import sys, os
sys.path.append(os.path.join(os.path.abspath(os.path.dirname(sys.argv[0])), '..'))

from tulip import *
import tulip.polytope as pc

# Specify where the smv file, spc file and aut file will go
testfile = 'intersection'
path = os.path.abspath(os.path.dirname(sys.argv[0]))
smvfile = os.path.join(path, 'specs', testfile+'.smv')
spcfile = os.path.join(path, 'specs', testfile+'.spc')
autfile = os.path.join(path, 'specs', testfile+'.aut')

# Specify the environment variables
env_vars = {'C2' : 'boolean', 'C3' : 'boolean', 'C4' : 'boolean', 'C5' : 'boolean', 'C7' : 'boolean'}

# Specify the discrete system variable
sys_disc_vars = {}

# Specify the transition system representing the continuous dynamics
disc_dynamics = prop2part.PropPreservingPartition(list_region=[], list_prop_symbol=[])

# These following propositions specify in which cell the robot is, i.e., 
# Xi means that the robot is in cell Ci
disc_dynamics.list_prop_symbol = ['X0', 'X2', 'X5', 'X6'] 
disc_dynamics.num_prop = len(disc_dynamics.list_prop_symbol)

# Regions. Note that the first argument of Region(poly, prop) should be a list of 
# polytopes. But since we are not dealing with the actual controller, we will 
# just fill it with a string (think of it as a name of the region).
# The second argument of Region(poly, prop) is a list that specifies which 
# propositions in cont_props above is satisfied. As specified below, regioni 
# satisfies proposition Xi.
region0 = pc.Region('C0', [1, 0, 0, 0])
region2 = pc.Region('C1', [0, 1, 0, 0])
region5 = pc.Region('C2', [0, 0, 1, 0])
region6 = pc.Region('C3', [0, 0, 0, 1])
disc_dynamics.list_region = [region0, region2, region5, region6]
disc_dynamics.num_regions = len(disc_dynamics.list_region)

# The transition relation between regions. disc_dynamics.trans[i][j] = 1 if starting from 
# region j, the robot can move to region i while only staying in the union of region i 
# and region j.
disc_dynamics.trans =   XXXX FILL IN THE TRANSITION MATRIX XXXX

# Spec
assumption = XXXX FILL IN THE ASSUMPTIONS XXXX

guarantee = XXXX FILL IN THE GUARANTEES XXXX

# Generate input to JTLV
prob = jtlvint.generateJTLVInput(env_vars, sys_disc_vars, [assumption, guarantee], \
                                   {}, disc_dynamics, smvfile, spcfile, verbose=2)

# Check realizability
realizability = jtlvint.checkRealizability(smv_file=smvfile, spc_file=spcfile, \
                                       aut_file=autfile, verbose=3)

# Compute an automaton
jtlvint.computeStrategy(smv_file=smvfile, spc_file=spcfile, aut_file=autfile, \
                                    priority_kind=3, verbose=3)
aut = automaton.Automaton(autfile, [], 3)

# Simulate
#states = grsim(aut, init_state={}, num_it=30, deterministic_env=False)
#writeStatesToFile(states, 'autonomous_car_int_sim.txt')



# Simulate
num_it = 30
# states = grsim.grsim(aut, init_state, num_it=num_it, deterministic_env=False)
states = grsim.grsim([aut], aut_trans_dict={}, env_states = [{}], num_it=num_it, deterministic_env=False)

destfile = 'intersection_sim.txt'
label_vars = ['C2','C3','C4','C5','C7','cellID']

#grsim.writeStatesToFile([aut], destfile, aut_states_list = states,label_vars = label_vars)
grsim.writeSimStatesToFile(states, destfile)