getDataFromSpreadsheet(dataFilename, helper.keyList)
plotData = []
run=0
pickleFilename = '%s_Default.pkl'%(country)
nametag = "Baseline"
plotcolor = 'grey'
file = open(pickleFilename, 'rb')
modelList = []
while 1:
try:
modelList.append(pickle.load(file))
except (EOFError):
break
file.close()
"""
import output as output
import pickle as pickle
import data as dataCode
country = 'Kenya'
ages = ["<1 month", "1-5 months", "6-11 months", "12-23 months", "24-59 months"]
birthOutcomes = ["Pre-term SGA", "Pre-term AGA", "Term SGA", "Term AGA"]
wastingList = ["normal", "mild", "moderate", "high"]
stuntingList = ["normal", "mild", "moderate", "high"]
breastfeedingList = ["exclusive", "predominant", "partial", "none"]
keyList = [ages, birthOutcomes, wastingList, stuntingList, breastfeedingList]
dataFilename = 'InputForCode_%s.xlsx'%(country)
spreadsheetData = dataCode.getDataFromSpreadsheet(dataFilename, keyList)
plotData = []
run=0
pickleFilename = '%s_Default.pkl'%(country)
nametag = "Baseline"
plotcolor = 'grey'
file = open(pickleFilename, 'rb')
modelList = []
while 1:
try:
modelList.append(pickle.load(file))
except (EOFError):
break
file.close()
import os, sys
moduleDir = os.path.join(os.path.dirname(__file__), '..')
sys.path.append(moduleDir)
import data
import helper
import output
country = 'Bangladesh'
helper = helper.Helper()
dataFilename = '../input_spreadsheets/%s/InputForCode_%s.xlsx' % (country,
country)
inputData = data.getDataFromSpreadsheet(dataFilename, helper.keyList)
plotData = []
run = 0
pickleFilename = '%s_Default.pkl' % (country)
nametag = "Baseline"
plotcolor = 'grey'
file = open(pickleFilename, 'rb')
modelList = []
while 1:
try:
modelList.append(pickle.load(file))
except (EOFError):
break
file.close()