import csv
import pymc3 as pc3
import numpy as np
import pandas as pd

PLA = pd.read_csv('./productliability_award.csv')

TH_MODEL = pc3.Model()

with TH_MODEL:
    A = pc3.Normal('alpha', mu=0, sd=10)
    BJR = pc3.Normal('betaJR', mu=0, sd=10)
    BL = pc3.Normal('betaL', mu=0, sd=10)
    BN = pc3.Normal('betaN', mu=0, sd=10)
    BO = pc3.Normal('betaO', mu=0, sd=10)
    BLO = pc3.Normal('betaLO', mu=0, sd=10)
    BNO = pc3.Normal('betaNO', mu=0, sd=10)

    P = A + BL * PLA['liability'] + BN * PLA['negligence'] + BO\
        * PLA['oralArg'] + BLO * PLA['liability'] * PLA['oralArg'] + BNO\
        * PLA['negligence'] * PLA['oralArg']
    AWARD = pc3.Binomial('award', 1, P)

MAP_PLA0 = pc3.find_MAP(model=TH_MODEL)

print(MAP_PLA0)