main.py

import argparse
from optimization.local import *
from optimization.grid_search import *

default_method = 'local'
default_budget = 10000
default_rtpcr_cost = 0.1
default_rat_cost = 0.5
default_igg_cost = 0.3

parser = argparse.ArgumentParser()
parser.add_argument('-C', help="Total budget available, C (in units of thousand rupees)", default=default_budget )
parser.add_argument('-cRAT', help="Cost for one RAT test(in units of thousand rupees)", default=default_rat_cost)
parser.add_argument('-cRTPCR', help="Cost for one RT-PCR test(in units of thousand rupees)", default=default_rtpcr_cost)
parser.add_argument('-cIGG', help="Cost for one IGG test(in units of thousand rupees)", default=default_igg_cost)
parser.add_argument("-m", help="select method to opimize, by default 'local optimization' is enabled, for exhaustive search, set -m grid", default=default_method)
args = parser.parse_args()

C = float(args.C)
cRAT = float(args.cRAT)
cRTPCR = float(args.cRTPCR)
cIgG = float(args.cIGG)
methods = args.m


if methods == "local":
  p_vec =  [0.1, 0.3, 0.01]
  res, objFunVal = local_optimization(cRAT, cRTPCR, cIgG, p_vec)
  res = get_final_solution(res, C, cRAT, cRTPCR, cIgG)   
  print(res)

if methods == "grid":
  res, objFunVal = exhaustive_search(cRAT, cRTPCR, cIgG, p1_start=0.01, p1_end=0.16, p2_start=0.10, p2_end=0.51, p3_start=0.00, p3_end=0.03)
  res = get_final_solution(res, C, cRAT, cRTPCR, cIgG)
  print(res)