simulate_nltax_compare_to_hy_ns.py

import numpy as np
import time
import subprocess
from SCEconomy_nltax import Economy, split_shock

import pickle


if __name__ == '__main__':
    
    import sys
    args = sys.argv    
    num_core = int(args[1])

    

    def curvedspace(begin, end, curve, num=100):
        import numpy as np
        ans = np.linspace(0, (end - begin)**(1.0/curve), num) ** (curve) + begin
        ans[-1] = end #so that the last element is exactly end
        return ans


    # additional info
    
    agrid2 = curvedspace(0., 200., 2., 40)
    kapgrid2 = curvedspace(0., 2.5, 2.0, 20)
    zgrid2 = np.load('./input_data/zgrid.npy') ** 2.0

    # prices
    # p_, rc_, ome_, varpi_ = 1.4461028141457346, 0.06194848724613948, 0.40772419502169976, 0.5822021442667737

    p_, rc_, ome_, varpi_ = 1.3594680204658702, 0.06136345811360533, 0.40, 0.60 #hy_ns upsilon = 0.5 case
    

    split_shock('./input_data/data_i_s', 100_000, num_core)
    
    ###end defining additional parameters###

    print('Solving the model with the given prices...')
    print('Do not simulate more than one models at the same time...')


    # alpha = 0.4
    # theta = 0.41
    # ynb = 0.451    
    # pure_sweat_share = 0.09 #target
    # s_emp_share = 0.30 #target

    # yc_init = 0.77 #1.0

    # GDP_implied = (1.-alpha + s_emp_share/(1. - s_emp_share)*(1.-theta)*yc_init + (1.-alpha)*ynb)/(1.-alpha - pure_sweat_share)

    # econ = Economy(alpha = alpha, theta = theta, yn = ynb,
    #                scaling_n = (1.-theta)*yc_init, scaling_b = pure_sweat_share*GDP_implied,
    #                agrid = agrid2, kapgrid = kapgrid2, zgrid = zgrid2, rho = 0.01, upsilon = 0.50,
    #                ome = ome_, varpi = varpi_, path_to_data_i_s = './input_data/data_i_s')
    

    econ = Economy(agrid = agrid2, kapgrid = kapgrid2, zgrid = zgrid2, rho = 0.01, upsilon = 0.50,
                   taun = np.ones(8)*0.4, psin_fixed = 0.15, taub = np.ones(6)*0.2, psib_fixed = 0.15,
                   scaling_n = 1.0, scaling_b = 1.0,
                   ome = ome_, varpi = varpi_, path_to_data_i_s = './input_data/data_i_s')
    
    econ.set_prices(p = p_, rc = rc_)
    with open('econ.pickle', mode='wb') as f: pickle.dump(econ, f)

    t0 = time.time()

    #don't forget to replace import argument
    result = subprocess.run(['mpiexec', '-n', str(num_core), 'python', 'SCEconomy_nltax.py'], stdout=subprocess.PIPE)
    
    t1 = time.time()

    detailed_output_file = './log/test.txt'
    f = open(detailed_output_file, 'ab') #use byte mode
    f.write(result.stdout)
    f.close()


    with open('econ.pickle', mode='rb') as f: econ = pickle.load(f)


    p = econ.p
    rc = econ.rc
    moms = econ.moms
    
    dist = np.sqrt(moms[0]**2.0 + moms[1]**2.0)
    
    if p != p_ or  rc != rc_:
        print('err: input prices and output prices do not coincide.')
        print('p = ', p, ', p_ = ', p_)
        print('rc = ', rc, ', rc_ = ', rc_)

    
    
    #calc main moments
    econ.print_parameters()
    econ.calc_moments()
    
    ###calculate other important variables###
    #econ.calc_sweat_eq_value()
    #econ.calc_age()
    #econ.simulate_other_vars()
    #econ.save_result()